A collection of 229 essays in English and Chinese
包含 229 篇中英对照文章
Date range: June 1998 - June 2025
Generated: 2025-07-14 23:02:19
This webpage was created for personal reading.
All content © Paul Graham. Chinese translations by AI.
June 2025 An essay has to tell people something they don't already know. But there are three different reasons people might not know something, and they yield three very different kinds of essays. One reason people won't know something is if it's not important to know. That doesn't mean it will make a bad essay. For example, you might write a good essay about a particular model of car. Readers would learn something from it. It would add to their picture of the world. For a handful of readers it might even spur some kind of epiphany. But unless this is a very unusual car it's not critical for everyone to know about it. [1] If something isn't important to know, there's no answer to the question of why people don't know it. Not knowing random facts is the default. But if you're going to write about things that _are_ important to know, you have to ask why your readers don't already know them. Is it because they're smart but inexperienced, or because they're obtuse? So the three reasons readers might not already know what you tell them are (a) that it's not important, (b) that they're obtuse, or (c) that they're inexperienced. The reason I did this breakdown was to get at the following fact, which might have seemed controversial if I'd led with it, but should be obvious now. If you're writing for smart people about important things, you're writing for the young. Or more precisely, that's where you'll have the most effect. Whatever you say should also be at least somewhat novel to you, however old you are. It's not an essay otherwise, because an essay is something you write to figure something out. But whatever you figure out will presumably be more of a surprise to younger readers than it is to you. There's a continuum of surprise. At one extreme, something you read can change your whole way of thinking. _The Selfish Gene_ did this to me.
It was like suddenly seeing the other interpretation of an ambiguous image: you can treat genes rather than organisms as the protagonists, and evolution becomes easier to understand when you do. At the other extreme, writing merely puts into words something readers were already thinking — or thought they were. The impact of an essay is how much it changes readers' thinking multiplied by the importance of the topic. But it's hard to do well at both. It's hard to have big new ideas about important topics. So in practice there's a tradeoff: you can change readers' thinking a lot about moderately important things, or change it a little about very important ones. But with younger readers the tradeoff shifts. There's more room to change their thinking, so there's a bigger payoff for writing about important things. The tradeoff isn't a conscious one, at least not for me. It's more like a kind of gravitational field that writers work in. But every essayist works in it, whether they realize it or not. This seems obvious once you state it, but it took me a long time to understand. I knew I wanted to write for smart people about important topics. I noticed empirically that I seemed to be writing for the young. But it took me years to understand that the latter was an automatic consequence of the former. In fact I only really figured it out as I was writing this essay. Now that I know it, should I change anything? I don't think so. In fact seeing the shape of the field that writers work in has reminded me that I'm not optimizing for returns in it. I'm not trying to surprise readers of any particular age; I'm trying to surprise myself. The way I usually decide what to write about is by following curiosity. I notice something new and dig into it. It would probably be a mistake to change that. But seeing the shape of the essay field has set me thinking.
What would surprise young readers? Which important things do people tend to learn late? Interesting question. I should think about that. Note [1] It's hard to write a really good essay about an unimportant topic, though, because a really good essayist will inevitably draw the topic into deeper waters. E. B. White could write an essay about how to boil potatoes that ended up being full of timeless wisdom. In which case, of course, it wouldn't really be about how to boil potatoes; that would just have been the starting point. Thanks to Jessica Livingston and Michael Nielsen for reading drafts of this..
2025年6月 一篇好的文章必须告诉人们他们尚不了解的事物。但人们无知的原因有三,由此衍生出三种截然不同的文章类型。 第一种无知源于信息本身无关紧要。这并不意味着文章质量低下。比如你完全可以写一篇关于某款车型的精彩文章,读者会从中获得新知,丰富他们的认知图景。对少数读者而言,甚至可能引发顿悟。但除非这款车非同寻常,否则并非人人必须知晓。[1] 若信息本身无足轻重,"人们为何不知"便不成其为问题。不知晓随机事实本是常态。但若你执笔书写真正重要之事,就必须追问读者尚未知晓的缘由:是他们虽聪慧却缺乏经验,还是天性愚钝? 因此读者不知晓你所言之事的三重原因是:(a)信息不重要,(b)读者愚钝,(c)读者缺乏经验。 我之所以进行这种分类,是为了揭示一个若直接提出可能引发争议、但此刻应显而易见的事实:当你为聪明人撰写重要议题时,你本质上是在为年轻人写作。 更准确地说,这是产生最大影响力的途径。无论作者年岁几何,所写内容至少应对自身有所启发——否则不成其为文章,因为文章本为探索真知而作。但你的发现对年轻读者带来的震撼,必然远胜于你自身的感受。 认知冲击存在渐变光谱。极致处,文字能彻底重塑思维模式。《自私的基因》于我便是如此。就像突然看清双关图的另一重解读:将基因而非生物体视作主角,进化论便豁然开朗。另一极端,文字仅道出读者心有所感却未能言明之事。 文章的冲击力等于它改变读者思维的程度乘以议题重要性。但两者难以兼得——重要议题上难有惊天新见。实践中需要权衡:或在较重要议题上引发适度思考转变,或在极其重要议题上促成微小认知突破。但对年轻读者而言,这种权衡会发生偏移。改变其思维的空间更大,因此在重要议题上写作的回报更为丰厚。 这种权衡未必出于刻意,至少于我如此。它更像是写作者所处的引力场——无论是否察觉,每位散文家都身处其中。 此理道破后看似浅显,我却历经漫长岁月才领悟。我早知自己愿为智者书写要事,也 empirically 发现读者似乎多为青年。但直到多年后——确切说是撰写本文时——我才明白后者实为前者的必然结果。 既明此理,是否应当调整写作策略?我想不必。看清写作领域的引力分布后,反而提醒我本就不为追求最大回报而作。我的目标从来不是震撼特定年龄的读者,而是震撼我自己。 我的选题方式向来是追随好奇心,捕捉新现象并深入挖掘。改变这种方式恐非明智。但洞悉文章领域的格局后,我不禁开始思考:什么会让年轻读者震撼?哪些重要事物常被人们迟悟?有趣的问题,值得深思。 注释 [1] 但无关主题确实难以成就真正佳作,因为杰出作者总会将话题引向深层水域。E·B·怀特若写煮土豆指南,最终必充满永恒智慧。此时文章自然不再关乎烹饪技法——那不过是思考的起点。 致谢 杰西卡·利文斯顿与迈克尔·尼尔森审阅本文草稿。
May 2025 There are two senses in which writing can be good: it can sound good, and the ideas can be right. It can have nice, flowing sentences, and it can draw correct conclusions about important things. It might seem as if these two kinds of good would be unrelated, like the speed of a car and the color it's painted. And yet I don't think they are. I think writing that sounds good is more likely to be right. So here we have the most exciting kind of idea: one that seems both preposterous and true. Let's examine it. How can this possibly be true? I know it's true from writing. You can't simultaneously optimize two unrelated things; when you push one far enough, you always end up sacrificing the other. And yet no matter how hard I push, I never find myself having to choose between the sentence that sounds best and the one that expresses an idea best. If I did, it would be frivolous to care how sentences sound. But in practice it feels the opposite of frivolous. Fixing sentences that sound bad seems to help get the ideas right. [1] By right I mean more than just true. Getting the ideas right means developing them well — drawing the conclusions that matter most, and exploring each one to the right level of detail. So getting the ideas right is not just a matter of saying true things, but saying the right true things. How could trying to make sentences sound good help you do that? The clue to the answer is something I noticed 30 years ago when I was doing the layout for my first book. Sometimes when you're laying out text you have bad luck. For example, you get a section that runs one line longer than the page. I don't know what ordinary typesetters do in this situation, but what I did was rewrite the section to make it a line shorter. You'd expect such an arbitrary constraint to make the writing worse. But I found, to my surprise, that it never did. I always ended up with something I liked better.
I don't think this was because my writing was especially careless. I think if you pointed to a random paragraph in anything written by anyone and told them to make it slightly shorter (or longer), they'd probably be able to come up with something better. The best analogy for this phenomenon is when you shake a bin full of different objects. The shakes are arbitrary motions. Or more precisely, they're not calculated to make any two specific objects fit more closely together. And yet repeated shaking inevitably makes the objects discover brilliantly clever ways of packing themselves. Gravity won't let them become less tightly packed, so any change has to be a change for the better. [2] So it is with writing. If you have to rewrite an awkward passage, you'll never do it in a way that makes it _less_ true. You couldn't bear it, any more than gravity could bear things floating upward. So any change in the ideas has to be a change for the better. It's obvious once you think about it. Writing that sounds good is more likely to be right for the same reason that a well-shaken bin is more likely to be tightly packed. But there's something else going on as well. Sounding good isn't just a random external force that leaves the ideas in an essay better off. It actually helps you to get them right. The reason is that it makes the essay easier to read. It's less work to read writing that flows well. How does that help the writer? _Because the writer is the first reader._ When I'm working on an essay, I spend far more time reading than writing. I'll reread some parts 50 or 100 times, replaying the thoughts in them and asking myself, like someone sanding a piece of wood, does anything catch? Does anything feel wrong? And the easier the essay is to read, the easier it is to notice if something catches. So yes, the two senses of good writing are connected in at least two ways.
2025年5月 好的写作可以从两个层面来理解:音韵之美与思想之真。它可以拥有优美流畅的句子,也能对重要事物得出正确结论。这两者看似毫不相干,就像汽车的速度与漆面颜色般毫无关联。但我认为事实并非如此——音韵优美的文字往往更可能蕴含真理。 于是我们遇到了最令人兴奋的观点:一个看似荒谬却又真实的命题。让我们深入剖析:这怎么可能成立? 从写作实践中我确信其真实性。人无法同时优化两个无关变量;当你在某方面追求极致时,总会牺牲另一方面。然而无论我如何竭力推敲,从未面临必须在最佳音韵与最佳表达之间抉择的困境。若真存在这种取舍,执着于音韵便是轻浮之举。但实际体验恰恰相反——修正拗口的句子似乎总能让思想更趋准确。[1] 所谓"准确"不仅指正确。思想准确意味着充分展开论述——得出最关键结论,并以恰如其分的细节进行探讨。因此思想准确不仅是陈述真相,更是呈现最关键的真相。 为何追求音韵能促进思想表达?答案线索来自三十年前我为处女作排版时的发现。文本排版时常会遇到厄运:比如某个章节比页面多出一行。不知专业排字工会如何处理,我的解决方案是重写这段文字使其缩短一行。这种武断限制本应损害文本质量,但令人惊讶的是,结果总是更令人满意。 我不认为这是因为我的写作特别草率。随机选取他人作品的任意段落要求稍作删减(或扩充),作者多半能改得更好。 这种现象的最佳类比是摇晃装满杂物的箱子。摇晃动作纯属随机,更准确地说,并非刻意让特定物品更紧密贴合。但持续摇晃终会使物品找到绝妙的排列方式。重力不允许它们松散排列,因此任何变化都是优化。[2] 写作亦是如此。改写生涩段落时,你永远不会朝"更不准确"的方向修改。这种结果令人难以忍受,就像物体违反重力向上漂浮。因此任何思想层面的调整必然趋向完善。 细想之下道理显而易见。音韵优美的文字更可能准确,正如充分摇晃的箱子更可能紧密填装。但还有更深层机制:音韵之美不仅是提升思想质量的外力,它确实能助你准确把握思想。 原因在于它提升了文章可读性。流畅的文字减轻了阅读负担。这对作者有何裨益?因为作者正是首位读者。撰写文章时,我的阅读时间远超写作时间。某些段落会重读50到100遍,反复琢磨其中思想,像打磨木材般自问:是否有阻滞?是否有违和?文章越易读,越容易察觉问题。 因此,优秀写作的两个维度至少通过两种方式关联:追求音韵之美既能无意识地修正错误,也能有意识地协助修正;既摇晃了思想之箱,又让错误更易显现。但解开一层荒谬之后,我忍不住要补充更惊人的观点:音韵之美仅止于辅助思想准确吗?音韵优美的文字是否本质上更可能准确?尽管看似疯狂,我认为确实如此。 单个词汇层面显然存在关联。英语中大量词汇的发音与其含义神似,且往往以精妙方式呈现。Glitter(闪烁). Round(圆润). Scrape(刮擦). Prim(拘谨).
Trying to make writing sound good makes you fix mistakes unconsciously, and also helps you fix them consciously; it shakes the bin of ideas, and also makes mistakes easier to see. But now that we've dissolved one layer of preposterousness, I can't resist adding another. Does sounding good do more than just help you get the ideas right? Is writing that sounds good _inherently_ more likely to be right? Crazy as it may seem, I think that's true too. Obviously there's a connection at the level of individual words. There are lots of words in English that sound like what they mean, often in wonderfully subtle ways. Glitter. Round. Scrape. Prim. Cavalcade. But the sound of good writing depends even more on the way you put words together, and there's a connection at that level too. When writing sounds good, it's mostly because it has good rhythm. But the rhythm of good writing is not the rhythm of music, or the meter of verse. It's not so regular. If it were, it wouldn't be good, because the rhythm of good writing has to match the ideas in it, and ideas have all kinds of different shapes. Sometimes they're simple and you just state them. But other times they're more subtle, and you need longer, more complicated sentences to tease out all the implications. An essay is a cleaned up train of thought, in the same way dialogue is cleaned up conversation, and a train of thought has a natural rhythm. So when an essay sounds good, it's not merely because it has a pleasing rhythm, but because it has its natural one. Which means you can use getting the rhythm right as a heuristic for getting the ideas right. And not just in principle: good writers do both simultaneously as a matter of course. Often I don't even distinguish between the two problems. I just think Ugh, this doesn't sound right; what do I mean to say here? [3] The sound of writing turns out to be more like the shape of a plane than the color of a car.
If it looks good, as Kelly Johnson used to say, it will fly well. This is only true of writing that's used to develop ideas, though. It doesn't apply when you have ideas in some other way and then write about them afterward — for example, if you build something, or conduct an experiment, and then write a paper about it. In such cases the ideas often live more in the work than the writing, so the writing can be bad even though the ideas are good. The writing in textbooks and popular surveys can be bad for the same reason: the author isn't developing the ideas, merely describing other people's. It's only when you're writing to develop ideas that there's such a close connection between the two senses of doing it well. Ok, many people will be thinking, this seems plausible so far, but what about liars? Is it not notoriously possible for a smooth-tongued liar to write something beautiful that's completely false? It is, of course. But not without method acting. The way to write something beautiful and false is to begin by making yourself almost believe it. So just like someone writing something beautiful and true, you're presenting a perfectly-formed train of thought. The difference is the point where it attaches to the world. You're saying something that would be true if certain false premises were. If for some bizarre reason the number of jobs in a country were fixed, then immigrants really would be taking our jobs. So it's not quite right to say that better sounding writing is more likely to be true. Better sounding writing is more likely to be internally consistent. If the writer is honest, internal consistency and truth converge. But while we can't safely conclude that beautiful writing is true, it's usually safe to conclude the converse: something that seems clumsily written will usually have gotten the ideas wrong too. Indeed, the two senses of good writing are more like two ends of the same thing.
The connection between them is not a rigid one; the goodness of good writing is not a rod but a rope, with multiple overlapping connections running through it. But it's hard to move one end without moving the other. It's hard to be right without sounding right. Notes [1] The closest thing to an exception is when you have to go back and insert a new point into the middle of something you've written. This often messes up the flow, sometimes in ways you can never quite repair. But I think the ultimate source of this problem is that ideas are tree-shaped and essays are linear. You inevitably run into difficulties when you try to cram the former into the latter. Frankly it's surprising how much you can get away with. But even so you sometimes have to resort to an endnote. [2] Obviously if you shake the bin hard enough the objects in it can become less tightly packed. And similarly, if you imposed some huge external constraint on your writing, like using alternating one and two syllable words, the ideas would start to suffer. [3] Bizarrely enough, this happened in the writing of this very paragraph. An earlier version shared several phrases in common with the preceding paragraph, and the repetition bugged me each time I reread it. When I got annoyed enough to fix it, I discovered that the repetition reflected a problem in the underlying ideas, and I fixed both simultaneously. Thanks to Jessica Livingston and Courtenay Pipkin for reading drafts of this..
Cavalcade(行列)。但优秀写作的音韵更取决于词语组合方式,这个层面同样存在关联。 优美文笔主要源于良好节奏。但优秀写作的节奏不同于音乐韵律或诗歌格律,它并不规则。规则化的节奏反而不好,因为写作节奏必须匹配思想脉络,而思想形态千差万别。有时思想简单只需直陈,有时思想精妙需要长句来梳理全部内涵。 文章是经过梳理的思想轨迹,如同对话是加工的交谈,而思想轨迹自有其天然节奏。因此文章音韵优美不仅因其节奏悦耳,更因其符合自然节奏。这意味着你可以将节奏调整作为思想校准的启发式方法。优秀作家在实践中往往同步解决这两个问题,我经常难以区分二者,只会觉得"这段听起来不对——我究竟想表达什么?"[3] 写作音韵更像是飞机造型而非汽车颜色。正如凯利·约翰逊所言:看起来对的飞机,飞起来自然好。 但这仅适用于发展思想的写作。若通过其他方式获得思想再行撰文——比如建造某物或进行实验后撰写论文——此法则不适用。此类情况下思想更多存在于工作中而非文字里,因此可能出现思想优质而文笔拙劣的情况。教科书和科普读物的文笔不佳同理:作者并非发展思想,只是转述他人观点。唯有通过写作发展思想时,优秀写作的两个维度才会如此紧密相连。 此刻许多人会想:以上论述看似合理,但骗子又当如何?巧舌如簧的骗子难道不能写出优美而完全虚假的文字吗? 当然可以。但必须借助方法派演技。创作优美谎言首先要让自己几乎信以为真。因此与创作优美真理相同,你呈现的是完美成型的思想轨迹。区别在于其与现实世界的连接点。你陈述的是"若某些错误前提成立则为真"的命题。如果某国工作岗位数量因荒诞理由固定不变,那么移民确实会抢走我们的工作。 因此"音韵优美的文字更可能为真"的表述并不完全准确。更准确的说法是:音韵优美的文字更可能保持内在一致性。若作者诚实,内在一致性与真理自会重合。 虽然不能断言优美文字必然真实,但反过来通常成立:文笔拙劣的作品通常也存在思想谬误。 事实上,优秀写作的两个维度更像是同一事物的两端。其联系并非刚性连接——优秀写作的"好"不是铁棍而是绳索,由多重交织的关联构成。但移动一端很难不牵动另一端。难以想象思想准确却音韵失调的文字。 注释 [1] 最接近例外的情况是:当你需要在已完成的文章中段插入新观点时。这通常会破坏行文流畅性,有时甚至无法完全修复。我认为根本原因在于思想呈树状结构而文章必须线性展开。将前者塞进后者难免遇到困难。说实话,我们目前的处理方式已算得上奇迹。但即便如此,有时仍不得不借助尾注。 [2] 显然过度摇晃会使箱内物品更松散。同理,若对写作施加某些极端限制(如交替使用单双音节词),思想表达就会受损。 [3] 离奇的是,本段写作时就发生了这种情况。前几个版本与上一段存在多处重复短语,每次重读都让我如鲠在喉。当我终于忍无可忍着手修改时,发现重复正反映了底层思想的问题,于是同步解决了这两个问题。 致谢 感谢杰西卡·利文斯顿和柯特妮·皮普金阅读本文草稿。.
March 2025 What should one do? That may seem a strange question, but it's not meaningless or unanswerable. It's the sort of question kids ask before they learn not to ask big questions. I only came across it myself in the process of investigating something else. But once I did, I thought I should at least try to answer it. So what _should_ one do? One should help people, and take care of the world. Those two are obvious. But is there anything else? When I ask that, the answer that pops up is _Make good new things_. I can't prove that one should do this, any more than I can prove that one should help people or take care of the world. We're talking about first principles here. But I can explain why this principle makes sense. The most impressive thing humans can do is to think. It may be the most impressive thing that can be done. And the best kind of thinking, or more precisely the best proof that one has thought well, is to make good new things. I mean new things in a very general sense. Newton's physics was a good new thing. Indeed, the first version of this principle was to have good new ideas. But that didn't seem general enough: it didn't include making art or music, for example, except insofar as they embody new ideas. And while they may embody new ideas, that's not all they embody, unless you stretch the word "idea" so uselessly thin that it includes everything that goes through your nervous system. Even for ideas that one has consciously, though, I prefer the phrasing "make good new things." There are other ways to describe the best kind of thinking. To make discoveries, for example, or to understand something more deeply than others have. But how well do you understand something if you can't make a model of it, or write about it? Indeed, trying to express what you understand is not just a way to prove that you understand it, but a way to understand it better.
人应当做什么?这看似是个奇怪的问题,却并非无意义或不可回答。这是孩子们在学会回避宏大问题前常问的那种问题。我本人也是在探究其他问题时偶然触及它的。但既然遇到了,我想至少应该尝试回答。
那么人究竟_应当_做什么?人应当帮助他人,并守护这个世界。这两点显而易见。但还有其他吗?当我这样问时,脑海中浮现的答案是_创造美好的新事物_。
我无法证明人必须这样做,就像我无法证明人必须帮助他人或守护世界。我们讨论的是最根本的原则。但我可以解释这个原则的合理性。人类最非凡的能力是思考——这可能是宇宙间最非凡的行为。而最佳思考的证明,或更准确地说,深思熟虑的最佳证据,就是创造出美好的新事物。
这里的"新事物"是广义的。牛顿的物理学是美好的新事物。最初这个原则的表述本是"产生美好的新想法",但显得不够普适:例如它未能涵盖艺术或音乐创作,除非将其勉强归为"体现新想法"的产物。尽管艺术可能蕴含新想法,但这并非其全部本质,除非将"想法"一词稀释到能囊括所有神经活动的地步。
Another reason I like this phrasing is that it biases us toward creation. It causes us to prefer the kind of ideas that are naturally seen as making things rather than, say, making critical observations about things other people have made. Those are ideas too, and sometimes valuable ones, but it's easy to trick oneself into believing they're more valuable than they are. Criticism seems sophisticated, and making new things often seems awkward, especially at first; and yet it's precisely those first steps that are most rare and valuable. Is newness essential? I think so. Obviously it's essential in science. If you copied a paper of someone else's and published it as your own, it would seem not merely unimpressive but dishonest. And it's similar in the arts. A copy of a good painting can be a pleasing thing, but it's not impressive in the way the original was. Which in turn implies it's not impressive to make the same thing over and over, however well; you're just copying yourself. Note though that we're talking about a different kind of should with this principle. Taking care of people and the world are shoulds in the sense that they're one's duty, but making good new things is a should in the sense that this is how to live to one's full potential. Historically most rules about how to live have been a mix of both kinds of should, though usually with more of the former than the latter. [1] For most of history the question "What should one do?" got much the same answer everywhere, whether you asked Cicero or Confucius. You should be wise, brave, honest, temperate, and just, uphold tradition, and serve the public interest. There was a long stretch where in some parts of the world the answer became "Serve God," but in practice it was still considered good to be wise, brave, honest, temperate, and just, uphold tradition, and serve the public interest. And indeed this recipe would have seemed right to most Victorians.
即便对于有意识产生的想法,我也更倾向"创造美好新事物"的表述。描述最佳思考还有其他方式,比如"做出发现"或"获得比他人更深刻的理解"。但若无法建立模型或撰写论述,这种理解又有多深刻?事实上,尝试表达你的理解不仅是证明理解的方式,更是深化理解的途径。
我偏爱这个表述的另一原因是它偏向创造。它促使我们青睐那些自然被视为"制造事物"的想法,而非对他人成果的批评性观察。后者同样属于想法,有时也具价值,但人们容易自欺地高估其价值。批评看似高明,而创造新事物常显得笨拙——尤其在初期;然而正是这些笨拙的第一步最为稀有珍贵。
"新"是否必要?我认为是。科学领域自不待言:抄袭他人论文发表不仅是平庸更是欺诈。艺术亦然。优秀画作的复制品或许悦目,却无法媲美原作震撼力。这也意味着重复制作相同事物——无论多完美——都不足称道,那不过是自我复制。
需注意这条原则中的"应当"与前两者性质不同。照顾他人与守护世界是责任层面的"应当",而创造美好新事物是实现潜能的"应当"。历史上多数生活准则都是这两种"应当"的混合,通常前者占比更大。[1]
But there's nothing in it about taking care of the world or making new things, and that's a bit worrying, because it seems like this question should be a timeless one. The answer shouldn't change much. I'm not too worried that the traditional answers don't mention taking care of the world. Obviously people only started to care about that once it became clear we could ruin it. But how can making good new things be important if the traditional answers don't mention it? The traditional answers were answers to a slightly different question. They were answers to the question of how to be, rather than what to do. The audience didn't have a lot of choice about what to do. The audience up till recent centuries was the landowning class, which was also the political class. They weren't choosing between doing physics and writing novels. Their work was foreordained: manage their estates, participate in politics, fight when necessary. It was ok to do certain other kinds of work in one's spare time, but ideally one didn't have any. Cicero's _De Officiis_ is one of the great classical answers to the question of how to live, and in it he explicitly says that he wouldn't even be writing it if he hadn't been excluded from public life by recent political upheavals. [2] There were of course people doing what we would now call "original work," and they were often admired for it, but they weren't seen as models. Archimedes knew that he was the first to prove that a sphere has 2/3 the volume of the smallest enclosing cylinder and was very pleased about it. But you don't find ancient writers urging their readers to emulate him. They regarded him more as a prodigy than a model. Now many more of us can follow Archimedes's example and devote most of our attention to one kind of work.
长久以来,"人应当做什么"的答案各地趋同,无论询问西塞罗还是孔子:应当智慧、勇敢、诚实、节制、公正,维护传统,服务公益。某些历史时期部分地区答案变为"侍奉上帝",但实践中前述品质仍被推崇。维多利亚时代多数人也会认同这个配方。但其中既无守护世界,也无创新,这令人忧虑——因为这个问题本应永恒,答案不该大改。
传统答案未提及守护世界我并不担忧,显然人类是在意识到可能毁灭世界后才开始关注这点。但若创造美好新事物如此重要,为何传统答案只字未提?
传统答案回答的是稍不同的问题:它们解答的是"如何为人"而非"如何行事"。古代受众对"做什么"并无太多选择。直至近代,受众始终是同时作为统治阶级的地主阶层。他们并非在从事物理或写小说间抉择,其职责早已注定:管理地产、参与政治、必要时作战。业余从事其他工作虽可接受,但理想状态是无业余时间。西塞罗《论义务》是古典时期对生活之道的伟大解答,其中他明确表示,若非政治动荡使他退出公共生活,他根本不会撰写此书。[2]
当然存在从事我们所谓"原创工作"的人,他们也常受钦佩,但未被视作典范。阿基米德自知是首位证明球体体积等于外切圆柱体积2/3的人并深感欣喜,但古代作家从不鼓励读者效仿他。他被视为天才而非楷模。
He turned out to be a model after all, along with a collection of other people that his contemporaries would have found it strange to treat as a distinct group, because the vein of people making new things ran at right angles to the social hierarchy. What kinds of new things count? I'd rather leave that question to the makers of them. It would be a risky business to try to define any kind of threshold, because new kinds of work are often despised at first. Raymond Chandler was writing literal pulp fiction, and he's now recognized as one of the best writers of the twentieth century. Indeed this pattern is so common that you can use it as a recipe: if you're excited about some kind of work that's not considered prestigious and you can explain what everyone else is overlooking about it, then this is not merely a kind of work that's ok to do, but one to seek out. The other reason I wouldn't want to define any thresholds is that we don't need them. The kind of people who make good new things don't need rules to keep them honest. So there's my guess at a set of principles to live by: take care of people and the world, and make good new things. Different people will do these to varying degrees. There will presumably be lots who focus entirely on taking care of people. There will be a few who focus mostly on making new things. But even if you're one of those, you should at least make sure that the new things you make don't net _harm_ people or the world. And if you go a step further and try to make things that help them, you may find you're ahead on the trade. You'll be more constrained in what you can make, but you'll make it with more energy. On the other hand, if you make something amazing, you'll often be helping people or the world even if you didn't mean to. Newton was driven by curiosity and ambition, not by any practical effect his work might have, and yet the practical effect of his work has been enormous.
如今更多人能效法阿基米德,将主要精力投入某类工作。他终究成为了楷模,与一群同时代人眼中难以归类的创新者一起——因为创新者的脉络与社会阶层正交。
哪些新事物算数?我宁愿将此问题留给创造者。设定任何标准都风险巨大,因为新型工作常初遭轻视。雷蒙德·钱德勒写的是名副其实的廉价小说,如今却被誉为二十世纪最杰出作家之一。这种模式如此普遍,以至可总结为诀窍:若你对某种不受重视的工作充满热情,并能解释众人忽视的价值,那么这不仅是可做的工作,更值得追寻。
我不愿设定标准的另一原因是我们无需它们。创造美好新事物的人本就不需要规则约束。
这就是我提出的一套生活原则:守护人与世界,创造美好新事物。不同人会有不同侧重。有人会完全专注于守护他人,少数人则主要致力于创新。但即便你是后者,至少应确保你的创造不会对人或世界造成净伤害。若更进一步,尝试创造有益之物,你可能会发现回报超出预期:虽受更多限制,却会获得更大能量。
And this seems the rule rather than the exception. So if you think you can make something amazing, you should probably just go ahead and do it. Notes [1] We could treat all three as the same kind of should by saying that it's one's duty to live well — for example by saying, as some Christians have, that it's one's duty to make the most of one's God-given gifts. But this seems one of those casuistries people invented to evade the stern requirements of religion: it was permissible to spend time studying math instead of praying or performing acts of charity because otherwise you were rejecting a gift God had given you. A useful casuistry no doubt, but we don't need it. We could also combine the first two principles, since people are part of the world. Why should our species get special treatment? I won't try to justify this choice, but I'm skeptical that anyone who claims to think differently actually lives according to their principles. [2] Confucius was also excluded from public life after ending up on the losing end of a power struggle, and presumably he too would not be so famous now if it hadn't been for this long stretch of enforced leisure. Thanks to Trevor Blackwell, Jessica Livingston, and Robert Morris for reading drafts of this..
反之,若你创造出非凡之物,即使无意也常会惠及他人与世界。牛顿受好奇心与野心驱动,而非其工作的实际影响,但其成果的实际影响无比巨大。这似乎是常态而非例外。因此若你认为自己能创造非凡之物,或许就该放手去做。
[1] 我们可将三者归为同类"应当",声称好好生活是种义务——例如像某些基督徒所言,充分利用上帝赐予的天赋是责任。但这看似是为逃避宗教严规发明的诡辩:允许研究数学而非祈祷或行善,因为否则就是拒绝神赐。这种诡辩无疑有用,但我们无需它。
前两条原则也可合并,毕竟人类属于世界。为何我们物种要特殊对待?我不试图辩护这个选择,但怀疑任何声称持相反原则者真能践行。
[2] 孔子在权力斗争中失败后同样退出公共生活,若非这段被迫赋闲的漫长岁月,想必他也不会如此闻名。
致谢 特雷弗·布莱克韦尔、杰西卡·利文斯顿和罗伯特·莫里斯阅读了本文草稿。
January 2025 The word "prig" isn't very common now, but if you look up the definition, it will sound familiar. Google's isn't bad: > A self-righteously moralistic person who behaves as if superior to others.
"道学先生"这个词如今已不常见,但若查阅其定义,定会感到似曾相识。谷歌给出的解释颇为贴切:
> 自以为是、好为人师之人,行事作风宛如高人一等。
This sense of the word originated in the 18th century, and its age is an important clue: it shows that although wokeness is a comparatively recent phenomenon, it's an instance of a much older one. There's a certain kind of person who's attracted to a shallow, exacting kind of moral purity, and who demonstrates his purity by attacking anyone who breaks the rules. Every society has these people. All that changes is the rules they enforce. In Victorian England it was Christian virtue. In Stalin's Russia it was orthodox Marxism-Leninism. For the woke, it's social justice. So if you want to understand wokeness, the question to ask is not why people behave this way. Every society has prigs. The question to ask is why our prigs are priggish about these ideas, at this moment. And to answer that we have to ask when and where wokeness began. The answer to the first question is the 1980s. Wokeness is a second, more aggressive wave of political correctness, which started in the late 1980s, died down in the late 1990s, and then returned with a vengeance in the early 2010s, finally peaking after the riots of 2020. What was political correctness, exactly? I'm often asked to define both this term and wokeness by people who think they're meaningless labels, so I will. They both have the same definition:
该词义起源于18世纪,其年代本身便是重要线索:它表明尽管"觉醒主义"是相对晚近的现象,却隶属于一种更为古老的行为模式。
世上总有一类人,他们痴迷于肤浅而严苛的道德纯洁性,并通过攻击违规者来标榜自身纯粹。每个社会都不乏此类人。变化的只是他们执守的教条——在维多利亚时代的英格兰是基督教美德,在斯大林时期的俄国是正统马列主义,对觉醒者而言则是社会正义。
因此若要理解觉醒主义,关键不在于追问人们为何如此行事(每个时代都有道学先生),而在于探究为何当下我们的道学先生偏偏执着于这些理念。要解答这个问题,就必须追溯觉醒主义的时空起源。
> An aggressively performative focus on social justice.
第一个问题的答案指向1980年代。觉醒主义是政治正确掀起的第二波更激进的浪潮——政治正确始于1980年代末,1990年代末式微,2010年代初卷土重来,最终在2020年骚乱后达到顶峰。
究竟何为政治正确?常有人请我定义这个与觉醒主义同样被视作空洞标签的术语,我的回答是:二者共享同一内核——
> 对社会正义充满攻击性的表演式关注。
In other words, it's people being prigs about social justice. And that's the real problem — the performativeness, not the social justice. [0] Racism, for example, is a genuine problem. Not a problem on the scale that the woke believe it to be, but a genuine one. I don't think any reasonable person would deny that. The problem with political correctness was not that it focused on marginalized groups, but the shallow, aggressive way in which it did so. Instead of going out into the world and quietly helping members of marginalized groups, the politically correct focused on getting people in trouble for using the wrong words to talk about them. As for where political correctness began, if you think about it, you probably already know the answer. Did it begin outside universities and spread to them from this external source? Obviously not; it has always been most extreme in universities. So where in universities did it begin? Did it begin in math, or the hard sciences, or engineering, and spread from there to the humanities and social sciences? Those are amusing images, but no, obviously it began in the humanities and social sciences. Why there? And why then? What happened in the humanities and social sciences in the 1980s? A successful theory of the origin of political correctness has to be able to explain why it didn't happen earlier. Why didn't it happen during the protest movements of the 1960s, for example? They were concerned with much the same issues. [1] The reason the student protests of the 1960s didn't lead to political correctness was precisely that — they were student movements. They didn't have any real power. The students may have been talking a lot about women's liberation and black power, but it was not what they were being taught in their classes. Not yet. But in the early 1970s the student protestors of the 1960s began to finish their dissertations and get hired as professors.
换言之,这是一群人在社会正义议题上摆出道德优越的姿态。真正的问题在于这种表演性,而非社会正义本身。[0]
以种族主义为例,这确实是个问题——虽不及"觉醒派"所认为的严重程度,但确实存在。任何理性人都不会否认这点。政治正确的问题不在于它关注边缘群体,而在于其肤浅且充满攻击性的方式。政治正确派不是默默帮助现实中的边缘群体,而是热衷于揪住人们谈论这些群体时用词不当的把柄。
At first they were neither powerful nor numerous. But as more of their peers joined them and the previous generation of professors started to retire, they gradually became both. The reason political correctness began in the humanities and social sciences was that these fields offered more scope for the injection of politics. A 1960s radical who got a job as a physics professor could still attend protests, but his political beliefs wouldn't affect his work. Whereas research in sociology and modern literature can be made as political as you like. [2] I saw political correctness arise. When I started college in 1982 it was not yet a thing. Female students might object if someone said something they considered sexist, but no one was getting _reported_ for it. It was still not a thing when I started grad school in 1986. It was definitely a thing in 1988 though, and by the early 1990s it seemed to pervade campus life. What happened? How did protest become punishment? Why were the late 1980s the point at which protests against male chauvinism (as it used to be called) morphed into formal complaints to university authorities about sexism? Basically, the 1960s radicals got tenure. They became the Establishment they'd protested against two decades before. Now they were in a position not just to speak out about their ideas, but to enforce them. A new set of moral rules to enforce was exciting news to a certain kind of student. What made it particularly exciting was that they were allowed to attack professors. I remember noticing that aspect of political correctness at the time. It wasn't simply a grass-roots student movement. It was faculty members encouraging students to attack other faculty members. In that respect it was like the Cultural Revolution. That wasn't a grass-roots movement either; that was Mao unleashing the younger generation on his political opponents.
若要追溯政治正确的起源,细想之下答案已呼之欲出。它是从校外传入大学的吗?显然不是,大学始终是其最极端的温床。那么大学里哪个学科是发源地?数学、自然科学还是工程学,再蔓延至人文社科?这些设想颇具喜剧效果,但真相显而易见:它始于人文与社会科学领域。
为何是这些学科?又为何始于1980年代?当时这些领域发生了什么?
任何成功的政治正确起源理论都必须解释它为何没更早出现。比如1960年代抗议运动时期,人们关注的议题何其相似,为何当时未形成气候?[1]
And in fact when Roderick MacFarquhar started teaching a class on the Cultural Revolution at Harvard in the late 1980s, many saw it as a comment on current events. I don't know if it actually was, but people thought it was, and that means the similarities were obvious. [3] College students larp. It's their nature. It's usually harmless. But larping morality turned out to be a poisonous combination. The result was a kind of moral etiquette, superficial but very complicated. Imagine having to explain to a well-meaning visitor from another planet why using the phrase "people of color" is considered particularly enlightened, but saying "colored people" gets you fired. And why exactly one isn't supposed to use the word "negro" now, even though Martin Luther King used it constantly in his speeches. There are no underlying principles. You'd just have to give him a long list of rules to memorize. [4] The danger of these rules was not just that they created land mines for the unwary, but that their elaborateness made them an effective substitute for virtue. Whenever a society has a concept of heresy and orthodoxy, orthodoxy becomes a substitute for virtue. You can be the worst person in the world, but as long as you're orthodox you're better than everyone who isn't. This makes orthodoxy very attractive to bad people. But for it to work as a substitute for virtue, orthodoxy must be difficult. If all you have to do to be orthodox is wear some garment or avoid saying some word, everyone knows to do it, and the only way to seem more virtuous than other people is to actually be virtuous. The shallow, complicated, and frequently changing rules of political correctness made it the perfect substitute for actual virtue. And the result was a world in which good people who weren't up to date on current moral fashions were brought down by people whose characters would make you recoil in horror if you could see them.
1960年代学生运动未能催生政治正确,恰恰因为那只是学生运动——他们缺乏实质权力。学生们可能大谈妇女解放和黑人权力,但这些并非课堂传授的内容。至少当时还不是。
转折点在1970年代初,1960年代的抗议学生陆续完成博士论文成为教授。起初他们人微言轻,但随着同辈不断加入及老一代教授退休,他们逐渐掌握了话语权。
政治正确始于人文社科,因这些领域更易注入政治色彩。1960年代的激进分子若成为物理学教授,仍可参加抗议活动,但其政治信念不会影响学术工作。而社会学与现代文学研究则能随心所欲地政治化。[2]
One big contributing factor in the rise of political correctness was the lack of other things to be morally pure about. Previous generations of prigs had been prigs mostly about religion and sex. But among the cultural elite these were the deadest of dead letters by the 1980s; if you were religious, or a virgin, this was something you tended to conceal rather than advertise. So the sort of people who enjoy being moral enforcers had become starved of things to enforce. A new set of rules was just what they'd been waiting for. Curiously enough, the tolerant side of the 1960s left helped create the conditions in which the intolerant side prevailed. The relaxed social rules advocated by the old, easy-going hippy left became the dominant ones, at least among the elite, and this left nothing for the naturally intolerant to be intolerant about. Another possibly contributing factor was the fall of the Soviet empire. Marxism had been a popular focus of moral purity on the left before political correctness emerged as a competitor, but the pro-democracy movements in Eastern Bloc countries took most of the shine off it. Especially the fall of the Berlin Wall in 1989. You couldn't be on the side of the Stasi. I remember looking at the moribund Soviet Studies section of a used bookshop in Cambridge in the late 1980s and thinking "what will those people go on about now?" As it turned out the answer was right under my nose. One thing I noticed at the time about the first phase of political correctness was that it was more popular with women than men. As many writers (perhaps most eloquently George Orwell) have observed, women seem more attracted than men to the idea of being moral enforcers. But there was another more specific reason women tended to be the enforcers of political correctness.
我亲历了政治正确的崛起。1982年我入读大学时它尚未成形,女生或许会反对某些被视为性别歧视的言论,但无人因此被举报。1986年我读研时依然如此。但到1988年它已蔚然成风,1990年代初更弥漫整个校园。
发生了什么?抗议如何演变成惩罚?为何1980年代末针对"大男子主义"(当时用语)的抗议会升级为向校方投诉性别歧视?根本原因在于:1960年代的激进分子获得了终身教职。他们成了二十年前自己抗议的"体制",如今不仅能宣扬理念,更能强制执行。
There was at this time a great backlash against sexual harassment; the mid 1980s were the point when the definition of sexual harassment was expanded from explicit sexual advances to creating a "hostile environment." Within universities the classic form of accusation was for a (female) student to say that a professor made her "feel uncomfortable." But the vagueness of this accusation allowed the radius of forbidden behavior to expand to include talking about heterodox ideas. Those make people uncomfortable too. [5] Was it sexist to propose that Darwin's greater male variability hypothesis might explain some variation in human performance? Sexist enough to get Larry Summers pushed out as president of Harvard, apparently. One woman who heard the talk in which he mentioned this idea said it made her feel "physically ill" and that she had to leave halfway through. If the test of a hostile environment is how it makes people feel, this certainly sounds like one. And yet it does seem plausible that greater male variability explains some of the variation in human performance. So which should prevail, comfort or truth? Surely if truth should prevail anywhere, it should be in universities; that's supposed to be their specialty; but for decades starting in the late 1980s the politically correct tried to pretend this conflict didn't exist. [6] Political correctness seemed to burn out in the second half of the 1990s. One reason, perhaps the main reason, was that it literally became a joke. It offered rich material for comedians, who performed their usual disinfectant action upon it. Humor is one of the most powerful weapons against priggishness of any sort, because prigs, being humorless, can't respond in kind. Humor was what defeated Victorian prudishness, and by 2000 it seemed to have done the same thing to political correctness. Unfortunately this was an illusion. Within universities the embers of political correctness were still glowing brightly.
对某些学生而言,这套新道德准则令人兴奋——尤其当他们获准攻击教授时。我清楚记得政治正确的这个特征:它并非纯粹的学生自发运动,而是教职人员鼓动学生攻击其他教员。这方面它酷似文化大革命,后者也非群众自发,而是毛泽东释放年轻一代对付政敌。1980年代末哈佛大学罗德里克·麦克法夸尔开设文革课程时,许多人视其为对时事的影射。无论是否属实,这种联想本身已说明两者的相似性昭然若揭。[3]
大学生热衷角色扮演,这本无伤大雅。但当道德成为扮演对象时,却产生了剧毒组合——形成一套肤浅却繁复的道德礼仪。试想如何向善意来访的外星人解释:用"有色人种"是进步,说"有色人民"会丢工作?为何如今禁用"negro"一词,尽管马丁·路德·金演讲中频繁使用?这些规则毫无底层逻辑,只能列出一长串条目要求死记硬背。[4]
这类规则的危险不仅在于为不慎者埋雷,更因其复杂性使其成为美德的完美替代品。当社会存在"异端/正统"概念时,正统性就成了道德优越的凭证。哪怕你是世上最恶劣之人,只要皈依正统就比所有异端高尚——这使正统对恶人格外诱人。
After all, the forces that created it were still there. The professors who started it were now becoming deans and department heads. And in addition to their departments there were now a bunch of new ones explicitly focused on social justice. Students were still hungry for things to be morally pure about. And there had been an explosion in the number of university administrators, many of whose jobs involved enforcing various forms of political correctness. In the early 2010s the embers of political correctness burst into flame anew. There were several differences between this new phase and the original one. It was more virulent. It spread further into the real world, although it still burned hottest within universities. And it was concerned with a wider variety of sins. In the first phase of political correctness there were really only three things people got accused of: sexism, racism, and homophobia (which at the time was a neologism invented for the purpose). But between then and 2010 a lot of people had spent a lot of time trying to invent new kinds of -isms and -phobias and seeing which could be made to stick. The second phase was, in multiple senses, political correctness metastasized. Why did it happen when it did? My guess is that it was due to the rise of social media, particularly Tumblr and Twitter, because one of the most distinctive features of the second wave of political correctness was the _cancel mob_ : a mob of angry people uniting on social media to get someone ostracized or fired. Indeed this second wave of political correctness was originally called "cancel culture"; it didn't start to be called "wokeness" till the 2020s. One aspect of social media that surprised almost everyone at first was the popularity of outrage. Users seemed to _like_ being outraged. We're so used to this idea now that we take it for granted, but really it's pretty strange. Being outraged is not a pleasant feeling. You wouldn't expect people to seek it out.
但要让正统性替代美德,它必须足够艰深。若只需穿戴特定服饰或规避某些词汇就能标榜正统,人人都能做到,唯有真正践行美德才能脱颖而出。政治正确那些肤浅、复杂且频繁变更的规则,恰好成为真实美德的最佳代用品。结果造就了这样的世界:跟不上道德时尚的好人被扳倒,而扳倒他们之人的真实品性若被窥见,定会令人毛骨悚然。
政治正确兴起的重大诱因,是其他可供标榜道德纯洁的领域已然枯竭。前几代卫道士主要在宗教与性道德上做文章,但对1980年代的文化精英而言,这些早成腐朽教条——信教或守贞反而需要遮掩而非炫耀。于是道德警察们陷入"无物可纠"的饥渴状态,新规则体系正是他们梦寐以求的猎物。
耐人寻味的是,1960年代左翼的宽容一面,反而为不宽容派的胜出创造了条件。老派嬉皮左翼倡导的宽松社会规则成为主流(至少在精英阶层),使得天生不宽容者失去了发泄对象。
But they do. And above all, they want to share it. I happened to be running a forum from 2007 to 2014, so I can actually quantify how much they want to share it: our users were about three times more likely to upvote something if it outraged them. This tilt toward outrage wasn't due to wokeness. It's an inherent feature of social media, or at least this generation of it. But it did make social media the perfect mechanism for fanning the flames of wokeness. [7] It wasn't just public social networks that drove the rise of wokeness though. Group chat apps were also critical, especially in the final step, cancellation. Imagine if a group of employees trying to get someone fired had to do it using only email. It would be hard to organize a mob. But once you have group chat, mobs form naturally. Another contributing factor in this second wave of political correctness was the dramatic increase in the polarization of the press. In the print era, newspapers were constrained to be, or at least seem, politically neutral. The department stores that ran ads in the New York Times wanted to reach everyone in the region, both liberal and conservative, so the Times had to serve both. But the Times didn't regard this neutrality as something forced upon them. They embraced it as their duty as a _paper of record_ — as one of the big newspapers that aimed to be chronicles of their times, reporting every sufficiently important story from a neutral point of view. When I grew up the papers of record seemed timeless, almost sacred institutions. Papers like the New York Times and Washington Post had immense prestige, partly because other sources of news were limited, but also because they did make some effort to be neutral. Unfortunately it turned out that the paper of record was mostly an artifact of the constraints imposed by print. [8] When your market was determined by geography, you had to be neutral.
另一潜在推手是苏联解体。在政治正确崛起前,马克思主义曾是左翼标榜道德纯洁的热门选项,但东欧民主运动(尤其是1989年柏林墙倒塌)使其光环尽失。你无法再为斯塔西特务辩护。1980年代末我曾见剑桥二手书店里苏联研究专区的凋零景象,当时暗想:"这些人接下来该鼓吹什么?"答案其实近在眼前。
政治正确初期有个显著特征:女性参与者远多于男性。正如许多作家(或许以乔治·奥威尔最为雄辩)指出,女性似乎比男性更热衷担任道德警察。但还有个更具体的原因:当时正值反性骚扰运动高潮,1980年代中期其定义从明确性邀约扩展至制造"敌意环境"。大学里经典指控模式是(女生)声称某教授让她"感到不适"。这种模糊指控的边界可不断扩张,直至将讨论异端思想纳入禁区——毕竟这些也会让人不适。[5]
提出达尔文的"男性变异性更大假说"可能解释人类表现差异,是否构成性别歧视?显然足以让拉里·萨默斯丢掉哈佛校长职位。有位聆听其演讲的女性称自己"生理性反胃"并中途退场。若以听众感受作为敌意环境的判定标准,这确实达标。但男性变异性假说解释部分人类表现差异确实具有合理性。那么,舒适与真理孰轻孰重?若说真理应在何处占上风,大学本应首当其冲——这本是它们的专长。但自1980年代末起数十年间,政治正确派始终假装这个矛盾不存在。[6]
But publishing online enabled — in fact probably forced — newspapers to switch to serving markets defined by ideology instead of geography. Most that remained in business fell in the direction they'd already been leaning: left. On October 11, 2020 the New York Times announced that "The paper is in the midst of an evolution from the stodgy paper of record into a juicy collection of great narratives." [9] Meanwhile journalists, of a sort, had arisen to serve the right as well. And so journalism, which in the previous era had been one of the great centralizing forces, now became one of the great polarizing ones. The rise of social media and the increasing polarization of journalism reinforced one another. In fact there arose a new variety of journalism involving a loop through social media. Someone would say something controversial on social media. Within hours it would become a news story. Outraged readers would then post links to the story on social media, driving further arguments online. It was the cheapest source of clicks imaginable. You didn't have to maintain overseas news bureaus or pay for month-long investigations. All you had to do was watch Twitter for controversial remarks and repost them on your site, with some additional comments to inflame readers further. For the press there was money in wokeness. But they weren't the only ones. That was one of the biggest differences between the two waves of political correctness: the first was driven almost entirely by amateurs, but the second was often driven by professionals. For some it was their whole job. By 2010 a new class of administrators had arisen whose job was basically to enforce wokeness. They played a role similar to that of the political commissars who got attached to military and industrial organizations in the USSR: they weren't directly in the flow of the organization's work, but watched from the side to ensure that nothing improper happened in the doing of it.
1990年代后半叶,政治正确看似式微。主因或许是它彻底沦为笑柄——喜剧演员从中挖掘大量素材,发挥其惯有的消毒作用。幽默是对抗任何形式道德优越感的最强武器,因卫道士们缺乏幽默感,无法以牙还牙。维多利亚时代的假正经正是如此溃败,到2000年政治正确似乎也重蹈覆辙。
可惜这只是假象。大学里政治正确的余烬仍在炽燃——毕竟催生它的力量依然存在。始作俑者们已成为系主任或院长,除原有院系外,还新增了许多专注社会正义的学科。学生们仍渴求道德纯洁的标的,而大学行政人员数量激增,其中多数职责涉及维护各类政治正确。
These new administrators could often be recognized by the word "inclusion" in their titles. Within institutions this was the preferred euphemism for wokeness; a new list of banned words, for example, would usually be called an "inclusive language guide." [10] This new class of bureaucrats pursued a woke agenda as if their jobs depended on it, because they did. If you hire people to keep watch for a particular type of problem, they're going to find it, because otherwise there's no justification for their existence. [11] But these bureaucrats also represented a second and possibly even greater danger. Many were involved in hiring, and when possible they tried to ensure their employers hired only people who shared their political beliefs. The most egregious cases were the new "DEI statements" that some universities started to require from faculty candidates, proving their commitment to wokeness. Some universities used these statements as the initial filter and only even considered candidates who scored high enough on them. You're not hiring Einstein that way; imagine what you get instead. Another factor in the rise of wokeness was the Black Lives Matter movement, which started in 2013 when a white man was acquitted after killing a black teenager in Florida. But this didn't launch wokeness; it was well underway by 2013. Similarly for the Me Too Movement, which took off in 2017 after the first news stories about Harvey Weinstein's history of raping women. It accelerated wokeness, but didn't play the same role in launching it that the 80s version did in launching political correctness. The election of Donald Trump in 2016 also accelerated wokeness, particularly in the press, where outrage now meant traffic. Trump made the New York Times a lot of money: headlines during his first administration mentioned his name at about four times the rate of previous presidents.
2010年代初,政治正确死灰复燃。新阶段有几个特征:毒性更强;虽仍以大学为最烈,但更深入现实世界;罪名种类大幅扩充。政治正确初期仅有三大罪名:性别歧视、种族主义、恐同(当时为达此目的新造词)。而到2010年前,许多人耗费大量精力发明各种新式"主义"与"恐惧症",试验哪些能站稳脚跟。
从多重意义上说,第二阶段是政治正确的癌变。为何此时爆发?我猜主因是社交媒体(尤其是Tumblr与Twitter)的崛起,因第二波政治正确最鲜明特征正是"取消文化"——愤怒网民在社交媒体集结,对目标实施排斥或职场封杀。这波浪潮最初确实被称为"取消文化",直至2020年代才改称"觉醒主义"。
社交媒体初期最令人惊讶的现象,是众怒的传播效率。用户似乎享受被激怒的感觉——如今我们已对此习以为常,但这实则非常反常。愤怒本非愉悦体验,理当避之不及,但人们却主动追寻,尤其热衷分享。2007-2014年我运营论坛期间,曾量化统计这种现象:使用户愤怒的内容获得点赞的概率是普通内容的三倍。
In 2020 we saw the biggest accelerant of all, after a white police officer asphyxiated a black suspect on video. At this point the metaphorical fire became a literal one, as violent protests broke out across America. But in retrospect this turned out to be peak woke, or close to it. By every measure I've seen, wokeness peaked in 2020 or 2021. Wokeness is sometimes described as a mind-virus. What makes it viral is that it defines new types of impropriety. Most people are afraid of impropriety; they're never exactly sure what the social rules are or which ones they might be breaking. Especially if the rules change rapidly. And since most people already worry that they might be breaking rules they don't know about, if you tell them they're breaking a rule, their default reaction is to believe you. Especially if multiple people tell them. Which in turn is a recipe for exponential growth. Zealots invent some new impropriety to avoid. The first people to adopt it are fellow zealots, eager for new ways to signal their virtue. If there are enough of these, the initial group of zealots is followed by a much larger group, motivated by fear. They're not trying to signal virtue; they're just trying to avoid getting in trouble. At this point the new impropriety is now firmly established. Plus its success has increased the rate of change in social rules, which, remember, is one of the reasons people are nervous about which rules they might be breaking. So the cycle accelerates. [12] What's true of individuals is even more true of organizations. Especially organizations without a powerful leader. Such organizations do everything based on "best practices." There's no higher authority; if some new "best practice" achieves critical mass, they _must_ adopt it. And in this case the organization can't do what it usually does when it's uncertain: delay.
这种愤怒倾向并非觉醒主义导致,而是社交媒体的固有特性(至少当前世代如此)。但它确实为觉醒主义的蔓延提供了完美机制。[7]
不过推动觉醒主义崛起的不仅是公共社交网络。群聊应用同样关键,尤其在"取消"的最终环节。试想若员工想联合炒掉某人却只能用邮件沟通,很难形成暴民效应。但群聊功能让暴民集结水到渠成。
第二波政治正确的另一推手是媒体极化程度剧增。纸质时代报纸被约束(或至少假装)保持政治中立。在《纽约时报》投放广告的百货公司希望覆盖全地区(无论自由派或保守派)客户,因此时报必须兼顾双方。但时报并非被迫保持中立,而是将其视为"记录性报纸"的职责——作为旨在记录时代的大型报纸,应以中立视角报道所有重要事件。
It might be committing improprieties right now! So it's surprisingly easy for a small group of zealots to capture this type of organization by describing new improprieties it might be guilty of. [13] How does this kind of cycle ever end? Eventually it leads to disaster, and people start to say enough is enough. The excesses of 2020 made a lot of people say that. Since then wokeness has been in gradual but continual retreat. Corporate CEOs, starting with Brian Armstrong, have openly rejected it. Universities, led by the University of Chicago and MIT, have explicitly confirmed their commitment to free speech. Twitter, which was arguably the hub of wokeness, was bought by Elon Musk in order to neutralize it, and he seems to have succeeded — and not, incidentally, by censoring left-wing users the way Twitter used to censor right-wing ones, but without censoring either. [14] Consumers have emphatically rejected brands that ventured too far into wokeness. The Bud Light brand may have been permanently damaged by it. I'm not going to claim Trump's second victory in 2024 was a referendum on wokeness; I think he won, as presidential candidates always do, because he was more _charismatic_; but voters' disgust with wokeness must have helped. So what do we do now? Wokeness is already in retreat. Obviously we should help it along. What's the best way to do that? And more importantly, how do we avoid a third outbreak? After all, it seemed to be dead once, but came back worse than ever. In fact there's an even more ambitious goal: is there a way to prevent any similar outbreak of aggressively performative moralism in the future — not just a third outbreak of political correctness, but the next thing like it? Because there will be a next thing. Prigs are prigs by nature. They need rules to obey and enforce, and now that Darwin has cut off their traditional supply of rules, they're constantly hungry for new ones.
在我成长年代,这类报纸宛如永恒的神圣机构。《纽约时报》《华盛顿邮报》享有巨大威望,部分因新闻来源有限,更因它们确实努力保持中立。
可惜后来证明,"记录性报纸"本质是纸质时代约束的产物。[8]当市场由地理划分时,中立是必须;而网络出版促使(甚至迫使)报纸转向以意识形态划分市场。幸存者大多倒向原本倾向的方向:左翼。2020年10月11日《纽约时报》宣布:"本报正从古板的记录性报纸转型为精彩叙事集合体。"[9]与此同时,某种为右翼服务的"新闻工作者"也应运而生。于是新闻业从上个时代的伟大凝聚力量,蜕变为巨大分化力量。
All they need is someone to meet them halfway by defining a new way to be morally pure, and we'll see the same phenomenon again. Let's start with the easier problem. Is there a simple, principled way to deal with wokeness? I think there is: to use the customs we already have for dealing with religion. Wokeness is effectively a religion, just with God replaced by protected classes. It's not even the first religion of this kind; Marxism had a similar form, with God replaced by the masses. [15] And we already have well-established customs for dealing with religion within organizations. You can express your own religious identity and explain your beliefs, but you can't call your coworkers infidels if they disagree, or try to ban them from saying things that contradict its doctrines, or insist that the organization adopt yours as its official religion. If we're not sure what to do about any particular manifestation of wokeness, imagine we were dealing with some other religion, like Christianity. Should we have people within organizations whose jobs are to enforce woke orthodoxy? No, because we wouldn't have people whose jobs were to enforce Christian orthodoxy. Should we censor _writers_ or _scientists_ whose work contradicts woke doctrines? No, because we wouldn't do this to people whose work contradicted Christian teachings. Should job candidates be required to write DEI statements? Of course not; imagine an employer requiring proof of one's religious beliefs.
社交媒体崛起与新闻业极化相互强化。甚至催生了通过社交媒体闭环的新型新闻模式:某人在社交平台发表争议言论→几小时内成为新闻→愤怒读者在社交媒分享报道→引发更多线上争论。这是想象得到的最廉价点击量来源——无需维持海外记者站或资助数月调查,只需盯着Twitter抓取争议言论,添油加醋后转载到自己网站。
对媒体而言,觉醒主义意味着真金白银。但它们并非唯一受益者。两波政治正确的关键区别在于:第一波几乎全由业余者推动,第二波则常有专业人士主导。对某些人而言这甚至是全职工作。到2010年,新涌现的行政阶层基本职责就是推行觉醒主义。他们类似苏联安插在军事和工业组织的政委——不直接参与核心工作,而是监督确保不出格。这些新人往往以"包容"头衔示人,该词在机构内是觉醒主义的委婉说法。例如新的禁词清单通常被称为"包容性语言指南"。[10]
这批新官僚推行觉醒议程的劲头仿佛事关饭碗——确实如此。若雇人专门防范某类问题,他们必会发现问题,否则自身就无存在价值。[11]但更危险的是,许多人参与招聘时,会尽可能确保雇主只录用与其政治立场一致者。最恶劣的案例是某些大学新增的"DEI声明"要求,应聘教职者须自证对觉醒主义的忠诚。有些大学将其作为初筛标准,仅考虑高分者。这种方式注定聘不到爱因斯坦之才——不妨想象实际会招来什么人。
Should students and employees have to participate in woke indoctrination sessions in which they're required to answer questions about their beliefs to ensure compliance? No, because we wouldn't dream of catechizing people in this way about their religion. [16] One shouldn't feel bad about not wanting to watch woke movies any more than one would feel bad about not wanting to listen to Christian rock. In my twenties I drove across America several times, listening to local radio stations. Occasionally I'd turn the dial and hear some new song. But the moment anyone mentioned Jesus I'd turn the dial again. Even the tiniest bit of being preached to was enough to make me lose interest. But by the same token we should not automatically reject everything the woke believe. I'm not a Christian, but I can see that many Christian principles are good ones. It would be a mistake to discard them all just because one didn't share the religion that espoused them. It would be the sort of thing a religious zealot would do. If we have genuine pluralism, I think we'll be safe from future outbreaks of woke intolerance. Wokeness itself won't go away. There will for the foreseeable future continue to be pockets of woke zealots inventing new moral fashions. The key is not to let them treat their fashions as normative. They can change what their coreligionists are allowed to say every few months if they like, but they mustn't be allowed to change what we're allowed to say. [17] The more general problem — how to prevent similar outbreaks of aggressively performative moralism — is of course harder. Here we're up against human nature. There will always be prigs. And in particular there will always be the enforcers among them, the _aggressively conventional-minded_. These people are born that way. Every society has them. So the best we can do is to keep them bottled up. The aggressively conventional-minded aren't always on the rampage.
觉醒主义兴起的另一因素是2013年始于佛罗里达州白人枪杀黑人少年被判无罪的"黑命贵"运动。但2013年时觉醒主义早已势成燎原。
2017年哈维·韦恩斯坦性侵案报道引爆的"MeToo运动"同样如此。它加速了觉醒主义,但不像1980年代版本对政治正确那样起到开创作用。
2016年特朗普当选同样加速觉醒主义,尤其在媒体界——愤怒此时意味着流量。特朗普让《纽约时报》赚得盆满钵满:其执政首年报道标题出现其名字的频率是前任总统的四倍。
Usually they just enforce whatever random rules are nearest to hand. They only become dangerous when some new ideology gets a lot of them pointed in the same direction at once. That's what happened during the Cultural Revolution, and to a lesser extent (thank God) in the two waves of political correctness we've experienced. We can't get rid of the aggressively conventional-minded. [18] And we couldn't prevent people from creating new ideologies that appealed to them even if we wanted to. So if we want to keep them bottled up, we have to do it one step downstream. Fortunately when the aggressively conventional-minded go on the rampage they always do one thing that gives them away: they define new _heresies_ to punish people for. So the best way to protect ourselves from future outbreaks of things like wokeness is to have powerful antibodies against the concept of heresy. We should have a conscious bias against defining new forms of heresy. Whenever anyone tries to ban saying something that we'd previously been able to say, our initial assumption should be that they're wrong. Only our initial assumption of course. If they can prove we should stop saying it, then we should. But the burden of proof is on them. In liberal democracies, people trying to prevent something from being said will usually claim they're not merely engaging in censorship, but trying to prevent some form of "harm". And maybe they're right. But once again, the burden of proof is on them. It's not enough to claim harm; they have to prove it. As long as the aggressively conventional-minded continue to give themselves away by banning heresies, we'll always be able to notice when they become aligned behind some new ideology. And if we always fight back at that point, with any luck we can stop them in their tracks. The number of true things we _can't say_ should not increase.
2020年白人警察跪杀黑人视频引发全美暴力抗议,成为最大助燃剂。此时隐喻之火化为真实烈焰。但事后看来,这恰是觉醒主义的顶峰(或接近顶峰)。所有数据都显示它在2020或2021年达到峰值。
觉醒主义常被比作思想病毒。其传染性在于不断定义新式"不当行为"。多数人害怕越界——他们永远不确定社交规则的具体边界,尤其当规则快速变更时。由于人们本就担心自己可能无意违规,若被告知触犯某条,第一反应往往是相信——尤其当多人同时指责时。这正是指数级增长的配方:狂热者发明新禁忌→首批追随者是同样热衷标榜美德的同类→若规模足够,会裹挟更大规模的恐惧驱动群体(他们不为彰显美德,只为避祸)→此时新禁忌已牢固确立→其成功又加速规则变化(而这正是人们担忧误触规则的主因)→循环不断加速。[12]
个人如此,组织更甚。尤其缺乏强有力领导的组织,其运作完全基于"最佳实践"。当某种新"最佳实践"形成规模,它们必须采纳。且这类组织无法像往常面对不确定性时那样拖延——可能此刻正在违规!因此少数狂热者通过描述组织可能触犯的新禁忌来劫持这类机构,竟出奇地容易。[13]
If it does, something is wrong. Notes [0] This was not the original meaning of "woke," but it's rarely used in the original sense now. Now the pejorative sense is the dominant one. [1] Why did 1960s radicals focus on the causes they did? One of the people who reviewed drafts of this essay explained this so well that I asked if I could quote him:.
这种循环如何终结?通常直到酿成灾难,人们才喊停。2020年的过火行为让许多人幡然醒悟。
此后觉醒主义持续缓步退潮。企业CEO们(始于布莱恩·阿姆斯特朗)公开抵制;以芝加哥大学和MIT为首的院校重申对言论自由的承诺;堪称觉醒主义枢纽的Twitter被埃隆·马斯克收购并成功去毒化(值得注意的是,他并未像原Twitter审查右翼那样审查左翼,而是停止审查各方)[14];消费者强烈抵制过度觉醒的品牌(如百威淡啤可能遭受永久性损伤);虽不能说特朗普2024年胜选是对觉醒主义的公投(我认为他像所有胜选总统一样赢在魅力),但选民对觉醒主义的厌恶必定有所贡献。
> The middle-class student protestors of the New Left rejected the socialist/Marxist left as unhip. They were interested in sexier forms of oppression uncovered by cultural analysis (Marcuse) and abstruse "Theory". Labor politics became stodgy and old-fashioned. This took a couple generations to work through. The woke ideology's conspicuous lack of interest in the working class is the tell-tale sign. Such fragments as are, er, left of the old left are anti-woke, and meanwhile the actual working class shifted to the populist right and gave us Trump. Trump and wokeness are cousins. > > The middle-class origins of wokeness smoothed its way through the institutions because it had no interest in "seizing the means of production" (how quaint such phrases seem now), which would quickly have run up against hard state and corporate power. The fact that wokeness only expressed interest in other kinds of class (race, sex, etc) signalled compromise with existing power: give us power within your system and we'll bestow the resource we control — moral rectitude — upon you. As an ideological stalking horse for gaining control over discourse and institutions, this succeeded where a more ambitious revolutionary program would not have.
当下我们该做什么?觉醒主义已在败退,显然应乘胜追击。但最佳方式是什么?更重要的是,如何避免第三波爆发?毕竟它曾看似消亡,却以更猛烈的态势卷土重来。
其实还有更宏大的目标:能否预防未来任何类似的攻击性表演式道德主义爆发——不仅是政治正确的第三波,还包括任何变种?因为必有后来者。卫道士天性如此,他们需要遵守并强加的规则。既然达尔文斩断了传统规则来源,他们便饥渴地寻找新目标。只要有人定义新的道德纯洁标准,同样现象就会重演。
先从简单问题入手:是否有原则性方法应对觉醒主义?我认为可沿用既有的宗教处理方式——觉醒主义实质是替代性宗教,只不过用"受保护群体"替换了上帝。这并非首例,马克思主义就以"人民"替代上帝。[15]我们早有成熟的机构内宗教管理规范:你可以表达信仰,但不能称异见同事为异端,不能禁止他们发表违背教义的言论,不能要求组织将其奉为官方信仰。
[2] It helped that the humanities and social sciences also included some of the biggest and easiest undergrad majors. If a political movement had to start with physics students, it could never get off the ground; there would be too few of them, and they wouldn't have the time to spare. At the top universities these majors are not as big as they used to be, though. A _2022 survey_ found that only 7% of Harvard undergrads plan to major in the humanities, vs nearly 30% during the 1970s. I expect wokeness is at least part of the reason; when undergrads consider majoring in English, it's presumably because they love the written word and not because they want to listen to lectures about racism. [3] The puppet-master-and-puppet character of political correctness became clearly visible when a bakery near Oberlin College was falsely accused of race discrimination in 2016. In the subsequent civil trial, lawyers for the bakery produced a text message from Oberlin Dean of Students Meredith Raimondo that read "I'd say unleash the students if I wasn't convinced this needs to be put behind us." [4] The woke sometimes claim that wokeness is simply treating people with respect. But if it were, that would be the only rule you'd have to remember, and this is comically far from being the case. My younger son likes to imitate voices, and at one point when he was about seven I had to explain which accents it was currently safe to imitate publicly and which not. It took about ten minutes, and I still hadn't covered all the cases. [5] In 1986 the Supreme Court ruled that creating a hostile work environment could constitute sex discrimination, which in turn affected universities via Title IX.
若对觉醒主义的具体表现犹豫不决,不妨设想面对的是基督教等其他宗教:该设专职人员强制推行觉醒教条吗?不该,正如我们不会设基督教教义警察;该审查违背觉醒教义的作家或科学家吗?不该,正如我们不会审查违背基督教教义者;应聘者需提交DEI声明吗?当然不,这如同要求求职者自证宗教信仰;该强制学生员工参加觉醒主义灌输会议并交代思想吗?不,正如我们不会用教理问答审查他人信仰。[16]
不想看觉醒主义电影无需愧疚,就像不听基督教摇滚乐一样合理。二十多岁时我数次驾车横穿美国,听着当地电台。偶尔调到新歌,但只要有人提及耶稣,我会立即换台——哪怕最轻微的布道也足以让我失去兴趣。
但同理,我们不应全盘否定觉醒派的所有观点。我不信基督教,但承认许多基督教原则确有价值。仅因不认同其宗教基础就抛弃所有原则,这恰是宗教狂热者的行径。
The court specified that the test of a hostile environment was whether it would bother a reasonable person, but since for a professor merely being the subject of a sexual harassment complaint would be a disaster whether the complainant was reasonable or not, in practice any joke or remark remotely connected with sex was now effectively forbidden. Which meant we'd now come full circle to Victorian codes of behavior, when there was a large class of things that might not be said "with ladies present." [6] Much as they tried to pretend there was no conflict between diversity and quality. But you can't simultaneously optimize for two things that aren't identical. What diversity actually means, judging from the way the term is used, is proportional representation, and unless you're selecting a group whose purpose is to be representative, like poll respondents, optimizing for proportional representation has to come at the expense of quality. This is not because of anything about representation; it's the nature of optimization; optimizing for x has to come at the expense of y unless x and y are identical. [7] Maybe societies will eventually develop antibodies to viral outrage. Maybe we were just the first to be exposed to it, so it tore through us like an epidemic through a previously isolated population. I'm fairly confident that it would be possible to create new social media apps that were less driven by outrage, and an app of this type would have a good chance of stealing users from existing ones, because the smartest people would tend to migrate to it. [8] I say "mostly" because I have hopes that journalistic neutrality will return in some form. There is some market for unbiased news, and while it may be small, it's valuable.
若实现真正的多元主义,未来应可免受觉醒主义荼毒。觉醒主义本身不会消失,未来仍会有小团体发明新道德时尚。关键是不让其将自身标准强加于人。他们可以每几个月更新内部禁忌,但无权规定我们的言论界限。[17]
更根本的问题——如何预防类似攻击性表演式道德主义爆发——显然更棘手。这直指人性本质:卫道士永远存在,尤其是其中积极维护正统的进攻性从众者。这类人与生俱来,每个社会都有。我们最多只能将其禁锢。
The rich and powerful want to know what's really going on; that's how they became rich and powerful. [9] The Times made this momentous announcement very informally, in passing in the middle of an _article_ about a Times reporter who'd been criticized for inaccuracy. It's quite possible no senior editor even approved it. But it's somehow appropriate that this particular universe ended with a whimper rather than a bang. [10] As the acronym DEI goes out of fashion, many of these bureaucrats will try to go underground by changing their titles. It looks like "belonging" will be a popular option. [11] If you've ever wondered why our legal system includes protections like the separation of prosecutor, judge, and jury, the right to examine evidence and cross-examine witnesses, and the right to be represented by legal counsel, the de facto parallel legal system established by Title IX makes that all too clear. [12] The invention of new improprieties is most visible in the rapid evolution of woke nomenclature. This is particularly annoying to me as a writer, because the new names are always worse. Any religious observance has to be inconvenient and slightly absurd; otherwise gentiles would do it too.
进攻性从众者并非时刻暴走,通常只是就近执行手边的随机规则。只有当某种新意识形态同时调动大批此类人时才会危险——文革如此,我们经历的两波政治正确(所幸程度较轻)亦如此。
我们无法消灭进攻性从众者,[18]即使想阻止也无力杜绝吸引他们的新意识形态。因此要禁锢他们,只能在下一环节设防。幸运的是,当这类人暴走时总有标志性动作:定义新异端罪名加以惩罚。故预防未来觉醒主义类现象的最佳方式,就是培养对"异端"概念的强大抗体。
我们应有意识地抵制新异端定义的产生。每当有人试图禁止既往允许的言论,预设立场应是反对。当然只是预设——若他们能证明禁言合理,我们自当遵从。但举证责任在他们。自由民主社会中,禁言者通常宣称是为防止某种"伤害"。或许属实,但同样需其举证。光声称有伤害不够,必须证明伤害存在。
So "slaves" becomes "enslaved individuals." But web search can show us the leading edge of moral growth in real time: if you search for "individuals experiencing slavery" you will as of this writing find five legit attempts to use the phrase, and you'll even find two for "individuals experiencing enslavement." [13] Organizations that do dubious things are particularly concerned with propriety, which is how you end up with absurdities like tobacco and oil companies having higher ESG ratings than Tesla. [14] Elon did something else that tilted Twitter rightward though: he gave more visibility to paying users. Paying users lean right on average, because people on the far left dislike Elon and don't want to give him money. Elon presumably knew this would happen. On the other hand, the people on the far left have only themselves to blame; they could tilt Twitter back to the left tomorrow if they wanted to. [15] It even, as James Lindsay and Peter Boghossian pointed out, has a concept of original sin: privilege. Which means unlike Christianity's egalitarian version, people have varying degrees of it. An able-bodied straight white American male is born with such a load of sin that only by the most abject repentance can he be saved. Wokeness also shares something rather funny with many actual versions of Christianity: like God, the people for whose sake wokeness purports to act are often revolted by the things done in their name. [16] There is one exception to most of these rules: actual religious organizations. It's reasonable for them to insist on orthodoxy. But they in turn should declare that they're religious organizations. It's rightly considered shady when something that appears to be an ordinary business or publication turns out to be a religious organization. [17] I don't want to give the impression that it will be simple to roll back wokeness.
只要进攻性从众者继续通过定义异端自我暴露,我们总能及时发现其集结 behind 新意识形态。若此时坚决反击,有望将其扼杀在萌芽状态。
我们不能说的真话数量不应增加。若增加,必有问题。
注释 [0] 这不是"woke"原意,但如今原意罕用,贬义已成主导。 [1] 1960年代激进派为何聚焦特定议题?某审稿人的解释精辟,经允许直接引用:
There will be places where the fight inevitably gets messy — particularly within universities, which everyone has to share, yet which are currently the most pervaded by wokeness of any institutions. [18] You can however get rid of aggressively conventional-minded people within an organization, and in many if not most organizations this would be an excellent idea. Even a handful of them can do a lot of damage. I bet you'd feel a noticeable improvement going from a handful to none. Thanks to Sam Altman, Ben Miller, Daniel Gackle, Robin Hanson, Jessica Livingston, Greg Lukianoff, Harj Taggar, Garry Tan, and Tim Urban for reading drafts of this..
新左派的中产阶级学生抗议者认为社会主义/马克思主义左派不够时髦而加以排斥。他们更热衷于文化分析(马尔库塞)和晦涩"理论"所揭示的那些更性感的压迫形式。劳工政治变得沉闷而过时。这一转变经历了两代人的时间才完成。觉醒意识形态对工人阶级明显缺乏兴趣,正是其典型特征。旧左派残存的零星势力如今反觉醒运动,而真正的工人阶级则转向民粹主义右翼,为我们带来了特朗普。特朗普与觉醒运动实为同根生。
觉醒运动的中产阶级出身使其在体制内畅行无阻,因为它对"夺取生产资料"毫无兴趣(这类措辞如今显得多么陈腐)——这种主张会立即遭遇国家和企业权力的强硬抵制。觉醒运动仅对其他类型的阶级(种族、性别等)表现出兴趣,这一事实暗示着与现有权力的妥协:让我们在你们的体系内获得权力,我们将回馈以我们所掌控的资源——道德正当性。作为一种夺取话语权和体制控制权的意识形态障眼法,这种策略取得了更为宏大的革命纲领所无法企及的成功。
[2] 人文与社会科学包含一些规模最大、门槛最低的本科专业,这为运动提供了便利。如果一场政治运动必须从物理系学生开始,它永远无法起步——他们人数太少,也抽不出时间参与。 不过在顶尖大学,这些专业的规模已今非昔比。2022年一项调查显示,哈佛大学仅7%的本科生计划主修人文学科,而1970年代这一比例接近30%。我认为"觉醒主义"至少是部分原因:当本科生考虑主修英语时,他们热爱的理应是文字本身,而非聆听关于种族主义的说教。 [3] 2016年欧柏林学院附近一家面包店被诬告种族歧视时,政治正确"提线与木偶"的特质暴露无遗。在随后的民事诉讼中,面包店律师出示了该校学生事务主任梅雷迪思·雷蒙多的短信:"要不是觉得这事该翻篇了,我早就放学生们去闹了。" [4] 觉醒派有时声称其理念只是"尊重他人"。若真如此,这本该是唯一需要牢记的准则,但现实却荒谬地南辕北辙。我七岁的小儿子喜欢模仿各种口音,有次我不得不花十分钟解释哪些口音可以公开模仿、哪些不行——即便如此仍未穷尽所有禁忌情形。 [5] 1986年最高法院裁定制造敌意工作环境可构成性别歧视,该判决通过《教育法第九修正案》影响高校。虽然法院明确以"理性人标准"判断环境敌意,但由于对教授而言,无论投诉是否合理,单是遭遇性骚扰指控就足以毁灭职业生涯,实践中任何涉及性话题的玩笑或言论都遭到实际禁止——这让我们彻底绕回维多利亚时代的行为准则,那时有大量话题"淑女在场时不宜谈论"。 [6] 尽管他们竭力假装多样性与质量不存在冲突。但对非等同物的双重优化注定无法实现。从实际用法来看,"多样性"本质是比例代表制——除非像民意调查那样需要刻意追求代表性,否则优化比例必然牺牲质量。这不是代表制本身的问题,而是优化的本质使然:除非x与y完全等同,优化x必定损耗y。 [7] 或许社会终将培养出对病毒式愤怒的抗体。我们可能只是首批暴露群体,就像流行病席卷与世隔绝的部落那样。我确信完全可能开发不那么煽动愤怒的社交应用,这类应用很有机会从现有平台夺取用户,因为最聪明的人群会率先迁移。 [8] 我说"基本"是因为仍期待新闻中立性以某种形式回归。虽然客观新闻的市场可能很小,但它极具价值——权贵阶层需要了解真实事态,这正是他们发迹的秘诀。 [9] 《纽约时报》在一篇关于某记者失实报道的争议文章中,以极其随意的姿态宣告了这个重大转变。很可能没有任何高层编辑批准这个决定。但某种程度上,这个特殊宇宙以呜咽而非爆炸终结,倒恰如其分。 [10] 随着DEI(多元平等包容) acronym 过时,许多官僚正试图通过改名潜伏。目前看来"归属感"将成为热门选项。 [11] 如果你曾疑惑为何司法体系需要检察官、法官、陪审团分权制衡,需要证据审查与交叉质证权,需要律师辩护权,看看《教育法第九修正案》建立的事实平行司法体系就豁然开朗了。 [12] 新禁忌的发明最直观体现在觉醒术语的快速迭代中。这对写作者尤为恼人,因为新称谓总是更糟。宗教仪轨必须不便且略显荒谬,否则外邦人也会效仿——于是"奴隶"变成"被奴役个体"。但网络搜索能实时展示道德进化的前沿:检索"经历奴役的个体"会找到五个正经用例,甚至还有两例"经历奴役处境的个体"。 [13] 从事可疑勾当的组织尤其注重表面正当性,这就解释了为何烟草石油公司的ESG评分能高于特斯拉这类荒谬现象。 [14] 不过马斯克确实做了另一件让推特右倾的事:提升付费用户能见度。由于极左人士厌恶马斯克不愿给他送钱,付费用户平均偏右。马斯克理应预见到这点。但话说回来,极左群体只能怪自己——他们随时可以通过充值让推特重新左转。 [15] 正如詹姆斯·林赛和彼得·博格西昂指出,觉醒主义甚至具备"原罪"概念:特权。不同于基督教平等主义的原罪观,这种罪孽因人而异。一个健全的顺性别白人男性天生背负如此深重的罪孽,唯有极度卑微的忏悔才能获得救赎。 觉醒主义还与许多基督教派共享一个滑稽特征:正如上帝与其信徒的关系,那些以之名行事的行为,常令觉醒主义声称要保护的群体感到恶心。 [16] 这些规则有个例外:真正的宗教组织。它们坚持正统教义无可厚非,但必须声明自己的宗教属性。若表面是普通企业或媒体,实则为宗教组织,理应被视为不光彩之举。 [17] 我不想给人留下"击退觉醒主义轻而易举"的印象。在某些领域——尤其是目前受觉醒主义渗透最深的大学这类公共机构——斗争注定混乱胶着。 [18] 但你可以清除组织内那些极具攻击性的守旧者,对多数机构而言这都是明智之举。即便少数这类人也危害巨大,我敢说从少量到清零的改善会立竿见影。 致谢 萨姆·奥尔特曼、本·米勒、丹尼尔·加克尔、罗宾·汉森、杰西卡·利文斯顿、格雷格·卢基亚诺夫、哈吉·塔加尔、加里·谭和蒂姆·尔班阅读了本文草稿。.
October 2024 I'm usually reluctant to make predictions about technology, but I feel fairly confident about this one: in a couple decades there won't be many people who can write. One of the strangest things you learn if you're a writer is how many people have trouble writing. Doctors know how many people have a mole they're worried about; people who are good at setting up computers know how many people aren't; writers know how many people need help writing. The reason so many people have trouble writing is that it's fundamentally difficult. To write well you have to think clearly, and thinking clearly is hard. And yet writing pervades many jobs, and the more prestigious the job, the more writing it tends to require. These two powerful opposing forces, the pervasive expectation of writing and the irreducible difficulty of doing it, create enormous pressure. This is why eminent professors often turn out to have resorted to plagiarism. The most striking thing to me about these cases is the pettiness of the thefts. The stuff they steal is usually the most mundane boilerplate — the sort of thing that anyone who was even halfway decent at writing could turn out with no effort at all. Which means they're not even halfway decent at writing. Till recently there was no convenient escape valve for the pressure created by these opposing forces. You could pay someone to write for you, like JFK, or plagiarize, like MLK, but if you couldn't buy or steal words, you had to write them yourself. And as a result nearly everyone who was expected to write had to learn how. Not anymore. AI has blown this world open. Almost all pressure to write has dissipated. You can have AI do it for you, both in school and at work. The result will be a world divided into writes and write-nots. There will still be some people who can write. Some of us like it.
我通常不愿对技术做出预测,但对这一点我相当确信:二十年后,能写作的人将所剩无几。
作为写作者,你会了解到一个最奇怪的现象——有多少人在写作上存在困难。医生知道有多少人担心身上的痣;擅长配置电脑的人知道有多少人不会;而写作者知道有多少人需要写作帮助。
这么多人写作困难的根本原因在于,写作本质上很难。要写好,你必须思路清晰,而清晰的思考本身就是困难的。
然而写作渗透在许多工作中,且工作越有声望,往往越需要写作能力。
这两种强大的对立力量——对写作的普遍期待与写作本身不可简化的难度——形成了巨大的压力。这就是为什么杰出的教授们常常被发现求助于抄袭。这些案例中最令我震惊的是剽窃内容的琐碎。他们窃取的通常是陈词滥调——任何稍有写作能力的人都能毫不费力写出的东西。这意味着他们连基本的写作能力都不具备。
But the middle ground between those who are good at writing and those who can't write at all will disappear. Instead of good writers, ok writers, and people who can't write, there will just be good writers and people who can't write. Is that so bad? Isn't it common for skills to disappear when technology makes them obsolete? There aren't many blacksmiths left, and it doesn't seem to be a problem. Yes, it's bad. The reason is something I mentioned earlier: writing is thinking. In fact there's a kind of thinking that can only be done by writing. You can't make this point better than Leslie Lamport did: > If you're thinking without writing, you only think you're thinking..
直到最近,这种对立压力仍没有便捷的释放阀。你可以像肯尼迪那样雇人代笔,或像马丁·路德·金那样抄袭,但如果无法购买或窃取文字,你就必须自己写。因此,几乎所有需要写作的人都不得不学习写作。
但现在不同了。人工智能彻底改变了这个世界。写作的压力几乎全部消散。无论是在学校还是职场,你都可以让人工智能代劳。
结果将是一个分裂的世界:会写的人与不会写的人。仍有一些人能写作——我们中有些人热爱写作。但介于擅长写作与完全不会写作之间的中间地带将消失。不再有优秀写手、普通写手和不会写作的人,只剩下优秀写手和不会写作的人。
这很糟糕吗?当技术让技能过时时,技能消失不是很常见吗?铁匠已所剩无几,但这似乎不是问题。
不,这很糟糕。原因我前文提过:写作即思考。事实上,有种思考只能通过写作完成。莱斯利·兰波特说得再透彻不过:
So a world divided into writes and write-nots is more dangerous than it sounds. It will be a world of thinks and think-nots. I know which half I want to be in, and I bet you do too. This situation is not unprecedented. In preindustrial times most people's jobs made them strong. Now if you want to be strong, you work out. So there are still strong people, but only those who choose to be. It will be the same with writing. There will still be smart people, but only those who choose to be. Thanks to Jessica Livingston, Ben Miller, and Robert Morris for reading drafts of this.
> 若不通过写作思考,你只是自以为在思考。
因此,一个被划分为"能写者"与"不能写者"的世界,其危险性远超表面所见。这将是一个"思考者"与"不思考者"并存的世界。我清楚自己想属于哪一半,想必你也心知肚明。
这般情形并非史无前例。在前工业时代,多数人的工作使他们身强体壮。如今若想强健体魄,你需主动锻炼。所以世上仍有强者,但仅限于那些主动选择成为强者的人。
写作之道亦是如此。智者仍将存在,但唯有主动选择思考之人方能跻身此列。
致谢 感谢杰西卡·利文斯顿、本·米勒和罗伯特·莫里斯审阅本文草稿。
September 2024 At a YC event last week Brian Chesky gave a talk that everyone who was there will remember. Most founders I talked to afterward said it was the best they'd ever heard. Ron Conway, for the first time in his life, forgot to take notes. I'm not going to try to reproduce it here. Instead I want to talk about a question it raised. The theme of Brian's talk was that the conventional wisdom about how to run larger companies is mistaken. As Airbnb grew, well-meaning people advised him that he had to run the company in a certain way for it to scale. Their advice could be optimistically summarized as "hire good people and give them room to do their jobs." He followed this advice and the results were disastrous. So he had to figure out a better way on his own, which he did partly by studying how Steve Jobs ran Apple. So far it seems to be working. Airbnb's free cash flow margin is now among the best in Silicon Valley. The audience at this event included a lot of the most successful founders we've funded, and one after another said that the same thing had happened to them. They'd been given the same advice about how to run their companies as they grew, but instead of helping their companies, it had damaged them. Why was everyone telling these founders the wrong thing? That was the big mystery to me. And after mulling it over for a bit I figured out the answer: what they were being told was how to run a company you hadn't founded — how to run a company if you're merely a professional manager. But this m.o. is so much less effective that to founders it feels broken. There are things founders can do that managers can't, and not doing them feels wrong to founders, because it is. In effect there are two different ways to run a company: founder mode and manager mode. Till now most people even in Silicon Valley have implicitly assumed that scaling a startup meant switching to manager mode.
But we can infer the existence of another mode from the dismay of founders who've tried it, and the success of their attempts to escape from it. There are as far as I know no books specifically about founder mode. Business schools don't know it exists. All we have so far are the experiments of individual founders who've been figuring it out for themselves. But now that we know what we're looking for, we can search for it. I hope in a few years founder mode will be as well understood as manager mode. We can already guess at some of the ways it will differ. The way managers are taught to run companies seems to be like modular design in the sense that you treat subtrees of the org chart as black boxes. You tell your direct reports what to do, and it's up to them to figure out how. But you don't get involved in the details of what they do. That would be micromanaging them, which is bad. Hire good people and give them room to do their jobs. Sounds great when it's described that way, doesn't it? Except in practice, judging from the report of founder after founder, what this often turns out to mean is: hire professional fakers and let them drive the company into the ground. One theme I noticed both in Brian's talk and when talking to founders afterward was the idea of being gaslit. Founders feel like they're being gaslit from both sides — by the people telling them they have to run their companies like managers, and by the people working for them when they do. Usually when everyone around you disagrees with you, your default assumption should be that you're mistaken. But this is one of the rare exceptions.
VCs who haven't been founders themselves don't know how founders should run companies, and C-level execs, as a class, include some of the most skillful liars in the world. [1] Whatever founder mode consists of, it's pretty clear that it's going to break the principle that the CEO should engage with the company only via his or her direct reports. "Skip-level" meetings will become the norm instead of a practice so unusual that there's a name for it. And once you abandon that constraint there are a huge number of permutations to choose from. For example, Steve Jobs used to run an annual retreat for what he considered the 100 most important people at Apple, and these were not the 100 people highest on the org chart. Can you imagine the force of will it would take to do this at the average company? And yet imagine how useful such a thing could be. It could make a big company feel like a startup. Steve presumably wouldn't have kept having these retreats if they didn't work. But I've never heard of another company doing this. So is it a good idea, or a bad one? We still don't know. That's how little we know about founder mode. [2] Obviously founders can't keep running a 2000 person company the way they ran it when it had 20. There's going to have to be some amount of delegation. Where the borders of autonomy end up, and how sharp they are, will probably vary from company to company. They'll even vary from time to time within the same company, as managers earn trust. So founder mode will be more complicated than manager mode. But it will also work better. We already know that from the examples of individual founders groping their way toward it.
Indeed, another prediction I'll make about founder mode is that once we figure out what it is, we'll find that a number of individual founders were already most of the way there — except that in doing what they did they were regarded by many as eccentric or worse. [3] Curiously enough it's an encouraging thought that we still know so little about founder mode. Look at what founders have achieved already, and yet they've achieved this against a headwind of bad advice. Imagine what they'll do once we can tell them how to run their companies like Steve Jobs instead of John Sculley. Notes [1] The more diplomatic way of phrasing this statement would be to say that experienced C-level execs are often very skilled at managing up. And I don't think anyone with knowledge of this world would dispute that. [2] If the practice of having such retreats became so widespread that even mature companies dominated by politics started to do it, we could quantify the senescence of companies by the average depth on the org chart of those invited. [3] I also have another less optimistic prediction: as soon as the concept of founder mode becomes established, people will start misusing it. Founders who are unable to delegate even things they should will use founder mode as the excuse. Or managers who aren't founders will decide they should try to act like founders. That may even work, to some extent, but the results will be messy when it doesn't; the modular approach does at least limit the damage a bad CEO can do. Thanks to Brian Chesky, Patrick Collison, Ron Conway, Jessica Livingston, Elon Musk, Ryan Petersen, Harj Taggar, and Garry Tan for reading drafts of this..
2024年9月 在上周的YC活动上,布莱恩·切斯基(Brian Chesky)进行了一场令所有在场者难忘的演讲。事后交流的大多数创始人表示,这是他们听过最精彩的分享。连罗恩·康威(Ron Conway)都生平第一次忘记了做笔记。本文不打算复现那场演讲,而是想探讨它引发的一个问题。 布莱恩演讲的核心观点是:关于如何运营大型公司的传统智慧是错误的。当爱彼迎(Airbnb)规模扩张时,善意的人们建议他必须采用某种特定管理模式才能实现规模化。他们的建议可以乐观地概括为"雇佣优秀人才并给予充分自主权"。他遵循了这些建议,结果却酿成灾难。于是他不得不自行探索更好的方式——部分通过研究史蒂夫·乔布斯(Steve Jobs)如何管理苹果公司。目前看来这个方法行之有效,爱彼迎的自由现金流利润率如今已是硅谷顶尖水平。 活动现场聚集了许多我们投资过的最成功创始人,他们接连表示遭遇过相同经历:在企业发展过程中收到过相同的管理建议,但这些建议非但没有帮助公司,反而造成了损害。 为什么所有人都在给创始人们错误的建议?这个谜团困扰着我。经过一番思考后,我找到了答案:人们告诉他们的其实是"如何管理一家非你创立的公司"——即职业经理人的管理方式。但这种模式效率如此低下,以至于对创始人而言简直形同故障。创始人能做到许多经理人无法做到的事,放弃这些优势对创始人来说就是错误的,因为事实本就如此。 实际上存在两种不同的公司运营模式:创始人模式与经理人模式。迄今为止,即使是硅谷大多数人也默认初创企业规模化意味着切换至经理人模式。但从尝试过该模式的创始人们的挫败感,以及他们挣脱束缚后取得的成功中,我们可以推断出另一种模式的存在。 据我所知,目前没有专门探讨创始人模式的书籍。商学院尚未意识到它的存在。我们现有的只是那些自行探索的创始人们的个体实践。但既然我们已知道寻找的目标,就能主动探寻。我希望几年后创始人模式能像经理人模式那样被充分理解。我们已经可以推测出它的一些差异化特征。 经理人接受的公司管理培训似乎类似于模块化设计——将组织架构图中的子树视为黑箱。你告知直接下属目标,具体实现交由他们决定。但你不介入他们的工作细节,否则就沦为糟糕的微观管理。"雇佣优秀人才并给予充分自主权",这种说法听起来很美好不是吗?但根据众多创始人的反馈,实践中往往演变成:雇佣职业伪装者,任由他们将公司推向深渊。 我在布莱恩演讲和后续交流中注意到一个共同主题:煤气灯效应(gaslighting)。创始人们感到遭受双重精神操控——既来自要求他们采用经理人模式的建议者,也来自实际执行时的下属团队。通常当周围所有人都反对你时,默认假设应该是你错了。但这是罕见的例外情况。未曾创业的风投人士并不清楚创始人该如何管理公司,而C级高管群体中包含着全世界最高明的谎言艺术家。[1] 无论创始人模式包含哪些要素,有一点很明确:它将打破"CEO只应通过直接下属管理公司"的原则。"跨级会议"将成为常态,而非需要专门术语标注的例外做法。一旦放弃这种约束,就会出现无数种排列组合的可能性。 例如,史蒂夫·乔布斯曾每年为他认定的苹果公司100位最关键人物举办闭门会议,这些人并不全是组织架构图中的高层。你能想象在普通公司推行这种做法需要多强的意志力吗?但请想想它能带来的巨大价值——让大公司重获初创企业的活力。如果无效,乔布斯不会持续举办这类会议。但我从未听闻其他公司效仿。所以这究竟是好主意还是坏主意?我们仍不得而知。这就是我们对创始人模式的认知匮乏程度。[2] 显然创始人无法用管理20人公司的方式运营2000人规模的企业。必然需要某种程度的授权。自治权限的边界及其严格程度可能因公司而异,甚至在同一公司内部,随着经理人赢得信任也会动态变化。因此创始人模式会比经理人模式更复杂,但效果也会更好。从那些摸索前行的创始人们身上,我们已经看到了证据。 事实上,关于创始人模式我还有另一个预测:当我们真正理解它时,会发现许多创始人早已实践了其中大部分内容——只是他们的做法曾被多数人视为离经叛道甚至更糟。[3] 有趣的是,对创始人模式的知之甚少反而令人振奋。想想创始人们已经取得的成就,而这还是在逆风承受错误建议的情况下实现的。试想当我们能指导他们像乔布斯而非约翰·斯卡利(John Sculley)那样管理公司时,他们会创造怎样的奇迹。 注释 [1] 这个说法更委婉的表达是:经验丰富的C级高管通常非常擅长向上管理。我相信了解这个领域的人都不会否认这点。 [2] 如果此类闭门会议变得普遍,甚至政治主导的成熟企业也开始效仿,我们就能通过受邀者在组织架构图中的平均层级来量化企业的衰老程度。 [3] 我还有个不太乐观的预测:一旦创始人模式概念确立,就会开始被滥用。那些该授权却不放权的创始人会以此为由,而非创始人的经理人也会试图模仿创始人行为。某种程度上可能奏效,但失败时将造成混乱;模块化设计至少能限制糟糕CEO的破坏力。 致谢 布莱恩·切斯基、帕特里克·克里森(Patrick Collison)、罗恩·康威、杰西卡·利文斯顿(Jessica Livingston)、埃隆·马斯克(Elon Musk)、瑞安·彼得森(Ryan Petersen)、哈吉·塔加(Harj Taggar)和盖瑞·谭(Garry Tan)审阅了本文草稿。.
September 2024 There's some debate about whether it's a good idea to "follow your passion." In fact the question is impossible to answer with a simple yes or no. Sometimes you should and sometimes you shouldn't, but the border between should and shouldn't is very complicated. The only way to give a general answer is to trace it. When people talk about this question, there's always an implicit "instead of." All other things being equal, why wouldn't you work on what interests you the most? So even raising the question implies that all other things aren't equal, and that you have to choose between working on what interests you the most and something else, like what pays the best. And indeed if your main goal is to make money, you can't usually afford to work on what interests you the most. People pay you for doing what they want, not what you want. But there's an obvious exception: when you both want the same thing. For example, if you love football, and you're good enough at it, you can get paid a lot to play it. Of course the odds are against you in a case like football, because so many other people like playing it too. This is not to say you shouldn't try though. It depends how much ability you have and how hard you're willing to work. The odds are better when you have strange tastes: when you like something that pays well and that few other people like. For example, it's clear that Bill Gates truly loved running a software company. He didn't just love programming, which a lot of people do. He loved writing software for customers. That is a very strange taste indeed, but if you have it, you can make a lot by indulging it. There are even some people who have a genuine intellectual interest in making money. This is distinct from mere greed. They just can't help noticing when something is mispriced, and can't help doing something about it.
关于"追随热情"是否明智存在争议。事实上,这个问题无法用简单的"是"或"否"来回答。有时你应该追随,有时则不该,但"应该"与"不该"之间的界限极为复杂。要给出普遍性答案,唯有追本溯源。
讨论这个问题时,总隐含着一个"而非"。在其他条件相同的情况下,为何不从事最感兴趣的工作?因此提出这个问题本身就意味着条件不均等,你必须在最感兴趣的工作与其他选项(如报酬最优厚的工作)之间做出选择。
若以赚钱为主要目标,通常难以负担只做最感兴趣之事。人们付钱是让你完成他们的需求,而非满足你的愿望。但存在明显例外:当双方需求一致时。比如热爱足球且球技出众者,完全可以通过踢球获得丰厚报酬。
当然,像足球这类领域成功几率渺茫,因为竞争者众多。但这不意味着不该尝试——取决于你的天赋与努力程度。
当你的兴趣冷门时,胜算更大:即热衷的事物既高薪又鲜少人爱。例如比尔·盖茨显然真心热爱经营软件公司,不仅止于编程(这很普遍),而是痴迷于为客户编写软件。这种偏好确实罕见,但若拥有,便能借此大获其利。
It's like a puzzle for them. [1] In fact there's an edge case here so spectacular that it turns all the preceding advice on its head. If you want to make a really huge amount of money — hundreds of millions or even billions of dollars — it turns out to be very useful to work on what interests you the most. The reason is not the extra motivation you get from doing this, but that the way to make a really large amount of money is to start a startup, and working on what interests you is an excellent way to discover _startup ideas_. Many if not most of the biggest startups began as projects the founders were doing for fun. Apple, Google, and Facebook all began that way. Why is this pattern so common? Because the best ideas tend to be such outliers that you'd overlook them if you were consciously looking for ways to make money. Whereas if you're young and good at technology, your unconscious instincts about what would be interesting to work on are very well aligned with what needs to be built. So there's something like a midwit peak for making money. If you don't need to make much, you can work on whatever you're most interested in; if you want to become moderately rich, you can't usually afford to; but if you want to become super rich, and you're young and good at technology, working on what you're most interested in becomes a good idea again. What if you're not sure what you want? What if you're attracted to the idea of making money and more attracted to some kinds of work than others, but neither attraction predominates? How do you break ties? The key here is to understand that such ties are only apparent. When you have trouble choosing between following your interests and making money, it's never because you have complete knowledge of yourself and of the types of work you're choosing between, and the options are perfectly balanced. When you can't decide which path to take, it's almost always due to ignorance.
甚至有人对赚钱怀有纯粹智力层面的兴趣,这不同于单纯贪婪。他们无法对定价失误视而不见,必然采取行动。这对他们如同解谜游戏。[1]
事实上存在一个极端案例,足以颠覆前文所有建议:若要赚取巨额财富(数亿乃至数十亿美元),从事最感兴趣之事反而极具价值。关键不在于额外动力,而在于创业才是暴富之道——而追随兴趣正是发掘_创业点子_的最佳途径。
绝大多数顶尖初创企业最初都是创始人的兴趣项目,苹果、谷歌和Facebook皆如此。为何这种模式如此普遍?因为绝佳创意往往偏离常规,刻意寻找赚钱之道时反而容易忽略。而若你年轻且技术精湛,潜意识里对工作内容的兴趣判断,恰恰与市场需求高度吻合。
因此赚钱存在某种"中等智商峰值"现象:若需求不高,尽可从事最爱;若要中等富裕,通常难以任性;但若追求超级财富,且年轻有为,那么追随热情又成为明智之选。
若不确定想要什么怎么办?若被赚钱吸引,又被某些工作更强烈地吸引,但两者都不占主导时,如何抉择?
In fact you're usually suffering from three kinds of ignorance simultaneously: you don't know what makes you happy, what the various kinds of work are really like, or how well you could do them. [2] In a way this ignorance is excusable. It's often hard to predict these things, and no one even tells you that you need to. If you're ambitious you're told you should go to college, and this is good advice so far as it goes, but that's where it usually ends. No one tells you how to figure out what to work on, or how hard this can be. What do you do in the face of uncertainty? Get more certainty. And probably the best way to do that is to try working on things you're interested in. That will get you more information about how interested you are in them, how good you are at them, and how much scope they offer for ambition. Don't wait. Don't wait till the end of college to figure out what to work on. Don't even wait for internships during college. You don't necessarily need a job doing x in order to work on x; often you can just start doing it in some form yourself. And since figuring out what to work on is a problem that could take years to solve, the sooner you start, the better. One useful trick for judging different kinds of work is to look at who your colleagues will be. You'll become like whoever you work with. Do you want to become like these people? Indeed, the difference in character between different kinds of work is magnified by the fact that everyone else is facing the same decisions as you. If you choose a kind of work mainly for how well it pays, you'll be surrounded by other people who chose it for the same reason, and that will make it even more soul-sucking than it seems from the outside.
关键在于明白这种纠结只是表象。当在兴趣与赚钱间难以抉择时,绝非因为你已完全了解自己和各类工作,且选项完全平衡。犹豫不决几乎总是源于认知不足——实际上往往同时存在三重无知:不了解何种事物使自己快乐,不了解各类工作的真实面貌,也不清楚自己能否胜任。[2]
这种无知情有可原。这些本就难以预测,甚至无人提醒你需要考虑。若有抱负,人们只会建议你上大学——这建议本身不错,但通常止步于此。无人告诉你如何确定职业方向,或这有多困难。
面对不确定性该怎么办?获取更多确定性。最佳方式或许是尝试感兴趣的工作,这将帮你了解:对其兴趣几何、能力如何、发展空间多大。
切勿等待。别等到大学毕业才思考职业方向,甚至别等到实习期。从事某领域工作未必需要正式职位,通常自己就能动手尝试。既然职业定位可能耗时数年,越早开始越好。
判断不同工作的窍门是观察未来同事。你会变得与共事者相似:你愿意成为他们那样的人吗?
Whereas if you choose work you're genuinely interested in, you'll be surrounded mostly by other people who are genuinely interested in it, and that will make it extra inspiring. [3] The other thing you do in the face of uncertainty is to make choices that are uncertainty-proof. The less sure you are about what to do, the more important it is to choose options that give you more options in the future. I call this "staying upwind." If you're unsure whether to major in math or economics, for example, choose math; math is upwind of economics in the sense that it will be easier to switch later from math to economics than from economics to math. There's one case, though, where it's easy to say whether you should work on what interests you the most: if you want to do _great work_. This is not a sufficient condition for doing great work, but it is a necessary one. There's a lot of selection bias in advice about whether to "follow your passion," and this is the reason. Most such advice comes from people who are famously successful, and if you ask someone who's famously successful how to do what they did, most will tell you that you have to work on what you're most interested in. And this is in fact true. That doesn't mean it's the right advice for everyone. Not everyone can do great work, or wants to. But if you do want to, the complicated question of whether or not to work on what interests you the most becomes simple. The answer is yes. The root of great work is a sort of ambitious curiosity, and you can't manufacture that. Notes [1] These examples show why it's a mistake to assume that economic inequality must be evidence of some kind of brokenness or unfairness.
不同工作的性格差异会因同行者的选择而放大。若为高薪选择某职业,周围尽是同道中人,这比表面看来更消磨灵魂;若选择真心热爱的工作,则大多与志同道合者为伍,这将带来额外激励。[3]
面对不确定性的另一策略是做出"防不确定"选择。越不确定方向,就越要选择能为未来保留更多选项的道路。我称之为"保持上风位"。例如不确定主修数学还是经济时,选数学——因为日后从数学转经济比反向转换更容易。
唯有一种情况能明确回答是否该做最感兴趣之事:若你想成就_伟大事业_。这虽非充分条件,却是必要条件。
关于"追随热情"的建议存在严重选择偏差,原因在此:这类建议多来自功成名就者。若询问其成功之道,多数会告诉你必须从事最感兴趣之事——这确是事实。
但这不意味着适用于所有人。并非人人都能或都想成就伟业。但若你志在于此,那个复杂的抉择问题就变得简单:答案是肯定的。伟大事业的根源是某种雄心勃勃的好奇心,而这是无法伪造的。
It's obvious that different people have different interests, and that some interests yield far more money than others, so how can it not be obvious that some people will end up much richer than others? In a world where some people like to write enterprise software and others like to make studio pottery, economic inequality is the natural outcome. [2] Difficulty choosing between interests is a different matter. That's not always due to ignorance. It's often intrinsically difficult. I still have trouble doing it. [3] You can't always take people at their word on this. Since it's more prestigious to work on things you're interested in than to be driven by money, people who are driven mainly by money will often claim to be more interested in their work than they actually are. One way to test such claims is by doing the following thought experiment: if their work didn't pay well, would they take day jobs doing something else in order to do it in their spare time? Lots of mathematicians and scientists and engineers would. Historically lots _have_. But I don't think as many investment bankers would. This thought experiment is also useful for distinguishing between university departments. Thanks to Trevor Blackwell, Paul Buchheit, Jessica Livingston, Robert Morris, Harj Taggar, and Garry Tan for reading drafts of this..
[1] 这些例子说明,将经济不平等归咎于制度缺陷或不公是谬误。人的兴趣各异,某些兴趣带来的收益远高于其他,那么贫富差距岂非必然?在有人热衷开发企业软件、有人偏爱制作陶艺的世界里,经济不平等是自然结果。
[2] 在不同兴趣间难以抉择是另一回事。这不总源于无知,往往本就困难。我至今仍受其困扰。
[3] 对此不可尽信人言。因"为兴趣工作"比"为钱工作"更体面,利益驱动者常夸大对工作的热爱。可用思想实验检验:若报酬微薄,他们是否愿兼职谋生,业余继续从事?许多数学家、科学家和工程师会。历史上不乏先例。但投行精英们恐怕寥寥。
这个思想实验也适用于区分大学院系。
致谢 感谢Trevor Blackwell、Paul Buchheit、Jessica Livingston、Robert Morris、Harj Taggar和Garry Tan阅读本文草稿。
July 2024 Successful people tend to be persistent. New ideas often don't work at first, but they're not deterred. They keep trying and eventually find something that does. Mere obstinacy, on the other hand, is a recipe for failure. Obstinate people are so annoying. They won't listen. They beat their heads against a wall and get nowhere. But is there any real difference between these two cases? Are persistent and obstinate people actually behaving differently? Or are they doing the same thing, and we just label them later as persistent or obstinate depending on whether they turned out to be right or not? If that's the only difference then there's nothing to be learned from the distinction. Telling someone to be persistent rather than obstinate would just be telling them to be right rather than wrong, and they already know that. Whereas if persistence and obstinacy are actually different kinds of behavior, it would be worthwhile to tease them apart. [1] I've talked to a lot of determined people, and it seems to me that they're different kinds of behavior. I've often walked away from a conversation thinking either "Wow, that guy is determined" or "Damn, that guy is stubborn," and I don't think I'm just talking about whether they seemed right or not. That's part of it, but not all of it. There's something annoying about the obstinate that's not simply due to being mistaken. They won't listen. And that's not true of all determined people. I can't think of anyone more determined than the Collison brothers, and when you point out a problem to them, they not only listen, but listen with an almost predatory intensity. Is there a hole in the bottom of their boat? Probably not, but if there is, they want to know about it. It's the same with most successful people. They're never _more_ engaged than when you disagree with them. Whereas the obstinate don't want to hear you.
成功人士往往具备坚持不懈的特质。新想法最初常常行不通,但他们不会因此退缩。他们持续尝试,最终找到可行方案。
而单纯的固执则是失败的配方。固执之人令人恼火。他们拒绝倾听。他们用头撞墙却徒劳无功。
但这两者真有本质区别吗?坚持与固执的人行为模式是否真的不同?还是说他们做着同样的事,我们只是根据最终成败来贴上"坚持"或"固执"的标签?
若区别仅在于此,这种区分便毫无意义。告诫某人要"坚持而非固执",无异于教他"做对而非做错",这道理谁都懂。但若两者确是不同行为模式,就有必要加以辨析。[1]
When you point out problems, their eyes glaze over, and their replies sound like ideologues talking about matters of doctrine. [2] The reason the persistent and the obstinate seem similar is that they're both hard to stop. But they're hard to stop in different senses. The persistent are like boats whose engines can't be throttled back. The obstinate are like boats whose rudders can't be turned. [3] In the degenerate case they're indistinguishable: when there's only one way to solve a problem, your only choice is whether to give up or not, and persistence and obstinacy both say no. This is presumably why the two are so often conflated in popular culture. It assumes simple problems. But as problems get more complicated, we can see the difference between them. The persistent are much more attached to points high in the decision tree than to minor ones lower down, while the obstinate spray "don't give up" indiscriminately over the whole tree. The persistent are attached to the goal. The obstinate are attached to their ideas about how to reach it. Worse still, that means they'll tend to be attached to their _first_ ideas about how to solve a problem, even though these are the least informed by the experience of working on it. So the obstinate aren't merely attached to details, but disproportionately likely to be attached to wrong ones. Why are they like this? Why are the obstinate obstinate? One possibility is that they're overwhelmed. They're not very capable. They take on a hard problem. They're immediately in over their head. So they grab onto ideas the way someone on the deck of a rolling ship might grab onto the nearest handhold. That was my initial theory, but on examination it doesn't hold up. If being obstinate were simply a consequence of being in over one's head, you could make persistent people become obstinate by making them solve harder problems. But that's not what happens.
我接触过许多意志坚定者,发现这确实是两种行为模式。常有人让我在交谈后暗叹"这人真有毅力"或"天哪这人太固执了",这种判断不仅基于他们观点的正确性。那只是部分因素。
固执者令人不适的特质不仅源于错误认知。他们拒绝倾听。但并非所有坚定者皆如此。我想不出比科里森兄弟更执着的人,可当你指出问题时,他们不仅倾听,还带着近乎捕食者的专注。若船底有洞,他们定要查明——即便可能性微乎其微。
多数成功者皆如此。他们最投入的时刻恰是遭遇反对之时。而固执者根本不愿听你说话。指出问题时,他们眼神涣散,回答如同教条主义者讨论信条。[2]
坚持与固执的相似处在于都难以阻挡。但"难以阻挡"的内涵不同:坚持者像无法减速的引擎,固执者像无法转向的舵轮。[3]
If you handed the Collisons an extremely hard problem to solve, they wouldn't become obstinate. If anything they'd become less obstinate. They'd know they had to be open to anything. Similarly, if obstinacy were caused by the situation, the obstinate would stop being obstinate when solving easier problems. But they don't. And if obstinacy isn't caused by the situation, it must come from within. It must be a feature of one's personality. Obstinacy is a reflexive resistance to changing one's ideas. This is not identical with stupidity, but they're closely related. A reflexive resistance to changing one's ideas becomes a sort of induced stupidity as contrary evidence mounts. And obstinacy is a form of not giving up that's easily practiced by the stupid. You don't have to consider complicated tradeoffs; you just dig in your heels. It even works, up to a point. The fact that obstinacy works for simple problems is an important clue. Persistence and obstinacy aren't opposites. The relationship between them is more like the relationship between the two kinds of respiration we can do: aerobic respiration, and the anaerobic respiration we inherited from our most distant ancestors. Anaerobic respiration is a more primitive process, but it has its uses. When you leap suddenly away from a threat, that's what you're using. The optimal amount of obstinacy is not zero. It can be good if your initial reaction to a setback is an unthinking "I won't give up," because this helps prevent panic. But unthinking only gets you so far. The further someone is toward the obstinate end of the continuum, the less likely they are to succeed in solving hard problems. [4] Obstinacy is a simple thing. Animals have it. But persistence turns out to have a fairly complicated internal structure. One thing that distinguishes the persistent is their energy. At the risk of putting too much weight on words, they persist rather than merely resisting.
极端情况下二者难以区分:当问题仅有一种解法时,你只能选择放弃或坚持。但随着问题复杂度增加,差异便显现。坚持者更关注决策树顶端的要点,固执者则不分轻重地对整棵树喷洒"永不放弃"。
坚持者忠于目标,固执者执着于实现路径。
更糟的是,他们往往死守最初构想——尽管这些构想最缺乏实践经验。因此固执者不仅纠缠细节,更易执着于错误细节。
为何如此?固执从何而来?起初我认为是能力不足所致:面对难题时,像颠簸船只上的乘客紧抓扶手般抓住想法。
They keep trying things. Which means the persistent must also be imaginative. To keep trying things, you have to keep thinking of things to try. Energy and imagination make a wonderful combination. Each gets the best out of the other. Energy creates demand for the ideas produced by imagination, which thus produces more, and imagination gives energy somewhere to go. [5] Merely having energy and imagination is quite rare. But to solve hard problems you need three more qualities: resilience, good judgement, and a focus on some kind of goal. Resilience means not having one's morale destroyed by setbacks. Setbacks are inevitable once problems reach a certain size, so if you can't bounce back from them, you can only do good work on a small scale. But resilience is not the same as obstinacy. Resilience means setbacks can't change your morale, not that they can't change your mind. Indeed, persistence often requires that one change one's mind. That's where good judgement comes in. The persistent are quite rational. They focus on expected value. It's this, not recklessness, that lets them work on things that are unlikely to succeed. There is one point at which the persistent are often irrational though: at the very top of the decision tree. When they choose between two problems of roughly equal expected value, the choice usually comes down to personal preference. Indeed, they'll often classify projects into deliberately wide bands of expected value in order to ensure that the one they want to work on still qualifies. Empirically this doesn't seem to be a problem. It's ok to be irrational near the top of the decision tree. One reason is that we humans will work harder on a problem we love. But there's another more subtle factor involved as well: our preferences among problems aren't random. When we love a problem that other people don't, it's often because we've unconsciously noticed that it's more important than they realize.
但细究之下此说不成立。若让坚持者解决更难题,他们不会变固执——科里森兄弟面对难题反而会更开放。同样,固执者解决简单问题时依然固执。可见固执源于性格特质。
固执是对改变想法的本能抗拒。这与愚蠢不同但密切相关:当反证堆积时,这种抗拒会演变为人为的愚蠢。且固执是不需复杂权衡的坚持方式——只需顽固到底。这在简单问题上偶有成效。
固执在简单问题上的有效性是重要线索。坚持与固执并非对立,其关系更似有氧呼吸与祖传的无氧呼吸。无氧呼吸虽原始却有用——躲避危险时的爆发力即源于此。
最佳固执度非零。遭遇挫折时本能反应"我不放弃"能防止恐慌。但本能仅能带你走这么远:越接近固执端,解决难题的可能性越低。[4]
Which leads to our fifth quality: there needs to be some overall goal. If you're like me you began, as a kid, merely with the desire to do something great. In theory that should be the most powerful motivator of all, since it includes everything that could possibly be done. But in practice it's not much use, precisely because it includes too much. It doesn't tell you what to do at this moment. So in practice your energy and imagination and resilience and good judgement have to be directed toward some fairly specific goal. Not too specific, or you might miss a great discovery adjacent to what you're searching for, but not too general, or it won't work to motivate you. [6] When you look at the internal structure of persistence, it doesn't resemble obstinacy at all. It's so much more complex. Five distinct qualities — energy, imagination, resilience, good judgement, and focus on a goal — combine to produce a phenomenon that seems a bit like obstinacy in the sense that it causes you not to give up. But the way you don't give up is completely different. Instead of merely resisting change, you're driven toward a goal by energy and resilience, through paths discovered by imagination and optimized by judgement. You'll give way on any point low down in the decision tree, if its expected value drops sufficiently, but energy and resilience keep pushing you toward whatever you chose higher up. Considering what it's made of, it's not surprising that the right kind of stubbornness is so much rarer than the wrong kind, or that it gets so much better results. Anyone can do obstinacy. Indeed, kids and drunks and fools are best at it.
固执是简单特质,动物也具备。但坚持却有着复杂的内在结构。
坚持者的首要特质是能量。他们不止抵抗,更持续尝试。这意味着坚持者还需想象力——要不断尝试新方案。
能量与想象力的结合妙不可言:能量激发想象产出,想象为能量指明方向。[5]
但解决难题还需三种特质:韧性、判断力和目标感。
Whereas very few people have enough of all five of the qualities that produce the right kind of stubbornness, but when they do the results are magical. Notes [1] I'm going to use "persistent" for the good kind of stubborn and "obstinate" for the bad kind, but I can't claim I'm simply following current usage. Conventional opinion barely distinguishes between good and bad kinds of stubbornness, and usage is correspondingly promiscuous. I could have invented a new word for the good kind, but it seemed better just to stretch "persistent." [2] There are some domains where one can succeed by being obstinate. Some political leaders have been notorious for it. But it won't work in situations where you have to pass external tests. And indeed the political leaders who are famous for being obstinate are famous for getting power, not for using it well. [3] There will be some resistance to turning the rudder of a persistent person, because there's some cost to changing direction. [4] The obstinate do sometimes succeed in solving hard problems. One way is through luck: like the stopped clock that's right twice a day, they seize onto some arbitrary idea, and it turns out to be right. Another is when their obstinacy cancels out some other form of error. For example, if a leader has overcautious subordinates, their estimates of the probability of success will always be off in the same direction. So if he mindlessly says "push ahead regardless" in every borderline case, he'll usually turn out to be right. [5] If you stop there, at just energy and imagination, you get the conventional caricature of an artist or poet. [6] Start by erring on the small side. If you're inexperienced you'll inevitably err on one side or the other, and if you err on the side of making the goal too broad, you won't get anywhere. Whereas if you err on the small side you'll at least be moving forward.
韧性指不被挫折摧毁士气。重大课题必遇挫折,若无恢复力则只能处理小问题。但韧性与固执不同:韧性保护的是士气而非观点。
坚持常需改变想法,此时判断力至关重要。坚持者非常理性,专注预期价值。正是这种理性(而非鲁莽)让他们敢于尝试低成功率的事。
但坚持者在决策树顶端常显非理性:当两个选项预期价值相当时,选择取决于个人偏好。他们常故意放宽预期价值区间,以确保心仪项目入选。
实践证明这无妨。在决策树顶端非理性是可以的——部分因为我们更努力解决热爱的问题。但还有更微妙的原因:我们对问题的偏好并非随机。当热爱某个被他人忽视的问题时,常因潜意识察觉其重要性被低估。
Then, once you're moving, you expand the goal. Thanks to Trevor Blackwell, Jessica Livingston, Jackie McDonough, Courtenay Pipkin, Harj Taggar, and Garry Tan for reading drafts of this..
由此引出第五种特质:需要总体目标。若你像我儿时那样仅怀"做大事"的愿望,这理论上应是最强动力。但实践中因过于空泛而难有指导意义。
因此能量、想象力、韧性和判断力需指向具体目标。不能太具体以免错过相邻发现,也不能太宽泛以致失去激励作用。[6]
剖析坚持的内在结构后,可见其与固执毫无相似。五种特质——能量、想象力、韧性、判断力和目标感——共同形成表面类似固执的"不放弃",但运作方式截然不同:你不是抗拒改变,而是在能量与韧性驱动下,沿着想象力发现、判断力优化的路径向目标迈进。决策树低端任何节点都可放弃(若预期价值不足),但能量与韧性会推动你持续向上攀登。
由此观之,正确的固执远比错误的罕见且高效,实属必然。任何人都能固执——孩童、醉汉和愚人最擅此道。但兼具五种特质者凤毛麟角,而他们创造的奇迹令人惊叹。
注释 [1] 本文用"persistent"指良性固执,"obstinate"指恶性固执,但并非严格遵循现有用法。 [2] 某些领域(如政界)靠固执可获成功,但需经外部检验的领域行不通。 [3] 改变坚持者的方向亦有阻力,因转向存在成本。 [4] 固执者偶能解决难题:或靠运气(如停走的钟每天准两次),或因固执抵消其他错误(如领导用固执平衡下属的过度谨慎)。 [5] 仅有能量与想象力会形成艺术家或诗人的刻板印象。 [6] 目标设定宜先偏具体。经验不足时犯错难免,但目标过宽会停滞不前,稍窄至少能推进。
March 2024 I met the Reddits before we even started Y Combinator. In fact they were one of the reasons we started it. YC grew out of a talk I gave to the Harvard Computer Society (the undergrad computer club) about how to start a startup. Everyone else in the audience was probably local, but Steve and Alexis came up on the train from the University of Virginia, where they were seniors. Since they'd come so far I agreed to meet them for coffee. They told me about the startup idea we'd later fund them to drop: a way to order fast food on your cellphone. This was before smartphones. They'd have had to make deals with cell carriers and fast food chains just to get it launched. So it was not going to happen. It still doesn't exist, 19 years later. But I was impressed with their brains and their energy. In fact I was so impressed with them and some of the other people I met at that talk that I decided to start something to fund them. A few days later I told Steve and Alexis that we were starting Y Combinator, and encouraged them to apply. That first batch we didn't have any way to identify applicants, so we made up nicknames for them. The Reddits were the "Cell food muffins." "Muffin" is a term of endearment Jessica uses for things like small dogs and two year olds. So that gives you some idea what kind of impression Steve and Alexis made in those days. They had the look of slightly ruffled surprise that baby birds have. Their idea was bad though. And since we thought then that we were funding ideas rather than founders, we rejected them. But we felt bad about it. Jessica was sad that we'd rejected the muffins. And it seemed wrong to me to turn down the people we'd been inspired to start YC to fund. I don't think the startup sense of the word "pivot" had been invented yet, but we wanted to fund Steve and Alexis, so if their idea was bad, they'd have to work on something else. And I knew what else.
早在Y Combinator成立之前,我就认识了Reddit的创始人。事实上,他们正是我们决定创立YC的原因之一。
YC源于我在哈佛计算机协会(本科生计算机社团)的一次演讲,主题是如何创业。观众中的其他人可能都是本地人,但史蒂夫和亚历克西斯却从弗吉尼亚大学乘火车赶来,当时他们是大四学生。由于他们远道而来,我同意和他们喝杯咖啡。他们向我讲述了一个创业想法,后来我们资助他们放弃了这个想法:一种通过手机订购快餐的方式。
那时还没有智能手机。他们必须与移动运营商和快餐连锁店达成协议才能推出这项服务。所以这根本不可能实现。19年后的今天,这个想法依然不存在。但他们的智慧和活力给我留下了深刻印象。事实上,我对他们以及在那次演讲中遇到的其他人印象如此深刻,以至于我决定创立一个项目来资助他们。几天后,我告诉史蒂夫和亚历克西斯,我们将成立Y Combinator,并鼓励他们申请。
在第一批项目中,我们没有任何方法来识别申请人,所以给他们起了绰号。Reddit的创始人被称为“Cell food muffins”(手机快餐松饼)。“松饼”是杰西卡用来称呼小狗或两岁小孩的昵称。这可以让你对史蒂夫和亚历克西斯当时给人的印象有所了解。他们看起来像小鸟一样,带着些许凌乱的惊讶。
In those days there was a site called Delicious where you could save links. It had a page called del.icio.us/popular that listed the most-saved links, and people were using this page as a de facto Reddit. I knew because a lot of the traffic to my site was coming from it. There needed to be something like del.icio.us/popular, but designed for sharing links instead of being a byproduct of saving them. So I called Steve and Alexis and said that we liked them, just not their idea, so we'd fund them if they'd work on something else. They were on the train home to Virginia at that point. They got off at the next station and got on the next train north, and by the end of the day were committed to working on what's now called Reddit. They would have liked to call it Snoo, as in "What snoo?" But snoo.com was too expensive, so they settled for calling the mascot Snoo and picked a name for the site that wasn't registered. Early on Reddit was just a provisional name, or so they told me at least, but it's probably too late to change it now. As with all the really great startups, there's an uncannily close match between the company and the founders. Steve in particular. Reddit has a certain personality — curious, skeptical, ready to be amused — and that personality is Steve's. Steve will roll his eyes at this, but he's an intellectual; he's interested in ideas for their own sake. That was how he came to be in that audience in Cambridge in the first place. He knew me because he was interested in a programming language I've written about called Lisp, and Lisp is one of those languages few people learn except out of intellectual curiosity. Steve's kind of vacuum-cleaner curiosity is exactly what you want when you're starting a site that's a list of links to literally anything interesting. Steve was not a big fan of authority, so he also liked the idea of a site without editors. In those days the top forum for programmers was a site called Slashdot.
不过,他们的想法很糟糕。由于当时我们认为我们是在资助想法而非创始人,所以我们拒绝了他们。但我们对此感到内疚。杰西卡因为拒绝了“松饼”而难过。对我来说,拒绝那些激励我们创立YC去资助的人似乎也是错误的。
我不认为“pivot”(转型)这个词的创业含义当时已经出现,但我们想资助史蒂夫和亚历克西斯,所以如果他们的想法不好,他们就得做点别的。而我知道该做什么。那时有一个叫Delicious的网站,可以保存链接。它有一个页面叫del.icio.us/popular,列出了最常保存的链接,人们把这个页面当作事实上的Reddit使用。我知道这一点,因为我的网站很多流量都来自那里。我们需要一个类似del.icio.us/popular的东西,但它是专门为分享链接而设计的,而不是保存链接的副产品。
于是我打电话给史蒂夫和亚历克西斯,说我们喜欢他们,只是不喜欢他们的想法,所以如果他们愿意做点别的,我们会资助他们。当时他们正在回弗吉尼亚的火车上。他们在下一站下车,换乘北上的列车,当天就决定着手开发现在被称为Reddit的东西。
他们本想叫它“Snoo”,比如“What snoo?”,但snoo.com太贵了,所以他们决定用Snoo作为吉祥物的名字,并为网站选了一个未被注册的名字。早期Reddit只是一个临时名称,至少他们是这么告诉我的,但现在可能已经来不及改了。
It was a lot like Reddit, except the stories on the frontpage were chosen by human moderators. And though they did a good job, that one small difference turned out to be a big difference. Being driven by user submissions meant Reddit was fresher than Slashdot. News there was newer, and users will always go where the newest news is. I pushed the Reddits to launch fast. A version one didn't need to be more than a couple hundred lines of code. How could that take more than a week or two to build? And they did launch comparatively fast, about three weeks into the first YC batch. The first users were Steve, Alexis, me, and some of their YC batchmates and college friends. It turns out you don't need that many users to collect a decent list of interesting links, especially if you have multiple accounts per user. Reddit got two more people from their YC batch: Chris Slowe and Aaron Swartz, and they too were unusually smart. Chris was just finishing his PhD in physics at Harvard. Aaron was younger, a college freshman, and even more anti-authority than Steve. It's not exaggerating to describe him as a martyr for what authority later did to him. Slowly but inexorably Reddit's traffic grew. At first the numbers were so small they were hard to distinguish from background noise. But within a few weeks it was clear that there was a core of real users returning regularly to the site. And although all kinds of things have happened to Reddit the company in the years since, Reddit the _site_ never looked back. Reddit the site (and now app) is such a fundamentally useful thing that it's almost unkillable. Which is why, despite a long stretch after Steve left when the management strategy ranged from benign neglect to spectacular blunders, traffic just kept growing. You can't do that with most companies. Most companies you take your eye off the ball for six months and you're in deep trouble.
和所有真正伟大的初创公司一样,这家公司和创始人之间有一种不可思议的契合。尤其是史蒂夫。Reddit有一种独特的个性——好奇、怀疑、乐于被逗乐——这种个性就是史蒂夫的个性。
史蒂夫会对这种说法翻白眼,但他确实是一个知识分子;他对思想本身感兴趣。这也是他最初出现在剑桥那次演讲现场的原因。他认识我是因为他对一种我写过的编程语言Lisp感兴趣,而Lisp是那种很少有人会出于纯粹的知识好奇而去学习的语言之一。史蒂夫那种吸尘器般的好奇心正是你创办一个链接列表网站时所需要的,这个网站可以链接到任何有趣的东西。
史蒂夫不太喜欢权威,所以他也很喜欢一个没有编辑的网站的想法。那时程序员最热衷的论坛是一个叫Slashdot的网站。它和Reddit很像,只是首页的故事是由人工版主挑选的。尽管他们做得不错,但这一小小的差异最终却产生了巨大的影响。由用户提交驱动意味着Reddit比Slashdot更新鲜。那里的新闻更新,而用户总是会去新闻最新鲜的地方。
我催促Reddit团队尽快上线。第一版只需要几百行代码。怎么可能需要超过一两周的时间来开发?他们的确相对较快地推出了,大约在YC第一批项目开始三周后。最初的用户是史蒂夫、亚历克西斯、我,以及他们的一些YC同学和大学朋友。事实证明,你不需要太多用户就能收集一份不错的有趣链接列表,尤其是如果每个用户有多个账号的话。
But Reddit was special, and when Steve came back in 2015, I knew the world was in for a surprise. People thought they had Reddit's number: one of the players in Silicon Valley, but not one of the big ones. But those who knew what had been going on behind the scenes knew there was more to the story than this. If Reddit could grow to the size it had with management that was harmless at best, what could it do if Steve came back? We now know the answer to that question. Or at least a lower bound on the answer. Steve is not out of ideas yet..
Reddit还从他们的YC批次中吸纳了另外两个人:克里斯·斯洛和亚伦·斯沃茨,他们也异常聪明。克里斯当时即将完成哈佛大学的物理学博士学位。亚伦更年轻,是一名大学新生,甚至比史蒂夫更反权威。后来权威对他所做的一切,用“殉道者”来形容他并不夸张。
Reddit的流量缓慢但不可阻挡地增长。起初数字太小,几乎无法与背景噪音区分。但几周内就很明显,有一批真正的核心用户在定期访问网站。尽管这些年来Reddit这家公司经历了各种各样的事情,但Reddit这个网站从未回头。
Reddit这个网站(现在是应用)是一个如此基础且有用的东西,几乎无法被摧毁。这就是为什么,尽管在史蒂夫离开后的一段时间里,管理策略从善意的忽视到惊人的失误不一而足,但流量仍在持续增长。大多数公司做不到这一点。大多数公司只要六个月不关注,就会陷入大麻烦。但Reddit很特别,当史蒂夫在2015年回归时,我知道世界将迎来一个惊喜。
人们以为他们看透了Reddit:硅谷的玩家之一,但不是巨头之一。但那些知道幕后故事的人明白,事情远不止如此。如果Reddit能在管理至多无害的情况下发展到如此规模,那么如果史蒂夫回来,它能做到什么程度?我们现在知道了这个问题的答案。或者至少是答案的下限。史蒂夫的想法还没有枯竭。
March 2024 Despite its title this isn't meant to be the best essay. My goal here is to figure out what the best essay would be like. It would be well-written, but you can write well about any topic. What made it special would be what it was about. Obviously some topics would be better than others. It probably wouldn't be about this year's lipstick colors. But it wouldn't be vaporous talk about elevated themes either. A good essay has to be surprising. It has to tell people something they don't already know. The best essay would be on the most important topic you could tell people something surprising about. That may sound obvious, but it has some unexpected consequences. One is that science enters the picture like an elephant stepping into a rowboat. For example, Darwin first described the idea of natural selection in an essay written in 1844. Talk about an important topic you could tell people something surprising about. If that's the test of a great essay, this was surely the best one written in 1844. And indeed, the best possible essay at any given time would usually be one describing the most important scientific or technological discovery it was possible to make. [1] Another unexpected consequence: I imagined when I started writing this that the best essay would be fairly timeless — that the best essay you could write in 1844 would be much the same as the best one you could write now. But in fact the opposite seems to be true. It might be true that the best painting would be timeless in this sense. But it wouldn't be impressive to write an essay introducing natural selection now. The best essay _now_ would be one describing a great discovery we didn't yet know about. If the question of how to write the best possible essay reduces to the question of how to make great discoveries, then I started with the wrong question.
尽管标题如此,本文并非要成为最佳文章。我的目标是探究最佳文章应该具备哪些特质。
它必然文笔优美,但任何主题都可以写出好文章。真正使其特别的是它所探讨的内容。
显然某些主题更具优势。它大概率不会讨论今年的口红流行色,但也不会是那些故作高深的空泛之谈。好文章必须出人意料,必须告诉人们他们尚未知晓的事物。
最佳文章应当在你所能告知人们最令人惊讶的重要主题上展开。
这听起来或许显而易见,却衍生出一些意料之外的结论。其一,科学如同大象踏入小舟般强势介入这个领域。例如达尔文在1844年的文章中首次阐述自然选择理论——这正是关于重要主题的惊人洞见。若以此作为评判标准,这无疑是1844年问世的最佳文章。事实上,任何时代可能诞生的最佳文章,通常都会是描述当时最重要的科学或技术发现的篇章。[1]
Perhaps what this exercise shows is that we shouldn't waste our time writing essays but instead focus on making discoveries in some specific domain. But I'm interested in essays and what can be done with them, so I want to see if there's some other question I could have asked. There is, and on the face of it, it seems almost identical to the one I started with. Instead of asking _what would the best essay be?_ I should have asked _how do you write essays well?_ Though these seem only phrasing apart, their answers diverge. The answer to the first question, as we've seen, isn't really about essay writing. The second question forces it to be. Writing essays, at its best, is a way of discovering ideas. How do you do that well? How do you discover by writing? An essay should ordinarily start with what I'm going to call a question, though I mean this in a very general sense: it doesn't have to be a question grammatically, just something that acts like one in the sense that it spurs some response. How do you get this initial question? It probably won't work to choose some important-sounding topic at random and go at it. Professional traders won't even trade unless they have what they call an _edge_ — a convincing story about why in some class of trades they'll win more than they lose. Similarly, you shouldn't attack a topic unless you have a way in — some new insight about it or way of approaching it. You don't need to have a complete thesis; you just need some kind of gap you can explore. In fact, merely having questions about something other people take for granted can be edge enough. If you come across a question that's sufficiently puzzling, it could be worth exploring even if it doesn't seem very momentous. Many an important discovery has been made by pulling on a thread that seemed insignificant at first. How can they _all_ be finches? [2] Once you've got a question, then what? You start thinking out loud about it.
另一个意外结论:动笔之初,我设想最佳文章应当具备永恒性——1844年能写出的最佳文章与今日并无二致。但事实似乎恰恰相反。最佳绘画或许能实现这种永恒,但如今再写介绍自然选择的文章已无震撼力。此刻的最佳文章应当揭示我们尚未知晓的伟大发现。
如果"如何写出最佳文章"的问题最终归结为"如何做出伟大发现",那么我从一开始就问错了问题。或许这个思考过程表明:我们不该浪费时间写文章,而应专注于特定领域的发现。但出于对文章形式的兴趣及其可能性,我想探寻是否存在更恰当的问题。
确实存在,且表面看来与我最初的问题几乎相同。与其问"最佳文章应该是怎样的",不如问"如何写好文章"。虽然二者看似仅措辞不同,答案却大相径庭。第一个问题的答案(如我们所见)实则与写作技巧无关,而第二个问题则强制回归写作本身。
写作本质上是一种发现思想的方式。如何做好这件事?如何通过写作进行探索?
文章通常始于我称之为"问题"的起点——此处"问题"取广义:不必是语法疑问句,只要能激发思考的切入点即可。
Not literally out loud, but you commit to a specific string of words in response, as you would if you were talking. This initial response is usually mistaken or incomplete. Writing converts your ideas from vague to bad. But that's a step forward, because once you can see the brokenness, you can fix it. Perhaps beginning writers are alarmed at the thought of starting with something mistaken or incomplete, but you shouldn't be, because this is why essay writing works. Forcing yourself to commit to some specific string of words gives you a starting point, and if it's wrong, you'll see that when you reread it. At least half of essay writing is rereading what you've written and asking _is this correct and complete?_ You have to be very strict when rereading, not just because you want to keep yourself honest, but because a gap between your response and the truth is often a sign of new ideas to be discovered. The prize for being strict with what you've written is not just refinement. When you take a roughly correct answer and try to make it exactly right, sometimes you find that you can't, and that the reason is that you were depending on a false assumption. And when you discard it, the answer turns out to be completely different. [3] Ideally the response to a question is two things: the first step in a process that converges on the truth, and a source of additional questions (in my very general sense of the word). So the process continues recursively, as response spurs response. [4] Usually there are several possible responses to a question, which means you're traversing a tree. But essays are linear, not tree-shaped, which means you have to choose one branch to follow at each point. How do you choose? Usually you should follow whichever offers the greatest combination of generality and novelty.
如何获得初始问题?随机选择听起来重要的主题往往行不通。专业交易员除非拥有所谓"优势"(即对某类交易盈亏比的确信),否则不会轻易出手。同理,除非你对某个主题有新见解或新方法,否则不宜贸然动笔。
你不需要完整的论点,只需发现值得探索的空白领域。事实上,仅对他人视为理所当然的事物提出质疑,就足以构成优势。
若遇到足够引人深思的问题,即便看似微不足道也值得探索。许多重要发现都始于最初不起眼的线索。比如:它们怎么可能都是雀鸟?[2]
获得问题后该做什么?开始"大声思考"——非字面意义的出声,而是像对话般用具体文字表述回应。初始回应通常存在谬误或不完整,写作会将模糊想法转化为糟糕文字。但这正是进步契机,因为发现缺陷才能修正。
新手作家或许会因始于错误或不完整而惶恐,但这正是写作的价值所在。强制用文字表述观点提供了起点,重读时你自会发现问题。至少半数写作时间应用于重读并自问:这正确且完整吗?必须严格审视,不仅为保持诚实,更因观点与真相的差距往往暗示新发现。
严格审视的回报不仅是精炼。当你试图将大致正确的答案修正为完全正确时,有时会发现受阻于错误假设。一旦摒弃假设,答案可能截然不同。[3]
I don't consciously rank branches this way; I just follow whichever seems most exciting; but generality and novelty are what make a branch exciting. [5] If you're willing to do a lot of rewriting, you don't have to guess right. You can follow a branch and see how it turns out, and if it isn't good enough, cut it and backtrack. I do this all the time. In this essay I've already cut a 17-paragraph subtree, in addition to countless shorter ones. Maybe I'll reattach it at the end, or boil it down to a footnote, or spin it off as its own essay; we'll see. [6] In general you want to be quick to cut. One of the most dangerous temptations in writing (and in software and painting) is to keep something that isn't right, just because it contains a few good bits or cost you a lot of effort. The most surprising new question being thrown off at this point is _does it really matter what the initial question is?_ If the space of ideas is highly connected, it shouldn't, because you should be able to get from any question to the most valuable ones in a few hops. And we see evidence that it's highly connected in the way, for example, that people who are obsessed with some topic can turn any conversation toward it. But that only works if you know where you want to go, and you don't in an essay. That's the whole point. You don't want to be the obsessive conversationalist, or all your essays will be about the same thing. [7] The other reason the initial question matters is that you usually feel somewhat obliged to stick to it. I don't think about this when I decide which branch to follow. I just follow novelty and generality. Sticking to the question is enforced later, when I notice I've wandered too far and have to backtrack. But I think this is the optimal solution. You don't want the hunt for novelty and generality to be constrained in the moment.
理想情况下,问题回应应具备双重属性:既是通向真相的第一步,又是新问题的源泉(取"问题"广义)。这个过程递归持续,回应不断催生新回应。[4]
通常问题存在多个可能回应,意味着你在遍历思维树。但文章是线性的,必须在每个节点选择分支。如何选择?通常应追随兼具普适性与新颖性的路径。我并非有意识评分,只是追随最令人兴奋的方向——而普适性与新颖性正是令人兴奋的要素。[5]
若愿意反复修改,就无需准确预判。你可以探索某条分支,效果不佳便回撤重来。我经常如此操作,本文已删去17段的子章节,更遑论无数短段落。或许我会将其重组为结尾,或浓缩为脚注,或另成新文。[6]
总之要果断删减。写作(及编程、绘画)最危险的诱惑就是保留不当内容,仅因其含某些亮点或耗费心血。
此时浮现的最惊人新问题是:初始问题真的重要吗?若思想空间高度互联,理论上不重要——你应能通过几次跳跃从任何问题抵达最有价值的问题。某些话题狂热者总能将任何对话转向其痴迷领域,就是这种互联性的体现。但这仅适用于目标明确的情况,而文章创作恰恰相反——你不想成为那种偏执的对话者,否则所有文章都会雷同。[7]
Go with it and see what you get. [8] Since the initial question does constrain you, in the best case it sets an upper bound on the quality of essay you'll write. If you do as well as you possibly can on the chain of thoughts that follow from the initial question, the initial question itself is the only place where there's room for variation. It would be a mistake to let this make you too conservative though, because you can't predict where a question will lead. Not if you're doing things right, because doing things right means making discoveries, and by definition you can't predict those. So the way to respond to this situation is not to be cautious about which initial question you choose, but to write a lot of essays. Essays are for taking risks. Almost any question can get you a good essay. Indeed, it took some effort to think of a sufficiently unpromising topic in the third paragraph, because any essayist's first impulse on hearing that the best essay couldn't be about x would be to try to write it. But if most questions yield good essays, only some yield great ones. Can we predict which questions will yield great essays? Considering how long I've been writing essays, it's alarming how novel that question feels. One thing I like in an initial question is outrageousness. I love questions that seem naughty in some way — for example, by seeming counterintuitive or overambitious or heterodox. Ideally all three. This essay is an example. Writing about the best essay implies there is such a thing, which pseudo-intellectuals will dismiss as reductive, though it follows necessarily from the possibility of one essay being better than another. And thinking about how to do something so ambitious is close enough to doing it that it holds your attention. I like to start an essay with a gleam in my eye.
初始问题重要的另一原因是:你通常有义务围绕它展开。选择分支时我并未考虑这点,只追随新颖与普适。当发现偏离太远需要回撤时,才体现对问题的忠诚。但这是最优解——不应在探索过程中限制对新奇与普适的追求。[8]
既然初始问题构成限制,最佳情况下它决定了文章质量上限。若你在问题引发的思维链上做到极致,唯一变量就是初始问题本身。
但因此变得保守则是错误,因为你无法预知问题导向何方。若你正确行事(即有所发现),这些发现本质上是不可预测的。正确应对方式是不要谨慎选择初始问题,而是多写文章。文章本为冒险而生。
几乎所有问题都能产出好文章。实际上,我在第三段刻意构想缺乏潜力的主题都颇费心思——因为任何作家听闻"最佳文章不能关于X"时,第一反应都是挑战这个论断。但若多数问题能产生好文章,只有少数能成就伟大篇章。
我们能否预测哪些问题催生伟大文章?考虑到我写作多年的经历,此刻才提出这个问题着实令人不安。
我钟爱具有挑衅性的初始问题——那些看似反直觉、野心过大或离经叛道的提问,最好三者兼备。本文即是一例。探讨"最佳文章"暗示其存在性,伪知识分子会斥之为简化论,但这不过是"文章有优劣之分"的必然推论。思考如此宏大的目标本身已足够吸引人。
This could be just a taste of mine, but there's one aspect of it that probably isn't: to write a really good essay on some topic, you have to be interested in it. A good writer can write well about anything, but to stretch for the novel insights that are the raison d'etre of the essay, you have to care. If caring about it is one of the criteria for a good initial question, then the optimal question varies from person to person. It also means you're more likely to write great essays if you care about a lot of different things. The more curious you are, the greater the probable overlap between the set of things you're curious about and the set of topics that yield great essays. What other qualities would a great initial question have? It's probably good if it has implications in a lot of different areas. And I find it's a good sign if it's one that people think has already been thoroughly explored. But the truth is that I've barely thought about how to choose initial questions, because I rarely do it. I rarely _choose_ what to write about; I just start thinking about something, and sometimes it turns into an essay. Am I going to stop writing essays about whatever I happen to be thinking about and instead start working my way through some systematically generated list of topics? That doesn't sound like much fun. And yet I want to write good essays, and if the initial question matters, I should care about it. Perhaps the answer is to go one step earlier: to write about whatever pops into your head, but try to ensure that what pops into your head is good. Indeed, now that I think about it, this has to be the answer, because a mere list of topics wouldn't be any use if you didn't have edge with any of them. To start writing an essay, you need a topic plus some initial insight about it, and you can't generate those systematically. If only. [9] You can probably cause yourself to have more of them, though.
我喜欢带着眼中闪光开始写作。这或许是我的个人偏好,但有一点具有普适性:要就某个主题写出真正的好文章,你必须对其充满兴趣。优秀作家可以写好任何主题,但要挖掘作为文章存在理由的新颖洞见,你必须心怀热忱。
若"热忱"是优秀初始问题的标准之一,那么最优问题因人而异。这也意味着,你对越多事物感兴趣,越可能写出伟大文章。好奇心越旺盛,你感兴趣的事物与能产出伟大文章的主题交集就越大。
伟大初始问题还需哪些特质?若其影响能辐射多个领域会更好。我发现,那些被认为已彻底探讨过的问题往往蕴藏潜力。但说实话,我很少思考如何选择初始问题——因为我极少主动选择。我很少"决定"写什么,只是开始思考某事,有时便自然成文。
我是否会停止随性写作,转而按系统生成的主题清单创作?这听起来毫无乐趣。但既然我想写出好文章,而初始问题又至关重要,我就应该重视它。
或许答案在于更早的环节:继续写脑海中浮现的内容,但努力确保这些内容是优质的。细想之下,这必是正解——若对清单上的主题毫无优势,清单本身便无意义。开始写作需要主题加初步见解,这些无法系统生成。要是能就好了。[9]
The quality of the ideas that come out of your head depends on what goes in, and you can improve that in two dimensions, breadth and depth. You can't learn everything, so getting breadth implies learning about topics that are very different from one another. When I tell people about my book-buying trips to Hay and they ask what I buy books about, I usually feel a bit sheepish answering, because the topics seem like a laundry list of unrelated subjects. But perhaps that's actually optimal in this business. You can also get ideas by talking to people, by doing and building things, and by going places and seeing things. I don't think it's important to talk to new people so much as the sort of people who make you have new ideas. I get more new ideas after talking for an afternoon with Robert Morris than from talking to 20 new smart people. I know because that's what a block of office hours at Y Combinator consists of. While breadth comes from reading and talking and seeing, depth comes from doing. The way to really learn about some domain is to have to solve problems in it. Though this could take the form of writing, I suspect that to be a good essayist you also have to do, or have done, some other kind of work. That may not be true for most other fields, but essay writing is different. You could spend half your time working on something else and be net ahead, so long as it was hard. I'm not proposing that as a recipe so much as an encouragement to those already doing it. If you've spent all your life so far working on other things, you're already halfway there. Though of course to be good at writing you have to like it, and if you like writing you'd probably have spent at least some time doing it. Everything I've said about initial questions applies also to the questions you encounter in writing the essay. They're the same thing; every subtree of an essay is usually a shorter essay, just as every subtree of a Calder mobile is a smaller mobile.
不过你或许可以主动催生更多灵感。头脑产出思想的质量取决于输入,这可以从广度和深度两个维度提升。
人无法学尽万物,获取广度意味着学习差异巨大的领域。当人们问及我在海伊镇购书的内容时,我常因书单主题杂乱而羞于启齿。但或许这正是最优策略。
与人交谈、动手实践、游历观察也能激发思想。重点不在于接触新人,而在于接触能激发新思想的人。与罗伯特·莫里斯聊一下午的收获,远胜于与二十个聪明新人的交谈——我在Y Combinator办公时间的经历证明了这点。
广度来自阅读、交谈与观察,深度则来自实践。真正掌握某个领域需要解决其中的问题。虽然写作本身也是实践,但我怀疑要成为优秀作家,还必须从事过其他类型的工作。这对其他领域或许不适用,但文章写作与众不同——只要你同时从事的领域足够艰深,即使分走一半时间也值得。
我提出这点更多是为鼓励已在实践的人。若你迄今都在从事其他工作,你已成功一半——当然,要写好文章必须热爱写作,而热爱写作的人多少会花时间练习。
关于初始问题的所有论述,同样适用于写作过程中遇到的问题。它们是同质的——文章的每个子章节都是更短的文章,就像考尔德动态雕塑的每个部件都是小型动态雕塑。因此,获取优质初始问题的方法,也是写出完整好文章的方法。
So any technique that gets you good initial questions also gets you good whole essays. At some point the cycle of question and response reaches what feels like a natural end. Which is a little suspicious; shouldn't every answer suggest more questions? I think what happens is that you start to feel sated. Once you've covered enough interesting ground, you start to lose your appetite for new questions. Which is just as well, because the reader is probably feeling sated too. And it's not lazy to stop asking questions, because you could instead be asking the initial question of a new essay. That's the ultimate source of drag on the connectedness of ideas: the discoveries you make along the way. If you discover enough starting from question A, you'll never make it to question B. Though if you keep writing essays you'll gradually fix this problem by burning off such discoveries. So bizarrely enough, writing lots of essays makes it as if the space of ideas were more highly connected. When a subtree comes to an end, you can do one of two things. You can either stop, or pull the Cubist trick of laying separate subtrees end to end by returning to a question you skipped earlier. Usually it requires some sleight of hand to make the essay flow continuously at this point, but not this time. This time I actually need an example of the phenomenon. For example, we discovered earlier that the best possible essay wouldn't usually be timeless in the way the best painting would. This seems surprising enough to be worth investigating further. There are two senses in which an essay can be timeless: to be about a matter of permanent importance, and always to have the same effect on readers. With art these two senses blend together. Art that looked beautiful to the ancient Greeks still looks beautiful to us. But with essays the two senses diverge, because essays teach, and you can't teach people something they already know.
当问答循环达到自然终点时,就该停笔了。这略显可疑——每个答案不该催生新问题吗?我想这是因为你开始感到满足。覆盖足够多有趣领域后,你对新问题的胃口自然减退。这正好,因为读者可能也满足了。停止提问并非懒惰,因为你完全可以转向新文章的初始问题。
这是思想互联性的终极阻力:你在探索过程中的发现。若从问题A出发发现足够多,你将永远无法抵达问题B。但通过持续写作逐步消耗这些发现,写作量越大,思想空间就越显得高度互联——这颇为吊诡。
当子章节结束时,你有两种选择:要么停笔,要么像立体派画家那样,将之前跳过的子章节首尾相连。通常这需要些技巧来保持行文流畅,但这次不必——我正好需要这种现象的例证。例如前文发现:最佳文章通常不具备最佳绘画那种永恒性。这足够令人惊讶,值得深入探讨。
文章的永恒性有两种含义:探讨永久重要的话题,或对读者产生恒久影响。艺术中二者交融——古希腊人认为美的艺术,今人依然觉得美。但文章的教学功能使二者分离,因为你无法教授已知知识。自然选择无疑是永恒重要的话题,但解释它的文章对今人的影响,不可能与达尔文时代相同——正因其理论太成功,已成为常识。[10]
动笔时我曾想象,最佳文章应具备更严格的永恒性:包含能同时吸引亚里士多德与费曼的深邃智慧。事实似乎并非如此。但若最佳文章通常不具备这种严格永恒性,那么如何写出具备这种特质的文章?
Natural selection is certainly a matter of permanent importance, but an essay explaining it couldn't have the same effect on us that it would have had on Darwin's contemporaries, precisely because his ideas were so successful that everyone already knows about them. [10] I imagined when I started writing this that the best possible essay would be timeless in the stricter, evergreen sense: that it would contain some deep, timeless wisdom that would appeal equally to Aristotle and Feynman. That doesn't seem to be true. But if the best possible essay wouldn't usually be timeless in this stricter sense, what would it take to write essays that were? The answer to that turns out to be very strange: to be the evergreen kind of timeless, an essay has to be ineffective, in the sense that its discoveries aren't assimilated into our shared culture. Otherwise there will be nothing new in it for the second generation of readers. If you want to surprise readers not just now but in the future as well, you have to write essays that won't stick — essays that, no matter how good they are, won't become part of what people in the future learn before they read them. [11] I can imagine several ways to do that. One would be to write about things people never learn. For example, it's a long-established pattern for ambitious people to chase after various types of prizes, and only later, perhaps too late, to realize that some of them weren't worth as much as they thought. If you write about that, you can be confident of a conveyor belt of future readers to be surprised by it. Ditto if you write about the tendency of the inexperienced to overdo things — of young engineers to produce overcomplicated solutions, for example. There are some kinds of mistakes people never learn to avoid except by making them. Any of those should be a timeless topic.
答案出人意料:要具备严格意义上的永恒性,文章必须"无效"——即其发现未被主流文化吸收。否则第二代读者将感受不到新意。若想持续给未来读者惊喜,你必须写那些"留不住"的文章——无论多优秀,都不会成为后人阅读前的必修课。[11]
我能想到几种方法:一是写人们永远学不会的事。例如,野心家追逐各类奖项后才发现某些奖项价值不符预期,这类主题永远会有新读者感到惊讶。
同样有效的还有写关于缺乏经验者容易过度的倾向——比如年轻工程师总设计过度复杂的方案。有些错误必须亲身经历才能避免,这类主题永远鲜活。
有时我们难以理解某事,不仅因为迟钝或否认,还因遭遇刻意欺骗。成人对孩子撒的谎_很多_,却不会在你成年后列出清单告知——他们不记得说过哪些谎,何况多数谎言本就隐晦。只要谎言持续,揭穿它们就永远能带来惊喜。
有时是系统在欺骗你。例如多数国家的教育体系训练你通过_应试技巧_取胜。但现实世界的重要考验不适用这套规则,数十年训练使新人难以理解这点。只要体制依旧畸形,帮助人们识破这类系统性谎言就永远有效。[12]
另一种永恒性配方是写读者已知、但文化传播难以详述的事。比如"人人都知道"_养育孩子_有回报,但未经历者不知具体形式,即便经历者也难言传。
Sometimes when we're slow to grasp things it's not just because we're obtuse or in denial but because we've been deliberately lied to. There are a lot of things adults _lie_ to kids about, and when you reach adulthood, they don't take you aside and hand you a list of them. They don't remember which lies they told you, and most were implicit anyway. So contradicting such lies will be a source of surprises for as long as adults keep telling them. Sometimes it's systems that lie to you. For example, the educational systems in most countries train you to win by _hacking the test_. But that's not how you win at the most important real-world tests, and after decades of training, this is hard for new arrivals in the real world to grasp. Helping them overcome such institutional lies will work as long as the institutions remain broken. [12] Another recipe for timelessness is to write about things readers already know, but in much more detail than can be transmitted culturally. "Everyone knows," for example, that it can be rewarding to have _kids_. But till you have them you don't know precisely what forms that takes, and even then much of what you know you may never have put into words. I've written about all these kinds of topics. But I didn't do it in a deliberate attempt to write essays that were timeless in the stricter sense. And indeed, the fact that this depends on one's ideas not sticking suggests that it's not worth making a deliberate attempt to. You should write about topics of timeless importance, yes, but if you do such a good job that your conclusions stick and future generations find your essay obvious instead of novel, so much the better. You've crossed into Darwin territory. Writing about topics of timeless importance is an instance of something even more general, though: breadth of applicability.
我写过所有这些类型的主题,但并非刻意追求严格永恒性。既然这种永恒性依赖于思想不被吸收,刻意追求或许不值。当然应该写具有永恒重要性的主题,但若你的结论被后世吸收,使其觉得你的文章平淡无奇而非新颖深刻——那更好,说明你已跻身达尔文的领域。
书写永恒重要主题是更普遍原则的特例:广泛适用性。除时间维度外,还有跨领域等多元广度。因此广度是终极目标。
我始终追求广度与新颖性。但现在更清楚永恒性在其中的位置。
通过这次对写作本质的巡礼,许多问题变得清晰。起初我希望能获得选题建议——若假设文笔俱佳,区分最佳文章的唯一因素就是主题。我确实得到了建议:去发现自然选择理论。这当然好,但退一步问:在无法取得重大发现时,最佳策略是什么?答案指向写作程序本身。文章质量最终取决于其中发现的思想,而获取方法在于广泛捕捉问题并严格审视答案。
这幅写作地图最显著的特征,是灵感与努力交替出现的条纹。问题依赖灵感,答案却可凭毅力获得。你不必一次答对,但最终必须正确——因为你可以不断修改直至完美。这不仅理论可行,也正是我的工作方式。此刻我就在边写边改。
And there are more kinds of breadth than chronological — applying to lots of different fields, for example. So breadth is the ultimate aim. I already aim for it. Breadth and novelty are the two things I'm always chasing. But I'm glad I understand where timelessness fits. I understand better where a lot of things fit now. This essay has been a kind of tour of essay writing. I started out hoping to get advice about topics; if you assume good writing, the only thing left to differentiate the best essay is its topic. And I did get advice about topics: discover natural selection. Yeah, that would be nice. But when you step back and ask what's the best you can do short of making some great discovery like that, the answer turns out to be about procedure. Ultimately the quality of an essay is a function of the ideas discovered in it, and the way you get them is by casting a wide net for questions and then being very exacting with the answers. The most striking feature of this map of essay writing are the alternating stripes of inspiration and effort required. The questions depend on inspiration, but the answers can be got by sheer persistence. You don't have to get an answer right the first time, but there's no excuse for not getting it right eventually, because you can keep rewriting till you do. And this is not just a theoretical possibility. It's a pretty accurate description of the way I work. I'm rewriting as we speak. But although I wish I could say that writing great essays depends mostly on effort, in the limit case it's inspiration that makes the difference. In the limit case, the questions are the harder thing to get. That pool has no bottom. How to get more questions? That is the most important question of all. Notes [1] There might be some resistance to this conclusion on the grounds that some of these discoveries could only be understood by a small number of readers.
尽管我希望可以说伟大文章主要依赖努力,但在极限情况下,灵感才是关键。极限情况下,问题才是更难获取的要素。这个深潭没有底。
如何获得更多问题?这才是最重要的问题。
[1] 有人可能反对这个结论,认为某些发现只有少数人能理解。但若因此否定文章价值会陷入困境:如何划定界限?如果病毒消灭全人类只留下洛斯阿拉莫斯的少数隔离者,曾被否定的文章是否重新符合资格?等等。
达尔文1844年的文章源自1839年的初稿,部分内容于1858年发表。
[2] 当你对看似次要的问题异常好奇时,这是个激动人心的信号。进化设计让你关注重要事物。所以当对随机事物产生强烈好奇,可能意味着你潜意识察觉它并不随机。
[3] 推论:若缺乏学术诚实,你的文章不仅会有偏见,还会无聊——因为你将错过所有追求真理过程中可能发现的洞见。
But you get into all sorts of difficulties if you want to disqualify essays on this account. How do you decide where the cutoff should be? If a virus kills off everyone except a handful of people sequestered at Los Alamos, could an essay that had been disqualified now be eligible? Etc. Darwin's 1844 essay was derived from an earlier version written in 1839. Extracts from it were published in 1858. [2] When you find yourself very curious about an apparently minor question, that's an exciting sign. Evolution has designed you to pay attention to things that matter. So when you're very curious about something random, that could mean you've unconsciously noticed it's less random than it seems. [3] Corollary: If you're not intellectually honest, your writing won't just be biased, but also boring, because you'll miss all the ideas you'd have discovered if you pushed for the truth. [4] Sometimes this process begins before you start writing. Sometimes you've already figured out the first few things you want to say. Schoolchildren are often taught they should decide _everything_ they want to say, and write this down as an outline before they start writing the essay itself. Maybe that's a good way to get them started — or not, I don't know — but it's antithetical to the spirit of essay writing. The more detailed your outline, the less your ideas can benefit from the sort of discovery that essays are for. [5] The problem with this type of "greedy" algorithm is that you can end up on a local maximum. If the most valuable question is preceded by a boring one, you'll overlook it. But I can't imagine a better strategy. There's no lookahead except by writing. So use a greedy algorithm and a lot of time. [6] I ended up reattaching the first 5 of the 17 paragraphs, and discarding the rest. [7] Stephen Fry confessed to making use of this phenomenon when taking exams at Oxford.
[4] 有时这个过程在动笔前就已开始。有时你已想好开头要说的内容。学校教育常要求学生在写作前决定所有内容并列出大纲。这对初学者或许有用(或许无用),但与写作精神背道而驰——大纲越详细,通过写作发现新思想的空间就越小。
[5] 这种"贪心算法"的问题是可能陷入局部最优。若最有价值的问题前有个无聊问题,你会错过它。但我想不出更好策略——除了写作无法预判未来。所以请用贪心算法加充足时间。
[6] 最终我重新采用了17段中的前5段,其余弃用。
[7] 斯蒂芬·弗莱承认在牛津考试时利用这种现象。他准备了一篇关于某文学主题的标准文章,设法将考题转向该主题后直接套用。
严格说是思想图高度互联,而非思想空间。但用"空间"能让不懂图论的人理解,懂的人自然明白。
He had in his head a standard essay about some general literary topic, and he would find a way to turn the exam question toward it and then just reproduce it again. Strictly speaking it's the graph of ideas that would be highly connected, not the space, but that usage would confuse people who don't know graph theory, whereas people who do know it will get what I mean if I say "space". [8] Too far doesn't depend just on the distance from the original topic. It's more like that distance divided by the value of whatever I've discovered in the subtree. [9] Or can you? I should try writing about this. Even if the chance of succeeding is small, the expected value is huge. [10] There was a vogue in the 20th century for saying that the purpose of art was also to teach. Some artists tried to justify their work by explaining that their goal was not to produce something good, but to challenge our preconceptions about art. And to be fair, art can teach somewhat. The ancient Greeks' naturalistic sculptures represented a new idea, and must have been extra exciting to contemporaries on that account. But they still look good to us. [11] Bertrand Russell caused huge controversy in the early 20th century with his ideas about "trial marriage." But they make boring reading now, because they prevailed. "Trial marriage" is what we call "dating." [12] If you'd asked me 10 years ago, I'd have predicted that schools would continue to teach hacking the test for centuries. But now it seems plausible that students will soon be taught individually by AIs, and that exams will be replaced by ongoing, invisible micro-assessments. Thanks to Sam Altman, Trevor Blackwell, Jessica Livingston, Robert Morris, Courtenay Pipkin, and Harj Taggar for reading drafts of this..
[8] "偏离太远"不仅取决于与原主题的距离,更像是该距离除以子章节发现的价值。
[9] 真没办法系统生成吗?我该就此写篇文章。即使成功率低,期望值也极高。
[10] 20世纪曾流行"艺术目的也是教育"的说法。某些艺术家辩解其作品旨在挑战艺术成见。公平地说,艺术确有教育功能——古希腊自然主义雕塑代表新思想,对当时人更具冲击力。但今人依然觉得它们美。
[11] 伯特兰·罗素在20世纪初提出的"试婚"理念曾引发巨大争议。如今读来却索然无味,因为它已普及——我们现在称之为"恋爱"。
[12] 若十年前问我,我会预测学校将继续教授应试技巧数百年。但现在看来,AI个性化教学取代考试,持续隐形微评估成为主流已具可能性。
致谢 Sam Altman、Trevor Blackwell、Jessica Livingston、Robert Morris、Courtenay Pipkin和Harj Taggar对本文初稿的审阅。
March 2024 _(This is a talk I gave to 14 and 15 year olds about what to do now if they might want to start a startup later. Lots of schools think they should tell students something about startups. This is what I think they should tell them.)_ Most of you probably think that when you're released into the so-called real world you'll eventually have to get some kind of job. That's not true, and today I'm going to talk about a trick you can use to avoid ever having to get a job. The trick is to start your own company. So it's not a trick for avoiding _work_ , because if you start your own company you'll work harder than you would if you had an ordinary job. But you will avoid many of the annoying things that come with a job, including a boss telling you what to do. It's more exciting to work on your own project than someone else's. And you can also get a lot richer. In fact, this is the standard way to get _really rich_. If you look at the lists of the richest people that occasionally get published in the press, nearly all of them did it by starting their own companies. Starting your own company can mean anything from starting a barber shop to starting Google. I'm here to talk about one extreme end of that continuum. I'm going to tell you how to start Google. The companies at the Google end of the continuum are called startups when they're young. The reason I know about them is that my wife Jessica and I started something called Y Combinator that is basically a startup factory. Since 2005, Y Combinator has funded over 4000 startups. So we know exactly what you need to start a startup, because we've helped people do it for the last 19 years. You might have thought I was joking when I said I was going to tell you how to start Google. You might be thinking "How could _we_ start Google?" But that's effectively what the people who did start Google were thinking before they started it.
(这是我对14、15岁青少年做的演讲,关于如果未来想创业现在该做什么。许多学校认为应该向学生传授创业知识,而这就是我认为他们应该讲的内容。)
你们大多数人可能认为,当踏入所谓的现实世界后,最终总要找份工作。事实并非如此。今天我要分享一个技巧,让你们永远不必找工作。
这个技巧就是创立自己的公司。这并非逃避工作的伎俩——创业会比普通工作更辛苦。但你能避开职场中诸多烦心事,比如被老板呼来喝去。
为自己做事比为别人打工更令人兴奋,还可能赚更多钱。事实上,这是实现真正致富的标准路径。看看媒体发布的富豪榜,几乎所有人都是通过创业实现的。
If you'd told Larry Page and Sergey Brin, the founders of Google, that the company they were about to start would one day be worth over a trillion dollars, their heads would have exploded. All you can know when you start working on a startup is that it seems worth pursuing. You can't know whether it will turn into a company worth billions or one that goes out of business. So when I say I'm going to tell you how to start Google, I mean I'm going to tell you how to get to the point where you can start a company that has as much chance of being Google as Google had of being Google. [1] How do you get from where you are now to the point where you can start a successful startup? You need three things. You need to be good at some kind of technology, you need an idea for what you're going to build, and you need cofounders to start the company with. How do you get good at technology? And how do you choose which technology to get good at? Both of those questions turn out to have the same answer: work on your own projects. Don't try to guess whether gene editing or LLMs or rockets will turn out to be the most valuable technology to know about. No one can predict that. Just work on whatever interests you the most. You'll work much harder on something you're interested in than something you're doing because you think you're supposed to. If you're not sure what technology to get good at, get good at programming. That has been the source of the median startup for the last 30 years, and this is probably not going to change in the next 10. Those of you who are taking computer science classes in school may at this point be thinking, ok, we've got this sorted. We're already being taught all about programming. But sorry, this is not enough. You have to be working on your own projects, not just learning stuff in classes. You can do well in computer science classes without ever really learning to program.
创业可以是从开理发店到创立谷歌的任何事。而我要讨论的是这个光谱的极端一端:如何创立谷歌这样的公司。
处于这个光谱端的年轻公司被称为初创企业。我对此的了解源于和妻子Jessica共同创立的Y Combinator——本质上是个创业工厂。自2005年以来,我们已资助超过4000家初创公司。过去19年我们持续帮助创业者,因此非常清楚创业需要什么。
当我说要教你们创立谷歌时,你们可能以为在开玩笑:"我们怎么可能创立谷歌?"但谷歌创始人拉里·佩奇和谢尔盖·布林起步时也是这么想的。若有人告诉他们这家公司日后市值会超万亿美元,他们肯定会惊掉下巴。
创业之初你只能确定这个方向值得探索,无法预知它会成为价值千亿的企业还是倒闭收场。所以当我说"教你们创立谷歌",实际是指教你们如何达到能创立具有谷歌级潜力的公司的起点。[1]
In fact you can graduate with a degree in computer science from a top university and still not be any good at programming. That's why tech companies all make you take a coding test before they'll hire you, regardless of where you went to university or how well you did there. They know grades and exam results prove nothing. If you really want to learn to program, you have to work on your own projects. You learn so much faster that way. Imagine you're writing a game and there's something you want to do in it, and you don't know how. You're going to figure out how a lot faster than you'd learn anything in a class. You don't have to learn programming, though. If you're wondering what counts as technology, it includes practically everything you could describe using the words "make" or "build." So welding would count, or making clothes, or making videos. Whatever you're most interested in. The critical distinction is whether you're producing or just consuming. Are you writing computer games, or just playing them? That's the cutoff. Steve Jobs, the founder of Apple, spent time when he was a teenager studying calligraphy — the sort of beautiful writing that you see in medieval manuscripts. No one, including him, thought that this would help him in his career. He was just doing it because he was interested in it. But it turned out to help him a lot. The computer that made Apple really big, the Macintosh, came out at just the moment when computers got powerful enough to make letters like the ones in printed books instead of the computery-looking letters you see in 8 bit games. Apple destroyed everyone else at this, and one reason was that Steve was one of the few people in the computer business who really got graphic design. Don't feel like your projects have to be _serious_. They can be as frivolous as you like, so long as you're building things you're excited about. Probably 90% of programmers start out building games.
如何从现状发展到能创立成功企业的阶段?需要三要素:掌握某项技术、有明确的构建方向,以及找到联合创始人。
如何精通技术?又该选择哪种技术?这两个问题的答案相同:做自己的项目。别试图预测基因编辑、大语言模型或火箭技术哪个最值钱——没人能预知未来。只需选择你最感兴趣的领域,因为兴趣驱动的学习效率远高于功利性学习。
如果不确定学什么,就学编程。过去30年绝大多数初创企业都源于此,未来10年很可能依旧如此。
正在学校上计算机课的同学们可能觉得已经掌握编程。但抱歉,这远远不够。必须通过实际项目学习,课堂知识并不等同编程能力。事实上,顶尖大学计算机系毕业生也可能完全不会编程,这就是科技公司招聘时无论学历都要进行编码测试的原因——成绩单证明不了实际能力。
真正学会编程必须通过项目实践。比如写游戏时遇到问题,你的学习速度会远超课堂。当然编程并非唯一选择,任何能用"制造"或"建造"描述的技能都算技术:焊接、制衣、视频制作...关键区别在于创造还是消费。你是开发游戏还是只玩游戏?这就是分界线。
They and their friends like to play games. So they build the kind of things they and their friends want. And that's exactly what you should be doing at 15 if you want to start a startup one day. You don't have to do just one project. In fact it's good to learn about multiple things. Steve Jobs didn't just learn calligraphy. He also learned about electronics, which was even more valuable. Whatever you're interested in. (Do you notice a theme here?) So that's the first of the three things you need, to get good at some kind or kinds of technology. You do it the same way you get good at the violin or football: practice. If you start a startup at 22, and you start writing your own programs now, then by the time you start the company you'll have spent at least 7 years practicing writing code, and you can get pretty good at anything after practicing it for 7 years. Let's suppose you're 22 and you've succeeded: You're now really good at some technology. How do you get _startup ideas_? It might seem like that's the hard part. Even if you are a good programmer, how do you get the idea to start Google? Actually it's easy to get startup ideas once you're good at technology. Once you're good at some technology, when you look at the world you see dotted outlines around the things that are missing. You start to be able to see both the things that are missing from the technology itself, and all the broken things that could be fixed using it, and each one of these is a potential startup. In the town near our house there's a shop with a sign warning that the door is hard to close. The sign has been there for several years. To the people in the shop it must seem like this mysterious natural phenomenon that the door sticks, and all they can do is put up a sign warning customers about it.
苹果创始人史蒂夫·乔布斯少年时痴迷书法——中世纪手抄本那种精美字体。当时没人(包括他自己)觉得这对职业生涯有帮助,纯粹出于兴趣。但结果证明这至关重要。当电脑性能足以显示印刷级字体(而非8位游戏的像素字)时,苹果凭借这项优势碾压对手,部分原因正是乔布斯是极懂平面设计的科技人。
项目不必"严肃",只要让你兴奋就行。约90%程序员起步时都写游戏,因为他们和朋友爱玩游戏。若你15岁想未来创业,就该做自己和朋友想要的东西。
不必局限于一个项目。多领域学习很有益——乔布斯不仅学书法还钻研电子学(后者价值更大)。关键永远是跟随兴趣。(注意到这个反复出现的主题了吗?)
这就是第一要素:通过实践掌握技术。就像学小提琴或足球需要练习,如果你22岁创业并从现在开始写程序,届时已有至少7年编码经验——足够精通任何领域。
But any carpenter looking at this situation would think "why don't you just plane off the part that sticks?" Once you're good at programming, all the missing software in the world starts to become as obvious as a sticking door to a carpenter. I'll give you a real world example. Back in the 20th century, American universities used to publish printed directories with all the students' names and contact info. When I tell you what these directories were called, you'll know which startup I'm talking about. They were called facebooks, because they usually had a picture of each student next to their name. So Mark Zuckerberg shows up at Harvard in 2002, and the university still hasn't gotten the facebook online. Each individual house has an online facebook, but there isn't one for the whole university. The university administration has been diligently having meetings about this, and will probably have solved the problem in another decade or so. Most of the students don't consciously notice that anything is wrong. But Mark is a programmer. He looks at this situation and thinks "Well, this is stupid. I could write a program to fix this in one night. Just let people upload their own photos and then combine the data into a new site for the whole university." So he does. And almost literally overnight he has thousands of users. Of course Facebook was not a startup yet. It was just a... project. There's that word again. Projects aren't just the best way to learn about technology. They're also the best source of startup ideas. Facebook was not unusual in this respect. Apple and Google also began as projects. Apple wasn't meant to be a company. Steve Wozniak just wanted to build his own computer. It only turned into a company when Steve Jobs said "Hey, I wonder if we could sell plans for this computer to other people." That's how Apple started. They weren't even selling computers, just plans for computers.
假设你22岁已精通某项技术,如何获得创业灵感?这看似最困难的部分:即便成为优秀程序员,怎么想到创立谷歌的点子?
实际上掌握技术后灵感自然涌现。你会像木匠看到歪斜的门框那样,敏锐发现技术本身的缺失和可改进之处——每个发现都是潜在的创业机会。
我们镇上有家店铺常年挂着"门不好关"的警示牌。店员视之为神秘自然现象,但任何木匠都会说:"把卡住的部分刨掉不就行了?"
精通编程后,世界缺失的软件会像歪斜的门框那样显眼。举个真实案例:20世纪美国大学曾印制包含学生照片和联系方式的纸质名册——当我说出它们叫"facebooks"时,你们就知道我在讲哪个创业故事了。
Can you imagine how lame this company seemed? Ditto for Google. Larry and Sergey weren't trying to start a company at first. They were just trying to make search better. Before Google, most search engines didn't try to sort the results they gave you in order of importance. If you searched for "rugby" they just gave you every web page that contained the word "rugby." And the web was so small in 1997 that this actually worked! Kind of. There might only be 20 or 30 pages with the word "rugby," but the web was growing exponentially, which meant this way of doing search was becoming exponentially more broken. Most users just thought, "Wow, I sure have to look through a lot of search results to find what I want." Door sticks. But like Mark, Larry and Sergey were programmers. Like Mark, they looked at this situation and thought "Well, this is stupid. Some pages about rugby matter more than others. Let's figure out which those are and show them first." It's obvious in retrospect that this was a great idea for a startup. It wasn't obvious at the time. It's never obvious. If it was obviously a good idea to start Apple or Google or Facebook, someone else would have already done it. That's why the best startups grow out of projects that aren't meant to be startups. You're not trying to start a company. You're just following your instincts about what's interesting. And if you're young and good at technology, then your unconscious instincts about what's interesting are better than your conscious ideas about what would be a good company. So it's critical, if you're a young founder, to build things for yourself and your friends to use. The biggest mistake young founders make is to build something for some mysterious group of other people.
2002年马克·扎克伯格入读哈佛时,校方仍未建立在线通讯录。虽然各宿舍有独立系统,全校范围的始终空缺。校方不停开会讨论,可能再过十年才能解决。多数学生并未察觉异常,但作为程序员的马克看到这种情况想:"太蠢了,我一晚上就能写程序解决——让学生自传照片,整合成全校系统。"他做到了,几乎一夜之间获得数千用户。
当然当时的Facebook还不是初创企业,只是个...项目。看,又是这个词。项目不仅是学习技术的最佳途径,也是创业灵感的源泉。
在这方面Facebook并非特例。苹果和谷歌同样始于项目。苹果本不想做公司——史蒂夫·沃兹尼亚克只想给自己造电脑,直到乔布斯提议"能不能卖组装图纸"才转型。你能想象这公司起步时多寒酸吗?
谷歌亦然。拉里和佩奇最初只想改进搜索。前谷歌时代,搜索引擎几乎不排序结果——1997年搜索"橄榄球"会显示全部含该词的网页(当时全网可能就二三十个)。随着网络指数级增长,这种搜索方式越来越糟。多数用户只是抱怨"要找的东西总藏在结果堆里",而程序员出身的两位创始人想:"太蠢了,有些橄榄球页面更重要,应该优先展示。"
回看历史这是个绝妙创意,但当时绝非显而易见。如果苹果、谷歌或Facebook的创意显而易见,早就有人做了。所以最佳初创企业往往源于非商业目的的项目——你不是为了创业,只是追随兴趣本能。年轻技术高手对兴趣的无意识直觉,远胜过对"好公司"的刻意构思。
But if you can make something that you and your friends truly want to use — something your friends aren't just using out of loyalty to you, but would be really sad to lose if you shut it down — then you almost certainly have the germ of a good startup idea. It may not seem like a startup to you. It may not be obvious how to make money from it. But trust me, there's a way. What you need in a startup idea, and all you need, is something your friends actually want. And those ideas aren't hard to see once you're good at technology. There are sticking doors everywhere. [2] Now for the third and final thing you need: a cofounder, or cofounders. The optimal startup has two or three founders, so you need one or two cofounders. How do you find them? Can you predict what I'm going to say next? It's the same thing: projects. You find cofounders by working on projects with them. What you need in a cofounder is someone who's good at what they do and that you work well with, and the only way to judge this is to work with them on things. At this point I'm going to tell you something you might not want to hear. It really matters to do well in your classes, even the ones that are just memorization or blathering about literature, because you need to do well in your classes to get into a good university. And if you want to start a startup you should try to get into the best university you can, because that's where the best cofounders are. It's also where the best employees are. When Larry and Sergey started Google, they began by just hiring all the smartest people they knew out of Stanford, and this was a real advantage for them. The empirical evidence is clear on this. If you look at where the largest numbers of successful startups come from, it's pretty much the same as the list of the most selective universities. I don't think it's the prestigious names of these universities that cause more good startups to come out of them.
因此年轻创始人必须为自己和朋友打造产品。他们最常犯的错误就是为某个模糊群体做东西。但如果你做出连朋友都爱不释手的产品(不只是出于友情支持,而是关闭会让他们难过),那几乎肯定抓住了好创意的萌芽。它可能看起来不像创业项目,盈利模式也不明显,但请相信总有办法实现。
创业创意唯一需要的就是朋友真正想要的东西。掌握技术后,这些创意随处可见——歪斜的门框无处不在。[2]
现在说第三也是最后的要素:联合创始人。最佳初创团队是2-3人,意味着你需要1-2位伙伴。如何寻找?能猜到我要说什么吗?答案依然是:项目。通过共同做项目发现伙伴。你需要的是技术过硬且合作愉快的人,唯一判断方式就是实际共事。
现在我要说些你们可能不爱听的话:即便死记硬背的文学课也要学好,因为进入好大学需要好成绩。而想创业就该争取进入最好的大学——那里有最优秀的潜在合伙人和员工。谷歌创始团队就是拉里和佩奇从斯坦福招募的顶尖人才,这成为他们的关键优势。
Nor do I think it's because the quality of the teaching is better. What's driving this is simply the difficulty of getting in. You have to be pretty smart and determined to get into MIT or Cambridge, so if you do manage to get in, you'll find the other students include a lot of smart and determined people. [3] You don't have to start a startup with someone you meet at university. The founders of Twitch met when they were seven. The founders of Stripe, Patrick and John Collison, met when John was born. But universities are the main source of cofounders. And because they're where the cofounders are, they're also where the ideas are, because the best ideas grow out of projects you do with the people who become your cofounders. So the list of what you need to do to get from here to starting a startup is quite short. You need to get good at technology, and the way to do that is to work on your own projects. And you need to do as well in school as you can, so you can get into a good university, because that's where the cofounders and the ideas are. That's it, just two things, build stuff and do well in school. Notes [1] The rhetorical trick in this sentence is that the "Google"s refer to different things. What I mean is: a company that has as much chance of growing as big as Google ultimately did as Larry and Sergey could have reasonably expected Google itself would at the time they started it. But I think the original version is zippier. [2] Making something for your friends isn't the only source of startup ideas. It's just the best source for young founders, who have the least knowledge of what other people want, and whose own wants are most predictive of future demand. [3] Strangely enough this is particularly true in countries like the US where undergraduate admissions are done badly.
数据很清楚:成功创业者最集中的院校,基本就是录取最严格的大学名单。
我认为这并非名校光环或教学质量所致,纯粹是录取难度使然。能进MIT或剑桥的人必然聪明且坚定,在这里你会遇见大量同类人。[3]
创业伙伴不一定要来自大学。Twitch创始人七岁相识,Stripe的Collison兄弟在约翰出生时就注定成为搭档。但大学仍是联合创始人的主要来源地,也因此成为创业灵感的沃土——最佳创意往往诞生于你与未来合伙人的合作项目中。
综上所述,从现状到创业只需做两件事:通过项目掌握技术,以及尽力考取好大学(那里有伙伴和灵感)。
US admissions departments make applicants jump through a lot of arbitrary hoops that have little to do with their intellectual ability. But the more arbitrary a test, the more it becomes a test of mere determination and resourcefulness. And those are the two most important qualities in startup founders. So US admissions departments are better at selecting founders than they would be if they were better at selecting students. Thanks to Jared Friedman, Carolynn Levy, Jessica Livingston, Harj Taggar, and Garry Tan for reading drafts of this..
就这么简单:创造东西,学好功课。
注释 [1] 这句话的修辞技巧在于两个"谷歌"指代不同事物。实际含义是:一家公司在创立时具备谷歌当年的成长潜力,就像拉里和佩奇创立谷歌时所能合理预期的那样。不过原句更简洁有力。
[2] 为朋友做东西并非唯一灵感来源,但对年轻创始人是最佳途径——他们最不了解他人需求,而自身需求最能预示未来趋势。
[3] 吊诡的是,在美国等本科录取不合理的国家这点尤其明显。美国大学设置大量与智力无关的 arbitrary 关卡,但越随机的测试越能检验决心和应变力——这两点正是创业者最重要的品质。所以美国招生办在筛选创始人方面,反而比他们正经招生更在行。
致谢 Jared Friedman、Carolynn Levy、Jessica Livingston、Harj Taggar和Garry Tan对本文的审阅。
October 2023 One of the most important things I didn't understand about the world when I was a child is the degree to which the returns for performance are superlinear. Teachers and coaches implicitly told us the returns were linear. "You get out," I heard a thousand times, "what you put in." They meant well, but this is rarely true. If your product is only half as good as your competitor's, you don't get half as many customers. You get no customers, and you go out of business. It's obviously true that the returns for performance are superlinear in business. Some think this is a flaw of capitalism, and that if we changed the rules it would stop being true. But superlinear returns for performance are a feature of the world, not an artifact of rules we've invented. We see the same pattern in fame, power, military victories, knowledge, and even benefit to humanity. In all of these, the rich get richer. [1] You can't understand the world without understanding the concept of superlinear returns. And if you're ambitious you definitely should, because this will be the wave you surf on. It may seem as if there are a lot of different situations with superlinear returns, but as far as I can tell they reduce to two fundamental causes: exponential growth and thresholds. The most obvious case of superlinear returns is when you're working on something that grows exponentially. For example, growing bacterial cultures. When they grow at all, they grow exponentially. But they're tricky to grow. Which means the difference in outcome between someone who's adept at it and someone who's not is very great. Startups can also grow exponentially, and we see the same pattern there. Some manage to achieve high growth rates. Most don't. And as a result you get qualitatively different outcomes: the companies with high growth rates tend to become immensely valuable, while the ones with lower growth rates may not even survive.
Y Combinator encourages founders to focus on growth rate rather than absolute numbers. It prevents them from being discouraged early on, when the absolute numbers are still low. It also helps them decide what to focus on: you can use growth rate as a compass to tell you how to evolve the company. But the main advantage is that by focusing on growth rate you tend to get something that grows exponentially. YC doesn't explicitly tell founders that with growth rate "you get out what you put in," but it's not far from the truth. And if growth rate were proportional to performance, then the reward for performance _p_ over time _t_ would be proportional to _p t_. Even after decades of thinking about this, I find that sentence startling. Whenever how well you do depends on how well you've done, you'll get exponential growth. But neither our DNA nor our customs prepare us for it. No one finds exponential growth natural; every child is surprised, the first time they hear it, by the story of the man who asks the king for a single grain of rice the first day and double the amount each successive day. What we don't understand naturally we develop customs to deal with, but we don't have many customs about exponential growth either, because there have been so few instances of it in human history. In principle herding should have been one: the more animals you had, the more offspring they'd have. But in practice grazing land was the limiting factor, and there was no plan for growing that exponentially. Or more precisely, no generally applicable plan. There _was_ a way to grow one's territory exponentially: by conquest. The more territory you control, the more powerful your army becomes, and the easier it is to conquer new territory. This is why history is full of empires. But so few people created or ran empires that their experiences didn't affect customs very much.
The emperor was a remote and terrifying figure, not a source of lessons one could use in one's own life. The most common case of exponential growth in preindustrial times was probably scholarship. The more you know, the easier it is to learn new things. The result, then as now, was that some people were startlingly more knowledgeable than the rest about certain topics. But this didn't affect customs much either. Although empires of ideas can overlap and there can thus be far more emperors, in preindustrial times this type of empire had little practical effect. [2] That has changed in the last few centuries. Now the emperors of ideas can design bombs that defeat the emperors of territory. But this phenomenon is still so new that we haven't fully assimilated it. Few even of the participants realize they're benefitting from exponential growth or ask what they can learn from other instances of it. The other source of superlinear returns is embodied in the expression "winner take all." In a sports match the relationship between performance and return is a step function: the winning team gets one win whether they do much better or just slightly better. [3] The source of the step function is not competition per se, however. It's that there are thresholds in the outcome. You don't need competition to get those. There can be thresholds in situations where you're the only participant, like proving a theorem or hitting a target. It's remarkable how often a situation with one source of superlinear returns also has the other. Crossing thresholds leads to exponential growth: the winning side in a battle usually suffers less damage, which makes them more likely to win in the future. And exponential growth helps you cross thresholds: in a market with network effects, a company that grows fast enough can shut out potential competitors. Fame is an interesting example of a phenomenon that combines both sources of superlinear returns.
Fame grows exponentially because existing fans bring you new ones. But the fundamental reason it's so concentrated is thresholds: there's only so much room on the A-list in the average person's head. The most important case combining both sources of superlinear returns may be learning. Knowledge grows exponentially, but there are also thresholds in it. Learning to ride a bicycle, for example. Some of these thresholds are akin to machine tools: once you learn to read, you're able to learn anything else much faster. But the most important thresholds of all are those representing new discoveries. Knowledge seems to be fractal in the sense that if you push hard at the boundary of one area of knowledge, you sometimes discover a whole new field. And if you do, you get first crack at all the new discoveries to be made in it. Newton did this, and so did Durer and Darwin. Are there general rules for finding situations with superlinear returns? The most obvious one is to seek work that compounds. There are two ways work can compound. It can compound directly, in the sense that doing well in one cycle causes you to do better in the next. That happens for example when you're building infrastructure, or growing an audience or brand. Or work can compound by teaching you, since learning compounds. This second case is an interesting one because you may feel you're doing badly as it's happening. You may be failing to achieve your immediate goal. But if you're learning a lot, then you're getting exponential growth nonetheless. This is one reason Silicon Valley is so tolerant of failure. People in Silicon Valley aren't blindly tolerant of failure. They'll only continue to bet on you if you're learning from your failures. But if you are, you are in fact a good bet: maybe your company didn't grow the way you wanted, but you yourself have, and that should yield results eventually.
Indeed, the forms of exponential growth that don't consist of learning are so often intermixed with it that we should probably treat this as the rule rather than the exception. Which yields another heuristic: always be learning. If you're not learning, you're probably not on a path that leads to superlinear returns. But don't overoptimize _what_ you're learning. Don't limit yourself to learning things that are already known to be valuable. You're learning; you don't know for sure yet what's going to be valuable, and if you're too strict you'll lop off the outliers. What about step functions? Are there also useful heuristics of the form "seek thresholds" or "seek competition?" Here the situation is trickier. The existence of a threshold doesn't guarantee the game will be worth playing. If you play a round of Russian roulette, you'll be in a situation with a threshold, certainly, but in the best case you're no better off. "Seek competition" is similarly useless; what if the prize isn't worth competing for? Sufficiently fast exponential growth guarantees both the shape and magnitude of the return curve — because something that grows fast enough will grow big even if it's trivially small at first — but thresholds only guarantee the shape. [4] A principle for taking advantage of thresholds has to include a test to ensure the game is worth playing. Here's one that does: if you come across something that's mediocre yet still popular, it could be a good idea to replace it. For example, if a company makes a product that people dislike yet still buy, then presumably they'd buy a better alternative if you made one. [5] It would be great if there were a way to find promising intellectual thresholds.
Is there a way to tell which questions have whole new fields beyond them? I doubt we could ever predict this with certainty, but the prize is so valuable that it would be useful to have predictors that were even a little better than random, and there's hope of finding those. We can to some degree predict when a research problem _isn't_ likely to lead to new discoveries: when it seems legit but boring. Whereas the kind that do lead to new discoveries tend to seem very mystifying, but perhaps unimportant. (If they were mystifying and obviously important, they'd be famous open questions with lots of people already working on them.) So one heuristic here is to be driven by curiosity rather than careerism — to give free rein to your curiosity instead of working on what you're supposed to. The prospect of superlinear returns for performance is an exciting one for the ambitious. And there's good news in this department: this territory is expanding in both directions. There are more types of work in which you can get superlinear returns, and the returns themselves are growing. There are two reasons for this, though they're so closely intertwined that they're more like one and a half: progress in technology, and the decreasing importance of organizations. Fifty years ago it used to be much more necessary to be part of an organization to work on ambitious projects. It was the only way to get the resources you needed, the only way to have colleagues, and the only way to get distribution. So in 1970 your prestige was in most cases the prestige of the organization you belonged to. And prestige was an accurate predictor, because if you weren't part of an organization, you weren't likely to achieve much. There were a handful of exceptions, most notably artists and writers, who worked alone using inexpensive tools and had their own brands.
But even they were at the mercy of organizations for reaching audiences. [6] A world dominated by organizations damped variation in the returns for performance. But this world has eroded significantly just in my lifetime. Now a lot more people can have the freedom that artists and writers had in the 20th century. There are lots of ambitious projects that don't require much initial funding, and lots of new ways to learn, make money, find colleagues, and reach audiences. There's still plenty of the old world left, but the rate of change has been dramatic by historical standards. Especially considering what's at stake. It's hard to imagine a more fundamental change than one in the returns for performance. Without the damping effect of institutions, there will be more variation in outcomes. Which doesn't imply everyone will be better off: people who do well will do even better, but those who do badly will do worse. That's an important point to bear in mind. Exposing oneself to superlinear returns is not for everyone. Most people will be better off as part of the pool. So who should shoot for superlinear returns? Ambitious people of two types: those who know they're so good that they'll be net ahead in a world with higher variation, and those, particularly the young, who can afford to risk trying it to find out. [7] The switch away from institutions won't simply be an exodus of their current inhabitants. Many of the new winners will be people they'd never have let in. So the resulting democratization of opportunity will be both greater and more authentic than any tame intramural version the institutions themselves might have cooked up. Not everyone is happy about this great unlocking of ambition. It threatens some vested interests and contradicts some ideologies. [8] But if you're an ambitious individual it's good news for you.
How should you take advantage of it? The most obvious way to take advantage of superlinear returns for performance is by doing exceptionally good work. At the far end of the curve, incremental effort is a bargain. All the more so because there's less competition at the far end — and not just for the obvious reason that it's hard to do something exceptionally well, but also because people find the prospect so intimidating that few even try. Which means it's not just a bargain to do exceptional work, but a bargain even to try to. There are many variables that affect how good your work is, and if you want to be an outlier you need to get nearly all of them right. For example, to do something exceptionally well, you have to be interested in it. Mere diligence is not enough. So in a world with superlinear returns, it's even more valuable to know what you're interested in, and to find ways to work on it. [9] It will also be important to choose work that suits your circumstances. For example, if there's a kind of work that inherently requires a huge expenditure of time and energy, it will be increasingly valuable to do it when you're young and don't yet have children. There's a surprising amount of technique to doing great work. It's not just a matter of trying hard. I'm going to take a shot giving a recipe in one paragraph. Choose work you have a natural aptitude for and a deep interest in. Develop a habit of working on your own projects; it doesn't matter what they are so long as you find them excitingly ambitious. Work as hard as you can without burning out, and this will eventually bring you to one of the frontiers of knowledge. These look smooth from a distance, but up close they're full of gaps. Notice and explore such gaps, and if you're lucky one will expand into a whole new field. Take as much risk as you can afford; if you're not failing occasionally you're probably being too conservative. Seek out the best colleagues.
Develop good taste and learn from the best examples. Be honest, especially with yourself. Exercise and eat and sleep well and avoid the more dangerous drugs. When in doubt, follow your curiosity. It never lies, and it knows more than you do about what's worth paying attention to. [10] And there is of course one other thing you need: to be lucky. Luck is always a factor, but it's even more of a factor when you're working on your own rather than as part of an organization. And though there are some valid aphorisms about luck being where preparedness meets opportunity and so on, there's also a component of true chance that you can't do anything about. The solution is to take multiple shots. Which is another reason to start taking risks early. The best example of a field with superlinear returns is probably science. It has exponential growth, in the form of learning, combined with thresholds at the extreme edge of performance — literally at the limits of knowledge. The result has been a level of inequality in scientific discovery that makes the wealth inequality of even the most stratified societies seem mild by comparison. Newton's discoveries were arguably greater than all his contemporaries' combined. [11] This point may seem obvious, but it might be just as well to spell it out. Superlinear returns imply inequality. The steeper the return curve, the greater the variation in outcomes. In fact, the correlation between superlinear returns and inequality is so strong that it yields another heuristic for finding work of this type: look for fields where a few big winners outperform everyone else. A kind of work where everyone does about the same is unlikely to be one with superlinear returns. What are fields where a few big winners outperform everyone else? Here are some obvious ones: sports, politics, art, music, acting, directing, writing, math, science, starting companies, and investing.
In sports the phenomenon is due to externally imposed thresholds; you only need to be a few percent faster to win every race. In politics, power grows much as it did in the days of emperors. And in some of the other fields (including politics) success is driven largely by fame, which has its own source of superlinear growth. But when we exclude sports and politics and the effects of fame, a remarkable pattern emerges: the remaining list is exactly the same as the list of fields where you have to be _independent-minded_ to succeed — where your ideas have to be not just correct, but novel as well. [12] This is obviously the case in science. You can't publish papers saying things that other people have already said. But it's just as true in investing, for example. It's only useful to believe that a company will do well if most other investors don't; if everyone else thinks the company will do well, then its stock price will already reflect that, and there's no room to make money. What else can we learn from these fields? In all of them you have to put in the initial effort. Superlinear returns seem small at first. _At this rate,_ you find yourself thinking, _I'll never get anywhere._ But because the reward curve rises so steeply at the far end, it's worth taking extraordinary measures to get there. In the startup world, the name for this principle is "do things that don't scale." If you pay a ridiculous amount of attention to your tiny initial set of customers, ideally you'll kick off exponential growth by word of mouth. But this same principle applies to anything that grows exponentially. Learning, for example. When you first start learning something, you feel lost. But it's worth making the initial effort to get a toehold, because the more you learn, the easier it will get. There's another more subtle lesson in the list of fields with superlinear returns: not to equate work with a job.
For most of the 20th century the two were identical for nearly everyone, and as a result we've inherited a custom that equates productivity with having a job. Even now to most people the phrase "your work" means their job. But to a writer or artist or scientist it means whatever they're currently studying or creating. For someone like that, their work is something they carry with them from job to job, if they have jobs at all. It may be done for an employer, but it's part of their portfolio. It's an intimidating prospect to enter a field where a few big winners outperform everyone else. Some people do this deliberately, but you don't need to. If you have sufficient natural ability and you follow your curiosity sufficiently far, you'll end up in one. Your curiosity won't let you be interested in boring questions, and interesting questions tend to create fields with superlinear returns if they're not already part of one. The territory of superlinear returns is by no means static. Indeed, the most extreme returns come from expanding it. So while both ambition and curiosity can get you into this territory, curiosity may be the more powerful of the two. Ambition tends to make you climb existing peaks, but if you stick close enough to an interesting enough question, it may grow into a mountain beneath you. Notes There's a limit to how sharply you can distinguish between effort, performance, and return, because they're not sharply distinguished in fact. What counts as return to one person might be performance to another. But though the borders of these concepts are blurry, they're not meaningless. I've tried to write about them as precisely as I could without crossing into error. [1] Evolution itself is probably the most pervasive example of superlinear returns for performance.
But this is hard for us to empathize with because we're not the recipients; we're the returns. [2] Knowledge did of course have a practical effect before the Industrial Revolution. The development of agriculture changed human life completely. But this kind of change was the result of broad, gradual improvements in technique, not the discoveries of a few exceptionally learned people. [3] It's not mathematically correct to describe a step function as superlinear, but a step function starting from zero works like a superlinear function when it describes the reward curve for effort by a rational actor. If it starts at zero then the part before the step is below any linearly increasing return, and the part after the step must be above the necessary return at that point or no one would bother. [4] Seeking competition could be a good heuristic in the sense that some people find it motivating. It's also somewhat of a guide to promising problems, because it's a sign that other people find them promising. But it's a very imperfect sign: often there's a clamoring crowd chasing some problem, and they all end up being trumped by someone quietly working on another one. [5] Not always, though. You have to be careful with this rule. When something is popular despite being mediocre, there's often a hidden reason why. Perhaps monopoly or regulation make it hard to compete. Perhaps customers have bad taste or have broken procedures for deciding what to buy. There are huge swathes of mediocre things that exist for such reasons. [6] In my twenties I wanted to be an _artist_ and even went to art school to study painting. Mostly because I liked art, but a nontrivial part of my motivation came from the fact that artists seemed least at the mercy of organizations. [7] In principle everyone is getting superlinear returns. Learning compounds, and everyone learns in the course of their life.
But in practice few push this kind of everyday learning to the point where the return curve gets really steep. [8] It's unclear exactly what advocates of "equity" mean by it. They seem to disagree among themselves. But whatever they mean is probably at odds with a world in which institutions have less power to control outcomes, and a handful of outliers do much better than everyone else. It may seem like bad luck for this concept that it arose at just the moment when the world was shifting in the opposite direction, but I don't think this was a coincidence. I think one reason it arose now is because its adherents feel threatened by rapidly increasing variation in performance. [9] Corollary: Parents who pressure their kids to work on something prestigious, like medicine, even though they have no interest in it, will be hosing them even more than they have in the past. [10] The original version of this paragraph was the first draft of " _How to Do Great Work_." As soon as I wrote it I realized it was a more important topic than superlinear returns, so I paused the present essay to expand this paragraph into its own. Practically nothing remains of the original version, because after I finished "How to Do Great Work" I rewrote it based on that. [11] Before the Industrial Revolution, people who got rich usually did it like emperors: capturing some resource made them more powerful and enabled them to capture more. Now it can be done like a scientist, by discovering or building something uniquely valuable. Most people who get rich use a mix of the old and the new ways, but in the most advanced economies the ratio has _shifted dramatically_ toward discovery just in the last half century. [12] It's not surprising that conventional-minded people would dislike inequality if independent-mindedness is one of the biggest drivers of it. But it's not simply that they don't want anyone to have what they can't.
The conventional-minded literally can't imagine what it's like to have novel ideas. So the whole phenomenon of great variation in performance seems unnatural to them, and when they encounter it they assume it must be due to cheating or to some malign external influence. Thanks to Trevor Blackwell, Patrick Collison, Tyler Cowen, Jessica Livingston, Harj Taggar, and Garry Tan for reading drafts of this..
2023年10月 我童年时最未能理解的世界真相之一,就是表现带来的回报往往呈现超线性增长。 老师和教练们总在暗示回报是线性的。"付出多少",我听过无数遍,"就会得到多少"。他们本意是好的,但现实很少如此。如果你的产品只有竞争对手一半好,你获得的客户不会是对手的一半——你会彻底失去客户,然后破产。 商业领域存在超线性回报是显而易见的。有人认为这是资本主义的缺陷,以为改变规则就能消除这种现象。但超线性回报是世界固有的特征,而非人为规则的产物。我们在名声、权力、军事胜利、知识甚至对人类贡献等各个领域都能看到相同模式:赢家通吃。[1] 不理解超线性回报概念就无法真正理解世界。如果你胸怀壮志,就更需要掌握这个规律,因为它将成为你乘势而上的浪潮。 看似存在无数种超线性回报的情境,但归根结底都源于两个本质原因:指数增长与临界阈值。 最直观的超线性回报来自指数增长型工作。比如培养细菌培养物:一旦开始生长就会呈指数扩张,但培养过程极其精密。这意味着精通者与生手的结果差异会天差地别。 初创企业同样可能指数增长,我们观察到相同规律。少数公司能实现高速增长,多数则不能。结果自然泾渭分明:高增长公司往往成就惊人价值,低增长者可能难以为继。 Y Combinator始终建议创始人关注增长率而非绝对数值。这能避免他们在早期因绝对数值偏低而气馁,也帮助他们明确方向:增长率就像指南针,指引公司进化路径。但最关键的是,专注增长率往往能催生指数级增长。 YC虽不明说"增长率与付出成正比",但这近乎真理。若增长率与表现正相关,那么表现_p_随时间_t_的回报将正比于_p t_。 即便思考这个问题数十年,这个结论仍令我震撼。 当当前成就决定未来表现时,指数增长就会出现。但无论基因还是传统都未为此做好准备。没人觉得指数增长理所当然——每个孩子初次听到"棋盘麦粒"故事时都会惊讶:第一天一粒米,之后每日翻倍。 对于不自然的事物,人类会发展应对习俗。但关于指数增长的习俗极少,因为历史上指数增长案例屈指可数。理论上畜牧本应如此:牲畜越多,后代越多。但实践中牧场才是限制因素,而牧场无法指数扩张。 更准确地说,缺乏普遍适用的扩张方案。领土确有一种指数扩张方式:征服。控制疆域越大,军力越强,征服新领土越容易。这就是历史上帝国林立的原因。但帝国缔造者寥寥,其经验难以影响大众习俗。帝王是遥远可怖的存在,而非生活指南。 前工业时代最常见的指数增长或许来自学术研究。知识越多,学习新事物越容易。古往今来,某些人在特定领域的知识储备总令常人望尘莫及。但这同样未能显著影响习俗。尽管思想帝国可以重叠(因此思想帝王更多),但在工业革命前,这类帝国影响甚微。[2] 近几个世纪情况剧变。如今思想帝王能设计击败疆域帝王的炸弹。但这个现象仍太新颖,人类尚未完全适应。即便参与者中,也少有人意识到自己正受益于指数增长,或思考能从其他案例中学到什么。 超线性回报的另一源头体现在"赢家通吃"法则中。体育比赛中表现与回报呈阶梯函数:无论优势悬殊还是微弱,胜者都获得同等胜利。[3] 但阶梯函数的本质不是竞争本身,而是结果存在临界阈值。即便没有竞争,单打独斗时阈值依然存在——比如证明定理或命中目标时。 值得注意的是,超线性回报的两大源头往往共生共存。跨越阈值能触发指数增长:战役胜者通常伤亡更少,未来更易取胜。指数增长又能助你突破阈值:在网络效应市场,快速增长的公司能封锁潜在竞争者。 名声是两大源头融合的典型案例。既有粉丝带来新粉丝,形成指数增长。但其高度集中的根本原因在于阈值:普通人脑中的"一线明星"席位极其有限。 学习可能是结合两大源头最重要的案例。知识呈指数增长,但存在诸多阈值。比如学骑自行车。某些阈值如同机床:掌握阅读后,学习其他事物快得多。但最重要的阈值代表新发现——知识疆界看似平滑,近观却布满裂隙。某些裂隙会扩展成全新领域,而开拓者将享有该领域所有新发现的首采权。牛顿如此,丢勒与达尔文亦然。 寻找超线性回报领域是否有通用法则?最明显的就是选择具有复合效应的工作。 工作复合有两种形式:直接复合(本轮表现提升下轮表现,如基建建设/受众培养/品牌打造);或通过学习的复合(学习本身具有复利效应)。后者尤为有趣——你可能在过程中自觉表现糟糕,未能达成短期目标。但只要持续学习,你实际上仍在指数成长。 硅谷对失败异常宽容正源于此。人们并非盲目宽容,只继续押注那些从失败中学习的人。这类人确实是优质赌注:公司或许未达预期增长,但创始人已然成长,终将开花结果。 事实上,不与学习交织的指数增长少之又少,这或许应视为常态而非例外。由此衍生另一启发式原则:保持学习。停止学习意味着你可能偏离了超线性回报之路。 但不必过度优化学习内容。不要局限在已知有价值领域。学习本就是探索未知价值的过程,过度设限会扼杀突破可能。 阶梯函数方面呢?"寻找阈值"或"寻找竞争"是否也是有效启发?情况更复杂。阈值存在不保证游戏值得参与。玩俄罗斯轮盘赌虽有明确阈值,但最佳结果也不过全身而退。"寻找竞争"同样空洞——若奖品本身不值呢?足够快的指数增长能同时确保回报曲线的形态与幅度(因为高速增长终将壮大,哪怕初期微不足道),而阈值仅能保证形态。[4] 利用阈值的原则必须包含价值检验:当你发现某事物平庸却流行,替代它或许就是良机。例如某公司产品令人不满却仍有销路,那么提供更优选择理应成功。[5] 若能预判知识阈值将事半功倍。是否存在识别"问题背后藏全新领域"的方法?虽无法绝对预测,但回报如此诱人,即便略优于随机的预测也价值连城。某种程度上我们确能排除某些研究方向:那些看似合理但乏味的问题。而可能引发新发现的问题往往神秘却看似次要(若既神秘又重要,早该成为著名开放问题,众人竞相研究)。因此这里的启发式是:追随好奇心而非功利心——解放好奇心,而非困在"应做之事"中。 超线性回报的前景令有志者振奋。更可喜的是:这个疆域正在双向扩展。能获得超线性回报的工作类型在增加,回报本身也在增长。 原因有二(实则一体两面):技术进步与组织重要性下降。 五十年前,参与雄心项目几乎必须依附组织。这是获取资源、协作伙伴、分销渠道的唯一途径。因此在1970年,个人声望通常就是所属组织的声望。这种关联真实有效——脱离组织难有作为。少数例外是艺术家与作家,他们独力创作,工具廉价,拥有个人品牌。但即便他们也需要组织触达受众。[6] 组织主导的世界抑制了表现回报的差异。但就在我的人生历程中,这个世界已剧烈瓦解。如今越来越多人能享有20世纪艺术家的自由:众多雄心项目不需初始资金,学习、盈利、寻伴、触达受众的新方式层出不穷。 旧世界依然存在,但变革速度史无前例——尤其考虑到事关表现回报这一根本要素。 组织缓冲作用消失后,结果差异将加剧。这并非人人受益:表现优异者会更成功,糟糕者会更失败。需谨记:接触超线性回报并非人人适宜。多数人更适合留在"安全池"。那么谁该追求超线性回报?两类有志者:自知卓越、确信能在高差异世界净收益者;以及(特别是年轻人)能承担试错成本者。[7] 脱离组织的趋势不会仅是现有成员的出走。许多新赢家将是组织永远拒之门外者。因此最终的机会民主化,将比组织内部任何温和改良都更彻底真实。 并非所有人都乐见雄心枷锁的解除。这威胁某些既得利益,违背某些意识形态。[8]但对有志者确是佳音。如何把握? 把握超线性回报最直接的方式就是做出卓越成果。在回报曲线远端,边际努力性价比极高——不仅因为做到极致本就困难,更因为多数人望而却步。因此追求卓越不仅是划算的投资,连尝试本身都性价比惊人。 影响工作质量的变量众多,要成为顶尖需要把控几乎所有变量。例如要做到极致,你必须对其怀有真兴趣。仅靠勤勉远远不够。因此在超线性回报世界,了解兴趣所在并找到践行之道价值倍增。[9]选择符合处境的工作也很关键。比如某些工作天然耗时耗力,年轻时无子女负担阶段从事将更高效。 成就伟业需要惊人技巧,非仅竭力而为。我尝试用一段话总结诀窍: 选择天赋与兴趣交汇的领域。培养自主项目习惯——只要让你兴奋且具野心的项目皆可。尽力工作但不透支,这终将带你至知识前沿。远看平滑的边界近观布满缺口。留意探索这些缺口,幸运的话某个缺口会扩展成全新领域。承担可承受的最大风险;若从未失败说明过于保守。寻找顶尖同伴。培养卓越品味,向最佳范例学习。保持诚实,尤其对自己。注重锻炼饮食睡眠,远离危险药物。疑惑时追随好奇心——它永不欺骗,且比你更懂何事值得关注。[10] 当然还需要另一样:运气。运气始终重要,独立工作时尤甚。尽管有"运气是准备遇见机遇"等箴言,但总存在无法掌控的纯粹偶然因素。解决方案就是多次尝试——这也是尽早冒险的另一理由。 超线性回报最典型领域或许是科学。它既有学习的指数增长,又有知识边界上的表现阈值。 结果导致科学发现的不平等程度,令最阶层化社会的财富不平等都相形见绌。牛顿的发现可能超过同期所有科学家总和。[11] 这看似显而易见,但值得阐明:超线性回报必然导致不平等。回报曲线越陡峭,结果差异越显著。 事实上,超线性回报与不平等的相关性如此之强,以至于衍生出另一条寻找此类工作的启发式:观察哪些领域少数赢家远超众人。人人表现相近的工作类型很难产生超线性回报。 哪些领域存在少数赢家通吃?明显包括:体育、政治、艺术、音乐、表演、导演、写作、数学、科学、创业、投资。体育中的现象源于外部设定的阈值——只需快百分之几就能包揽冠军。政治中权力增长仍如帝王时代。其他领域(包括政治)的成功多由名声驱动,而名声自有其超线性增长源泉。但排除体育、政治与名声效应后,惊人规律浮现:剩余清单恰恰与需要独立思维才能成功的领域完全重合——这些领域不仅要求正确,更要求创新。[12] 科学领域显然如此。重复他人成果的论文无法发表。投资领域同样:只有当多数投资者不看好某公司时,你的看好才有价值;若众人皆看好,股价已反映预期,无利可图。 还能从这些领域学到什么?所有领域都需要初始投入。超线性回报初期看似微弱。"照这个速度",你会想,"永远无法成功。"但因回报曲线远端急剧上升,值得采取非常手段抵达。 创业界称此原则为"做不可扩展之事"。对初期少量客户倾注离谱的注意力,理想情况下能启动口碑传播的指数增长。该原则同样适用于任何指数增长事物。以学习为例:初学某物时总感迷茫。但值得付出初始努力获得立足点,因为学得越多进展越快。 超线性回报领域清单还隐含更微妙启示:勿将工作等同于职业。20世纪多数人二者等同,导致我们继承将生产力等同于有工作的习俗。如今对多数人"你的工作"仍指其职业。但对作家、艺术家或科学家而言,它意味着正在研究或创造的内容。这类人的工作随他们跨越不同职业(如果他们真有职业的话),可能为雇主完成,但始终是其作品集的一部分。 进入赢家通吃领域令人却步。有人刻意为之,但你不必如此。只要具备足够天赋并追随好奇心足够远,你终将抵达。好奇心不容你对无聊问题感兴趣,而有趣问题若非已属超线性回报领域,往往会自创此类领域。 超线性回报疆域绝非静止。事实上,最极端的回报正来自扩展疆界。因此虽然雄心与好奇心都能带你进入,后者可能力量更强。雄心驱使你攀登既有高峰,但若紧贴足够有趣的问题,它可能在你脚下成长为新的山脉。 注释 努力、表现与回报的界限本质上是模糊的——某人眼中的回报可能是他人的表现。尽管这些概念边界模糊,但并非无意义。我尽可能精确表述而不致谬误。 [1] 进化本身或许是超线性回报最普遍的案例。但我们难以共情,因为接受者不是我们——我们就是回报本身。 [2] 工业革命前知识当然有实际影响。农业革命彻底改变人类生活。但这类变化源于技术广泛渐进改良,而非个别博学者发现。 [3] 严格说阶梯函数不算超线性,但始于零点的阶梯函数对理性行为者的努力回报曲线作用类似超线性函数。若起点为零,阈值前段低于任何线性回报,后段必须高于该点必要回报才有人尝试。 [4] "寻找竞争"作为启发式或有价值,因某些人因此获得动力。某种程度上也指示有前景的问题(他人认可的标志)。但这标志极不完美:常见人群喧嚣追逐某问题,最终却被静心研究其他问题者超越。 [5] 但非绝对。需谨慎应用该原则。平庸却流行的事物往往有隐藏原因:垄断/监管阻碍竞争;顾客品味差或采购流程缺陷。大量平庸事物正因此存在。 [6] 二十多岁时我想成为艺术家,甚至就读艺术学院学画。主因是热爱艺术,但部分动机确实源于艺术家看似最少受制于组织。 [7] 理论上人人都获超线性回报。学习具有复利效应,人人终生学习。但实践中少有人将日常学习推至回报曲线真正陡峭的程度。 [8] "公平"倡导者的确切含义模糊,他们内部也存在分歧。但无论何种定义,恐怕都与"组织对结果控制力减弱,少数异类远超常人"的世界观冲突。 这个概念恰在世界反向转变时兴起看似不幸,但我想并非巧合。其兴起的部分原因正是信徒们对表现差异急剧扩大的恐慌。 [9] 推论:强迫孩子从事医学等体面职业却无视其兴趣的家长,其伤害将比过去更甚。 [10] 这段文字初稿原是《如何成就伟业》的起点。刚写完我就意识到这比超线性回报更重要,遂暂停本文先扩展成独立文章。现版本已几乎重写,因《伟业》完成后我据此修订了这部分。 [11] 工业革命前致富者多如帝王:掌控资源增强实力,进而获取更多。如今则可如科学家般,通过发现或创造独特价值致富。多数富人新旧方式混用,但最近半世纪发达经济体的比例已显著转向发现型致富。 [12] 若独立思维是最大不平等驱动力,那么从众者厌恶不平等并不意外。但这不止是"不欲人得己所不能"——从众者根本无法想象拥有新创见的感觉。因此表现的巨大差异对他们而言全然陌生,遭遇时总认定必是作弊或外界恶意影响所致。 致谢Trevor Blackwell、Patrick Collison、Tyler Cowen、Jessica Livingston、Harj Taggar与Garry Tan审阅了本文草稿。.
July 2023 If you collected lists of techniques for doing great work in a lot of different fields, what would the intersection look like? I decided to find out by making it. Partly my goal was to create a guide that could be used by someone working in any field. But I was also curious about the shape of the intersection. And one thing this exercise shows is that it does have a definite shape; it's not just a point labelled "work hard." The following recipe assumes you're very ambitious. The first step is to decide what to work on. The work you choose needs to have three qualities: it has to be something you have a natural aptitude for, that you have a deep interest in, and that offers scope to do great work. In practice you don't have to worry much about the third criterion. Ambitious people are if anything already too conservative about it. So all you need to do is find something you have an aptitude for and great interest in. [1] That sounds straightforward, but it's often quite difficult. When you're young you don't know what you're good at or what different kinds of work are like. Some kinds of work you end up doing may not even exist yet. So while some people know what they want to do at 14, most have to figure it out. The way to figure out what to work on is by working. If you're not sure what to work on, guess. But pick something and get going. You'll probably guess wrong some of the time, but that's fine. It's good to know about multiple things; some of the biggest discoveries come from noticing connections between different fields. Develop a habit of working on your own projects. Don't let "work" mean something other people tell you to do. If you do manage to do great work one day, it will probably be on a project of your own. It may be within some bigger project, but you'll be driving your part of it. What should your projects be? Whatever seems to you excitingly ambitious.
如果你收集许多不同领域做出伟大工作的技巧清单,它们的交集会是什么样子?我决定通过制作这样一份清单来找出答案。
部分目标是创建一个适用于任何领域工作者的指南。但我也对这个交集的具体形态感到好奇。这个练习表明,它确实有一个明确的形态;不仅仅是标着“努力工作”的一个点。
As you grow older and your taste in projects evolves, exciting and important will converge. At 7 it may seem excitingly ambitious to build huge things out of Lego, then at 14 to teach yourself calculus, till at 21 you're starting to explore unanswered questions in physics. But always preserve excitingness. There's a kind of excited curiosity that's both the engine and the rudder of great work. It will not only drive you, but if you let it have its way, will also show you what to work on. What are you excessively curious about — curious to a degree that would bore most other people? That's what you're looking for. Once you've found something you're excessively interested in, the next step is to learn enough about it to get you to one of the frontiers of knowledge. Knowledge expands fractally, and from a distance its edges look smooth, but once you learn enough to get close to one, they turn out to be full of gaps. The next step is to notice them. This takes some skill, because your brain wants to ignore such gaps in order to make a simpler model of the world. Many discoveries have come from asking questions about things that everyone else took for granted. [2] If the answers seem strange, so much the better. Great work often has a tincture of strangeness. You see this from painting to math. It would be affected to try to manufacture it, but if it appears, embrace it. Boldly chase outlier ideas, even if other people aren't interested in them — in fact, especially if they aren't. If you're excited about some possibility that everyone else ignores, and you have enough expertise to say precisely what they're all overlooking, that's as good a bet as you'll find. [3] Four steps: choose a field, learn enough to get to the frontier, notice gaps, explore promising ones. This is how practically everyone who's done great work has done it, from painters to physicists. Steps two and four will require hard work.
以下方法假设你非常有雄心。
第一步是决定做什么工作。你选择的工作需要具备三个品质:它必须是你天生擅长的,你对其有浓厚兴趣的,并且提供了做出伟大工作的空间。
在实践中,你不必太担心第三个标准。雄心勃勃的人在这方面往往已经过于保守了。所以你只需要找到你既擅长又非常感兴趣的东西。[1]
It may not be possible to prove that you have to work hard to do great things, but the empirical evidence is on the scale of the evidence for mortality. That's why it's essential to work on something you're deeply interested in. Interest will drive you to work harder than mere diligence ever could. The three most powerful motives are curiosity, delight, and the desire to do something impressive. Sometimes they converge, and that combination is the most powerful of all. The big prize is to discover a new fractal bud. You notice a crack in the surface of knowledge, pry it open, and there's a whole world inside. Let's talk a little more about the complicated business of figuring out what to work on. The main reason it's hard is that you can't tell what most kinds of work are like except by doing them. Which means the four steps overlap: you may have to work at something for years before you know how much you like it or how good you are at it. And in the meantime you're not doing, and thus not learning about, most other kinds of work. So in the worst case you choose late based on very incomplete information. [4] The nature of ambition exacerbates this problem. Ambition comes in two forms, one that precedes interest in the subject and one that grows out of it. Most people who do great work have a mix, and the more you have of the former, the harder it will be to decide what to do. The educational systems in most countries pretend it's easy. They expect you to commit to a field long before you could know what it's really like. And as a result an ambitious person on an optimal trajectory will often read to the system as an instance of breakage. It would be better if they at least admitted it — if they admitted that the system not only can't do much to help you figure out what to work on, but is designed on the assumption that you'll somehow magically guess as a teenager.
这听起来很简单,但往往相当困难。年轻时,你不知道自己擅长什么,也不知道不同类型的工作是什么样子。有些你最终从事的工作甚至可能还不存在。所以虽然有些人在14岁时就知道自己想做什么,但大多数人需要去探索。
找出该做什么的方法是工作。如果你不确定该做什么,就猜一个。但选一个并开始行动。有时你可能会猜错,但这没关系。了解多个领域是好事;一些最大的发现来自于注意到不同领域之间的联系。
They don't tell you, but I will: when it comes to figuring out what to work on, you're on your own. Some people get lucky and do guess correctly, but the rest will find themselves scrambling diagonally across tracks laid down on the assumption that everyone does. What should you do if you're young and ambitious but don't know what to work on? What you should _not_ do is drift along passively, assuming the problem will solve itself. You need to take action. But there is no systematic procedure you can follow. When you read biographies of people who've done great work, it's remarkable how much luck is involved. They discover what to work on as a result of a chance meeting, or by reading a book they happen to pick up. So you need to make yourself a big target for luck, and the way to do that is to be curious. Try lots of things, meet lots of people, read lots of books, ask lots of questions. [5] When in doubt, optimize for interestingness. Fields change as you learn more about them. What mathematicians do, for example, is very different from what you do in high school math classes. So you need to give different types of work a chance to show you what they're like. But a field should become _increasingly_ interesting as you learn more about it. If it doesn't, it's probably not for you. Don't worry if you find you're interested in different things than other people. The stranger your tastes in interestingness, the better. Strange tastes are often strong ones, and a strong taste for work means you'll be productive. And you're more likely to find new things if you're looking where few have looked before. One sign that you're suited for some kind of work is when you like even the parts that other people find tedious or frightening. But fields aren't people; you don't owe them any loyalty. If in the course of working on one thing you discover another that's more exciting, don't be afraid to switch.
养成自己做项目的习惯。不要让“工作”意味着别人告诉你做的事。如果你有一天真的做出了伟大的工作,那很可能是在你自己的项目上。它可能是一个更大项目的一部分,但你会推动你负责的部分。
你的项目应该是什么?任何让你感到兴奋且雄心勃勃的事情。随着年龄增长,你对项目的品味会演变,兴奋和重要会趋于一致。7岁时,用乐高搭建巨大的东西可能显得雄心勃勃;14岁时,自学微积分;到21岁时,你开始探索物理学中未解答的问题。但始终要保持兴奋感。
有一种兴奋的好奇心,既是伟大工作的引擎,也是它的舵。它不仅会驱动你,如果你顺其自然,它还会告诉你该做什么。
If you're making something for people, make sure it's something they actually want. The best way to do this is to make something you yourself want. Write the story you want to read; build the tool you want to use. Since your friends probably have similar interests, this will also get you your initial audience. This _should_ follow from the excitingness rule. Obviously the most exciting story to write will be the one you want to read. The reason I mention this case explicitly is that so many people get it wrong. Instead of making what they want, they try to make what some imaginary, more sophisticated audience wants. And once you go down that route, you're lost. [6] There are a lot of forces that will lead you astray when you're trying to figure out what to work on. Pretentiousness, fashion, fear, money, politics, other people's wishes, eminent frauds. But if you stick to what you find genuinely interesting, you'll be proof against all of them. If you're interested, you're not astray. Following your interests may sound like a rather passive strategy, but in practice it usually means following them past all sorts of obstacles. You usually have to risk rejection and failure. So it does take a good deal of boldness. But while you need boldness, you don't usually need much planning. In most cases the recipe for doing great work is simply: work hard on excitingly ambitious projects, and something good will come of it. Instead of making a plan and then executing it, you just try to preserve certain invariants. The trouble with planning is that it only works for achievements you can describe in advance. You can win a gold medal or get rich by deciding to as a child and then tenaciously pursuing that goal, but you can't discover natural selection that way. I think for most people who want to do great work, the right strategy is not to plan too much.
你对什么过度好奇——好奇到会让大多数其他人感到无聊的程度?那就是你要找的。
一旦你找到了你过度感兴趣的东西,下一步是学习足够多的知识,以到达知识的前沿。知识以分形的方式扩展,从远处看,它的边缘看起来是平滑的,但一旦你学到足够接近一个边缘,你会发现它充满了缺口。
下一步是注意到这些缺口。这需要一些技巧,因为你的大脑会忽略这些缺口,以便对世界建立一个更简单的模型。许多发现来自于对其他人认为理所当然的事情提出问题。[2]
At each stage do whatever seems most interesting and gives you the best options for the future. I call this approach "staying upwind." This is how most people who've done great work seem to have done it. Even when you've found something exciting to work on, working on it is not always straightforward. There will be times when some new idea makes you leap out of bed in the morning and get straight to work. But there will also be plenty of times when things aren't like that. You don't just put out your sail and get blown forward by inspiration. There are headwinds and currents and hidden shoals. So there's a technique to working, just as there is to sailing. For example, while you must work hard, it's possible to work too hard, and if you do that you'll find you get diminishing returns: fatigue will make you stupid, and eventually even damage your health. The point at which work yields diminishing returns depends on the type. Some of the hardest types you might only be able to do for four or five hours a day. Ideally those hours will be contiguous. To the extent you can, try to arrange your life so you have big blocks of time to work in. You'll shy away from hard tasks if you know you might be interrupted. It will probably be harder to start working than to keep working. You'll often have to trick yourself to get over that initial threshold. Don't worry about this; it's the nature of work, not a flaw in your character. Work has a sort of activation energy, both per day and per project. And since this threshold is fake in the sense that it's higher than the energy required to keep going, it's ok to tell yourself a lie of corresponding magnitude to get over it. It's usually a mistake to lie to yourself if you want to do great work, but this is one of the rare cases where it isn't.
如果答案看起来很奇怪,那就更好了。伟大工作往往带有一种奇怪的色彩。从绘画到数学,你都能看到这一点。刻意制造这种奇怪会显得做作,但如果它自然出现,就拥抱它。
大胆追求离群的想法,即使其他人对它们不感兴趣——事实上,尤其是当他们不感兴趣时。如果你对某种可能性感到兴奋,而其他人都忽略了它,并且你有足够的专业知识准确指出他们忽略了什么,这就是你能找到的最好的赌注。[3]
When I'm reluctant to start work in the morning, I often trick myself by saying "I'll just read over what I've got so far." Five minutes later I've found something that seems mistaken or incomplete, and I'm off. Similar techniques work for starting new projects. It's ok to lie to yourself about how much work a project will entail, for example. Lots of great things began with someone saying "How hard could it be?" This is one case where the young have an advantage. They're more optimistic, and even though one of the sources of their optimism is ignorance, in this case ignorance can sometimes beat knowledge. Try to finish what you start, though, even if it turns out to be more work than you expected. Finishing things is not just an exercise in tidiness or self-discipline. In many projects a lot of the best work happens in what was meant to be the final stage. Another permissible lie is to exaggerate the importance of what you're working on, at least in your own mind. If that helps you discover something new, it may turn out not to have been a lie after all. [7] Since there are two senses of starting work — per day and per project — there are also two forms of procrastination. Per-project procrastination is far the more dangerous. You put off starting that ambitious project from year to year because the time isn't quite right. When you're procrastinating in units of years, you can get a lot not done. [8] One reason per-project procrastination is so dangerous is that it usually camouflages itself as work. You're not just sitting around doing nothing; you're working industriously on something else. So per-project procrastination doesn't set off the alarms that per-day procrastination does. You're too busy to notice it.
四个步骤:选择一个领域,学习足够到达前沿,注意到缺口,探索有前景的。几乎所有做出伟大工作的人都是这样做的,从画家到物理学家。
第二步和第四步需要艰苦的工作。可能无法证明你必须努力工作才能做出伟大的事情,但经验证据的规模与死亡率的证据相当。这就是为什么你必须深入研究你深感兴趣的东西。兴趣会驱使你比单纯的勤奋更加努力。
最强大的三种动机是好奇心、愉悦感和做出令人印象深刻的事情的欲望。有时它们会汇聚,这种组合是最强大的。
The way to beat it is to stop occasionally and ask yourself: Am I working on what I most want to work on? When you're young it's ok if the answer is sometimes no, but this gets increasingly dangerous as you get older. [9] Great work usually entails spending what would seem to most people an unreasonable amount of time on a problem. You can't think of this time as a cost, or it will seem too high. You have to find the work sufficiently engaging as it's happening. There may be some jobs where you have to work diligently for years at things you hate before you get to the good part, but this is not how great work happens. Great work happens by focusing consistently on something you're genuinely interested in. When you pause to take stock, you're surprised how far you've come. The reason we're surprised is that we underestimate the cumulative effect of work. Writing a page a day doesn't sound like much, but if you do it every day you'll write a book a year. That's the key: consistency. People who do great things don't get a lot done every day. They get something done, rather than nothing. If you do work that compounds, you'll get exponential growth. Most people who do this do it unconsciously, but it's worth stopping to think about. Learning, for example, is an instance of this phenomenon: the more you learn about something, the easier it is to learn more. Growing an audience is another: the more fans you have, the more new fans they'll bring you. The trouble with exponential growth is that the curve feels flat in the beginning. It isn't; it's still a wonderful exponential curve. But we can't grasp that intuitively, so we underrate exponential growth in its early stages. Something that grows exponentially can become so valuable that it's worth making an extraordinary effort to get it started.
最大的奖赏是发现一个新的分形芽。你注意到知识表面的一个裂缝,撬开它,里面有一个全新的世界。
让我们再谈谈弄清楚该做什么这一复杂的事情。主要困难在于,除非你亲自去做,否则你无法了解大多数工作的真实情况。这意味着四个步骤是重叠的:你可能需要在某件事上工作多年,才能知道你有多喜欢它或你有多擅长它。与此同时,你没有做,因此也没有了解大多数其他类型的工作。所以最坏的情况下,你会在信息非常不完整的情况下迟做选择。[4]
雄心的本质加剧了这个问题。雄心有两种形式,一种是对主题的兴趣之前就有的,另一种是从兴趣中产生的。大多数做出伟大工作的人两者兼有,前一种越多,决定做什么就越困难。
But since we underrate exponential growth early on, this too is mostly done unconsciously: people push through the initial, unrewarding phase of learning something new because they know from experience that learning new things always takes an initial push, or they grow their audience one fan at a time because they have nothing better to do. If people consciously realized they could invest in exponential growth, many more would do it. Work doesn't just happen when you're trying to. There's a kind of undirected thinking you do when walking or taking a shower or lying in bed that can be very powerful. By letting your mind wander a little, you'll often solve problems you were unable to solve by frontal attack. You have to be working hard in the normal way to benefit from this phenomenon, though. You can't just walk around daydreaming. The daydreaming has to be interleaved with deliberate work that feeds it questions. [10] Everyone knows to avoid distractions at work, but it's also important to avoid them in the other half of the cycle. When you let your mind wander, it wanders to whatever you care about most at that moment. So avoid the kind of distraction that pushes your work out of the top spot, or you'll waste this valuable type of thinking on the distraction instead. (Exception: Don't avoid love.) Consciously cultivate your taste in the work done in your field. Until you know which is the best and what makes it so, you don't know what you're aiming for. And that _is_ what you're aiming for, because if you don't try to be the best, you won't even be good. This observation has been made by so many people in so many different fields that it might be worth thinking about why it's true. It could be because ambition is a phenomenon where almost all the error is in one direction — where almost all the shells that miss the target miss by falling short.
大多数国家的教育系统假装这很容易。他们期望你在真正了解一个领域之前就长期投入其中。因此,一个雄心勃勃的人在最优轨迹上往往会被系统视为一个破坏实例。
如果他们至少承认这一点会更好——承认系统不仅无法帮助你弄清楚该做什么,而且是基于你会在十几岁时以某种方式神奇地猜中的假设设计的。他们不会告诉你,但我会:在弄清楚该做什么时,你只能靠自己。有些人很幸运,猜对了,但其他人会发现自己在假设每个人都这样做的轨道上斜向爬行。
Or it could be because ambition to be the best is a qualitatively different thing from ambition to be good. Or maybe being good is simply too vague a standard. Probably all three are true. [11] Fortunately there's a kind of economy of scale here. Though it might seem like you'd be taking on a heavy burden by trying to be the best, in practice you often end up net ahead. It's exciting, and also strangely liberating. It simplifies things. In some ways it's easier to try to be the best than to try merely to be good. One way to aim high is to try to make something that people will care about in a hundred years. Not because their opinions matter more than your contemporaries', but because something that still seems good in a hundred years is more likely to be genuinely good. Don't try to work in a distinctive style. Just try to do the best job you can; you won't be able to help doing it in a distinctive way. Style is doing things in a distinctive way without trying to. Trying to is affectation. Affectation is in effect to pretend that someone other than you is doing the work. You adopt an impressive but fake persona, and while you're pleased with the impressiveness, the fakeness is what shows in the work. [12] The temptation to be someone else is greatest for the young. They often feel like nobodies. But you never need to worry about that problem, because it's self-solving if you work on sufficiently ambitious projects. If you succeed at an ambitious project, you're not a nobody; you're the person who did it. So just do the work and your identity will take care of itself. "Avoid affectation" is a useful rule so far as it goes, but how would you express this idea positively? How would you say what to be, instead of what not to be? The best answer is earnest. If you're earnest you avoid not just affectation but a whole set of similar vices. The core of being earnest is being intellectually honest.
如果你年轻有雄心,但不知道该做什么,你该怎么办?你不应该做的是被动地随波逐流,假设问题会自行解决。你需要采取行动。但没有你可以遵循的系统程序。当你阅读做出伟大工作的人的传记时,会发现其中有多少运气成分。他们通过偶然的相遇或偶然拿起的一本书发现了该做什么。所以你需要让自己成为一个幸运的大目标,方法就是保持好奇。尝试很多事情,认识很多人,读很多书,问很多问题。[5]
有疑问时,优化有趣性。随着你对领域的了解加深,领域会变化。例如,数学家所做的与你在高中数学课上所做的非常不同。所以你需要给不同类型的工作一个机会,展示它们的真实面貌。但一个领域应该随着你了解更多而变得越来越有趣。如果没有,它可能不适合你。
如果你发现自己对与其他人不同的事物感兴趣,不要担心。你对有趣性的品味越奇怪越好。奇怪的品味往往是强烈的品味,对工作的强烈品味意味着你会富有成效。而且,如果你在很少有人涉足的领域寻找,你更有可能发现新事物。
We're taught as children to be honest as an unselfish virtue — as a kind of sacrifice. But in fact it's a source of power too. To see new ideas, you need an exceptionally sharp eye for the truth. You're trying to see more truth than others have seen so far. And how can you have a sharp eye for the truth if you're intellectually dishonest? One way to avoid intellectual dishonesty is to maintain a slight positive pressure in the opposite direction. Be aggressively willing to admit that you're mistaken. Once you've admitted you were mistaken about something, you're free. Till then you have to carry it. [13] Another more subtle component of earnestness is informality. Informality is much more important than its grammatically negative name implies. It's not merely the absence of something. It means focusing on what matters instead of what doesn't. What formality and affectation have in common is that as well as doing the work, you're trying to seem a certain way as you're doing it. But any energy that goes into how you seem comes out of being good. That's one reason nerds have an advantage in doing great work: they expend little effort on seeming anything. In fact that's basically the definition of a nerd. Nerds have a kind of innocent boldness that's exactly what you need in doing great work. It's not learned; it's preserved from childhood. So hold onto it. Be the one who puts things out there rather than the one who sits back and offers sophisticated-sounding criticisms of them. "It's easy to criticize" is true in the most literal sense, and the route to great work is never easy. There may be some jobs where it's an advantage to be cynical and pessimistic, but if you want to do great work it's an advantage to be optimistic, even though that means you'll risk looking like a fool sometimes. There's an old tradition of doing the opposite. The Old Testament says it's better to keep quiet lest you look like a fool.
你适合某种工作的一个标志是,即使其他人觉得无聊或可怕的部分你也喜欢。
但领域不是人;你不必对它们忠诚。如果在做一个事情的过程中发现了另一个更令人兴奋的事情,不要害怕转换。
如果你在为人们制作东西,确保它确实是他们想要的。最好的方法是制作你自己想要的东西。写你想读的故事;建造你想使用的工具。因为你的朋友可能有相似的兴趣,这也会为你赢得最初的观众。
But that's advice for _seeming_ smart. If you actually want to discover new things, it's better to take the risk of telling people your ideas. Some people are naturally earnest, and with others it takes a conscious effort. Either kind of earnestness will suffice. But I doubt it would be possible to do great work without being earnest. It's so hard to do even if you are. You don't have enough margin for error to accommodate the distortions introduced by being affected, intellectually dishonest, orthodox, fashionable, or cool. [14] Great work is consistent not only with who did it, but with itself. It's usually all of a piece. So if you face a decision in the middle of working on something, ask which choice is more consistent. You may have to throw things away and redo them. You won't necessarily have to, but you have to be willing to. And that can take some effort; when there's something you need to redo, status quo bias and laziness will combine to keep you in denial about it. To beat this ask: If I'd already made the change, would I want to revert to what I have now? Have the confidence to cut. Don't keep something that doesn't fit just because you're proud of it, or because it cost you a lot of effort. Indeed, in some kinds of work it's good to strip whatever you're doing to its essence. The result will be more concentrated; you'll understand it better; and you won't be able to lie to yourself about whether there's anything real there. Mathematical elegance may sound like a mere metaphor, drawn from the arts. That's what I thought when I first heard the term "elegant" applied to a proof. But now I suspect it's conceptually prior — that the main ingredient in artistic elegance is mathematical elegance. At any rate it's a useful standard well beyond math. Elegance can be a long-term bet, though. Laborious solutions will often have more prestige in the short term.
这应该遵循有趣性规则。显然,最令人兴奋的故事是你想读的故事。我明确提到这一点是因为很多人会弄错。他们不制作自己想要的东西,而是试图制作一些想象中的、更复杂的观众想要的东西。一旦你走上这条路,你就迷失了。[6]
当你试图弄清楚该做什么时,有很多力量会让你误入歧途。矫揉造作、时尚、恐惧、金钱、政治、他人的愿望、著名的骗局。但如果你坚持你真正感兴趣的东西,你就能抵御所有这些。如果你感兴趣,你就没有误入歧途。
They cost a lot of effort and they're hard to understand, both of which impress people, at least temporarily. Whereas some of the very best work will seem like it took comparatively little effort, because it was in a sense already there. It didn't have to be built, just seen. It's a very good sign when it's hard to say whether you're creating something or discovering it. When you're doing work that could be seen as either creation or discovery, err on the side of discovery. Try thinking of yourself as a mere conduit through which the ideas take their natural shape. (Strangely enough, one exception is the problem of choosing a problem to work on. This is usually seen as search, but in the best case it's more like creating something. In the best case you create the field in the process of exploring it.) Similarly, if you're trying to build a powerful tool, make it gratuitously unrestrictive. A powerful tool almost by definition will be used in ways you didn't expect, so err on the side of eliminating restrictions, even if you don't know what the benefit will be. Great work will often be tool-like in the sense of being something others build on. So it's a good sign if you're creating ideas that others could use, or exposing questions that others could answer. The best ideas have implications in many different areas. If you express your ideas in the most general form, they'll be truer than you intended. True by itself is not enough, of course. Great ideas have to be true and new. And it takes a certain amount of ability to see new ideas even once you've learned enough to get to one of the frontiers of knowledge. In English we give this ability names like originality, creativity, and imagination. And it seems reasonable to give it a separate name, because it does seem to some extent a separate skill.
追随你的兴趣听起来像是一个相当被动的策略,但在实践中,它通常意味着追随它们越过各种障碍。你通常需要冒被拒绝和失败的风险。所以这确实需要相当大的勇气。
但虽然你需要勇气,你通常不需要太多计划。在大多数情况下,做出伟大工作的秘诀很简单:在令人兴奋的雄心勃勃的项目上努力工作,好事就会发生。与其制定计划然后执行它,不如尝试保持某些不变性。
计划的问题在于它只适用于你可以提前描述的成就。你可以通过从小决定并坚持不懈地追求目标来赢得金牌或致富,但你无法以这种方式发现自然选择。
It's possible to have a great deal of ability in other respects — to have a great deal of what's often called _technical_ ability — and yet not have much of this. I've never liked the term "creative process." It seems misleading. Originality isn't a process, but a habit of mind. Original thinkers throw off new ideas about whatever they focus on, like an angle grinder throwing off sparks. They can't help it. If the thing they're focused on is something they don't understand very well, these new ideas might not be good. One of the most original thinkers I know decided to focus on dating after he got divorced. He knew roughly as much about dating as the average 15 year old, and the results were spectacularly colorful. But to see originality separated from expertise like that made its nature all the more clear. I don't know if it's possible to cultivate originality, but there are definitely ways to make the most of however much you have. For example, you're much more likely to have original ideas when you're working on something. Original ideas don't come from trying to have original ideas. They come from trying to build or understand something slightly too difficult. [15] Talking or writing about the things you're interested in is a good way to generate new ideas. When you try to put ideas into words, a missing idea creates a sort of vacuum that draws it out of you. Indeed, there's a kind of thinking that can only be done by writing. Changing your context can help. If you visit a new place, you'll often find you have new ideas there. The journey itself often dislodges them. But you may not have to go far to get this benefit. Sometimes it's enough just to go for a walk. [16] It also helps to travel in topic space. You'll have more new ideas if you explore lots of different topics, partly because it gives the angle grinder more surface area to work on, and partly because analogies are an especially fruitful source of new ideas.
我认为对于大多数想做出伟大工作的人来说,正确的策略是不要过多计划。在每个阶段做看起来最有趣、为你提供最佳未来选择的事情。我称这种方法为“保持逆风”。大多数做出伟大工作的人似乎都是这样做的。
即使你找到了令人兴奋的工作,做起来也不总是直截了当的。有时某个新想法会让你早上跳下床直接开始工作。但也有很多时候并非如此。
你不能只是扬起帆,被灵感吹着前进。有逆风、水流和隐藏的浅滩。所以工作有技巧,就像航海一样。
Don't divide your attention _evenly_ between many topics though, or you'll spread yourself too thin. You want to distribute it according to something more like a power law. [17] Be professionally curious about a few topics and idly curious about many more. Curiosity and originality are closely related. Curiosity feeds originality by giving it new things to work on. But the relationship is closer than that. Curiosity is itself a kind of originality; it's roughly to questions what originality is to answers. And since questions at their best are a big component of answers, curiosity at its best is a creative force. Having new ideas is a strange game, because it usually consists of seeing things that were right under your nose. Once you've seen a new idea, it tends to seem obvious. Why did no one think of this before? When an idea seems simultaneously novel and obvious, it's probably a good one. Seeing something obvious sounds easy. And yet empirically having new ideas is hard. What's the source of this apparent contradiction? It's that seeing the new idea usually requires you to change the way you look at the world. We see the world through models that both help and constrain us. When you fix a broken model, new ideas become obvious. But noticing and fixing a broken model is hard. That's how new ideas can be both obvious and yet hard to discover: they're easy to see after you do something hard. One way to discover broken models is to be stricter than other people. Broken models of the world leave a trail of clues where they bash against reality. Most people don't want to see these clues. It would be an understatement to say that they're attached to their current model; it's what they think in; so they'll tend to ignore the trail of clues left by its breakage, however conspicuous it may seem in retrospect. To find new ideas you have to seize on signs of breakage instead of looking away. That's what Einstein did.
例如,虽然你必须努力工作,但有可能工作过度,如果你这样做,你会发现收益递减:疲劳会让你变笨,最终甚至损害你的健康。工作产生收益递减的点取决于类型。一些最困难的工作你可能一天只能做四五个小时。
理想情况下,这些小时是连续的。尽可能安排你的生活,以便有大块的时间工作。如果你知道自己可能会被打断,你会回避困难的任务。
He was able to see the wild implications of Maxwell's equations not so much because he was looking for new ideas as because he was stricter. The other thing you need is a willingness to break rules. Paradoxical as it sounds, if you want to fix your model of the world, it helps to be the sort of person who's comfortable breaking rules. From the point of view of the old model, which everyone including you initially shares, the new model usually breaks at least implicit rules. Few understand the degree of rule-breaking required, because new ideas seem much more conservative once they succeed. They seem perfectly reasonable once you're using the new model of the world they brought with them. But they didn't at the time; it took the greater part of a century for the heliocentric model to be generally accepted, even among astronomers, because it felt so wrong. Indeed, if you think about it, a good new idea has to seem bad to most people, or someone would have already explored it. So what you're looking for is ideas that seem crazy, but the right kind of crazy. How do you recognize these? You can't with certainty. Often ideas that seem bad are bad. But ideas that are the right kind of crazy tend to be exciting; they're rich in implications; whereas ideas that are merely bad tend to be depressing. There are two ways to be comfortable breaking rules: to enjoy breaking them, and to be indifferent to them. I call these two cases being aggressively and passively independent-minded. The aggressively independent-minded are the naughty ones. Rules don't merely fail to stop them; breaking rules gives them additional energy. For this sort of person, delight at the sheer audacity of a project sometimes supplies enough activation energy to get it started. The other way to break rules is not to care about them, or perhaps even to know they exist.
开始工作可能比继续工作更难。你经常需要欺骗自己越过最初的阈值。不要担心;这是工作的本质,不是你性格的缺陷。工作有一种激活能量,无论是每天还是每个项目。因为这个阈值是虚假的,高于继续工作所需的能量,所以用相应大小的谎言骗自己越过它是可以的。
如果你想做出伟大的工作,对自己撒谎通常是一个错误,但这是少数例外之一。当我早上不愿开始工作时,我经常骗自己说“我只是看看已经做了什么”。五分钟后,我发现了一些看起来错误或不完整的东西,然后我就开始了。
类似的技术适用于启动新项目。例如,你可以对自己撒谎说一个项目需要多少工作。许多伟大的事情始于有人说“这能有多难?”
This is why novices and outsiders often make new discoveries; their ignorance of a field's assumptions acts as a source of temporary passive independent-mindedness. Aspies also seem to have a kind of immunity to conventional beliefs. Several I know say that this helps them to have new ideas. Strictness plus rule-breaking sounds like a strange combination. In popular culture they're opposed. But popular culture has a broken model in this respect. It implicitly assumes that issues are trivial ones, and in trivial matters strictness and rule-breaking _are_ opposed. But in questions that really matter, only rule-breakers can be truly strict. An overlooked idea often doesn't lose till the semifinals. You do see it, subconsciously, but then another part of your subconscious shoots it down because it would be too weird, too risky, too much work, too controversial. This suggests an exciting possibility: if you could turn off such filters, you could see more new ideas. One way to do that is to ask what would be good ideas for _someone else_ to explore. Then your subconscious won't shoot them down to protect you. You could also discover overlooked ideas by working in the other direction: by starting from what's obscuring them. Every cherished but mistaken principle is surrounded by a dead zone of valuable ideas that are unexplored because they contradict it. Religions are collections of cherished but mistaken principles. So anything that can be described either literally or metaphorically as a religion will have valuable unexplored ideas in its shadow. Copernicus and Darwin both made discoveries of this type. [18] What are people in your field religious about, in the sense of being too attached to some principle that might not be as self-evident as they think? What becomes possible if you discard it? People show much more originality in solving problems than in deciding which problems to solve.
在这种情况下,年轻人有优势。他们更乐观,尽管乐观的一个来源是无知,但在这种情况下,无知有时可以胜过知识。
不过,尽量完成你开始的事情,即使它比你预期的更多工作。完成事情不仅仅是整洁或自律的练习。在许多项目中,最好的工作发生在原本应该是最后阶段的时候。
另一个允许的谎言是夸大你正在做的工作的重要性,至少在你自己的心目中。如果这帮助你发现新东西,它可能最终并不是谎言。[7]
Even the smartest can be surprisingly conservative when deciding what to work on. People who'd never dream of being fashionable in any other way get sucked into working on fashionable problems. One reason people are more conservative when choosing problems than solutions is that problems are bigger bets. A problem could occupy you for years, while exploring a solution might only take days. But even so I think most people are too conservative. They're not merely responding to risk, but to fashion as well. Unfashionable problems are undervalued. One of the most interesting kinds of unfashionable problem is the problem that people think has been fully explored, but hasn't. Great work often takes something that already exists and shows its latent potential. Durer and Watt both did this. So if you're interested in a field that others think is tapped out, don't let their skepticism deter you. People are often wrong about this. Working on an unfashionable problem can be very pleasing. There's no hype or hurry. Opportunists and critics are both occupied elsewhere. The existing work often has an old-school solidity. And there's a satisfying sense of economy in cultivating ideas that would otherwise be wasted. But the most common type of overlooked problem is not explicitly unfashionable in the sense of being out of fashion. It just doesn't seem to matter as much as it actually does. How do you find these? By being self-indulgent — by letting your curiosity have its way, and tuning out, at least temporarily, the little voice in your head that says you should only be working on "important" problems. You do need to work on important problems, but almost everyone is too conservative about what counts as one. And if there's an important but overlooked problem in your neighborhood, it's probably already on your subconscious radar screen.
因为开始工作有两种意义——每天和每个项目——所以也有两种形式的拖延。每个项目的拖延要危险得多。你年复一年地推迟开始那个雄心勃勃的项目,因为时机不太合适。当你以年为单位拖延时,你可以有很多事情没做。[8]
每个项目的拖延如此危险的一个原因是它通常伪装成工作。你不是无所事事;你在勤奋地做其他事情。所以每个项目的拖延不会像每天拖延那样触发警报。你太忙了,没有注意到它。
So try asking yourself: if you were going to take a break from "serious" work to work on something just because it would be really interesting, what would you do? The answer is probably more important than it seems. Originality in choosing problems seems to matter even more than originality in solving them. That's what distinguishes the people who discover whole new fields. So what might seem to be merely the initial step — deciding what to work on — is in a sense the key to the whole game. Few grasp this. One of the biggest misconceptions about new ideas is about the ratio of question to answer in their composition. People think big ideas are answers, but often the real insight was in the question. Part of the reason we underrate questions is the way they're used in schools. In schools they tend to exist only briefly before being answered, like unstable particles. But a really good question can be much more than that. A really good question is a partial discovery. How do new species arise? Is the force that makes objects fall to earth the same as the one that keeps planets in their orbits? By even asking such questions you were already in excitingly novel territory. Unanswered questions can be uncomfortable things to carry around with you. But the more you're carrying, the greater the chance of noticing a solution — or perhaps even more excitingly, noticing that two unanswered questions are the same. Sometimes you carry a question for a long time. Great work often comes from returning to a question you first noticed years before — in your childhood, even — and couldn't stop thinking about. People talk a lot about the importance of keeping your youthful dreams alive, but it's just as important to keep your youthful questions alive. [19] This is one of the places where actual expertise differs most from the popular picture of it. In the popular picture, experts are certain.
克服它的方法是偶尔停下来问自己:我正在做我最想做的事情吗?年轻时,答案有时是否定的也没关系,但随着年龄增长,这会变得越来越危险。[9]
伟大工作通常意味着在问题上花费大多数人认为不合理的时间。你不能认为这段时间是一种成本,否则它会显得太高。你必须在进行时发现工作足够吸引人。
有些工作可能需要你多年来勤奋地做你讨厌的事情,然后才能进入好的部分,但伟大工作不是这样发生的。伟大工作是通过持续专注于你真正感兴趣的事情而发生的。当你停下来盘点时,你会惊讶于自己已经走了多远。
But actually the more puzzled you are, the better, so long as (a) the things you're puzzled about matter, and (b) no one else understands them either. Think about what's happening at the moment just before a new idea is discovered. Often someone with sufficient expertise is puzzled about something. Which means that originality consists partly of puzzlement — of confusion! You have to be comfortable enough with the world being full of puzzles that you're willing to see them, but not so comfortable that you don't want to solve them. [20] It's a great thing to be rich in unanswered questions. And this is one of those situations where the rich get richer, because the best way to acquire new questions is to try answering existing ones. Questions don't just lead to answers, but also to more questions. The best questions grow in the answering. You notice a thread protruding from the current paradigm and try pulling on it, and it just gets longer and longer. So don't require a question to be obviously big before you try answering it. You can rarely predict that. It's hard enough even to notice the thread, let alone to predict how much will unravel if you pull on it. It's better to be promiscuously curious — to pull a little bit on a lot of threads, and see what happens. Big things start small. The initial versions of big things were often just experiments, or side projects, or talks, which then grew into something bigger. So start lots of small things. Being prolific is underrated. The more different things you try, the greater the chance of discovering something new. Understand, though, that trying lots of things will mean trying lots of things that don't work. You can't have a lot of good ideas without also having a lot of bad ones. [21] Though it sounds more responsible to begin by studying everything that's been done before, you'll learn faster and have more fun by trying stuff.
我们感到惊讶的原因是我们低估了工作的累积效应。每天写一页听起来不多,但如果你每天都写,一年就能写一本书。这就是关键:一致性。做出伟大事情的人并不是每天做很多事。他们做了一些事,而不是什么都没做。
如果你的工作有复合效应,你会得到指数增长。大多数这样做的人是无意识的,但值得停下来思考。例如,学习就是这种现象的一个例子:你对某件事了解得越多,就越容易学到更多。增长观众是另一个例子:你拥有的粉丝越多,他们会给你带来更多新粉丝。
And you'll understand previous work better when you do look at it. So err on the side of starting. Which is easier when starting means starting small; those two ideas fit together like two puzzle pieces. How do you get from starting small to doing something great? By making successive versions. Great things are almost always made in successive versions. You start with something small and evolve it, and the final version is both cleverer and more ambitious than anything you could have planned. It's particularly useful to make successive versions when you're making something for people — to get an initial version in front of them quickly, and then evolve it based on their response. Begin by trying the simplest thing that could possibly work. Surprisingly often, it does. If it doesn't, this will at least get you started. Don't try to cram too much new stuff into any one version. There are names for doing this with the first version (taking too long to ship) and the second (the second system effect), but these are both merely instances of a more general principle. An early version of a new project will sometimes be dismissed as a toy. It's a good sign when people do this. That means it has everything a new idea needs except scale, and that tends to follow. [22] The alternative to starting with something small and evolving it is to plan in advance what you're going to do. And planning does usually seem the more responsible choice. It sounds more organized to say "we're going to do x and then y and then z" than "we're going to try x and see what happens." And it is more _organized_ ; it just doesn't work as well. Planning per se isn't good. It's sometimes necessary, but it's a necessary evil — a response to unforgiving conditions. It's something you have to do because you're working with inflexible media, or because you need to coordinate the efforts of a lot of people.
指数增长的问题在于曲线在开始时感觉是平的。它不是;它仍然是一条美妙的指数曲线。但我们无法直观地理解这一点,所以我们在早期低估了指数增长。
指数增长的东西可能变得非常有价值,值得付出非凡的努力来启动它。但由于我们在早期低估了指数增长,这大多也是无意识地完成的:人们推动学习新事物的最初、无回报的阶段,因为他们从经验中知道学习新事物总是需要最初的推动,或者他们一次一个粉丝地增长观众,因为他们没有更好的事情可做。如果人们意识到他们可以投资于指数增长,更多的人会这样做。
工作不仅仅发生在你尝试的时候。当你走路、洗澡或躺在床上时,你会进行一种无方向的思考,这可能非常强大。让你的思维稍微漫游,你通常会解决你无法通过正面攻击解决的问题。
If you keep projects small and use flexible media, you don't have to plan as much, and your designs can evolve instead. Take as much risk as you can afford. In an efficient market, risk is proportionate to reward, so don't look for certainty, but for a bet with high expected value. If you're not failing occasionally, you're probably being too conservative. Though conservatism is usually associated with the old, it's the young who tend to make this mistake. Inexperience makes them fear risk, but it's when you're young that you can afford the most. Even a project that fails can be valuable. In the process of working on it, you'll have crossed territory few others have seen, and encountered questions few others have asked. And there's probably no better source of questions than the ones you encounter in trying to do something slightly too hard. Use the advantages of youth when you have them, and the advantages of age once you have those. The advantages of youth are energy, time, optimism, and freedom. The advantages of age are knowledge, efficiency, money, and power. With effort you can acquire some of the latter when young and keep some of the former when old. The old also have the advantage of knowing which advantages they have. The young often have them without realizing it. The biggest is probably time. The young have no idea how rich they are in time. The best way to turn this time to advantage is to use it in slightly frivolous ways: to learn about something you don't need to know about, just out of curiosity, or to try building something just because it would be cool, or to become freakishly good at something. That "slightly" is an important qualification. Spend time lavishly when you're young, but don't simply waste it. There's a big difference between doing something you worry might be a waste of time and doing something you know for sure will be.
不过,你必须以正常方式努力工作才能从这种现象中受益。你不能只是四处游荡做白日梦。白日梦必须与有意识的工作交替进行,后者为它提供问题。[10]
每个人都知道要避免工作中的干扰,但在另一半周期中避免干扰也很重要。当你让你的思维漫游时,它会漫游到你当时最关心的事情上。所以避免那种把你的工作挤出首要位置的干扰,否则你会把这种宝贵的思考浪费在干扰上。(例外:不要回避爱情。)
有意识地培养你对所在领域工作的品味。在你知道哪个是最好的以及它为什么好之前,你不知道你的目标是什么。
The former is at least a bet, and possibly a better one than you think. [23] The most subtle advantage of youth, or more precisely of inexperience, is that you're seeing everything with fresh eyes. When your brain embraces an idea for the first time, sometimes the two don't fit together perfectly. Usually the problem is with your brain, but occasionally it's with the idea. A piece of it sticks out awkwardly and jabs you when you think about it. People who are used to the idea have learned to ignore it, but you have the opportunity not to. [24] So when you're learning about something for the first time, pay attention to things that seem wrong or missing. You'll be tempted to ignore them, since there's a 99% chance the problem is with you. And you may have to set aside your misgivings temporarily to keep progressing. But don't forget about them. When you've gotten further into the subject, come back and check if they're still there. If they're still viable in the light of your present knowledge, they probably represent an undiscovered idea. One of the most valuable kinds of knowledge you get from experience is to know what you _don't_ have to worry about. The young know all the things that could matter, but not their relative importance. So they worry equally about everything, when they should worry much more about a few things and hardly at all about the rest. But what you don't know is only half the problem with inexperience. The other half is what you do know that ain't so. You arrive at adulthood with your head full of nonsense — bad habits you've acquired and false things you've been taught — and you won't be able to do great work till you clear away at least the nonsense in the way of whatever type of work you want to do. Much of the nonsense left in your head is left there by schools.
这就是你的目标,因为如果你不努力成为最好的,你甚至不会成为好的。许多人在许多不同领域都注意到了这一点,可能值得思考为什么这是真的。可能是因为雄心是一种几乎所有错误都在一个方向上的现象——几乎所有未击中目标的炮弹都因射程不足而错过。或者可能是因为成为最好的雄心与成为好的雄心在性质上是不同的。或者也许成为好的标准太模糊了。可能三者都是真的。[11]
幸运的是,这里有一种规模经济。虽然试图成为最好的似乎会让你承担沉重的负担,但实际上你通常会最终净胜出。这令人兴奋,也奇怪地解放。它简化了事情。在某些方面,试图成为最好的比仅仅试图成为好的更容易。
We're so used to schools that we unconsciously treat going to school as identical with learning, but in fact schools have all sorts of strange qualities that warp our ideas about learning and thinking. For example, schools induce passivity. Since you were a small child, there was an authority at the front of the class telling all of you what you had to learn and then measuring whether you did. But neither classes nor tests are intrinsic to learning; they're just artifacts of the way schools are usually designed. The sooner you overcome this passivity, the better. If you're still in school, try thinking of your education as your project, and your teachers as working for you rather than vice versa. That may seem a stretch, but it's not merely some weird thought experiment. It's the truth economically, and in the best case it's the truth intellectually as well. The best teachers don't want to be your bosses. They'd prefer it if you pushed ahead, using them as a source of advice, rather than being pulled by them through the material. Schools also give you a misleading impression of what work is like. In school they tell you what the problems are, and they're almost always soluble using no more than you've been taught so far. In real life you have to figure out what the problems are, and you often don't know if they're soluble at all. But perhaps the worst thing schools do to you is train you to win by hacking the test. You can't do great work by doing that. You can't trick God. So stop looking for that kind of shortcut. The way to beat the system is to focus on problems and solutions that others have overlooked, not to skimp on the work itself. Don't think of yourself as dependent on some gatekeeper giving you a "big break." Even if this were true, the best way to get it would be to focus on doing good work rather than chasing influential people. And don't take rejection by committees to heart.
瞄准高远的一个方法是尝试制作人们在一百年后仍会关心的东西。不是因为他们的意见比你同时代的人更重要,而是因为一百年后仍然看起来好的东西更可能是真正好的。
不要试图以一种独特的风格工作。只要尽力做到最好;你无法避免以独特的方式做到这一点。
风格是在不刻意的情况下以独特的方式做事。刻意为之就是矫揉造作。
The qualities that impress admissions officers and prize committees are quite different from those required to do great work. The decisions of selection committees are only meaningful to the extent that they're part of a feedback loop, and very few are. People new to a field will often copy existing work. There's nothing inherently bad about that. There's no better way to learn how something works than by trying to reproduce it. Nor does copying necessarily make your work unoriginal. Originality is the presence of new ideas, not the absence of old ones. There's a good way to copy and a bad way. If you're going to copy something, do it openly instead of furtively, or worse still, unconsciously. This is what's meant by the famously misattributed phrase "Great artists steal." The really dangerous kind of copying, the kind that gives copying a bad name, is the kind that's done without realizing it, because you're nothing more than a train running on tracks laid down by someone else. But at the other extreme, copying can be a sign of superiority rather than subordination. [25] In many fields it's almost inevitable that your early work will be in some sense based on other people's. Projects rarely arise in a vacuum. They're usually a reaction to previous work. When you're first starting out, you don't have any previous work; if you're going to react to something, it has to be someone else's. Once you're established, you can react to your own. But while the former gets called derivative and the latter doesn't, structurally the two cases are more similar than they seem. Oddly enough, the very novelty of the most novel ideas sometimes makes them seem at first to be more derivative than they are. New discoveries often have to be conceived initially as variations of existing things, _even by their discoverers_ , because there isn't yet the conceptual vocabulary to express them. There are definitely some dangers to copying, though.
矫揉造作实际上是假装别人在做这项工作。你采用了一个令人印象深刻但虚假的角色,虽然你对这种印象深刻感到高兴,但虚假性会在工作中显现出来。[12]
成为别人的诱惑对年轻人最大。他们常常觉得自己是无名小卒。但你永远不需要担心这个问题,因为如果你从事足够雄心勃勃的项目,它会自行解决。如果你在一个雄心勃勃的项目上取得成功,你不是无名小卒;你是那个做到的人。所以只要做工作,你的身份会自行解决。
“避免矫揉造作”是一个有用的规则,但如何正面表达这个想法呢?你会怎么说应该是什么,而不是不应该是什么?最好的答案是认真。如果你是认真的,你不仅避免了矫揉造作,还避免了一整套类似的恶习。
One is that you'll tend to copy old things — things that were in their day at the frontier of knowledge, but no longer are. And when you do copy something, don't copy every feature of it. Some will make you ridiculous if you do. Don't copy the manner of an eminent 50 year old professor if you're 18, for example, or the idiom of a Renaissance poem hundreds of years later. Some of the features of things you admire are flaws they succeeded despite. Indeed, the features that are easiest to imitate are the most likely to be the flaws. This is particularly true for behavior. Some talented people are jerks, and this sometimes makes it seem to the inexperienced that being a jerk is part of being talented. It isn't; being talented is merely how they get away with it. One of the most powerful kinds of copying is to copy something from one field into another. History is so full of chance discoveries of this type that it's probably worth giving chance a hand by deliberately learning about other kinds of work. You can take ideas from quite distant fields if you let them be metaphors. Negative examples can be as inspiring as positive ones. In fact you can sometimes learn more from things done badly than from things done well; sometimes it only becomes clear what's needed when it's missing. If a lot of the best people in your field are collected in one place, it's usually a good idea to visit for a while. It will increase your ambition, and also, by showing you that these people are human, increase your self-confidence. [26] If you're earnest you'll probably get a warmer welcome than you might expect. Most people who are very good at something are happy to talk about it with anyone who's genuinely interested. If they're really good at their work, then they probably have a hobbyist's interest in it, and hobbyists always want to talk about their hobbies. It may take some effort to find the people who are really good, though.
认真的核心是智力上的诚实。我们从小被教导诚实是一种无私的美德——一种牺牲。但实际上,它也是一种力量的来源。要看到新想法,你需要对真相有异常敏锐的眼光。你试图看到比其他人迄今为止更多的真相。如果你在智力上不诚实,你怎么能对真相有敏锐的眼光呢?
避免智力上不诚实的一种方法是在相反方向上保持轻微的正压。积极愿意承认自己是错的。一旦你承认自己在某件事上错了,你就自由了。在此之前,你必须承受它。[13]
Doing great work has such prestige that in some places, particularly universities, there's a polite fiction that everyone is engaged in it. And that is far from true. People within universities can't say so openly, but the quality of the work being done in different departments varies immensely. Some departments have people doing great work; others have in the past; others never have. Seek out the best colleagues. There are a lot of projects that can't be done alone, and even if you're working on one that can be, it's good to have other people to encourage you and to bounce ideas off. Colleagues don't just affect your work, though; they also affect you. So work with people you want to become like, because you will. Quality is more important than quantity in colleagues. It's better to have one or two great ones than a building full of pretty good ones. In fact it's not merely better, but necessary, judging from history: the degree to which great work happens in clusters suggests that one's colleagues often make the difference between doing great work and not. How do you know when you have sufficiently good colleagues? In my experience, when you do, you know. Which means if you're unsure, you probably don't. But it may be possible to give a more concrete answer than that. Here's an attempt: sufficiently good colleagues offer _surprising_ insights. They can see and do things that you can't. So if you have a handful of colleagues good enough to keep you on your toes in this sense, you're probably over the threshold. Most of us can benefit from collaborating with colleagues, but some projects require people on a larger scale, and starting one of those is not for everyone. If you want to run a project like that, you'll have to become a manager, and managing well takes aptitude and interest like any other kind of work.
认真的另一个更微妙的组成部分是非正式。非正式比其语法上的负面名称所暗示的要重要得多。它不仅仅是某种东西的缺失。它意味着专注于重要的事情,而不是不重要的事情。
形式主义和矫揉造作的共同点是,除了做工作,你还试图在做的时候显得某种样子。但任何投入到你看起来如何的能量都会从做好中抽走。这就是为什么书呆子在做出伟大工作时有优势:他们在显得如何上花费很少的精力。事实上,这基本上是书呆子的定义。
书呆子有一种天真的勇气,这正是做出伟大工作所需要的。这不是学来的;这是从童年保留的。所以保持它。成为那个把东西拿出来的人,而不是那个坐在后面提出听起来复杂的批评的人。“批评很容易”是最字面的真实,而伟大工作的道路从来都不容易。
If you don't have them, there is no middle path: you must either force yourself to learn management as a second language, or avoid such projects. [27] Husband your morale. It's the basis of everything when you're working on ambitious projects. You have to nurture and protect it like a living organism. Morale starts with your view of life. You're more likely to do great work if you're an optimist, and more likely to if you think of yourself as lucky than if you think of yourself as a victim. Indeed, work can to some extent protect you from your problems. If you choose work that's pure, its very difficulties will serve as a refuge from the difficulties of everyday life. If this is escapism, it's a very productive form of it, and one that has been used by some of the greatest minds in history. Morale compounds via work: high morale helps you do good work, which increases your morale and helps you do even better work. But this cycle also operates in the other direction: if you're not doing good work, that can demoralize you and make it even harder to. Since it matters so much for this cycle to be running in the right direction, it can be a good idea to switch to easier work when you're stuck, just so you start to get something done. One of the biggest mistakes ambitious people make is to allow setbacks to destroy their morale all at once, like a balloon bursting. You can inoculate yourself against this by explicitly considering setbacks a part of your process. Solving hard problems always involves some backtracking. Doing great work is a depth-first search whose root node is the desire to. So "If at first you don't succeed, try, try again" isn't quite right. It should be: If at first you don't succeed, either try again, or backtrack and then try again. "Never give up" is also not quite right. Obviously there are times when it's the right choice to eject.
有些工作可能以愤世嫉俗和悲观为优势,但如果你想做出伟大工作,乐观是一个优势,尽管这意味着你有时会冒着看起来像傻瓜的风险。有一个古老的传统是做相反的事情。《旧约》说最好保持安静,以免看起来像傻瓜。但这是为了显得聪明的建议。如果你真的想发现新事物,最好冒险告诉人们你的想法。
有些人天生认真,而其他人则需要有意识的努力。任何一种认真都足够了。但我怀疑如果不认真,就不可能做出伟大的工作。即使你是认真的,这也非常困难。你没有足够的误差余地来容纳由矫揉造作、智力不诚实、正统、时尚或酷引入的扭曲。[14]
伟大工作不仅与做它的人一致,而且与自身一致。它通常是一个整体。所以如果你在工作中面临一个决定,问问哪个选择更一致。
A more precise version would be: Never let setbacks panic you into backtracking more than you need to. Corollary: Never abandon the root node. It's not necessarily a bad sign if work is a struggle, any more than it's a bad sign to be out of breath while running. It depends how fast you're running. So learn to distinguish good pain from bad. Good pain is a sign of effort; bad pain is a sign of damage. An audience is a critical component of morale. If you're a scholar, your audience may be your peers; in the arts, it may be an audience in the traditional sense. Either way it doesn't need to be big. The value of an audience doesn't grow anything like linearly with its size. Which is bad news if you're famous, but good news if you're just starting out, because it means a small but dedicated audience can be enough to sustain you. If a handful of people genuinely love what you're doing, that's enough. To the extent you can, avoid letting intermediaries come between you and your audience. In some types of work this is inevitable, but it's so liberating to escape it that you might be better off switching to an adjacent type if that will let you go direct. [28] The people you spend time with will also have a big effect on your morale. You'll find there are some who increase your energy and others who decrease it, and the effect someone has is not always what you'd expect. Seek out the people who increase your energy and avoid those who decrease it. Though of course if there's someone you need to take care of, that takes precedence. Don't marry someone who doesn't understand that you need to work, or sees your work as competition for your attention. If you're ambitious, you need to work; it's almost like a medical condition; so someone who won't let you work either doesn't understand you, or does and doesn't care. Ultimately morale is physical. You think with your body, so it's important to take care of it.
你可能需要扔掉东西并重做它们。你不一定需要这样做,但你必须愿意这样做。这可能需要一些努力;当有东西需要重做时,现状偏见和懒惰会结合起来让你否认它。要克服这一点,问问自己:如果我已经做了改变,我会想恢复到现在的状态吗?
有信心削减。不要保留不合适的东西,仅仅因为你为之骄傲,或者因为它花费了你很多努力。
That means exercising regularly, eating and sleeping well, and avoiding the more dangerous kinds of drugs. Running and walking are particularly good forms of exercise because they're good for thinking. [29] People who do great work are not necessarily happier than everyone else, but they're happier than they'd be if they didn't. In fact, if you're smart and ambitious, it's dangerous _not_ to be productive. People who are smart and ambitious but don't achieve much tend to become bitter. It's ok to want to impress other people, but choose the right people. The opinion of people you respect is signal. Fame, which is the opinion of a much larger group you might or might not respect, just adds noise. The prestige of a type of work is at best a trailing indicator and sometimes completely mistaken. If you do anything well enough, you'll make it prestigious. So the question to ask about a type of work is not how much prestige it has, but how well it could be done. Competition can be an effective motivator, but don't let it choose the problem for you; don't let yourself get drawn into chasing something just because others are. In fact, don't let competitors make you do anything much more specific than work harder. Curiosity is the best guide. Your curiosity never lies, and it knows more than you do about what's worth paying attention to. Notice how often that word has come up. If you asked an oracle the secret to doing great work and the oracle replied with a single word, my bet would be on "curiosity." That doesn't translate directly to advice. It's not enough just to be curious, and you can't command curiosity anyway. But you can nurture it and let it drive you. Curiosity is the key to all four steps in doing great work: it will choose the field for you, get you to the frontier, cause you to notice the gaps in it, and drive you to explore them. The whole process is a kind of dance with curiosity.
事实上,在某些类型的工作中,剥离你所做的事情的本质是好的。结果会更集中;你会更好地理解它;你无法对自己撒谎说那里是否有任何真实的东西。
数学优雅听起来可能只是一个隐喻,来自艺术。当我第一次听到“优雅”这个词用于证明时,我就是这么想的。但现在我怀疑它在概念上是优先的——艺术优雅的主要成分是数学优雅。无论如何,这是一个超越数学的有用标准。
优雅可能是一个长期的赌注。繁琐的解决方案在短期内往往更有声望。它们花费了很多努力,而且很难理解,这两点都会给人留下印象,至少是暂时的。
Believe it or not, I tried to make this essay as short as I could. But its length at least means it acts as a filter. If you made it this far, you must be interested in doing great work. And if so you're already further along than you might realize, because the set of people willing to want to is small. The factors in doing great work are factors in the literal, mathematical sense, and they are: ability, interest, effort, and luck. Luck by definition you can't do anything about, so we can ignore that. And we can assume effort, if you do in fact want to do great work. So the problem boils down to ability and interest. Can you find a kind of work where your ability and interest will combine to yield an explosion of new ideas? Here there are grounds for optimism. There are so many different ways to do great work, and even more that are still undiscovered. Out of all those different types of work, the one you're most suited for is probably a pretty close match. Probably a comically close match. It's just a question of finding it, and how far into it your ability and interest can take you. And you can only answer that by trying. Many more people could try to do great work than do. What holds them back is a combination of modesty and fear. It seems presumptuous to try to be Newton or Shakespeare. It also seems hard; surely if you tried something like that, you'd fail. Presumably the calculation is rarely explicit. Few people consciously decide not to try to do great work. But that's what's going on subconsciously; they shy away from the question. So I'm going to pull a sneaky trick on you. Do you want to do great work, or not? Now you have to decide consciously. Sorry about that. I wouldn't have done it to a general audience. But we already know you're interested. Don't worry about being presumptuous. You don't have to tell anyone. And if it's too hard and you fail, so what? Lots of people have worse problems than that.
而一些最好的工作看起来像是花费了相对较少的努力,因为在某种意义上它已经在那里了。它不需要被建造,只需要被看到。当你很难说是在创造还是在发现时,这是一个非常好的迹象。
当你做的工作可以被视为创造或发现时,偏向于发现。试着把自己看作仅仅是想法自然形成的渠道。
(奇怪的是,一个例外是选择要解决的问题。这通常被视为搜索,但在最好的情况下,它更像是创造。在最好的情况下,你在探索的过程中创造了这个领域。)
In fact you'll be lucky if it's the worst problem you have. Yes, you'll have to work hard. But again, lots of people have to work hard. And if you're working on something you find very interesting, which you necessarily will if you're on the right path, the work will probably feel less burdensome than a lot of your peers'. The discoveries are out there, waiting to be made. Why not by you? Notes [1] I don't think you could give a precise definition of what counts as great work. Doing great work means doing something important so well that you expand people's ideas of what's possible. But there's no threshold for importance. It's a matter of degree, and often hard to judge at the time anyway. So I'd rather people focused on developing their interests rather than worrying about whether they're important or not. Just try to do something amazing, and leave it to future generations to say if you succeeded. [2] A lot of standup comedy is based on noticing anomalies in everyday life. "Did you ever notice...?" New ideas come from doing this about nontrivial things. Which may help explain why people's reaction to a new idea is often the first half of laughing: Ha! [3] That second qualifier is critical. If you're excited about something most authorities discount, but you can't give a more precise explanation than "they don't get it," then you're starting to drift into the territory of cranks. [4] Finding something to work on is not simply a matter of finding a match between the current version of you and a list of known problems. You'll often have to coevolve with the problem. That's why it can sometimes be so hard to figure out what to work on. The search space is huge. It's the cartesian product of all possible types of work, both known and yet to be discovered, and all possible future versions of you.
同样,如果你试图构建一个强大的工具,让它无限制地自由。一个强大的工具几乎从定义上就会被以你意想不到的方式使用,所以偏向于消除限制,即使你不知道好处会是什么。
伟大工作往往是工具性的,因为其他人可以在此基础上构建。所以如果你创造的想法别人可以使用,或者暴露的问题别人可以回答,这是一个好迹象。最好的想法在许多不同领域都有影响。
There's no way you could search this whole space, so you have to rely on heuristics to generate promising paths through it and hope the best matches will be clustered. Which they will not always be; different types of work have been collected together as much by accidents of history as by the intrinsic similarities between them. [5] There are many reasons curious people are more likely to do great work, but one of the more subtle is that, by casting a wide net, they're more likely to find the right thing to work on in the first place. [6] It can also be dangerous to make things for an audience you feel is less sophisticated than you, if that causes you to talk down to them. You can make a lot of money doing that, if you do it in a sufficiently cynical way, but it's not the route to great work. Not that anyone using this m.o. would care. [7] This idea I learned from Hardy's _A Mathematician's Apology_ , which I recommend to anyone ambitious to do great work, in any field. [8] Just as we overestimate what we can do in a day and underestimate what we can do over several years, we overestimate the damage done by procrastinating for a day and underestimate the damage done by procrastinating for several years. [9] You can't usually get paid for doing exactly what you want, especially early on. There are two options: get paid for doing work close to what you want and hope to push it closer, or get paid for doing something else entirely and do your own projects on the side. Both can work, but both have drawbacks: in the first approach your work is compromised by default, and in the second you have to fight to get time to do it. [10] If you set your life up right, it will deliver the focus-relax cycle automatically. The perfect setup is an office you work in and that you walk to and from. [11] There may be some very unworldly people who do great work without consciously trying to.
如果你以最普遍的形式表达你的想法,它们会比你预期的更真实。
当然,真实本身是不够的。伟大的想法必须既真实又新颖。即使你已经学到了足够到达知识的前沿,也需要一定的能力才能看到新想法。
在英语中,我们给这种能力命名为原创性、创造力和想象力。给它一个单独的名字似乎是合理的,因为它在一定程度上似乎是一种独立的技能。在其他方面拥有大量能力——通常被称为技术能力——而没有太多这种能力是可能的。
If you want to expand this rule to cover that case, it becomes: Don't try to be anything except the best. [12] This gets more complicated in work like acting, where the goal is to adopt a fake persona. But even here it's possible to be affected. Perhaps the rule in such fields should be to avoid _unintentional_ affectation. [13] It's safe to have beliefs that you treat as unquestionable if and only if they're also unfalsifiable. For example, it's safe to have the principle that everyone should be treated equally under the law, because a sentence with a "should" in it isn't really a statement about the world and is therefore hard to disprove. And if there's no evidence that could disprove one of your principles, there can't be any facts you'd need to ignore in order to preserve it. [14] Affectation is easier to cure than intellectual dishonesty. Affectation is often a shortcoming of the young that burns off in time, while intellectual dishonesty is more of a character flaw. [15] Obviously you don't have to be working at the exact moment you have the idea, but you'll probably have been working fairly recently. [16] Some say psychoactive drugs have a similar effect. I'm skeptical, but also almost totally ignorant of their effects. [17] For example you might give the nth most important topic (m-1)/m^n of your attention, for some m > 1\. You couldn't allocate your attention so precisely, of course, but this at least gives an idea of a reasonable distribution. [18] The principles defining a religion have to be mistaken. Otherwise anyone might adopt them, and there would be nothing to distinguish the adherents of the religion from everyone else. [19] It might be a good exercise to try writing down a list of questions you wondered about in your youth.
我从来不喜欢“创造性过程”这个词。它似乎有误导性。原创性不是一个过程,而是一种思维习惯。原创思想家对他们关注的任何事情都会抛出新想法,就像角磨机抛出火花一样。他们无法控制。
[21] 源自莱纳斯·鲍林的名言:"若想获得好主意,必须先拥有大量主意。"
[22] 将某个项目贬为"玩具",与指责某句话"不合时宜"如出一辙——这往往意味着无法提出更具实质性的批评。
You might find you're now in a position to do something about some of them. [20] The connection between originality and uncertainty causes a strange phenomenon: because the conventional-minded are more certain than the independent-minded, this tends to give them the upper hand in disputes, even though they're generally stupider. > The best lack all conviction, while the worst > Are full of passionate intensity..
[23] 判断是否虚度光阴的方法很简单:自问是在创造还是消费。编写电子游戏比沉迷游戏更有价值,而在能创造内容的游戏中消遣,又比纯粹消耗性游戏更有意义。
[24] 另一个相关优势是:若你从未公开表态,就不会被支撑先前结论的证据所束缚。理论上保持绝对诚实能让人在这方面永葆青春,但鲜有人能做到。对多数人而言,已发表的见解会像意识形态般产生桎梏,只是程度较轻。
[21] Derived from Linus Pauling's "If you want to have good ideas, you must have many ideas." [22] Attacking a project as a "toy" is similar to attacking a statement as "inappropriate." It means that no more substantial criticism can be made to stick. [23] One way to tell whether you're wasting time is to ask if you're producing or consuming. Writing computer games is less likely to be a waste of time than playing them, and playing games where you create something is less likely to be a waste of time than playing games where you don't. [24] Another related advantage is that if you haven't said anything publicly yet, you won't be biased toward evidence that supports your earlier conclusions. With sufficient integrity you could achieve eternal youth in this respect, but few manage to. For most people, having previously published opinions has an effect similar to ideology, just in quantity 1. [25] In the early 1630s Daniel Mytens made a painting of Henrietta Maria handing a laurel wreath to Charles I. Van Dyck then painted his own version to show how much better he was. [26] I'm being deliberately vague about what a place is. As of this writing, being in the same physical place has advantages that are hard to duplicate, but that could change. [27] This is false when the work the other people have to do is very constrained, as with SETI@home or Bitcoin. It may be possible to expand the area in which it's false by defining similarly restricted protocols with more freedom of action in the nodes. [28] Corollary: Building something that enables people to go around intermediaries and engage directly with their audience is probably a good idea. [29] It may be helpful always to walk or run the same route, because that frees attention for thinking.
[25] 1630年代初,丹尼尔·米滕斯绘制了亨利埃塔·玛丽亚向查理一世献上月桂花环的画作。随后范·戴克重绘此场景,只为彰显自己技高一筹。
[26] 我刻意模糊了"场所"的定义。就目前而言,实体共处仍具难以复制的优势,但未来可能改变。
[27] 当他人承担的工作高度受限时(如SETI@home或比特币项目),这个论断并不成立。或许可以通过设计节点自由度更高的限定协议来拓展例外领域。
It feels that way to me, and there is some historical evidence for it. Thanks to Trevor Blackwell, Daniel Gackle, Pam Graham, Tom Howard, Patrick Hsu, Steve Huffman, Jessica Livingston, Henry Lloyd-Baker, Bob Metcalfe, Ben Miller, Robert Morris, Michael Nielsen, Courtenay Pipkin, Joris Poort, Mieke Roos, Rajat Suri, Harj Taggar, Garry Tan, and my younger son for suggestions and for reading drafts..
[28] 推论:创建能让人绕过中间环节、直接触达受众的工具,往往是个好主意。
[29] 坚持固定路线散步或跑步或许有益,这样能解放注意力用于思考。我个人深有体会,历史上也不乏佐证。
致谢 感谢特雷弗·布莱克韦尔、丹尼尔·加克尔、帕姆·格雷厄姆、汤姆·霍华德、帕特里克·徐、史蒂夫·霍夫曼、杰西卡·利文斯顿、亨利·劳埃德-贝克、鲍勃·梅特卡夫、本·米勒、罗伯特·莫里斯、迈克尔·尼尔森、考特尼·皮普金、乔里斯·波特、米克·鲁斯、拉贾特·苏里、哈吉·塔加尔、加里·谭,以及我的幼子提供的建议和文稿审阅。
January 2023 _( _Someone_ fed my essays into GPT to make something that could answer questions based on them, then asked it where good ideas come from. The answer was ok, but not what I would have said. This is what I would have said.)_ The way to get new ideas is to notice anomalies: what seems strange, or missing, or broken? You can see anomalies in everyday life (much of standup comedy is based on this), but the best place to look for them is at the frontiers of knowledge. Knowledge grows fractally. From a distance its edges look smooth, but when you learn enough to get close to one, you'll notice it's full of gaps. These gaps will seem obvious; it will seem inexplicable that no one has tried x or wondered about y. In the best case, exploring such gaps yields whole new fractal buds.
_(某人将我的文章输入GPT,生成能基于这些内容回答问题的程序,然后询问它好点子的来源。答案尚可,但并非我的观点。以下才是我的回答。)_
获得新想法的方法是留意异常:什么看起来奇怪、缺失或有问题?你可以在日常生活中发现异常(许多单口喜剧正是基于此),但寻找它们的最佳地点是知识的边缘。
知识以分形的方式生长。从远处看,其边缘显得平滑,但当你学得足够多、足够接近时,会发现它充满缺口。这些缺口会显得显而易见;似乎难以理解为何没人尝试过x或思考过y。在最好的情况下,探索这些缺口会催生出全新的分形萌芽。
November 2022 Since I was about 9 I've been puzzled by the apparent contradiction between being made of matter that behaves in a predictable way, and the feeling that I could choose to do whatever I wanted. At the time I had a self-interested motive for exploring the question. At that age (like most succeeding ages) I was always in trouble with the authorities, and it seemed to me that there might possibly be some way to get out of trouble by arguing that I wasn't responsible for my actions. I gradually lost hope of that, but the puzzle remained: How do you reconcile being a machine made of matter with the feeling that you're free to choose what you do? [1] The best way to explain the answer may be to start with a slightly wrong version, and then fix it. The wrong version is: You can do what you want, but you can't want what you want. Yes, you can control what you do, but you'll do what you want, and you can't control that. The reason this is mistaken is that people do sometimes change what they want. People who don't want to want something — drug addicts, for example — can sometimes make themselves stop wanting it. And people who want to want something — who want to like classical music, or broccoli — sometimes succeed. So we modify our initial statement: You can do what you want, but you can't want to want what you want. That's still not quite true. It's possible to change what you want to want. I can imagine someone saying "I decided to stop wanting to like classical music." But we're getting closer to the truth. It's rare for people to change what they want to want, and the more "want to"s we add, the rarer it gets. We can get arbitrarily close to a true statement by adding more "want to"s in much the same way we can get arbitrarily close to 1 by adding more 9s to a string of 9s following a decimal point. In practice three or four "want to"s must surely be enough.
自从九岁起,我就被一个看似矛盾的问题困扰:一方面我由行为可预测的物质构成,另一方面却感觉自己能自由选择行动。当时探究这个问题带着利己动机——那个年纪(以及之后多数时期)我总是惹上权威人士的麻烦,似乎有可能通过"我对自己的行为不负责任"的论点脱身。虽然这种希望逐渐破灭,但谜题始终存在:如何将"作为物质构成的机器"与"感觉能自由选择行为"这两者统一起来?[1]
解释答案的最佳方式或许是从一个略有偏差的版本开始,再予以修正。有偏差的版本是:你能做想做的事,但不能想要想要的东西。没错,你能控制行为,但行为由欲望驱动,而欲望不受你控制。
这个说法的谬误在于,人们确实有时会改变自己的欲望。不想渴望某物的人——比如瘾君子——有时能成功戒除渴望;而想要渴望某物的人——比如想爱上古典音乐或西兰花的人——偶尔也能如愿。
于是我们修正初始陈述:你能做想做的事,但不能想要去想要想要的东西。
这仍不完全正确。改变"想要去想要"的欲望是可能的。我能想象有人说"我决定不再强迫自己喜欢古典音乐"。但我们正逼近真相。人们极少改变"想要去想要"的欲望,叠加的"想要"层级越多,改变就越罕见。
It's hard even to envision what it would mean to change what you want to want to want to want, let alone actually do it. So one way to express the correct answer is to use a regular expression. You can do what you want, but there's some statement of the form "you can't (want to)* want what you want" that's true. Ultimately you get back to a want that you don't control. [2] Notes [1] I didn't know when I was 9 that matter might behave randomly, but I don't think it affects the problem much. Randomness destroys the ghost in the machine as effectively as determinism. [2] If you don't like using an expression, you can make the same point using higher-order desires: There is some n such that you don't control your nth-order desires. Thanks to Trevor Blackwell, Jessica Livingston, Robert Morris, and Michael Nielsen for reading drafts of this.
就像在小数点后添加更多9能使数值无限趋近于1,我们通过叠加更多"想要"也能无限逼近真理。实践中三四层"想要"必然足够——即便想象"改变想要想要想要想要的东西"意味着什么都困难,遑论真正实施。
因此,用正则表达式能准确表述答案:你能做想做的事,但存在某个形如"你不能(想要)*想要想要的东西"的真实陈述。最终你会回归到某个不受控制的根本欲望。[2]
[1] 九岁时我不知道物质可能随机运动,但这不影响问题核心。随机性与确定性同样有效地摧毁了"机器中的幽灵"。
[2] 若不喜欢表达式,可用高阶欲望表述相同观点:存在某个n,使得你无法控制第n阶欲望。
致谢 感谢Trevor Blackwell、Jessica Livingston、Robert Morris和Michael Nielsen阅读本文草稿。
November 2022 In the science fiction books I read as a kid, reading had often been replaced by some more efficient way of acquiring knowledge. Mysterious "tapes" would load it into one's brain like a program being loaded into a computer. That sort of thing is unlikely to happen anytime soon. Not just because it would be hard to build a replacement for reading, but because even if one existed, it would be insufficient. Reading about x doesn't just teach you about x; it also teaches you how to write. [1] Would that matter? If we replaced reading, would anyone need to be good at writing? The reason it would matter is that writing is not just a way to convey ideas, but also a way to have them. A good writer doesn't just think, and then write down what he thought, as a sort of transcript. A good writer will almost always discover new things in the process of writing. And there is, as far as I know, no substitute for this kind of discovery. Talking about your ideas with other people is a good way to develop them. But even after doing this, you'll find you still discover new things when you sit down to write. There is a kind of thinking that can only be done by _writing_. There are of course kinds of thinking that can be done without writing. If you don't need to go too deeply into a problem, you can solve it without writing. If you're thinking about how two pieces of machinery should fit together, writing about it probably won't help much. And when a problem can be described formally, you can sometimes solve it in your head. But if you need to solve a complicated, ill-defined problem, it will almost always help to write about it. Which in turn means that someone who's not good at writing will almost always be at a disadvantage in solving such problems. You can't think well without writing well, and you can't write well without reading well. And I mean that last "well" in both senses.
在我小时候读的科幻小说里,阅读常常被某种更高效的知识获取方式取代。神秘的"磁带"会将知识载入大脑,就像程序被载入计算机那样。
这种事短期内不太可能发生。不仅因为构建阅读的替代品很困难,更因为即使存在这样的替代品,它也是不够的。阅读关于x的内容不仅教会你x的知识,还教会你如何写作。[1]
这重要吗?如果我们取代了阅读,还有人需要擅长写作吗?
之所以重要,是因为写作不仅是传递想法的方式,更是产生想法的方式。
优秀的作家不只是思考,然后把想法像抄本一样写下来。优秀的作家几乎总会在写作过程中发现新事物。据我所知,这种发现过程无可替代。与他人讨论想法是完善它们的好方法。但即便如此,当你坐下来写作时,仍会发现新的东西。有些思考只能通过_写作_来完成。
当然也存在不需要写作的思考方式。如果不需要深入探究问题,你可以不借助写作就解决它。如果你在思考两个机械部件如何装配,写作可能帮助不大。当问题能被形式化描述时,有时你可以在脑中解决它。但若要解决复杂、定义模糊的问题,写作几乎总能提供帮助。这意味着不擅长写作的人在解决这类问题时几乎总是处于劣势。
You have to be good at reading, and read good things. [2] People who just want information may find other ways to get it. But people who want to have ideas can't afford to. Notes [1] Audiobooks can give you examples of good writing, but having them read to you doesn't teach you as much about writing as reading them yourself. [2] By "good at reading" I don't mean good at the mechanics of reading. You don't have to be good at extracting words from the page so much as extracting meaning from the words.
Japanese Translation | Chinese Translation Italian Translation | French Translation.
October 2022 If there were intelligent beings elsewhere in the universe, they'd share certain truths in common with us. The truths of mathematics would be the same, because they're true by definition. Ditto for the truths of physics; the mass of a carbon atom would be the same on their planet. But I think we'd share other truths with aliens besides the truths of math and physics, and that it would be worthwhile to think about what these might be. For example, I think we'd share the principle that a controlled experiment testing some hypothesis entitles us to have proportionally increased belief in it. It seems fairly likely, too, that it would be true for aliens that one can get better at something by practicing. We'd probably share Occam's razor. There doesn't seem anything specifically human about any of these ideas. We can only guess, of course. We can't say for sure what forms intelligent life might take. Nor is it my goal here to explore that question, interesting though it is. The point of the idea of alien truth is not that it gives us a way to speculate about what forms intelligent life might take, but that it gives us a threshold, or more precisely a target, for truth. If you're trying to find the most general truths short of those of math or physics, then presumably they'll be those we'd share in common with other forms of intelligent life. Alien truth will work best as a heuristic if we err on the side of generosity. If an idea might plausibly be relevant to aliens, that's enough. Justice, for example. I wouldn't want to bet that all intelligent beings would understand the concept of justice, but I wouldn't want to bet against it either. The idea of alien truth is related to Erdos's idea of God's book. He used to describe a particularly good proof as being in God's book, the implication being (a) that a sufficiently good proof was more discovered than invented, and (b) that its goodness would be universally recognized.
If there's such a thing as alien truth, then there's more in God's book than math. What should we call the search for alien truth? The obvious choice is "philosophy." Whatever else philosophy includes, it should probably include this. I'm fairly sure Aristotle would have thought so. One could even make the case that the search for alien truth is, if not an accurate description _of_ philosophy, a good definition _for_ it. I.e. that it's what people who call themselves philosophers should be doing, whether or not they currently are. But I'm not wedded to that; doing it is what matters, not what we call it. We may one day have something like alien life among us in the form of AIs. And that may in turn allow us to be precise about what truths an intelligent being would have to share with us. We might find, for example, that it's impossible to create something we'd consider intelligent that doesn't use Occam's razor. We might one day even be able to prove that. But though this sort of research would be very interesting, it's not necessary for our purposes, or even the same field; the goal of philosophy, if we're going to call it that, would be to see what ideas we come up with using alien truth as a target, not to say precisely where the threshold of it is. Those two questions might one day converge, but they'll converge from quite different directions, and till they do, it would be too constraining to restrict ourselves to thinking only about things we're certain would be alien truths. Especially since this will probably be one of those areas where the best guesses turn out to be surprisingly close to optimal. (Let's see if that one does.) Whatever we call it, the attempt to discover alien truths would be a worthwhile undertaking. And curiously enough, that is itself probably an alien truth. Thanks to Trevor Blackwell, Greg Brockman, Patrick Collison, Robert Morris, and Michael Nielsen for reading drafts of this..
2022年10月 倘若宇宙他处存在智慧生命,他们必定与我们共享某些真理。数学真理自不待言,因其本质即为真。物理真理亦然,碳原子的质量在他们星球上也不会改变。但我认为,除了数学与物理之外,我们与外星生命还将共享其他真理,而思考这些真理将大有裨益。 例如,我们都认同这一原则:若某项受控实验验证了某个假设,我们对该假设的置信度就应相应提升。勤能补拙这一道理,想必对外星生命同样适用。奥卡姆剃刀原则或许也是共通的。这些理念似乎都不专属于人类。 当然,我们只能猜测。我们无法断言智慧生命会以何种形态存在。尽管这个问题很有趣,但此刻我的目标并非探讨它。"外星真理"这一概念的意义,不在于让我们推测智慧生命可能的形式,而在于为我们提供一种衡量真理的标尺——更准确地说,是一个靶心。若你想寻找除数学和物理外最具普适性的真理,它们很可能正是我们与其他智慧生命共有的那些。 若我们以包容的态度看待"外星真理",这一启发式思维将最为有效。只要某个理念可能适用于外星生命,便已足够。以"正义"为例:我不敢断言所有智慧生命都理解正义概念,但同样不愿断言他们无法理解。 "外星真理"与埃尔德什的"天书"概念异曲同工。他常将精妙的证明称为"天书所载",其隐含之意在于:(a)真正卓越的证明更像是被发现而非发明;(b)其卓越性将获普遍认可。若"外星真理"存在,那么天书中的内容就远不止数学。 我们该如何称呼对"外星真理"的追寻?最直白的答案当属"哲学"。无论哲学还包含什么,它理应涵盖这一探索。我确信亚里士多德也会赞同。甚至可以说,对"外星真理"的追寻即便不能准确描述哲学的全部,至少为其提供了绝佳的定义——即自称为哲学家者应致力的方向,无论他们当下是否如此实践。不过名称并非关键,付诸实践才最重要。 或许某天,人工智能将成为我们身边的"外星生命"。届时我们或能精确界定智慧生命必须与我们共享哪些真理。例如,我们或许会发现,若不运用奥卡姆剃刀原则,就不可能创造出我们认可的智能体。甚至某天我们能对此加以证明。尽管这类研究极富趣味,但它既非我们此刻的目标,亦非同一领域——如果我们仍称之为哲学,其目标应是以"外星真理"为靶心进行思考,而非精确划定其边界。这两个问题或将在某日交汇,但它们的出发点截然不同。在交汇之前,若仅思考我们确信的"外星真理",未免过于局限。更何况在此领域,最佳猜想往往出人意料地接近终极答案。(让我们拭目以待这一猜想是否成立。) 无论冠以何名,探索"外星真理"都值得为之。耐人寻味的是,这个论断本身或许正是条"外星真理"。 致谢 感谢Trevor Blackwell、Greg Brockman、Patrick Collison、Robert Morris和Michael Nielsen审阅本文草稿。
September 2022 I recently told applicants to Y Combinator that the best advice I could give for getting in, per word, was > Explain what you've learned from users.
我最近告诉Y Combinator的申请者,就每个字而言,我能给出的最佳建议是:
> 说明你从用户那里学到了什么。
这检验了许多方面:你是否在关注用户、你对他们理解得有多深入,甚至他们对你所创造的产品需求有多大。
That tests a lot of things: whether you're paying attention to users, how well you understand them, and even how much they need what you're making. Afterward I asked myself the same question. What have I learned from YC's users, the startups we've funded? The first thing that came to mind was that most startups have the same problems. No two have exactly the same problems, but it's surprising how much the problems remain the same, regardless of what they're making. Once you've advised 100 startups all doing different things, you rarely encounter problems you haven't seen before. This fact is one of the things that makes YC work. But I didn't know it when we started YC. I only had a few data points: our own startup, and those started by friends. It was a surprise to me how often the same problems recur in different forms. Many later stage investors might never realize this, because later stage investors might not advise 100 startups in their whole career, but a YC partner will get this much experience in the first year or two. That's one advantage of funding large numbers of early stage companies rather than smaller numbers of later-stage ones. You get a lot of data. Not just because you're looking at more companies, but also because more goes wrong. But knowing (nearly) all the problems startups can encounter doesn't mean that advising them can be automated, or reduced to a formula. There's no substitute for individual office hours with a YC partner. Each startup is unique, which means they have to be advised by specific partners who know them well. [1] We learned that the hard way, in the notorious "batch that broke YC" in the summer of 2012. Up till that point we treated the partners as a pool. When a startup requested office hours, they got the next available slot posted by any partner. That meant every partner had to know every startup. This worked fine up to 60 startups, but when the batch grew to 80, everything broke.
之后我也问了自己同样的问题。我从YC的用户——我们投资的初创公司——身上学到了什么?
首先浮现在脑海的是,大多数初创公司面临的问题都是相似的。虽然没有任何两家公司的问题完全相同,但令人惊讶的是,无论他们在做什么,问题的本质往往如出一辙。当你为100家从事不同领域的初创公司提供建议后,很少会遇到从未见过的新问题。
这一事实正是YC得以运作的原因之一。但在创办YC之初,我并未意识到这一点。当时我只有少量数据点:我们自己的初创公司,以及朋友们创办的公司。令我惊讶的是,相同的问题会以不同形式反复出现。许多后期阶段的投资者可能永远无法察觉这一点,因为他们整个职业生涯或许都接触不到100家初创公司,而YC合伙人只需一两年就能积累同等经验。
投资大量早期公司而非少量后期公司的一个优势在于:你能获得海量数据。这不仅因为接触的公司数量更多,更因为早期阶段更容易暴露问题。
The founders probably didn't realize anything was wrong, but the partners were confused and unhappy because halfway through the batch they still didn't know all the companies yet. [2] At first I was puzzled. How could things be fine at 60 startups and broken at 80? It was only a third more. Then I realized what had happened. We were using an _O(n 2)_ algorithm. So of course it blew up. The solution we adopted was the classic one in these situations. We sharded the batch into smaller groups of startups, each overseen by a dedicated group of partners. That fixed the problem, and has worked fine ever since. But the batch that broke YC was a powerful demonstration of how individualized the process of advising startups has to be. Another related surprise is how bad founders can be at realizing what their problems are. Founders will sometimes come in to talk about some problem, and we'll discover another much bigger one in the course of the conversation. For example (and this case is all too common), founders will come in to talk about the difficulties they're having raising money, and after digging into their situation, it turns out the reason is that the company is doing badly, and investors can tell. Or founders will come in worried that they still haven't cracked the problem of user acquisition, and the reason turns out to be that their product isn't good enough. There have been times when I've asked "Would you use this yourself, if you hadn't built it?" and the founders, on thinking about it, said "No." Well, there's the reason you're having trouble getting users. Often founders know what their problems are, but not their relative importance. [3] They'll come in to talk about three problems they're worrying about. One is of moderate importance, one doesn't matter at all, and one will kill the company if it isn't addressed immediately.
但了解(几乎)所有初创公司可能遇到的问题,并不意味着提供建议可以自动化或简化为固定公式。与YC合伙人一对一的办公时间无可替代。每家初创公司都是独特的,这意味着必须由熟悉他们的特定合伙人提供指导。[1]
我们在2012年夏天那批"搞垮YC"的著名项目中深刻领悟了这一点。此前我们将合伙人视为统一资源池——当初创公司申请办公时间时,他们会被分配给任何一位有空档的合伙人。这意味着每位合伙人都需要了解所有公司。这套机制在60家公司规模时运作良好,但当批次增长到80家时,系统彻底崩溃。创始人可能并未察觉异常,但合伙人却陷入混乱与沮丧,因为项目过半时他们仍未能认全所有公司。[2]
起初我困惑不解:为何60家时运转正常,80家时就崩溃?这不过增加了三分之一。随后我意识到问题所在——我们使用的是O(n²)复杂度的算法,崩溃自然不可避免。
我们采用的解决方案是此类情境下的经典方法:将批次拆分为更小的小组,每组由固定合伙人团队负责。这解决了问题并沿用至今。但"搞垮YC"的那批项目有力证明了初创公司指导必须高度个性化。
It's like watching one of those horror movies where the heroine is deeply upset that her boyfriend cheated on her, and only mildly curious about the door that's mysteriously ajar. You want to say: never mind about your boyfriend, think about that door! Fortunately in office hours you can. So while startups still die with some regularity, it's rarely because they wandered into a room containing a murderer. The YC partners can warn them where the murderers are. Not that founders listen. That was another big surprise: how often founders don't listen to us. A couple weeks ago I talked to a partner who had been working for YC for a couple batches and was starting to see the pattern. "They come back a year later," she said, "and say 'We wish we'd listened to you.'" It took me a long time to figure out why founders don't listen. At first I thought it was mere stubbornness. That's part of the reason, but another and probably more important reason is that so much about startups is counterintuitive. And when you tell someone something counterintuitive, what it sounds to them is wrong. So the reason founders don't listen to us is that they don't _believe_ us. At least not till experience teaches them otherwise. [4] The reason startups are so counterintuitive is that they're so different from most people's other experiences. No one knows what it's like except those who've done it. Which is why YC partners should usually have been founders themselves. But strangely enough, the counterintuitiveness of startups turns out to be another of the things that make YC work. If it weren't counterintuitive, founders wouldn't need our advice about how to do it. Focus is doubly important for early stage startups, because not only do they have a hundred different problems, they don't have anyone to work on them except the founders. If the founders focus on things that don't matter, there's no one focusing on the things that do.
另一个相关发现是:创始人往往难以准确识别自身问题。他们有时会带着某个问题来讨论,而我们却在对话中发现更严重的隐患。例如(这种情况极其常见),创始人可能为融资困难前来咨询,深入分析后却发现根本原因是公司表现不佳,而投资者早已察觉;或是创始人忧心用户增长乏力,实则问题出在产品不够出色。有几次当我问"如果这不是你们做的产品,你们自己会使用吗?",创始人沉思后回答"不会"——这就是用户获取困难的根源所在。
更多时候创始人清楚问题所在,却难以判断优先级。[3]他们会带着三个担忧的问题前来:一个中等重要,一个无关紧要,另一个若不立即解决就会让公司猝死。这就像恐怖片里女主角为男友出轨痛不欲生,却对神秘半开的门漠不关心。你忍不住想说:别管男友了,看看那扇门!幸运的是在办公时间里我们确实可以这样提醒。因此虽然初创公司仍会定期消亡,但很少是因为误入有杀人狂的房间——YC合伙人会提前警告危险区域。
并非创始人都会听从建议。这是另一个重大发现:创始人经常忽视我们的建议。几周前我与一位工作过几个批次的合伙人交谈,她开始注意到这种模式:"一年后他们回来时说'真希望当初听了你们的话'。"
我花了很长时间才明白创始人为何不听劝告。最初以为只是固执使然,这确实是部分原因,但更重要的可能是初创公司的反直觉特性。当告诉别人反直觉的事情时,他们听来就像是错误的。所以创始人不听从建议的根本原因是不相信我们——至少直到现实教训他们为止。[4]
So the essence of what happens at YC is to figure out which problems matter most, then cook up ideas for solving them — ideally at a resolution of a week or less — and then try those ideas and measure how well they worked. The focus is on action, with measurable, near-term results. This doesn't imply that founders should rush forward regardless of the consequences. If you correct course at a high enough frequency, you can be simultaneously decisive at a micro scale and tentative at a macro scale. The result is a somewhat winding path, but executed very rapidly, like the path a running back takes downfield. And in practice there's less backtracking than you might expect. Founders usually guess right about which direction to run in, especially if they have someone experienced like a YC partner to bounce their hypotheses off. And when they guess wrong, they notice fast, because they'll talk about the results at office hours the next week. [5] A small improvement in navigational ability can make you a lot faster, because it has a double effect: the path is shorter, and you can travel faster along it when you're more certain it's the right one. That's where a lot of YC's value lies, in helping founders get an extra increment of focus that lets them move faster. And since moving fast is the essence of a startup, YC in effect makes startups more startup-like. Speed defines startups. Focus enables speed. YC improves focus. Why are founders uncertain about what to do? Partly because startups almost by definition are doing something new, which means no one knows how to do it yet, or in most cases even what "it" is. Partly because startups are so counterintuitive generally. And partly because many founders, especially young and ambitious ones, have been trained to win the wrong way. That took me years to figure out.
初创公司如此反直觉,是因为它们与多数人的日常经验截然不同。只有亲历者才真正理解其中滋味,这就是YC合伙人通常需要曾是创始人的原因。但吊诡的是,这种反直觉特性恰恰成为YC运作的又一基石——若非如此,创始人根本不需要我们关于"如何做"的建议。
专注力对早期初创公司尤为重要,因为他们不仅面临成百上千的问题,且除创始人外无人分担。若创始人聚焦于无关紧要之事,关键问题就会无人问津。因此YC的核心工作就是识别最关键问题,构思解决方案(理想周期控制在一周内),测试方案并评估效果。整个过程强调行动导向,追求可衡量的短期成果。
这并不意味着创始人应该不计后果地冒进。若能保持足够高的纠偏频率,就能在微观层面果断决策,同时在宏观层面保持灵活。最终形成的路径虽有些曲折,但执行速度极快,就像跑卫在球场上的冲刺路线。实践中回溯修正的次数往往比预期更少——创始人通常能猜对奔跑方向,尤其当有YC合伙人这样的经验者验证其假设时。即便猜错,他们也会通过下周的办公时间快速察觉。[5]
The educational system in most countries trains you to win by hacking the test instead of actually doing whatever it's supposed to measure. But that stops working when you start a startup. So part of what YC does is to retrain founders to stop trying to hack the test. (It takes a surprisingly long time. A year in, you still see them reverting to their old habits.) YC is not simply more experienced founders passing on their knowledge. It's more like specialization than apprenticeship. The knowledge of the YC partners and the founders have different shapes: It wouldn't be worthwhile for a founder to acquire the encyclopedic knowledge of startup problems that a YC partner has, just as it wouldn't be worthwhile for a YC partner to acquire the depth of domain knowledge that a founder has. That's why it can still be valuable for an experienced founder to do YC, just as it can still be valuable for an experienced athlete to have a coach. The other big thing YC gives founders is colleagues, and this may be even more important than the advice of partners. If you look at history, great work clusters around certain places and institutions: Florence in the late 15th century, the University of G�ttingen in the late 19th, _The New Yorker_ under Ross, Bell Labs, Xerox PARC. However good you are, good colleagues make you better. Indeed, very ambitious people probably need colleagues more than anyone else, because they're so starved for them in everyday life. Whether or not YC manages one day to be listed alongside those famous clusters, it won't be for lack of trying. We were very aware of this historical phenomenon and deliberately designed YC to be one. By this point it's not bragging to say that it's the biggest cluster of great startup founders. Even people trying to attack YC concede that. Colleagues and startup founders are two of the most powerful forces in the world, so you'd expect it to have a big effect to combine them.
导航能力的微小提升能带来显著加速,因其具有双重效应:路径更短,且当确信方向正确时行进更快。这正是YC的重要价值所在——帮助创始人获得额外的专注增量从而加速前进。而快速行动恰是初创公司的本质,因此YC实质上让初创公司更具"初创性"。
速度定义初创公司,专注成就速度,YC优化专注。
为何创始人会犹豫不决?部分因为初创公司本质上就在探索未知领域,意味着无人知晓正确方法,甚至多数情况下连"它"是什么都尚未明确;部分因为初创公司整体就充满反直觉;还有部分原因是许多创始人(尤其是年轻有为者)被培养成了"应试高手"。我花了数年才明白:多数国家的教育体系训练人们通过应试技巧获胜,而非真正掌握考核内容。但创立公司时这套方法彻底失效。因此YC的部分工作就是重塑创始人的思维模式,戒除应试心态(这个过程长得出奇——一年后仍能看到旧习惯复萌)。
YC不只是经验丰富的创始人传递知识,更像专业分工而非师徒制。YC合伙人与创始人的知识结构截然不同:创始人无需掌握合伙人百科全书式的初创问题库,正如合伙人不必具备创始人般的领域深度。这就是为何即便经验丰富的创始人参加YC仍有价值,就像顶尖运动员仍需教练一样。
Before YC, to the extent people thought about the question at all, most assumed they couldn't be combined — that loneliness was the price of independence. That was how it felt to us when we started our own startup in Boston in the 1990s. We had a handful of older people we could go to for advice (of varying quality), but no peers. There was no one we could commiserate with about the misbehavior of investors, or speculate with about the future of technology. I often tell founders to make something they themselves want, and YC is certainly that: it was designed to be exactly what we wanted when we were starting a startup. One thing we wanted was to be able to get seed funding without having to make the rounds of random rich people. That has become a commodity now, at least in the US. But great colleagues can never become a commodity, because the fact that they cluster in some places means they're proportionally absent from the rest. Something magical happens where they do cluster though. The energy in the room at a YC dinner is like nothing else I've experienced. We would have been happy just to have one or two other startups to talk to. When you have a whole roomful it's another thing entirely. YC founders aren't just inspired by one another. They also help one another. That's the happiest thing I've learned about startup founders: how generous they can be in helping one another. We noticed this in the first batch and consciously designed YC to magnify it. The result is something far more intense than, say, a university. Between the partners, the alumni, and their batchmates, founders are surrounded by people who want to help them, and can. Notes [1] This is why I've never liked it when people refer to YC as a "bootcamp." It's intense like a bootcamp, but the opposite in structure.
YC给予创始人的另一重要资源是同行者,其价值可能超越合伙人建议。回望历史,伟大作品总是聚集于特定时空:15世纪末的佛罗伦萨、19世纪末的哥廷根大学、罗斯时代的《纽约客》、贝尔实验室、施乐帕克研究中心。无论你多优秀,优秀的同行都能让你更出色。事实上,志向远大者可能比任何人都更需要同行,因为日常生活中他们极度缺乏这类伙伴。
无论YC未来能否跻身那些著名集群之列,我们都始终以此为目标。我们深谙这一历史现象,并刻意将YC设计成此类集群。时至今日,称YC为顶级初创创始人最大聚集地已非自夸——就连攻击YC的人都不得不承认这点。
同行者与初创创始人都是世界上最强大的力量,二者结合理应产生巨大效应。在YC之前,人们普遍认为这两者不可兼得——孤独是独立的代价。1990年代我们在波士顿创业时深有体会:仅有几位提供(质量参差的)建议的前辈,却无真正同路人。无人可倾诉投资者的刁难,无人可探讨技术未来。我常建议创始人做自己需要的东西,YC正是如此——它完全按照我们当年创业时的渴望设计。
我们当年的愿望之一,就是不必辗转于随机富豪之间就能获得种子资金。这在美国已成标配,但优秀的同行者永远无法商品化——因其聚集特性必然导致其他地区的相对匮乏。
Instead of everyone doing the same thing, they're each talking to YC partners to figure out what their specific startup needs. [2] When I say the summer 2012 batch was broken, I mean it felt to the partners that something was wrong. Things weren't yet so broken that the startups had a worse experience. In fact that batch did unusually well. [3] This situation reminds me of the research showing that people are much better at answering questions than they are at judging how accurate their answers are. The two phenomena feel very similar. [4] The Airbnbs were particularly good at listening — partly because they were flexible and disciplined, but also because they'd had such a rough time during the preceding year. They were ready to listen. [5] The optimal unit of decisiveness depends on how long it takes to get results, and that depends on the type of problem you're solving. When you're negotiating with investors, it could be a couple days, whereas if you're building hardware it could be months. Thanks to Trevor Blackwell, Jessica Livingston, Harj Taggar, and Garry Tan for reading drafts of this..
当同行者真正聚集时,魔法就会发生。YC晚餐时的现场能量是我此生未见的奇观。当年若能有两三家初创公司交流我们就心满意足,而满堂精英齐聚时则完全是另一番境界。
YC创始人不仅相互激励,更会彼此扶持。这是关于初创创始人最令我欣慰的发现:他们帮助同行的慷慨程度。我们在第一批项目就注意到这点,并有意识地放大这种效应。最终形成的氛围远比大学等机构浓厚——合伙人、校友同批成员构建的生态中,创始人始终被愿意且能够帮助他们的人环绕。
注释 [1] 因此我从不认同将YC称为"新兵训练营"。强度或许相似,但结构截然相反——不是统一训练,而是通过与合伙人交流制定个性化方案。 [2] 2012年夏季批次的问题在于合伙人感受到异常,初创公司体验尚未受影响。事实上那批表现格外优异。 [3] 这让我想起研究显示:人们回答问题的能力远高于评估答案准确性的能力。两者现象极其相似。 [4] Airbnb团队特别善于倾听——既因灵活自律,更因前一年的艰难经历让他们准备好接纳建议。 [5] 最佳决策单元取决于获取结果的时间周期,这又因问题类型而异:投资谈判可能需数天,硬件开发则可能需数月。
致谢 特雷弗·布莱克韦尔、杰西卡·利文斯顿、哈吉·塔加尔和加里·谭审阅了本文草稿。
April 2022 One of the most surprising things I've witnessed in my lifetime is the rebirth of the concept of heresy. In his excellent biography of Newton, Richard Westfall writes about the moment when he was elected a fellow of Trinity College: > Supported comfortably, Newton was free to devote himself wholly to whatever he chose. To remain on, he had only to avoid the three unforgivable sins: crime, heresy, and marriage. [1]
2022年4月 我一生中目睹最令人惊讶的事情之一,就是异端概念的复兴。 在理查德·韦斯特福尔那本出色的牛顿传记中,他写到牛顿当选三一学院院士的时刻: > 有了优渥的保障,牛顿可以自由地全身心投入任何他选择的领域。要保住这个位置,他只需避免犯下三种不可饶恕的罪行:刑事犯罪、宣扬异端以及结婚。[1]
我第一次读到这段话是在20世纪90年代,当时觉得它带着可笑的中世纪色彩。多奇怪啊,竟然要避免犯下异端之罪。但二十年后重读时,这听起来就像对当代职场的描述。
如今可能让你丢掉工作的观点正变得越来越多。那些解雇者不会用"异端"这个词来形容这些观点,但它们在结构上是等同的。异端有两个结构性特征:(1)它优先于观点本身的真伪问题;(2)它足以抵消发言者过去的所有作为。
The first time I read that, in the 1990s, it sounded amusingly medieval. How strange, to have to avoid committing heresy. But when I reread it 20 years later it sounded like a description of contemporary employment. There are an ever-increasing number of opinions you can be fired for. Those doing the firing don't use the word "heresy" to describe them, but structurally they're equivalent. Structurally there are two distinctive things about heresy: (1) that it takes priority over the question of truth or falsity, and (2) that it outweighs everything else the speaker has done. For example, when someone calls a statement "x-ist," they're also implicitly saying that this is the end of the discussion. They do not, having said this, go on to consider whether the statement is true or not. Using such labels is the conversational equivalent of signalling an exception. That's one of the reasons they're used: to end a discussion. If you find yourself talking to someone who uses these labels a lot, it might be worthwhile to ask them explicitly if they believe any babies are being thrown out with the bathwater. Can a statement be x-ist, for whatever value of x, and also true? If the answer is yes, then they're admitting to banning the truth. That's obvious enough that I'd guess most would answer no. But if they answer no, it's easy to show that they're mistaken, and that in practice such labels are applied to statements regardless of their truth or falsity. The clearest evidence of this is that whether a statement is considered x-ist often depends on who said it. Truth doesn't work that way. The same statement can't be true when one person says it, but x-ist, and therefore false, when another person does. [2] The other distinctive thing about heresies, compared to ordinary opinions, is that the public expression of them outweighs everything else the speaker has done.
例如,当有人称某个说法是"X主义"时,他们也在暗示讨论就此终结。说完这句话后,他们不会继续考虑该说法是否属实。使用这类标签相当于在对话中抛出异常信号——这正是它们被使用的目的之一:终结讨论。
如果你发现对话对象频繁使用这类标签,不妨直接问他们:是否认为存在"把婴儿和洗澡水一起倒掉"的情况?一个说法有没有可能既是X主义的(无论X指代什么),同时又是真实的?如果对方回答"是",就等于承认他们在禁止真相。这个结论如此显而易见,我猜多数人会回答"否"。但若回答"否",我们很容易证明他们错了——实践中这类标签的贴附根本与真伪无关。
最明显的证据是:一个说法是否被视为X主义,往往取决于发言者是谁。真相从不是这样运作的。同一句话不可能由A说出时是真理,由B说出时就变成X主义的谬误。
In ordinary matters, like knowledge of history, or taste in music, you're judged by the average of your opinions. A heresy is qualitatively different. It's like dropping a chunk of uranium onto the scale. Back in the day (and still, in some places) the punishment for heresy was death. You could have led a life of exemplary goodness, but if you publicly doubted, say, the divinity of Christ, you were going to burn. Nowadays, in civilized countries, heretics only get fired in the metaphorical sense, by losing their jobs. But the structure of the situation is the same: the heresy outweighs everything else. You could have spent the last ten years saving children's lives, but if you express certain opinions, you're automatically fired. It's much the same as if you committed a crime. No matter how virtuously you've lived, if you commit a crime, you must still suffer the penalty of the law. Having lived a previously blameless life might mitigate the punishment, but it doesn't affect whether you're guilty or not. A heresy is an opinion whose expression is treated like a crime — one that makes some people feel not merely that you're mistaken, but that you should be punished. Indeed, their desire to see you punished is often stronger than it would be if you'd committed an actual crime. There are many on the far left who believe strongly in the reintegration of felons (as I do myself), and yet seem to feel that anyone guilty of certain heresies should never work again. There are always some heresies — some opinions you'd be punished for expressing. But there are a lot more now than there were a few decades ago, and even those who are happy about this would have to agree that it's so. Why? Why has this antiquated-sounding religious concept come back in a secular form? And why now? You need two ingredients for a wave of intolerance: intolerant people, and an ideology to guide them. The intolerant people are always there.
异端与普通观点的另一个关键区别在于:公开表达异端的行为会抵消发言者的全部过往。在历史知识、音乐品味等普通领域,人们根据你观点的平均水平来评判你。而异端则是质的不同——就像在天平上扔下一块铀。
在过去(某些地方至今如此),异端的惩罚是死刑。即便一生行善,只要公开质疑基督的神性就会被烧死。如今在文明国家,异端者只会遭遇隐喻性的"火刑"——丢掉工作。但结构完全一致:异端压倒一切。哪怕你十年如一日拯救儿童生命,只要表达某些观点就会立即被解雇。
这与犯罪后的处境极为相似。无论生平多么高尚,犯罪就必须接受法律制裁。清白历史或许能减轻惩罚,但不会改变有罪事实。
异端是一种被视同犯罪的言论——它不仅让人认为你错了,更认为你该受惩罚。事实上,这种惩罚欲往往比对待真正犯罪时更强烈。许多极左人士坚信应帮助刑满人员回归社会(我本人也这么认为),却觉得某些异端者永世不得翻身。
They exist in every sufficiently large society. That's why waves of intolerance can arise so suddenly; all they need is something to set them off. I've already written an _essay_ describing the aggressively conventional-minded. The short version is that people can be classified in two dimensions according to (1) how independent- or conventional-minded they are, and (2) how aggressive they are about it. The aggressively conventional-minded are the enforcers of orthodoxy. Normally they're only locally visible. They're the grumpy, censorious people in a group — the ones who are always first to complain when something violates the current rules of propriety. But occasionally, like a vector field whose elements become aligned, a large number of aggressively conventional-minded people unite behind some ideology all at once. Then they become much more of a problem, because a mob dynamic takes over, where the enthusiasm of each participant is increased by the enthusiasm of the others. The most notorious 20th century case may have been the Cultural Revolution. Though initiated by Mao to undermine his rivals, the Cultural Revolution was otherwise mostly a grass-roots phenomenon. Mao said in essence: There are heretics among us. Seek them out and punish them. And that's all the aggressively conventional-minded ever need to hear. They went at it with the delight of dogs chasing squirrels. To unite the conventional-minded, an ideology must have many of the features of a religion. In particular it must have strict and arbitrary rules that adherents can demonstrate their _purity_ by obeying, and its adherents must believe that anyone who obeys these rules is ipso facto morally superior to anyone who doesn't. [3] In the late 1980s a new ideology of this type appeared in US universities.
每个时代都存在异端——那些会因表达而受惩罚的观点。但今天的异端比几十年前多得多,就连乐见此事的人也不得不承认这一点。
为什么?这个听起来陈腐的宗教概念为何会以世俗形式复活?又为何是现在?
掀起不宽容浪潮需要两种要素:不宽容的人群,以及指引他们的意识形态。不宽容者始终存在,任何足够大的社会都有他们的身影。这就是不宽容浪潮能突然兴起的原因——只需要一个触发点。
It had a very strong component of moral purity, and the aggressively conventional-minded seized upon it with their usual eagerness — all the more because the relaxation of social norms in the preceding decades meant there had been less and less to forbid. The resulting wave of intolerance has been eerily similar in form to the Cultural Revolution, though fortunately much smaller in magnitude. [4] I've deliberately avoided mentioning any specific heresies here. Partly because one of the universal tactics of heretic hunters, now as in the past, is to accuse those who disapprove of the way in which they suppress ideas of being heretics themselves. Indeed, this tactic is so consistent that you could use it as a way of detecting witch hunts in any era. And that's the second reason I've avoided mentioning any specific heresies. I want this essay to work in the future, not just now. And unfortunately it probably will. The aggressively conventional-minded will always be among us, looking for things to forbid. All they need is an ideology to tell them what. And it's unlikely the current one will be the last. There are aggressively conventional-minded people on both the right and the left. The reason the current wave of intolerance comes from the left is simply because the new unifying ideology happened to come from the left. The next one might come from the right. Imagine what that would be like. Fortunately in western countries the suppression of heresies is nothing like as bad as it used to be. Though the window of opinions you can express publicly has narrowed in the last decade, it's still much wider than it was a few hundred years ago. The problem is the derivative. Up till about 1985 the window had been growing ever wider. Anyone looking into the future in 1985 would have expected freedom of expression to continue to increase. Instead it has decreased. [5] The situation is similar to what's happened with infectious diseases like measles.
我在《从众心理》一文中描述过"好斗的守旧者"。简言之,人们可以按两个维度分类:(1)思想独立性/从众性;(2)对此的激进程度。好斗的守旧者正是正统的执法者。
通常他们只在局部可见——是群体中那些暴躁苛刻的成员,总是最先跳出来指责某事违反现行规范。但偶尔,就像矢量场突然同向排列,大批好斗的守旧者会瞬间集结在某意识形态旗下。此时他们就会成为大麻烦,因为群体动力学开始生效——每个人的狂热都在彼此助长。
20世纪最臭名昭著的案例或许是文化大革命。虽然毛泽东发动它是为了打击政敌,但本质上这是一场草根运动。毛的号召很简单:我们中间有异端,找出他们并惩罚。这对好斗的守旧者来说就足够了。他们像追逐松鼠的狗一般扑向这场运动。
Anyone looking into the future in 2010 would have expected the number of measles cases in the US to continue to decrease. Instead, thanks to anti-vaxxers, it has increased. The absolute number is still not that high. The problem is the derivative. [6] In both cases it's hard to know how much to worry. Is it really dangerous to society as a whole if a handful of extremists refuse to get their kids vaccinated, or shout down speakers at universities? The point to start worrying is presumably when their efforts start to spill over into everyone else's lives. And in both cases that does seem to be happening. So it's probably worth spending some amount of effort on pushing back to keep open the window of free expression. My hope is that this essay will help form social antibodies not just against current efforts to suppress ideas, but against the concept of heresy in general. That's the real prize. How do you disable the concept of heresy? Since the Enlightenment, western societies have discovered many techniques for doing that, but there are surely more to be discovered. Overall I'm optimistic. Though the trend in freedom of expression has been bad over the last decade, it's been good over the longer term. And there are signs that the current wave of intolerance is peaking. Independent-minded people I talk to seem more confident than they did a few years ago. On the other side, even some of the _leaders_ are starting to wonder if things have gone too far. And popular culture among the young has already moved on. All we have to do is keep pushing back, and the wave collapses.
要团结守旧者,意识形态必须具备宗教的诸多特征。尤其是它需要包含严格而武断的规则——信徒通过遵守这些规则来证明其"纯洁性",且必须相信遵守规则者在道德上天然高于违背者。
1980年代末,美国大学出现了这类新意识形态。它具有极强的道德纯洁性诉求,好斗的守旧者以惯常的热忱抓住了它——尤其因为此前数十年社会规范的松弛让他们越来越无事可禁。由此产生的不宽容浪潮在形式上与文化革命诡异相似,所幸规模小得多。
我刻意避免在此列举具体异端。部分原因是:古往今来,猎巫者的通用伎俩之一,就是把反对压制思想方式的人也指控为异端。这个伎俩如此恒定,简直可以作为任何时代识别猎巫运动的标志。
这也是我避免举例的第二个原因:我希望这篇文章在未来依然有效。不幸的是,它很可能真的会。好斗的守旧者永远存在,永远在寻找可禁止之物。他们只需要一个意识形态来指明目标——而当前的意识形态不太可能是最后一个。
And then we'll be net ahead, because as well as having defeated this wave, we'll also have developed new tactics for resisting the next one. Notes [1] Or more accurately, biographies of Newton, since Westfall wrote two: a long version called _Never at Rest_ , and a shorter one called _The Life of Isaac Newton_. Both are great. The short version moves faster, but the long one is full of interesting and often very funny details. This passage is the same in both. [2] Another more subtle but equally damning bit of evidence is that claims of x-ism are never qualified. You never hear anyone say that a statement is "probably x-ist" or "almost certainly y-ist." If claims of x-ism were actually claims about truth, you'd expect to see "probably" in front of "x-ist" as often as you see it in front of "fallacious." [3] The rules must be strict, but they need not be demanding. So the most effective type of rules are those about superficial matters, like doctrinal minutiae, or the precise words adherents must use. Such rules can be made extremely complicated, and yet don't repel potential converts by requiring significant sacrifice. The superficial demands of orthodoxy make it an inexpensive substitute for virtue. And that in turn is one of the reasons orthodoxy is so attractive to bad people. You could be a horrible person, and yet as long as you're orthodox, you're better than everyone who isn't. [4] Arguably there were two. The first had died down somewhat by 2000, but was followed by a second in the 2010s, probably caused by social media. [5] Fortunately most of those trying to suppress ideas today still respect Enlightenment principles enough to pay lip service to them. They know they're not supposed to ban ideas per se, so they have to recast the ideas as causing "harm," which sounds like something that can be banned. The more extreme try to claim speech itself is violence, or even that silence is.
左右两翼都有好斗的守旧者。当前不宽容浪潮来自左翼,仅仅因为新意识形态恰好诞生于左翼。下一波可能来自右翼。想象一下那会是什么景象。
幸运的是,西方国家压制异端的程度已远不如前。尽管过去十年可公开表达的观点范围在缩小,但相比几百年前仍宽广得多。问题在于变化趋势:直到1985年左右,这个范围还在持续扩大。当时展望未来的人本应看到表达自由继续增长,结果却出现了倒退。
这类似于麻疹等传染病的状况。2010年时人们预期美国麻疹病例会持续减少,结果由于反疫苗运动,数字反而上升。绝对数量虽仍不高,但趋势令人担忧。
But strange as it may sound, such gymnastics are a good sign. We'll know we're really in trouble when they stop bothering to invent pretenses for banning ideas — when, like the medieval church, they say "Damn right we're banning ideas, and in fact here's a list of them." [6] People only have the luxury of ignoring the medical consensus about vaccines because vaccines have worked so well. If we didn't have any vaccines at all, the mortality rate would be so high that most current anti-vaxxers would be begging for them. And the situation with freedom of expression is similar. It's only because they live in a world created by the Enlightenment that kids from the suburbs can play at banning ideas. Thanks to Marc Andreessen, Chris Best, Trevor Blackwell, Nicholas Christakis, Daniel Gackle, Jonathan Haidt, Claire Lehmann, Jessica Livingston, Greg Lukianoff, Robert Morris, and Garry Tan for reading drafts of this..
两者都让人难以判断该担忧到什么程度:少数极端分子拒绝给孩子接种疫苗,或在大学里轰赶演讲者,真的会危及整个社会吗?真正的警讯应该是当这些行为开始侵蚀普通人的生活——而两种情况似乎都在发生。
因此值得投入一定精力来捍卫表达自由的疆域。我希望这篇文章不仅能帮助形成对抗当前压制思想行为的社会抗体,更能从根本上消解"异端"这个概念。这才是真正的胜利。如何解构异端概念?自启蒙运动以来,西方社会已发现许多方法,但肯定还有更多待发掘。
总体而言我持乐观态度。虽然过去十年表达自由的趋势不佳,但长期来看仍在进步。有迹象表明当前不宽容浪潮已到顶峰。我接触的思想独立者比几年前更自信;就连某些运动领袖也开始反思是否做得过火;年轻群体的流行文化早已转向。我们只需继续抵抗,浪潮自会崩溃。届时我们将取得净收益——既击退了这波浪潮,也积累了抵抗下一波的新策略。
注释 [1] 更准确说是牛顿传记——韦斯特福尔写过两版:详尽的《永不停息》和简明的《艾萨克·牛顿的一生》。两本都很精彩,简版节奏更快,详版充满有趣且常令人捧腹的细节。引文在两版中相同。 [2] 另一个更微妙但同样确凿的证据是:X主义的指控从不带限定词。没人会说某观点"可能是X主义"或"基本属于Y主义"。如果这类指控真与真实性有关,我们应该会像看到"可能是谬误"那样频繁看到"可能是X主义"。 [3] 规则必须严格,但不一定苛刻。因此最有效的规则往往关于表面事务,比如教义细节或必须使用的特定词汇。这类规则可以极其复杂,却不会因要求实质性牺牲而吓退潜在皈依者。 正统的表面要求使其成为美德的廉价替代品——这也正是坏人对正统趋之若鹜的原因。你可以品行恶劣,但只要皈依正统,就比所有异端者高贵。 [4] 严格说有两波。第一波到2000年已有所消退,但2010年代社交媒体很可能催生了第二波。 [5] 所幸当今多数压制思想者至少口头上还尊重启蒙原则。他们知道不能直接禁止思想,于是把思想重新定义为造成"伤害"——听起来就属于可禁范畴。更极端者声称言论本身就是暴力,甚至沉默也是暴力。尽管荒谬,但这种诡辩反而是好迹象。当有一天他们懒得再为禁绝思想找借口——像中世纪教会那样直说"我们就是要禁思想,清单在此"——那才是真正的危机。 [6] 人们之所以能无视疫苗的医学共识,恰恰因为疫苗太有效。如果根本没有疫苗,死亡率会高到让现在多数反疫苗者跪求接种。表达自由的情况类似——正因为生活在启蒙运动创造的世界里,郊区长大的孩子才能把禁止思想当作游戏。
February 2022 Writing about something, even something you know well, usually shows you that you didn't know it as well as you thought. Putting ideas into words is a severe test. The first words you choose are usually wrong; you have to rewrite sentences over and over to get them exactly right. And your ideas won't just be imprecise, but incomplete too. Half the ideas that end up in an essay will be ones you thought of while you were writing it. Indeed, that's why I write them. Once you publish something, the convention is that whatever you wrote was what you thought before you wrote it. These were your ideas, and now you've expressed them. But you know this isn't true. You know that putting your ideas into words changed them. And not just the ideas you published. Presumably there were others that turned out to be too broken to fix, and those you discarded instead. It's not just having to commit your ideas to specific words that makes writing so exacting. The real test is reading what you've written. You have to pretend to be a neutral reader who knows nothing of what's in your head, only what you wrote. When he reads what you wrote, does it seem correct? Does it seem complete? If you make an effort, you can read your writing as if you were a complete stranger, and when you do the news is usually bad. It takes me many cycles before I can get an essay past the stranger. But the stranger is rational, so you always can, if you ask him what he needs. If he's not satisfied because you failed to mention x or didn't qualify some sentence sufficiently, then you mention x or add more qualifications. Happy now? It may cost you some nice sentences, but you have to resign yourself to that. You just have to make them as good as you can and still satisfy the stranger. This much, I assume, won't be that controversial. I think it will accord with the experience of anyone who has tried to write about anything nontrivial.
将想法诉诸文字,即便是你非常熟悉的事物,往往会让你意识到自己的认知并不如想象中透彻。文字表达堪称严苛的试炼。最初选用的词句往往词不达意,必须反复修改才能准确传达。你的思想不仅会显得模糊不清,更会暴露其残缺本质。最终成文的观点中,半数都是在写作过程中萌生的。事实上,这正是我坚持写作的原因。
公开发表的内容,惯例上会被视为作者动笔前的既定思想。这些是你的观点,如今你已将其表达。但你知道事实并非如此。你明白文字化的过程已经改变了它们。不仅限于已发表的观点,那些支离破碎无法修补的念头,最终都被你弃如敝屣。
文字创作的严苛不仅在于必须将思想固化于特定词汇。真正的考验在于重读自己的作品。你必须扮演一个对你脑中思绪一无所知的中立读者,仅凭文字本身作出判断。当他阅读这些文字时,观点是否准确?论述是否完整?若你足够努力,确实能像陌生人般审视自己的文字,而结果往往令人沮丧。我通常需要反复修改多次,才能让文章通过这位"陌生人"的检验。但这位陌生人理性客观,只要询问他的需求,总能找到改进方向。若他因你遗漏要点X或某处表述不够严谨而不满,你就补充X或增加限定条件。现在满意了吗?或许要牺牲某些精彩句子,但你必须学会妥协。在保证陌生人认可的前提下,尽力让文字臻于完美。
There may exist people whose thoughts are so perfectly formed that they just flow straight into words. But I've never known anyone who could do this, and if I met someone who said they could, it would seem evidence of their limitations rather than their ability. Indeed, this is a trope in movies: the guy who claims to have a plan for doing some difficult thing, and who when questioned further, taps his head and says "It's all up here." Everyone watching the movie knows what that means. At best the plan is vague and incomplete. Very likely there's some undiscovered flaw that invalidates it completely. At best it's a plan for a plan. In precisely defined domains it's possible to form complete ideas in your head. People can play chess in their heads, for example. And mathematicians can do some amount of math in their heads, though they don't seem to feel sure of a proof over a certain length till they write it down. But this only seems possible with ideas you can express in a formal language. [1] Arguably what such people are doing is putting ideas into words in their heads. I can to some extent write essays in my head. I'll sometimes think of a paragraph while walking or lying in bed that survives nearly unchanged in the final version. But really I'm writing when I do this. I'm doing the mental part of writing; my fingers just aren't moving as I do it. [2] You can know a great deal about something without writing about it. Can you ever know so much that you wouldn't learn more from trying to explain what you know? I don't think so. I've written about at least two subjects I know well — Lisp hacking and startups — and in both cases I learned a lot from writing about them. In both cases there were things I didn't consciously realize till I had to explain them. And I don't think my experience was anomalous. A great deal of knowledge is unconscious, and experts have if anything a higher proportion of unconscious knowledge than beginners.
这些见解想必不会引发太多争议。任何尝试过严肃写作的人应该都有共鸣。或许存在思维天生完美、能直接转化为文字的天才。但我从未遇见这样的奇才,若有人声称具备此能,这反而更像是其局限性的证明。电影里就常见这类桥段:某人宣称对难题成竹在胸,被追问细节时却轻点太阳穴说"全在这里"。观众都心知肚明——这计划充其量只是个模糊构想,更可能暗藏致命漏洞。最多算是个"计划的雏形"。
在精确定义的领域,确实可能在脑中构建完整想法。比如人们能进行盲棋对弈,数学家也能心算部分数学问题,但超过特定复杂度的证明,似乎必须落笔才能确信。[1] 这类情况仅适用于能用形式化语言表达的思想。可以说,这些人其实是在脑中完成了文字转化。某种程度上,我也能在脑中构思文章。散步或卧床时萌生的段落,有时几乎原封不动地出现在终稿里。但这本质上仍是写作行为——我正在进行写作的思维过程,只是手指没有同步动作。[2]
不写作也能精通某个领域。但是否存在这样的境界:尝试解释所知时不会获得新知?我认为不存在。我至少深入撰写过两个精通领域——Lisp编程与创业——每次写作都带来认知突破。两个领域都有许多洞见,是在必须解释时才被意识到的。这绝非特例。大量知识以潜意识形式存在,专家的隐性知识比例往往高于初学者。
并非所有思想探索都需仰赖写作。建筑理念的最佳验证方式显然是实体建造。但我想强调的是:无论通过其他方式获得多少认知,文字记录总能带来新发现。
I'm not saying that writing is the best way to explore all ideas. If you have ideas about architecture, presumably the best way to explore them is to build actual buildings. What I'm saying is that however much you learn from exploring ideas in other ways, you'll still learn new things from writing about them. Putting ideas into words doesn't have to mean writing, of course. You can also do it the old way, by talking. But in my experience, writing is the stricter test. You have to commit to a single, optimal sequence of words. Less can go unsaid when you don't have tone of voice to carry meaning. And you can focus in a way that would seem excessive in conversation. I'll often spend 2 weeks on an essay and reread drafts 50 times. If you did that in conversation it would seem evidence of some kind of mental disorder. If you're lazy, of course, writing and talking are equally useless. But if you want to push yourself to get things right, writing is the steeper hill. [3] The reason I've spent so long establishing this rather obvious point is that it leads to another that many people will find shocking. If writing down your ideas always makes them more precise and more complete, then no one who hasn't written about a topic has fully formed ideas about it. And someone who never writes has no fully formed ideas about anything nontrivial. It feels to them as if they do, especially if they're not in the habit of critically examining their own thinking. Ideas can feel complete. It's only when you try to put them into words that you discover they're not. So if you never subject your ideas to that test, you'll not only never have fully formed ideas, but also never realize it. Putting ideas into words is certainly no guarantee that they'll be right. Far from it.
思想表达未必限于写作,传统对话同样可行。但据我经验,写作是更严苛的考验。你必须确定唯一最优的词句组合。当失去语调辅助,每个语义空白都无所遁形。且你能进行对话中显得病态的极致推敲——我常花两周打磨文章,重读草稿五十次。若在谈话中如此,必被视作精神异常。当然,若态度敷衍,写作与交谈同样无效。但若追求极致,写作才是更陡峭的高峰。[3]
我之所以长篇论证这个显而易见的观点,因其引出的推论将令多数人震惊:若文字化总能提升思想的精确性与完整性,那么未就某主题写作之人,对此必无成熟见解。而从不写作之人,对所有重要事物都缺乏系统认知。
他们自以为胸有成竹,尤其当缺乏批判性思维习惯时。想法可能"感觉"很完整,唯有诉诸文字时才会暴露缺陷。若永远逃避这种检验,不仅无法形成完整思想,甚至永远意识不到这点。
将思想转化为文字当然不能保证其正确性。远非如此。但这虽非充分条件,却是必要条件。
But though it's not a sufficient condition, it is a necessary one. Notes [1] Machinery and circuits are formal languages. [2] I thought of this sentence as I was walking down the street in Palo Alto. [3] There are two senses of talking to someone: a strict sense in which the conversation is verbal, and a more general sense in which it can take any form, including writing. In the limit case (e.g. Seneca's letters), conversation in the latter sense becomes essay writing. It can be very useful to talk (in either sense) with other people as you're writing something. But a verbal conversation will never be more exacting than when you're talking about something you're writing. Thanks to Trevor Blackwell, Patrick Collison, and Robert Morris for reading drafts of this.
注释 [1] 机械结构与电路图都属于形式化语言 [2] 此句构思于帕罗奥图街头漫步时 [3] "交谈"有双重含义:严格指言语对话,广义则包含写作等任何形式。极端情况下(如塞涅卡书信),广义交谈即等同于文章创作
写作过程中与他人交流(任一形式)极具价值。但口头讨论的严谨性永远无法超越正在撰写的文字。
致谢 感谢Trevor Blackwell、Patrick Collison与Robert Morris审阅本文草稿
November 2021 _(This essay is derived from a talk at the Cambridge Union.)_ When I was a kid, I'd have said there wasn't. My father told me so. Some people like some things, and other people like other things, and who's to say who's right? It seemed so obvious that there was no such thing as good taste that it was only through indirect evidence that I realized my father was wrong. And that's what I'm going to give you here: a proof by reductio ad absurdum. If we start from the premise that there's no such thing as good taste, we end up with conclusions that are obviously false, and therefore the premise must be wrong. We'd better start by saying what good taste is. There's a narrow sense in which it refers to aesthetic judgements and a broader one in which it refers to preferences of any kind. The strongest proof would be to show that taste exists in the narrowest sense, so I'm going to talk about taste in art. You have better taste than me if the art you like is better than the art I like. If there's no such thing as good taste, then there's no such thing as _good art_. Because if there is such a thing as good art, it's easy to tell which of two people has better taste. Show them a lot of works by artists they've never seen before and ask them to choose the best, and whoever chooses the better art has better taste. So if you want to discard the concept of good taste, you also have to discard the concept of good art. And that means you have to discard the possibility of people being good at making it. Which means there's no way for artists to be good at their jobs. And not just visual artists, but anyone who is in any sense an artist. You can't have good actors, or novelists, or composers, or dancers either. You can have popular novelists, but not good ones. We don't realize how far we'd have to go if we discarded the concept of good taste, because we don't even debate the most obvious cases.
But it doesn't just mean we can't say which of two famous painters is better. It means we can't say that any painter is better than a randomly chosen eight year old. That was how I realized my father was wrong. I started studying painting. And it was just like other kinds of work I'd done: you could do it well, or badly, and if you tried hard, you could get better at it. And it was obvious that Leonardo and Bellini were much better at it than me. That gap between us was not imaginary. They were so good. And if they could be good, then art could be good, and there was such a thing as good taste after all. Now that I've explained how to show there is such a thing as good taste, I should also explain why people think there isn't. There are two reasons. One is that there's always so much disagreement about taste. Most people's response to art is a tangle of unexamined impulses. Is the artist famous? Is the subject attractive? Is this the sort of art they're supposed to like? Is it hanging in a famous museum, or reproduced in a big, expensive book? In practice most people's response to art is dominated by such extraneous factors. And the people who do claim to have good taste are so often mistaken. The paintings admired by the so-called experts in one generation are often so different from those admired a few generations later. It's easy to conclude there's nothing real there at all. It's only when you isolate this force, for example by trying to paint and comparing your work to Bellini's, that you can see that it does in fact exist. The other reason people doubt that art can be good is that there doesn't seem to be any room in the art for this goodness. The argument goes like this. Imagine several people looking at a work of art and judging how good it is. If being good art really is a property of objects, it should be in the object somehow. But it doesn't seem to be; it seems to be something happening in the heads of each of the observers.
And if they disagree, how do you choose between them? The solution to this puzzle is to realize that the purpose of art is to work on its human audience, and humans have a lot in common. And to the extent the things an object acts upon respond in the same way, that's arguably what it means for the object to have the corresponding property. If everything a particle interacts with behaves as if the particle had a mass of _m_ , then it has a mass of _m_. So the distinction between "objective" and "subjective" is not binary, but a matter of degree, depending on how much the subjects have in common. Particles interacting with one another are at one pole, but people interacting with art are not all the way at the other; their reactions aren't _random_. Because people's responses to art aren't random, art can be designed to operate on people, and be good or bad depending on how effectively it does so. Much as a vaccine can be. If someone were talking about the ability of a vaccine to confer immunity, it would seem very frivolous to object that conferring immunity wasn't really a property of vaccines, because acquiring immunity is something that happens in the immune system of each individual person. Sure, people's immune systems vary, and a vaccine that worked on one might not work on another, but that doesn't make it meaningless to talk about the effectiveness of a vaccine. The situation with art is messier, of course. You can't measure effectiveness by simply taking a vote, as you do with vaccines. You have to imagine the responses of subjects with a deep knowledge of art, and enough clarity of mind to be able to ignore extraneous influences like the fame of the artist. And even then you'd still see some disagreement. People do vary, and judging art is hard, especially recent art. There is definitely not a total order either of works or of people's ability to judge them. But there is equally definitely a partial order of both.
So while it's not possible to have perfect taste, it is possible to have good taste. Thanks to the Cambridge Union for inviting me, and to Trevor Blackwell, Jessica Livingston, and Robert Morris for reading drafts of this..
2021年11月 (本文改编自剑桥联盟学会的一次演讲) 小时候我会斩钉截铁地说"好品味"不存在。父亲就是这么教我的——有人喜欢这个,有人喜欢那个,谁有资格评判对错? 这个结论曾如此不言而喻,以至于我后来是通过间接证据才意识到父亲的错误。今天我要用归谬法来论证:如果我们假设"好品味"不存在,最终会得出明显荒谬的结论,因此前提必然是错误的。 首先要界定"好品味"的定义。狭义指审美判断力,广义涵盖所有偏好判断。最有力的证明是展示其狭义存在性,因此我将以艺术鉴赏为例。如果你欣赏的艺术作品比我欣赏的更优秀,那么你的品味就更高。 若"好品味"不存在,则"好艺术"也不存在。因为倘若存在好艺术,只需让两人从未知艺术家中挑选最佳作品,选得更优者自然拥有更好品味。 因此摒弃"好品味"概念,就必须同时否定"好艺术"。这意味着人们不可能擅长艺术创作,艺术家也无法精进技艺——不仅是视觉艺术家,所有领域的创作者皆然。不可能存在优秀演员、小说家、作曲家或舞者,只会有受欢迎的小说家而非杰出者。 我们尚未意识到摒弃"好品味"将导致的深远影响,因为连最显而易见的案例都无人质疑。这不仅意味着无法比较两位著名画家的高下,更意味着不能断言任何画家比随机选择的八岁儿童更出色。 正是绘画学习让我醒悟父亲的错误。绘画与其他工作无异:存在优劣之分,通过努力可以进步。达芬奇和贝里尼显然远胜于我,这种差距真实存在。既然他们能成为大师,艺术就存在优劣,好品味自然存在。 既然已论证好品味的存在性,还需解释人们的误解根源。其一,审美总是充满分歧。多数人对艺术的反应是未经审视的冲动混合体:作者是否著名?主题是否吸引人?是否符合预期品味?是否陈列于著名博物馆或精装画册?实践中,这些外在因素主导着人们的艺术判断。 而自诩品味卓越者又常犯错误。所谓专家推崇的画作,往往与后世评价大相径庭。这容易让人认为根本不存在客观标准。唯有当你亲身实践(比如尝试绘画并与贝里尼比较),才能感知这种力量确实存在。 其二,艺术品的"优秀"似乎无处安放。质疑者认为:当众人评判艺术品时,若优秀真是作品的属性,它应存在于物体本身。但事实上这似乎只发生在观察者脑海中,若观点相左该如何取舍? 解答关键在于认识到艺术的目的是作用于人类观众,而人类存在普遍共性。当作用对象产生一致反应时,即可认为物体具有相应属性。如同粒子质量:若所有交互对象都表现出质量为m的特性,则该粒子质量即为m。因此"客观"与"主观"并非二元对立,而是程度问题——取决于主体的共性程度。粒子交互处于光谱一端,人类对艺术的反应虽非完全一致,但也绝非随机。 正因人们对艺术的反应存在规律,艺术品才能被设计来影响观众,并根据效果分优劣——这与疫苗原理相似。若有人质疑疫苗的免疫效力并非其真实属性(因为免疫发生在个体免疫系统中),这种反驳显然轻率。虽然个体免疫系统存在差异,但讨论疫苗有效性绝非无意义。 当然艺术领域更为复杂。不能像疫苗试验般简单投票测量效果,而需设想具备深厚艺术修养、能摒除作者名声等干扰因素的理想观众反应。即便如此仍存在分歧——个体差异确实存在,艺术评判本就困难,当代艺术尤甚。艺术品与鉴赏力都不存在完美排序,但部分排序确实存在。因此虽然完美品味不可企及,但优秀品味确实存在。 致谢剑桥联盟学会的邀请,以及Trevor Blackwell、Jessica Livingston和Robert Morris对本文初稿的审阅。
October 2021 If you asked people what was special about Einstein, most would say that he was really smart. Even the ones who tried to give you a more sophisticated-sounding answer would probably think this first. Till a few years ago I would have given the same answer myself. But that wasn't what was special about Einstein. What was special about him was that he had important new ideas. Being very smart was a necessary precondition for having those ideas, but the two are not identical. It may seem a hair-splitting distinction to point out that intelligence and its consequences are not identical, but it isn't. There's a big gap between them. Anyone who's spent time around universities and research labs knows how big. There are a lot of genuinely smart people who don't achieve very much. I grew up thinking that being smart was the thing most to be desired. Perhaps you did too. But I bet it's not what you really want. Imagine you had a choice between being really smart but discovering nothing new, and being less smart but discovering lots of new ideas. Surely you'd take the latter. I would. The choice makes me uncomfortable, but when you see the two options laid out explicitly like that, it's obvious which is better. The reason the choice makes me uncomfortable is that being smart still feels like the thing that matters, even though I know intellectually that it isn't. I spent so many years thinking it was. The circumstances of childhood are a perfect storm for fostering this illusion. Intelligence is much easier to measure than the value of new ideas, and you're constantly being judged by it. Whereas even the kids who will ultimately discover new things aren't usually discovering them yet. For kids that way inclined, intelligence is the only game in town. There are more subtle reasons too, which persist long into adulthood.
如果问人们爱因斯坦的特别之处是什么,大多数人会说因为他极其聪明。即便是那些试图给出更复杂答案的人,脑海中首先浮现的恐怕也是这个答案。几年前的我也会如此回答。但这并非爱因斯坦真正的特别之处。他的非凡在于提出了重要的新思想。极高的智慧是孕育这些思想的必要前提,但两者并不等同。
指出智力与其成果并非同一事物,看似是吹毛求疵的区分,实则不然。二者之间存在着巨大鸿沟。任何在高校或实验室工作过的人都深知这一点——有多少真正聪明的人最终成就寥寥。
我从小认为聪明是最值得追求的品质。或许你也如此。但我敢打赌这并非你真正的渴望。试想:若要在"极其聪明却毫无新发现"与"稍欠聪慧但不断提出新思想"之间选择,你必定会选择后者。我也会。这个选择令人不安,但当两个选项如此明确地摆在面前时,优劣立判。
Intelligence wins in conversation, and thus becomes the basis of the dominance hierarchy. [1] Plus having new ideas is such a new thing historically, and even now done by so few people, that society hasn't yet assimilated the fact that this is the actual destination, and intelligence merely a means to an end. [2] Why do so many smart people fail to discover anything new? Viewed from that direction, the question seems a rather depressing one. But there's another way to look at it that's not just more optimistic, but more interesting as well. Clearly intelligence is not the only ingredient in having new ideas. What are the other ingredients? Are they things we could cultivate? Because the trouble with intelligence, they say, is that it's mostly inborn. The evidence for this seems fairly convincing, especially considering that most of us don't want it to be true, and the evidence thus has to face a stiff headwind. But I'm not going to get into that question here, because it's the other ingredients in new ideas that I care about, and it's clear that many of them can be cultivated. That means the truth is excitingly different from the story I got as a kid. If intelligence is what matters, and also mostly inborn, the natural consequence is a sort of _Brave New World_ fatalism. The best you can do is figure out what sort of work you have an "aptitude" for, so that whatever intelligence you were born with will at least be put to the best use, and then work as hard as you can at it. Whereas if intelligence isn't what matters, but only one of several ingredients in what does, and many of those aren't inborn, things get more interesting. You have a lot more control, but the problem of how to arrange your life becomes that much more complicated.
这种不安源于我们潜意识仍将聪明视为核心价值,即便理性上已知其非。童年环境完美强化了这种错觉:智力比思想价值更易衡量,你时刻都在接受它的评判;而那些最终会有所发现的孩子,彼时通常还未崭露头角。对这类孩子而言,智力是唯一可追逐的游戏。
更微妙的原因延续至成年:智力主导着话语权,成为社会等级的基础[1]。加之新思想的诞生在历史上如此短暂,至今仍属极少数人的领域,社会尚未真正意识到这才是终极目标,而智力仅是手段[2]。
为何众多聪明人未能有所发现?这个角度令人沮丧。但换个视角则充满希望:显然智力并非创新的唯一要素。还有哪些要素?它们可否被培养?
So what are the other ingredients in having new ideas? The fact that I can even ask this question proves the point I raised earlier — that society hasn't assimilated the fact that it's this and not intelligence that matters. Otherwise we'd all know the answers to such a fundamental question. [3] I'm not going to try to provide a complete catalogue of the other ingredients here. This is the first time I've posed the question to myself this way, and I think it may take a while to answer. But I wrote recently about one of the most important: an obsessive _interest_ in a particular topic. And this can definitely be cultivated. Another quality you need in order to discover new ideas is _independent-mindedness_. I wouldn't want to claim that this is distinct from intelligence — I'd be reluctant to call someone smart who wasn't independent-minded — but though largely inborn, this quality seems to be something that can be cultivated to some extent. There are general techniques for having new ideas — for example, for working on your own _projects_ and for overcoming the obstacles you face with _early_ work — and these can all be learned. Some of them can be learned by societies. And there are also collections of techniques for generating specific types of new ideas, like startup ideas and essay topics. And of course there are a lot of fairly mundane ingredients in discovering new ideas, like _working hard_, getting enough sleep, avoiding certain kinds of stress, having the right colleagues, and finding tricks for working on what you want even when it's not what you're supposed to be working on. Anything that prevents people from doing great work has an inverse that helps them to. And this class of ingredients is not as boring as it might seem at first. For example, having new ideas is generally associated with youth.
据说智力的困境在于其天生性——证据相当确凿,尤其考虑到我们多数人都不愿承认这点。但此刻我更关注其他可塑的要素,它们显然能够培育。
这意味着真相远比童年认知更激动人心。若智力至上且天生注定,结局只能是《美丽新世界》般的宿命论:你至多找到与"天资"匹配的工作,竭力发挥那点与生俱来的聪明。但若智力只是创新要素之一,且许多要素可后天培养,局面就变得复杂而有趣:你拥有更多掌控权,但生活规划也更具挑战性。
那么创新的其他要素是什么?能提出这个问题本身,就印证了前文观点——社会尚未认清真正重要的是创新而非智力[3]。否则我们早该知晓这个根本问题的答案。
在此我不打算穷尽所有要素(这是首次如此自问,答案可能需要时间沉淀)。但最近我写过最关键的一项:对特定领域【痴迷】般的兴趣。这绝对可以培养。
But perhaps it's not youth per se that yields new ideas, but specific things that come with youth, like good health and lack of responsibilities. Investigating this might lead to strategies that will help people of any age to have better ideas. One of the most surprising ingredients in having new ideas is writing ability. There's a class of new ideas that are best discovered by writing essays and books. And that "by" is deliberate: you don't think of the ideas first, and then merely write them down. There is a kind of thinking that one does by writing, and if you're clumsy at writing, or don't enjoy doing it, that will get in your way if you try to do this kind of thinking. [4] I predict the gap between intelligence and new ideas will turn out to be an interesting place. If we think of this gap merely as a measure of unrealized potential, it becomes a sort of wasteland that we try to hurry through with our eyes averted. But if we flip the question, and start inquiring into the other ingredients in new ideas that it implies must exist, we can mine this gap for discoveries about discovery. Notes [1] What wins in conversation depends on who with. It ranges from mere aggressiveness at the bottom, through quick-wittedness in the middle, to something closer to actual intelligence at the top, though probably always with some component of quick-wittedness. [2] Just as intelligence isn't the only ingredient in having new ideas, having new ideas isn't the only thing intelligence is useful for. It's also useful, for example, in diagnosing problems and figuring out how to fix them. Both overlap with having new ideas, but both have an end that doesn't. Those ways of using intelligence are much more common than having new ideas.
另一要素是【独立思考力】。虽不愿断言其完全独立于智力(很难称缺乏独立思考者为真正聪明),但这个主要与生俱来的品质似乎也能通过后天培养获得提升。
存在通用的创新方法:比如开展自主【项目】,克服早期工作的障碍——这些均可习得,某些甚至能被社会集体学习。还有针对特定创新的技巧集,如创业构思和论文选题。
当然也存在诸多平凡要素:勤奋工作、充足睡眠、规避压力、选择合适同事、掌握在非本职领域偷闲研究的技巧。任何阻碍伟大工作的因素,其反面即是助力。这类要素初看平淡,实则不然。例如创新常与年轻相关联,但真正起作用的或许并非年龄本身,而是青春附带的健康与无负担。深入研究或可得出适用于各年龄段的创新策略。
And in such cases intelligence is even harder to distinguish from its consequences. [3] Some would attribute the difference between intelligence and having new ideas to "creativity," but this doesn't seem a very useful term. As well as being pretty vague, it's shifted half a frame sideways from what we care about: it's neither separable from intelligence, nor responsible for all the difference between intelligence and having new ideas. [4] Curiously enough, this essay is an example. It started out as an essay about writing ability. But when I came to the distinction between intelligence and having new ideas, that seemed so much more important that I turned the original essay inside out, making that the topic and my original topic one of the points in it. As in many other fields, that level of reworking is easier to contemplate once you've had a lot of practice. Thanks to Trevor Blackwell, Patrick Collison, Jessica Livingston, Robert Morris, Michael Nielsen, and Lisa Randall for reading drafts of this..
最令人意外的创新要素当属写作能力。某类新思想唯有通过撰写文章和书籍才能被发现。此处"通过"二字用意深刻:你不是先有想法再记录,而是通过写作本身进行思考。若文笔笨拙或厌恶写作,这种思考方式就会受阻[4]。
我预言智力与创新之间的鸿沟将成为有趣的探索领域。若仅将其视为未开发潜力的量尺,它就是我们避之不及的荒原。但若转换视角,探寻其中隐含的其他创新要素,我们就能在这片裂隙中发掘关于"发现"本身的新发现。
注释 [1] 话语权的决胜因素因对象而异:底层靠蛮横,中层凭机敏,顶层近智慧,但机敏始终贯穿其中。 [2] 如同智力只是创新要素之一,创新也只是智力的用途之一。智力亦可用于问题诊断与解决——这些与创新有交集,但也有独立领域。 [3] 有人将智力与创新的差异归因于"创造力",但这个模糊概念偏离了核心:它既无法与智力割裂,又不能解释全部差异。 [4] 本文恰成例证:原拟探讨写作能力,但智力与创新的分野显得更为重要,遂将全文重构。这种颠覆性调整需经长期写作训练方能驾驭。
致谢 感谢特雷弗·布莱克韦尔、帕特里克·科利森等诸位审阅草稿。
August 2021 When people say that in their experience all programming languages are basically equivalent, they're making a statement not about languages but about the kind of programming they've done. 99.5% of programming consists of gluing together calls to library functions. All popular languages are equally good at this. So one can easily spend one's whole career operating in the intersection of popular programming languages. But the other .5% of programming is disproportionately interesting. If you want to learn what it consists of, the weirdness of weird languages is a good clue to follow. Weird languages aren't weird by accident. Not the good ones, at least. The weirdness of the good ones usually implies the existence of some form of programming that's not just the usual gluing together of library calls. A concrete example: Lisp macros. Lisp macros seem weird even to many Lisp programmers. They're not only not in the intersection of popular languages, but by their nature would be hard to implement properly in a language without turning it into a dialect of Lisp. And macros are definitely evidence of techniques that go beyond glue programming. For example, solving problems by first writing a language for problems of that type, and then writing your specific application in it. Nor is this all you can do with macros; it's just one region in a space of program-manipulating techniques that even now is far from fully explored. So if you want to expand your concept of what programming can be, one way to do it is by learning weird languages. Pick a language that most programmers consider weird but whose median user is smart, and then focus on the differences between this language and the intersection of popular languages.
What can you say in this language that would be impossibly inconvenient to say in others? In the process of learning how to say things you couldn't previously say, you'll probably be learning how to think things you couldn't previously think. Thanks to Trevor Blackwell, Patrick Collison, Daniel Gackle, Amjad Masad, and Robert Morris for reading drafts of this.
2021年8月 当人们说根据他们的经验,所有编程语言基本都差不多时,他们其实不是在谈论语言本身,而是在描述他们所从事的编程类型。 99.5%的编程工作不过是把各种库函数调用粘合在一起。所有流行语言在这方面都同样出色。因此,人们很容易在整个职业生涯中都只使用流行语言的共有功能。 但剩下的0.5%编程工作却格外有趣。如果你想了解这部分内容,那些"怪异"语言的独特之处就是很好的线索。 怪异语言的"怪异"并非偶然。至少优秀的怪异语言不是这样。优秀怪异语言的独特性往往意味着存在某种超越常规库函数粘合的编程范式。 举个具体例子:Lisp宏。即使对许多Lisp程序员来说,宏也显得很怪异。它们不仅不在流行语言的共有功能中,而且从本质上说,要想在非Lisp语言中正确实现宏,几乎必然要把该语言变成Lisp的方言。宏的存在明确证明了存在超越"粘合编程"的技术。比如先为某类问题创建专用语言,再用该语言编写具体应用的解题方式。宏的潜力远不止于此——它只是程序操控技术领域中一个尚未被完全探索的维度。 因此,如果你想拓展对编程可能性的认知,学习怪异语言是个好方法。选择一种多数程序员认为怪异、但其用户群体普遍聪明的语言,重点关注它与主流语言的差异之处。用这种语言能表达哪些在其他语言中难以实现的想法?在学习表达新概念的过程中,你很可能会习得全新的思维方式。 致谢:感谢Trevor Blackwell、Patrick Collison、Daniel Gackle、Amjad Masad和Robert Morris审阅本文草稿。
June 2021 It might not seem there's much to learn about how to work hard. Anyone who's been to school knows what it entails, even if they chose not to do it. There are 12 year olds who work amazingly hard. And yet when I ask if I know more about working hard now than when I was in school, the answer is definitely yes. One thing I know is that if you want to do great things, you'll have to work very hard. I wasn't sure of that as a kid. Schoolwork varied in difficulty; one didn't always have to work super hard to do well. And some of the things famous adults did, they seemed to do almost effortlessly. Was there, perhaps, some way to evade hard work through sheer brilliance? Now I know the answer to that question. There isn't. The reason some subjects seemed easy was that my school had low standards. And the reason famous adults seemed to do things effortlessly was years of practice; they made it look easy. Of course, those famous adults usually had a lot of natural ability too. There are three ingredients in great work: natural ability, practice, and effort. You can do pretty well with just two, but to do the best work you need all three: you need great natural ability _and_ to have practiced a lot _and_ to be trying very hard. [1] Bill Gates, for example, was among the smartest people in business in his era, but he was also among the hardest working. "I never took a day off in my twenties," he said. "Not one." It was similar with Lionel Messi. He had great natural ability, but when his youth coaches talk about him, what they remember is not his talent but his dedication and his desire to win. P. G. Wodehouse would probably get my vote for best English writer of the 20th century, if I had to choose. Certainly no one ever made it look easier. But no one ever worked harder. At 74, he wrote > with each new book of mine I have, as I say, the feeling that this time I have picked a lemon in the garden of literature.
关于如何努力工作,似乎没什么可学的。上过学的人都知道这意味着什么,哪怕他们选择不去努力。有些12岁的孩子就非常用功。但当我问自己,我现在是否比上学时更懂得如何努力工作时,答案无疑是肯定的。
我深知的一点是,如果你想成就伟大的事业,就必须非常努力。小时候我并不确定这一点。学校作业的难度参差不齐;有时不需要特别努力就能取得好成绩。而一些著名成年人所做的事,看起来几乎毫不费力。是否有可能凭借纯粹的才华逃避艰苦的工作?现在我知道答案了。不可能。
有些科目看起来简单,是因为我的学校标准太低。而那些著名成年人看似轻松的背后,是多年的练习;他们只是让事情看起来容易罢了。
A good thing, really, I suppose. Keeps one up on one's toes and makes one rewrite every sentence ten times. Or in many cases twenty times..
当然,这些著名成年人通常也拥有极高的天赋。伟大的工作需要三个要素:天赋、练习和努力。仅凭其中两点,你也能做得不错,但要做到最好,三者缺一不可:你需要非凡的天赋、大量的练习,以及全力以赴的拼搏。[1]
以比尔·盖茨为例,他不仅是那个时代商界最聪明的人之一,也是最勤奋的人之一。“我二十多岁时从未休息过一天,”他说,“一天都没有。”莱昂内尔·梅西也是如此。他天赋异禀,但他的青训教练谈起他时,印象深刻的不是他的才华,而是他的奉献精神和求胜欲望。如果要我投票选出20世纪最优秀的英语作家,我可能会选P.G.伍德豪斯。当然,没人能让写作看起来比他更轻松。但也没人比他更努力。74岁时,他写道:
> 每次开始写新书时,我都觉得这次自己在文学园地里摘了个酸柠檬。我想这其实是件好事。它让人保持警觉,迫使我把每个句子重写十遍。很多时候甚至是二十遍。
Sounds a bit extreme, you think. And yet Bill Gates sounds even more extreme. Not one day off in ten years? These two had about as much natural ability as anyone could have, and yet they also worked about as hard as anyone could work. You need both. That seems so obvious, and yet in practice we find it slightly hard to grasp. There's a faint xor between talent and hard work. It comes partly from popular culture, where it seems to run very deep, and partly from the fact that the outliers are so rare. If great talent and great drive are both rare, then people with both are rare squared. Most people you meet who have a lot of one will have less of the other. But you'll need both if you want to be an outlier yourself. And since you can't really change how much natural talent you have, in practice doing great work, insofar as you can, reduces to working very hard. It's straightforward to work hard if you have clearly defined, externally imposed goals, as you do in school. There is some technique to it: you have to learn not to lie to yourself, not to procrastinate (which is a form of lying to yourself), not to get distracted, and not to give up when things go wrong. But this level of discipline seems to be within the reach of quite young children, if they want it. What I've learned since I was a kid is how to work toward goals that are neither clearly defined nor externally imposed. You'll probably have to learn both if you want to do really great things. The most basic level of which is simply to feel you should be working without anyone telling you to. Now, when I'm not working hard, alarm bells go off. I can't be sure I'm getting anywhere when I'm working hard, but I can be sure I'm getting nowhere when I'm not, and it feels awful. [2] There wasn't a single point when I learned this. Like most little kids, I enjoyed the feeling of achievement when I learned or did something new.
听起来有点极端,你想。而比尔·盖茨的话听起来更极端。十年间没有休息过一天?这两个人拥有常人难以企及的天赋,却也付出了常人难以想象的努力。二者缺一不可。
这道理看似显而易见,但在现实中我们却有点难以把握。天赋与努力之间似乎存在一种微妙的排他性。这种错觉部分源于流行文化——它似乎根深蒂固,部分源于顶尖人才实在稀少。如果卓越天赋和强大驱动力都很罕见,那么同时具备两者的人就更是凤毛麟角。你遇到的大多数人,往往在某一方面突出,另一方面就有所欠缺。但如果你想成为顶尖人物,两者都必须具备。既然你无法改变与生俱来的天赋,那么在实践中,想要做出杰出成就,就只剩下拼命努力这一条路。
如果目标明确且由外界设定(比如在学校时),努力并不难。这需要一些技巧:你必须学会不自欺、不拖延(拖延也是自欺的一种)、不分心,遇到困难时不放弃。但只要能下定决心,这种程度的自律连小孩子也能做到。
As I grew older, this morphed into a feeling of disgust when I wasn't achieving anything. The one precisely dateable landmark I have is when I stopped watching TV, at age 13. Several people I've talked to remember getting serious about work around this age. When I asked Patrick Collison when he started to find idleness distasteful, he said.
我从小时候到现在学会的,是如何朝着既不明确定义、也非外界强加的目标努力。要想成就真正伟大的事业,这两者可能都得掌握。
最基础的层面是,即使没人要求,你也觉得自己应该工作。现在,如果我不努力工作,警铃就会在脑中响起。我无法确定努力工作时是否有所进展,但可以确定不工作时必定一事无成——这种感觉糟透了。[2]
我并非在某个瞬间突然领悟这点。和大多数孩子一样,我小时候会因为学会或做成新事物而获得成就感。随着年龄增长,这种感受逐渐转变为:当毫无建树时,我会感到厌恶。我能明确追溯的一个节点是13岁那年,我戒掉了看电视的习惯。
与我交谈过的几个人都记得,他们在这个年纪左右开始认真对待工作。当我问帕特里克·科里森何时开始觉得虚度光阴令人不适时,他说:
> I think around age 13 or 14. I have a clear memory from around then of sitting in the sitting room, staring outside, and wondering why I was wasting my summer holiday.
> 大概是13或14岁。我清楚记得那时坐在客厅里望着窗外,疑惑自己为何要浪费整个暑假。
或许在青春期会发生某种转变。这倒也合乎情理。
奇怪的是,认真对待工作的最大障碍或许正是学校——它让所谓"工作"显得枯燥而无意义。我必须先理解真正的工作是什么,才能全心全意渴望投入其中。这花费了不少时间,因为即便在大学阶段,许多课业仍毫无意义;某些院系的存在本身就是无意义的。但当我逐渐领悟真正工作的形态时,我发现对工作的渴望与之完美契合,仿佛它们本就是天造地设的一对。
Perhaps something changes at adolescence. That would make sense. Strangely enough, the biggest obstacle to getting serious about work was probably school, which made work (what they called work) seem boring and pointless. I had to learn what real work was before I could wholeheartedly desire to do it. That took a while, because even in college a lot of the work is pointless; there are entire departments that are pointless. But as I learned the shape of real work, I found that my desire to do it slotted into it as if they'd been made for each other. I suspect most people have to learn what work is before they can love it. Hardy wrote eloquently about this in _A Mathematician's Apology_ :
我猜想多数人需要先理解工作的本质,才可能爱上它。哈代在《一个数学家的辩白》中精彩地描述了这种体验:
> 我不记得童年时对数学怀有任何热情,当时对数学家生涯的想象也毫不崇高。我眼中的数学无非关乎考试与奖学金:我只想击败其他男孩,而数学似乎是最具决定性的取胜之道。
直到大学期间读到若尔当的《分析教程》,他才真正明白数学的本质:
> I do not remember having felt, as a boy, any _passion_ for mathematics, and such notions as I may have had of the career of a mathematician were far from noble. I thought of mathematics in terms of examinations and scholarships: I wanted to beat other boys, and this seemed to be the way in which I could do so most decisively.
> 我永远无法忘记阅读这部杰作时的震撼——它曾激励我们这代无数数学家,当我初次通过它领悟数学真谛时,那种惊艳之感永生难忘。
要理解什么是真正的工作,你需要学会辨别两种不同的虚假形式。一种是哈代在学校里遇到的那种。当学科被改编用于教学时,它们往往被扭曲——有时扭曲到与实际从业者所做的工作毫无相似之处。[3] 另一种虚假性则内在于某些类型的工作中。有些工作本质上是虚假的,或者充其量只是无意义的忙碌。
真正的工作有一种坚实的特质。并非所有工作都像撰写《自然哲学的数学原理》那样伟大,但它们都让人感到必要。这是一个模糊的标准,但它是故意模糊的,因为它需要涵盖许多不同类型的工作。[4]
一旦你了解了真正工作的形态,你就需要学会每天投入多少时间。你不能简单地通过醒着的每一刻都在工作来解决这个问题,因为在许多类型的工作中,超过某个临界点后,成果的质量就会开始下降。
He didn't learn what math was really about till part way through college, when he read Jordan's _Cours d'analyse_.
这个限制因工作类型和个人而异。我从事过几种不同类型的工作,每种工作的限制都不同。对于较难的写作或编程工作,我的极限大约是每天五个小时。而当我经营一家初创公司时,我可以全天候工作。至少在我这么做的三年里是这样;如果持续更长时间,我可能偶尔需要休假。[5]
找到工作极限的唯一方法是超越它。培养对你所做工作质量的敏感度,这样你就能注意到是否因为过度工作而导致质量下降。在这里,诚实至关重要,无论是哪个方向:你必须注意到自己何时懒惰,也要注意到何时过度工作。如果你认为过度工作是一种值得钦佩的行为,请摒弃这种想法。你不仅会得到更差的结果,而且这些结果是因为你在炫耀——如果不是向别人炫耀,那就是在向自己炫耀。[6]
找到努力工作的极限是一个持续不断的过程,而不是一次性的事情。工作的难度和你完成它的能力每小时都可能变化,因此你需要不断评估你投入的努力程度和你表现的好坏。
> I shall never forget the astonishment with which I read that remarkable work, the first inspiration for so many mathematicians of my generation, and learnt for the first time as I read it what mathematics really meant.
然而,努力尝试并不意味着不断强迫自己工作。可能有些人会这样做,但我认为我的经历相当典型,我只需要在开始一个项目或遇到某种障碍时偶尔强迫自己。那是我容易拖延的时候。但一旦我进入状态,我就会继续下去。
让我持续工作的动力取决于工作的类型。当我开发Viaweb时,驱使我的是对失败的恐惧。那时我几乎从不拖延,因为总有事情需要做,如果我能通过做这些事情拉开与追赶者的距离,为什么要等待?[7] 而现在,驱动我写作的是文章中的缺陷。在文章之间,我会纠结几天,就像一只狗在决定躺下的确切位置前转圈。但一旦我开始写一篇,我就不需要强迫自己工作,因为总有一些错误或遗漏在推动我。
我会在一定程度上努力专注于重要的话题。许多问题的核心是困难的,周围则是较容易的部分。努力工作意味着尽可能瞄准核心。有些日子你可能做不到;有些日子你只能处理外围的简单内容。但你应该始终在不陷入停滞的情况下尽可能接近核心。
There are two separate kinds of fakeness you need to learn to discount in order to understand what real work is. One is the kind Hardy encountered in school. Subjects get distorted when they're adapted to be taught to kids — often so distorted that they're nothing like the work done by actual practitioners. [3] The other kind of fakeness is intrinsic to certain types of work. Some types of work are inherently bogus, or at best mere busywork. There's a kind of solidity to real work. It's not all writing the _Principia_ , but it all feels necessary. That's a vague criterion, but it's deliberately vague, because it has to cover a lot of different types. [4] Once you know the shape of real work, you have to learn how many hours a day to spend on it. You can't solve this problem by simply working every waking hour, because in many kinds of work there's a point beyond which the quality of the result will start to decline. That limit varies depending on the type of work and the person. I've done several different kinds of work, and the limits were different for each. My limit for the harder types of writing or programming is about five hours a day. Whereas when I was running a startup, I could work all the time. At least for the three years I did it; if I'd kept going much longer, I'd probably have needed to take occasional vacations. [5] The only way to find the limit is by crossing it. Cultivate a sensitivity to the quality of the work you're doing, and then you'll notice if it decreases because you're working too hard. Honesty is critical here, in both directions: you have to notice when you're being lazy, but also when you're working too hard. And if you think there's something admirable about working too hard, get that idea out of your head.
关于人生方向的更大问题就是这类核心难题之一。核心是重要但困难的问题,边缘则是较不重要且容易的问题。因此,除了在日常工作中进行小的调整外,你偶尔还需要对从事哪种工作做出重大的、人生尺度的调整。规则是一样的:努力工作意味着瞄准核心——瞄准最具雄心的难题。
不过,这里的“核心”指的是真正的核心,而不仅仅是当前的共识。关于哪些问题最重要的共识往往是错误的,无论是总体上还是在特定领域内。如果你不同意这种共识,而你是对的,这可能代表了一个做新事物的宝贵机会。
更具雄心的类型的工作通常会更难,但尽管你不应否认这一点,也不应将难度作为决定做什么的绝对指南。如果你发现某种雄心勃勃的工作对你来说比其他工作更容易——无论是由于你恰好拥有的能力,还是因为你找到了新的方法,或者仅仅是因为你对它更感兴趣——那么一定要从事这项工作。一些最好的工作是由那些找到简单方法解决难题的人完成的。
除了了解真正工作的形态外,你还需要弄清楚自己适合哪种类型。这不仅仅是找出你的天赋最适合哪种工作;并不是说如果你身高7英尺,你就必须打篮球。你适合什么不仅取决于你的才能,甚至可能更多地取决于你的兴趣。对一个话题的深度兴趣比任何纪律都能让人更努力地工作。
You're not merely getting worse results, but getting them because you're showing off — if not to other people, then to yourself. [6] Finding the limit of working hard is a constant, ongoing process, not something you do just once. Both the difficulty of the work and your ability to do it can vary hour to hour, so you need to be constantly judging both how hard you're trying and how well you're doing. Trying hard doesn't mean constantly pushing yourself to work, though. There may be some people who do, but I think my experience is fairly typical, and I only have to push myself occasionally when I'm starting a project or when I encounter some sort of check. That's when I'm in danger of procrastinating. But once I get rolling, I tend to keep going. What keeps me going depends on the type of work. When I was working on Viaweb, I was driven by fear of failure. I barely procrastinated at all then, because there was always something that needed doing, and if I could put more distance between me and the pursuing beast by doing it, why wait? [7] Whereas what drives me now, writing essays, is the flaws in them. Between essays I fuss for a few days, like a dog circling while it decides exactly where to lie down. But once I get started on one, I don't have to push myself to work, because there's always some error or omission already pushing me. I do make some amount of effort to focus on important topics. Many problems have a hard core at the center, surrounded by easier stuff at the edges. Working hard means aiming toward the center to the extent you can. Some days you may not be able to; some days you'll only be able to work on the easier, peripheral stuff. But you should always be aiming as close to the center as you can without stalling. The bigger question of what to do with your life is one of these problems with a hard core. There are important problems at the center, which tend to be hard, and less important, easier ones at the edges.
发现你的兴趣可能比发现你的才能更难。才能的类型比兴趣少,而且才能从童年早期就开始被评判,而对一个话题的兴趣是一种微妙的东西,可能直到二十多岁甚至更晚才会成熟。这个话题甚至可能在那之前并不存在。此外,你还需要学会忽略一些强大的错误来源。你是真的对x感兴趣,还是因为你想赚很多钱,或者因为别人会对你印象深刻,或者因为你的父母希望你这样做?[8]
弄清楚该做什么的难度因人而异。这是我从小时候以来关于工作学到的最重要的事情之一。小时候,你会觉得每个人都有一种使命,他们只需要弄清楚它是什么。电影和给孩子们看的简化传记中就是这样描述的。有时现实生活也是如此。有些人像莫扎特一样,从小就知道该做什么并去做。但其他人,像牛顿一样,会不安地从一种工作转向另一种工作。也许回顾过去,我们可以将其中一种视为他们的使命——我们希望牛顿花更多时间在数学和物理上,而不是炼金术和神学上——但这是由后见之明导致的错觉。并没有他能听到的声音在召唤他。
因此,虽然有些人的生活很快聚焦,但也有些人的人生永远不会聚焦。对于这些人来说,弄清楚该做什么与其说是努力工作的前奏,不如说是其中的一个持续部分,就像一组联立方程中的一个。对于这些人来说,我之前描述的过程有第三个组成部分:除了衡量你工作的努力程度和表现的好坏外,你还需要思考是否应该继续在这个领域工作还是转向另一个领域。如果你工作努力但没有得到足够好的结果,你应该转向。这样表达听起来很简单,但在实践中非常困难。你不应该因为第一天努力工作却毫无进展就放弃。你需要给自己时间去启动。但多少时间?如果原本进展顺利的工作突然不顺利了,你该怎么办?那时你给自己多少时间?[9]
So as well as the small, daily adjustments involved in working on a specific problem, you'll occasionally have to make big, lifetime-scale adjustments about which type of work to do. And the rule is the same: working hard means aiming toward the center — toward the most ambitious problems. By center, though, I mean the actual center, not merely the current consensus about the center. The consensus about which problems are most important is often mistaken, both in general and within specific fields. If you disagree with it, and you're right, that could represent a valuable opportunity to do something new. The more ambitious types of work will usually be harder, but although you should not be in denial about this, neither should you treat difficulty as an infallible guide in deciding what to do. If you discover some ambitious type of work that's a bargain in the sense of being easier for you than other people, either because of the abilities you happen to have, or because of some new way you've found to approach it, or simply because you're more excited about it, by all means work on that. Some of the best work is done by people who find an easy way to do something hard. As well as learning the shape of real work, you need to figure out which kind you're suited for. And that doesn't just mean figuring out which kind your natural abilities match the best; it doesn't mean that if you're 7 feet tall, you have to play basketball. What you're suited for depends not just on your talents but perhaps even more on your interests. A _deep interest_ in a topic makes people work harder than any amount of discipline can. It can be harder to discover your interests than your talents. There are fewer types of talent than interest, and they start to be judged early in childhood, whereas interest in a topic is a subtle thing that may not mature till your twenties, or even later. The topic may not even exist earlier.
什么才算好结果?这可能真的很难判断。如果你正在探索一个很少有人涉足的领域,你可能甚至不知道好结果是什么样子。历史上充满了人们错误判断自己工作重要性的例子。
判断某项工作是否值得做的最佳标准是你是否觉得它有趣。这听起来像是一个危险的主观标准,但它可能是你能得到的最准确的。你是做这件事的人。谁比你更有资格判断它是否重要?有什么比它是否有趣更能预测它的重要性?
然而,要让这个测试有效,你必须对自己诚实。事实上,这是关于努力工作整个问题中最引人注目的一点:在每个环节,它都依赖于你对自己诚实。
Plus there are some powerful sources of error you need to learn to discount. Are you really interested in x, or do you want to work on it because you'll make a lot of money, or because other people will be impressed with you, or because your parents want you to? [8] The difficulty of figuring out what to work on varies enormously from one person to another. That's one of the most important things I've learned about work since I was a kid. As a kid, you get the impression that everyone has a calling, and all they have to do is figure out what it is. That's how it works in movies, and in the streamlined biographies fed to kids. Sometimes it works that way in real life. Some people figure out what to do as children and just do it, like Mozart. But others, like Newton, turn restlessly from one kind of work to another. Maybe in retrospect we can identify one as their calling — we can wish Newton spent more time on math and physics and less on alchemy and theology — but this is an _illusion_ induced by hindsight bias. There was no voice calling to him that he could have heard. So while some people's lives converge fast, there will be others whose lives never converge. And for these people, figuring out what to work on is not so much a prelude to working hard as an ongoing part of it, like one of a set of simultaneous equations. For these people, the process I described earlier has a third component: along with measuring both how hard you're working and how well you're doing, you have to think about whether you should keep working in this field or switch to another. If you're working hard but not getting good enough results, you should switch. It sounds simple expressed that way, but in practice it's very difficult. You shouldn't give up on the first day just because you work hard and don't get anywhere. You need to give yourself time to get going.
努力工作不仅仅是一个可以调到11的刻度盘。它是一个复杂的动态系统,必须在每个环节都调整得恰到好处。你必须了解真正工作的形态,清楚地看到你最适合哪种类型,尽可能瞄准其真正的核心,在每个时刻准确判断你的能力和表现,并在不损害结果质量的情况下每天投入尽可能多的时间。这个网络太复杂,无法欺骗。但如果你始终诚实和清醒,它会自动呈现出最佳状态,你会以一种很少有人能做到的方式高效工作。
[1] 在《天才的公交车票理论》中,我说伟大工作的三个要素是天赋、决心和兴趣。这是前一阶段的公式;决心和兴趣产生练习和努力。
[2] 我指的是以天为单位的分辨率,而不是小时。你常常会在不工作时取得进展,比如在淋浴时或甚至在睡觉时想到问题的解决方案,但这只是因为前一天你在努力解决它。
偶尔去度假是好的,但当我度假时,我喜欢学习新东西。我不喜欢只是坐在海滩上。
But how much time? And what should you do if work that was going well stops going well? How much time do you give yourself then? [9] What even counts as good results? That can be really hard to decide. If you're exploring an area few others have worked in, you may not even know what good results look like. History is full of examples of people who misjudged the importance of what they were working on. The best test of whether it's worthwhile to work on something is whether you find it interesting. That may sound like a dangerously subjective measure, but it's probably the most accurate one you're going to get. You're the one working on the stuff. Who's in a better position than you to judge whether it's important, and what's a better predictor of its importance than whether it's interesting? For this test to work, though, you have to be honest with yourself. Indeed, that's the most striking thing about the whole question of working hard: how at each point it depends on being honest with yourself. Working hard is not just a dial you turn up to 11. It's a complicated, dynamic system that has to be tuned just right at each point. You have to understand the shape of real work, see clearly what kind you're best suited for, aim as close to the true core of it as you can, accurately judge at each moment both what you're capable of and how you're doing, and put in as many hours each day as you can without harming the quality of the result. This network is too complicated to trick. But if you're consistently honest and clear-sighted, it will automatically assume an optimal shape, and you'll be productive in a way few people are. Notes [1] In "The Bus Ticket Theory of Genius" I said the three ingredients in great work were natural ability, determination, and interest.
[3] 孩子们在学校里做的最接近真实版本的事情是体育。诚然,这是因为许多体育运动起源于学校的游戏。但至少在这一领域,孩子们做的正是成年人做的。
在美国普通高中,你可以选择假装做严肃的事情,或者认真地做假装的事情。可以说后者并不更糟。
[4] 知道你想做什么并不意味着你就能做到。大多数人不得不花很多时间做他们不想做的事情,尤其是在早期。但如果你知道自己想做什么,你至少知道该朝哪个方向推动你的生活。
That's the formula in the preceding stage; determination and interest yield practice and effort. [2] I mean this at a resolution of days, not hours. You'll often get somewhere while not working in the sense that the solution to a problem comes to you while taking a _shower_, or even in your sleep, but only because you were working hard on it the day before. It's good to go on vacation occasionally, but when I go on vacation, I like to learn new things. I wouldn't like just sitting on a beach. [3] The thing kids do in school that's most like the real version is sports. Admittedly because many sports originated as games played in schools. But in this one area, at least, kids are doing exactly what adults do. In the average American high school, you have a choice of pretending to do something serious, or seriously doing something pretend. Arguably the latter is no worse. [4] Knowing what you want to work on doesn't mean you'll be able to. Most people have to spend a lot of their time working on things they don't want to, especially early on. But if you know what you want to do, you at least know what direction to nudge your life in. [5] The lower time limits for intense work suggest a solution to the problem of having less time to work after you have kids: switch to harder problems. In effect I did that, though not deliberately. [6] Some cultures have a tradition of performative hard work. I don't love this idea, because (a) it makes a parody of something important and (b) it causes people to wear themselves out doing things that don't matter. I don't know enough to say for sure whether it's net good or bad, but my guess is bad. [7] One of the reasons people work so hard on startups is that startups can fail, and when they do, that failure tends to be both decisive and conspicuous. [8] It's ok to work on something to make a lot of money.
[5] 高强度工作的时间限制较短,这为解决有了孩子后工作时间减少的问题提供了一个方案:转向更难的问题。实际上我这样做了,尽管不是故意的。
[6] 一些文化有表演性努力工作的传统。我不喜欢这个观念,因为(a)它把重要的事情变成了滑稽戏,(b)它让人们在做无关紧要的事情时筋疲力尽。我不确定它总体上是有益还是有害,但我猜是有害的。
[7] 人们在初创公司如此努力工作的原因之一是初创公司可能会失败,而当它们失败时,这种失败往往是决定性的和引人注目的。
You need to solve the money problem somehow, and there's nothing wrong with doing that efficiently by trying to make a lot at once. I suppose it would even be ok to be interested in money for its own sake; whatever floats your boat. Just so long as you're conscious of your motivations. The thing to avoid is _unconsciously_ letting the need for money warp your ideas about what kind of work you find most interesting. [9] Many people face this question on a smaller scale with individual projects. But it's easier both to recognize and to accept a dead end in a single project than to abandon some type of work entirely. The more determined you are, the harder it gets. Like a Spanish Flu victim, you're fighting your own immune system: Instead of giving up, you tell yourself, I should just try harder. And who can say you're not right? Thanks to Trevor Blackwell, John Carmack, John Collison, Patrick Collison, Robert Morris, Geoff Ralston, and Harj Taggar for reading drafts of this.
[8] 为了赚很多钱而做某事是可以的。你需要以某种方式解决金钱问题,通过一次性赚很多钱来高效地解决这个问题并没有什么错。我想,甚至为了钱本身而对钱感兴趣也是可以的;只要你觉得开心。只要你是意识到自己的动机。要避免的是无意识地让对金钱的需求扭曲你对最感兴趣的工作类型的看法。
[9] 许多人在单个项目的较小范围内面临这个问题。但认识到并接受单个项目的死胡同比完全放弃某种类型的工作要容易得多。你越坚定,就越难做到。就像西班牙流感的受害者一样,你是在与自己的免疫系统作斗争:你不会放弃,而是告诉自己,我应该更努力。谁能说你不对呢?
致谢 感谢Trevor Blackwell、John Carmack、John Collison、Patrick Collison、Robert Morris、Geoff Ralston和Harj Taggar阅读本文的草稿。
June 2021 A few days ago, on the way home from school, my nine year old son told me he couldn't wait to get home to write more of the story he was working on. This made me as happy as anything I've heard him say — not just because he was excited about his story, but because he'd discovered this way of working. Working on a project of your own is as different from ordinary work as skating is from walking. It's more fun, but also much more productive. What proportion of great work has been done by people who were skating in this sense? If not all of it, certainly a lot. There is something special about working on a project of your own. I wouldn't say exactly that you're happier. A better word would be excited, or engaged. You're happy when things are going well, but often they aren't. When I'm writing an essay, most of the time I'm worried and puzzled: worried that the essay will turn out badly, and puzzled because I'm groping for some idea that I can't see clearly enough. Will I be able to pin it down with words? In the end I usually can, if I take long enough, but I'm never sure; the first few attempts often fail. You have moments of happiness when things work out, but they don't last long, because then you're on to the next problem. So why do it at all? Because to the kind of people who like working this way, nothing else feels as right. You feel as if you're an animal in its natural habitat, doing what you were meant to do — not always happy, maybe, but awake and alive. Many kids experience the excitement of working on projects of their own. The hard part is making this converge with the work you do as an adult. And our customs make it harder. We treat "playing" and "hobbies" as qualitatively different from "work". It's not clear to a kid building a treehouse that there's a direct (though long) route from that to architecture or engineering.
几天前,我九岁的儿子放学回家路上告诉我,他迫不及待想回家继续写他正在创作的故事。这句话让我感到无比欣慰——不仅因为他为自己的故事兴奋,更因为他发现了这种工作方式。为自己项目奋斗的感觉,就像滑冰之于步行般与众不同。它更有趣,同时也高效得多。
历史上多少伟大成果诞生于这种"滑冰式"工作?即便不是全部,也必定占据极大比重。
为自己项目奋斗有种特殊魔力。与其说是更快乐,不如说是更兴奋、更投入。顺利时固然欣喜,但挫折才是常态。当我撰写文章时,多数时间都在焦虑与困惑中度过:担心文章质量,又因捕捉模糊的灵感而绞尽脑汁。最终总能找到恰当表达,但前几次尝试往往失败。
And instead of pointing out the route, we conceal it, by implicitly treating the stuff kids do as different from real work. [1] Instead of telling kids that their treehouses could be on the path to the work they do as adults, we tell them the path goes through school. And unfortunately schoolwork tends to be very different from working on projects of one's own. It's usually neither a project, nor one's own. So as school gets more serious, working on projects of one's own is something that survives, if at all, as a thin thread off to the side. It's a bit sad to think of all the high school kids turning their backs on building treehouses and sitting in class dutifully learning about Darwin or Newton to pass some exam, when the work that made Darwin and Newton famous was actually closer in spirit to building treehouses than studying for exams. If I had to choose between my kids getting good grades and working on ambitious projects of their own, I'd pick the projects. And not because I'm an indulgent parent, but because I've been on the other end and I know which has more predictive value. When I was picking startups for Y Combinator, I didn't care about applicants' grades. But if they'd worked on projects of their own, I wanted to hear all about those. [2] It may be inevitable that school is the way it is. I'm not saying we have to redesign it (though I'm not saying we don't), just that we should understand what it does to our attitudes to work — that it steers us toward the dutiful plodding kind of work, often using competition as bait, and away from skating. There are occasionally times when schoolwork becomes a project of one's own. Whenever I had to write a paper, that would become a project of my own — except in English classes, ironically, because the things one has to write in English classes are so _bogus_. And when I got to college and started taking CS classes, the programs I had to write became projects of my own.
突破时的喜悦转瞬即逝,因为新问题接踵而至。为何还要坚持?因为对钟情此道者而言,这才是生命应有的状态。就像回归自然栖息地的动物,虽非时刻快乐,却始终清醒而鲜活。
许多孩子都体验过这种创造激情,难的是将之延续至成人世界。社会习俗更添阻碍——我们将"玩耍""爱好"与"工作"人为割裂。搭建树屋的孩子不会想到,这条路径(尽管漫长)直通建筑或工程领域。我们非但不指明道路,反而用"这不是正经事"的潜台词遮蔽了可能性。
我们告诉孩子通往成年的路径必须经过学校,却绝口不提树屋可能是起点。可悲的是,学业与自主项目天差地别:既非自主选择,亦非完整项目。随着课业加重,自主创作即便幸存,也沦为边缘的细线。
想到高中生们放弃搭建树屋,乖乖坐在教室为考试背诵达尔文理论,实在令人唏嘘。须知达尔文真正的精神更接近树屋建造,而非应试学习。
Whenever I was writing or programming, I was usually skating, and that has been true ever since. So where exactly is the edge of projects of one's own? That's an interesting question, partly because the answer is so complicated, and partly because there's so much at stake. There turn out to be two senses in which work can be one's own: 1) that you're doing it voluntarily, rather than merely because someone told you to, and 2) that you're doing it by yourself. The edge of the former is quite sharp. People who care a lot about their work are usually very sensitive to the difference between pulling, and being pushed, and work tends to fall into one category or the other. But the test isn't simply whether you're told to do something. You can choose to do something you're told to do. Indeed, you can own it far more thoroughly than the person who told you to do it. For example, math homework is for most people something they're told to do. But for my father, who was a mathematician, it wasn't. Most of us think of the problems in a math book as a way to test or develop our knowledge of the material explained in each section. But to my father the problems were the part that mattered, and the text was merely a sort of annotation. Whenever he got a new math book it was to him like being given a puzzle: here was a new set of problems to solve, and he'd immediately set about solving all of them. The other sense of a project being one's own — working on it by oneself — has a much softer edge. It shades gradually into collaboration. And interestingly, it shades into collaboration in two different ways. One way to collaborate is to share a single project. For example, when two mathematicians collaborate on a proof that takes shape in the course of a conversation between them. The other way is when multiple people work on separate projects of their own that fit together like a jigsaw puzzle.
若要在孩子取得高分与开展雄心项目间选择,我会毫不犹豫选择后者。这并非溺爱——作为过来人,我深知何者更具预测价值。在YC筛选初创企业时,我从不关心申请者成绩,但对他们的自主项目总是充满兴趣。
或许现行教育体制难以避免。我们不必立即重构它(虽然并非不可),但必须认清其如何扭曲我们的工作观——用竞争为诱饵,将人驯化为循规蹈矩的苦力,远离创造的本能。
学业偶尔也会蜕变为自主项目。我的课程论文常成为真正创作(英语课除外,因其命题作文实在荒谬)。大学接触计算机课程后,编程作业也成了我的激情项目。每当执笔或编程时,我都在"滑冰",这种状态延续至今。
那么自主项目的边界究竟何在?这个问题之所以有趣,既因答案复杂,更因事关重大。我们发现"自主性"包含两层含义:1)自愿而非被迫从事;2)独立完成。
For example, when one person writes the text of a book and another does the graphic design. [3] These two paths into collaboration can of course be combined. But under the right conditions, the excitement of working on a project of one's own can be preserved for quite a while before disintegrating into the turbulent flow of work in a large organization. Indeed, the history of successful organizations is partly the history of techniques for preserving that excitement. [4] The team that made the original Macintosh were a great example of this phenomenon. People like Burrell Smith and Andy Hertzfeld and Bill Atkinson and Susan Kare were not just following orders. They were not tennis balls hit by Steve Jobs, but rockets let loose by Steve Jobs. There was a lot of collaboration between them, but they all seem to have individually felt the excitement of working on a project of one's own. In Andy Hertzfeld's book on the Macintosh, he describes how they'd come back into the office after dinner and work late into the night. People who've never experienced the thrill of working on a project they're excited about can't distinguish this kind of working long hours from the kind that happens in sweatshops and boiler rooms, but they're at opposite ends of the spectrum. That's why it's a mistake to insist dogmatically on "work/life balance." Indeed, the mere expression "work/life" embodies a mistake: it assumes work and life are distinct. For those to whom the word "work" automatically implies the dutiful plodding kind, they are. But for the skaters, the relationship between work and life would be better represented by a dash than a slash. I wouldn't want to work on anything that I didn't want to take over my life. Of course, it's easier to achieve this level of motivation when you're making something like the Macintosh. It's easy for something new to feel like a project of your own.
前者的边界非常清晰。真正投入工作者对"自主驱动"与"外力推动"的区别极度敏感,工作往往非此即彼。但判断标准不在是否受人指派——你可以主动选择被分配的任务,甚至比指派者更全身心投入。
例如数学作业对多数人只是任务,但对我数学家父亲却非如此。我们视习题为检验知识的手段,他却视其为精髓,教材反成注解。每获新数学书,他都如获至宝般逐题攻克。
"独立完成"的边界则模糊得多,渐次过渡到协作状态。有趣的是,这种过渡有两种形式:一是共同推进同一项目(如数学家合作论证);二是各自完成能拼合成整体的独立项目(如文字作者与平面设计搭档)。
两种协作模式当然可以结合。在理想条件下,自主项目的激情能在大型组织的混沌中存续许久。成功组织的历史,某种程度上正是保存这种激情的技术演进史。
That's one of the reasons for the tendency programmers have to rewrite things that don't need rewriting, and to write their own versions of things that already exist. This sometimes alarms managers, and measured by total number of characters typed, it's rarely the optimal solution. But it's not always driven simply by arrogance or cluelessness. Writing code from scratch is also much more rewarding — so much more rewarding that a good programmer can end up net ahead, despite the shocking waste of characters. Indeed, it may be one of the advantages of capitalism that it encourages such rewriting. A company that needs software to do something can't use the software already written to do it at another company, and thus has to write their own, which often turns out better. [5] The natural alignment between skating and solving new problems is one of the reasons the payoffs from startups are so high. Not only is the market price of unsolved problems higher, you also get a discount on productivity when you work on them. In fact, you get a double increase in productivity: when you're doing a clean-sheet design, it's easier to recruit skaters, and they get to spend all their time skating. Steve Jobs knew a thing or two about skaters from having watched Steve Wozniak. If you can find the right people, you only have to tell them what to do at the highest level. They'll handle the details. Indeed, they insist on it. For a project to feel like your own, you must have sufficient autonomy. You can't be working to order, or _slowed down_ by bureaucracy. One way to ensure autonomy is not to have a boss at all. There are two ways to do that: to be the boss yourself, and to work on projects outside of work. Though they're at opposite ends of the scale financially, startups and open source projects have a lot in common, including the fact that they're often run by skaters.
初代Macintosh团队堪称典范。Burrell Smith、Andy Hertzfeld等成员绝非简单执行命令,他们不是被乔布斯击打的网球,而是他点燃的火箭。虽密切协作,但每个人都保持着为自己项目奋斗的激情。
Hertzfeld在书中描述团队如何晚餐后主动返回办公室通宵工作。未曾体验创作激情者,难以区分这种状态与血汗工厂的被迫加班,实则二者天差地别。这也解释了为何教条强调"工作/生活平衡"实属谬误——该表述本身就有问题,它假设工作与生活割裂。对将工作等同于苦役者确实如此,但对创造者而言,二者关系更该用连接号而非斜杠标示。若非甘愿让其占据生活,我根本不愿开展任何项目。
当然,开发Macintosh这类产品更容易激发这种状态。程序员总爱重写现有程序或开发同类产品,这种倾向常令管理者不安。若以代码量为标准,这绝非最优解。但驱动他们的不全是傲慢或无知——从零开始编码带来的满足感如此强烈,以致优秀程序员最终仍能领先,尽管看似浪费资源。资本主义的优势或许正在于鼓励这种重写:企业需定制软件时,无法直接套用现成方案,这种"浪费"反而催生更优解。
"滑冰"与解决新问题的天然契合,正是初创企业回报惊人的原因之一。未解问题不仅市场价值更高,你在解决时还能获得生产力加成——清洁设计既容易吸引创造者,又能让他们全程保持"滑冰"状态。
And indeed, there's a wormhole from one end of the scale to the other: one of the best ways to discover _startup ideas_ is to work on a project just for fun. If your projects are the kind that make money, it's easy to work on them. It's harder when they're not. And the hardest part, usually, is morale. That's where adults have it harder than kids. Kids just plunge in and build their treehouse without worrying about whether they're wasting their time, or how it compares to other treehouses. And frankly we could learn a lot from kids here. The high standards most grownups have for "real" work do not always serve us well. The most important phase in a project of one's own is at the beginning: when you go from thinking it might be cool to do x to actually doing x. And at that point high standards are not merely useless but positively harmful. There are a few people who start too many new projects, but far more, I suspect, who are deterred by fear of failure from starting projects that would have succeeded if they had. But if we couldn't benefit as kids from the knowledge that our treehouses were on the path to grownup projects, we can at least benefit as grownups from knowing that our projects are on a path that stretches back to treehouses. Remember that careless confidence you had as a kid when starting something new? That would be a powerful thing to recapture. If it's harder as adults to retain that kind of confidence, we at least tend to be more aware of what we're doing. Kids bounce, or are herded, from one kind of work to the next, barely realizing what's happening to them. Whereas we know more about different types of work and have more control over which we do. Ideally we can have the best of both worlds: to be deliberate in choosing to work on projects of our own, and carelessly confident in starting new ones. Notes [1] "Hobby" is a curious word.
乔布斯从沃兹尼亚克身上深谙创造者特质:找到对的人,只需指明方向,细节自会完美解决。要维持项目自主感,必须拥有充分自治权——不受官僚程序拖累,拒绝按订单生产。
确保自治的方法之一是完全不要上司。这有两种实现路径:自己当老板,或在正职外开展项目。初创企业与开源项目虽财力悬殊,却共享许多特质,包括常由创造者主导。二者间甚至存在虫洞:为兴趣而做的项目往往孕育最佳创业点子。
盈利项目容易坚持,非盈利项目则困难得多,最难的是保持士气。这正是成人不如孩子之处——孩子会毫不犹豫搭建树屋,既不担心浪费时间,也不比较优劣。坦率说,我们真该向孩子学习。成年人对"正经工作"的严苛标准往往弊大于利。
自主项目最重要的阶段是起步期——从"做X可能很酷"到真正实践X的跨越。此时高标准非但无用,反而有害。世上鲜少有人启动过多项目,却有无数人因恐惧失败而放弃本可成功的尝试。
Now it means work that isn't _real_ work — work that one is not to be judged by — but originally it just meant an obsession in a fairly general sense (even a political opinion, for example) that one metaphorically rode as a child rides a hobby-horse. It's hard to say if its recent, narrower meaning is a change for the better or the worse. For sure there are lots of false positives — lots of projects that end up being important but are dismissed initially as mere hobbies. But on the other hand, the concept provides valuable cover for projects in the early, ugly duckling phase. [2] Tiger parents, as parents so often do, are fighting the last war. Grades mattered more in the old days when the route to success was to acquire _credentials_ while ascending some predefined ladder. But it's just as well that their tactics are focused on grades. How awful it would be if they invaded the territory of projects, and thereby gave their kids a distaste for this kind of work by forcing them to do it. Grades are already a grim, fake world, and aren't harmed much by parental interference, but working on one's own projects is a more delicate, private thing that could be damaged very easily. [3] The complicated, gradual edge between working on one's own projects and collaborating with others is one reason there is so much disagreement about the idea of the "lone genius." In practice people collaborate (or not) in all kinds of different ways, but the idea of the lone genius is definitely not a myth. There's a core of truth to it that goes with a certain way of working. [4] Collaboration is powerful too. The optimal organization would combine collaboration and ownership in such a way as to do the least damage to each.
既然童年时未能意识到树屋是成人项目的起点,成年后的我们至少该明白,当下项目与儿时树屋同属一条光谱。还记得儿时开始新事物时那种无所畏惧的自信吗?重获这种心态将带来巨大力量。
若成人难以保持这种自信,至少我们对自身行为更具觉察力。孩子在各类任务间被动切换,浑然不觉其中差异;而我们既了解工作类型,又能自主选择。理想状态下,我们可兼得二者优势:审慎选择自主项目,又带着儿时般的无畏开启新篇章。
注释 [1] "爱好"是个耐人寻味的词。如今它意指非正经工作——不被严肃评价之事——但原义泛指任何执念(甚至包括政治观点),如同孩童骑木马。很难说词义窄化是好是坏:一方面许多重要项目初期常被误判为"纯爱好";另一方面这个概念为丑小鸭阶段的项目提供了保护伞。
[2] 虎妈虎爸们像多数家长一样在打上一场战争。在凭学历攀登预设阶梯的年代,成绩确实重要。但庆幸他们只盯着分数——若将控制欲延伸至项目领域,强迫孩子从事此类工作反而会扼杀兴趣。分数本就是虚假战场,父母干预无伤大雅;但自主项目如同精密仪器,稍加干涉便可能永久损坏。
Interestingly, companies and university departments approach this ideal from opposite directions: companies insist on collaboration, and occasionally also manage both to recruit skaters and allow them to skate, and university departments insist on the ability to do independent research (which is by custom treated as skating, whether it is or not), and the people they hire collaborate as much as they choose. [5] If a company could design its software in such a way that the best newly arrived programmers always got a clean sheet, it could have a kind of eternal youth. That might not be impossible. If you had a software backbone defining a game with sufficiently clear rules, individual programmers could write their own players. Thanks to Trevor Blackwell, Paul Buchheit, Andy Hertzfeld, Jessica Livingston, and Peter Norvig for reading drafts of this..
[3] 自主项目与协作间复杂渐变的边界,正是关于"孤独天才"争论不休的原因。实践中协作形式千差万别,但孤独天才绝非神话——某些工作方式确实需要这种特质。
[4] 协作同样强大。理想组织应平衡协作与自主,将二者损伤降至最低。有趣的是,企业与大学从相反方向逼近这个理想:企业强制协作,偶尔也允许创造者自由发挥;大学强调独立研究(无论实际是否为创造性工作),学者们按意愿协作。
[5] 若企业能设计出让新锐程序员始终从零开始的软件架构,或将永葆青春。这并非天方夜谭——用明确规则构建软件框架后,程序员可各自编写独立模块。
致谢 感谢Trevor Blackwell等人审阅本文草稿。
May 2021 There's one kind of opinion I'd be very afraid to express publicly. If someone I knew to be both a domain expert and a reasonable person proposed an idea that sounded preposterous, I'd be very reluctant to say "That will never work." Anyone who has studied the history of ideas, and especially the history of science, knows that's how big things start. Someone proposes an idea that sounds crazy, most people dismiss it, then it gradually takes over the world. Most implausible-sounding ideas are in fact bad and could be safely dismissed. But not when they're proposed by reasonable domain experts. If the person proposing the idea is reasonable, then they know how implausible it sounds. And yet they're proposing it anyway. That suggests they know something you don't. And if they have deep domain expertise, that's probably the source of it. [1] Such ideas are not merely unsafe to dismiss, but disproportionately likely to be interesting. When the average person proposes an implausible-sounding idea, its implausibility is evidence of their incompetence. But when a reasonable domain expert does it, the situation is reversed. There's something like an efficient market here: on average the ideas that seem craziest will, if correct, have the biggest effect. So if you can eliminate the theory that the person proposing an implausible-sounding idea is incompetent, its implausibility switches from evidence that it's boring to evidence that it's exciting. [2] Such ideas are not guaranteed to work. But they don't have to be. They just have to be sufficiently good bets — to have sufficiently high expected value. And I think on average they do. I think if you bet on the entire set of implausible-sounding ideas proposed by reasonable domain experts, you'd end up net ahead. The reason is that everyone is too conservative. The word "paradigm" is overused, but this is a case where it's warranted.
Everyone is too much in the grip of the current paradigm. Even the people who have the new ideas undervalue them initially. Which means that before they reach the stage of proposing them publicly, they've already subjected them to an excessively strict filter. [3] The wise response to such an idea is not to make statements, but to ask questions, because there's a real mystery here. Why has this smart and reasonable person proposed an idea that seems so wrong? Are they mistaken, or are you? One of you has to be. If you're the one who's mistaken, that would be good to know, because it means there's a hole in your model of the world. But even if they're mistaken, it should be interesting to learn why. A trap that an expert falls into is one you have to worry about too. This all seems pretty obvious. And yet there are clearly a lot of people who don't share my fear of dismissing new ideas. Why do they do it? Why risk looking like a jerk now and a fool later, instead of just reserving judgement? One reason they do it is envy. If you propose a radical new idea and it succeeds, your reputation (and perhaps also your wealth) will increase proportionally. Some people would be envious if that happened, and this potential envy propagates back into a conviction that you must be wrong. Another reason people dismiss new ideas is that it's an easy way to seem sophisticated. When a new idea first emerges, it usually seems pretty feeble. It's a mere hatchling. Received wisdom is a full-grown eagle by comparison. So it's easy to launch a devastating attack on a new idea, and anyone who does will seem clever to those who don't understand this asymmetry. This phenomenon is exacerbated by the difference between how those working on new ideas and those attacking them are rewarded. The rewards for working on new ideas are weighted by the value of the outcome.
So it's worth working on something that only has a 10% chance of succeeding if it would make things more than 10x better. Whereas the rewards for attacking new ideas are roughly constant; such attacks seem roughly equally clever regardless of the target. People will also attack new ideas when they have a vested interest in the old ones. It's not surprising, for example, that some of Darwin's harshest critics were churchmen. People build whole careers on some ideas. When someone claims they're false or obsolete, they feel threatened. The lowest form of dismissal is mere factionalism: to automatically dismiss any idea associated with the opposing faction. The lowest form of all is to dismiss an idea because of who proposed it. But the main thing that leads reasonable people to dismiss new ideas is the same thing that holds people back from proposing them: the sheer pervasiveness of the current paradigm. It doesn't just affect the way we think; it is the Lego blocks we build thoughts out of. Popping out of the current paradigm is something only a few people can do. And even they usually have to suppress their intuitions at first, like a pilot flying through cloud who has to trust his instruments over his sense of balance. [4] Paradigms don't just define our present thinking. They also vacuum up the trail of crumbs that led to them, making our standards for new ideas impossibly high. The current paradigm seems so perfect to us, its offspring, that we imagine it must have been accepted completely as soon as it was discovered — that whatever the church thought of the heliocentric model, astronomers must have been convinced as soon as Copernicus proposed it. Far, in fact, from it. Copernicus published the heliocentric model in 1532, but it wasn't till the mid seventeenth century that the balance of scientific opinion shifted in its favor. [5] Few understand how feeble new ideas look when they first appear.
So if you want to have new ideas yourself, one of the most valuable things you can do is to learn what they look like when they're born. Read about how new ideas happened, and try to get yourself into the heads of people at the time. How did things look to them, when the new idea was only half-finished, and even the person who had it was only half-convinced it was right? But you don't have to stop at history. You can observe big new ideas being born all around you right now. Just look for a reasonable domain expert proposing something that sounds wrong. If you're nice, as well as wise, you won't merely resist attacking such people, but encourage them. Having new ideas is a lonely business. Only those who've tried it know how lonely. These people need your help. And if you help them, you'll probably learn something in the process. Notes [1] This domain expertise could be in another field. Indeed, such crossovers tend to be particularly promising. [2] I'm not claiming this principle extends much beyond math, engineering, and the hard sciences. In politics, for example, crazy-sounding ideas generally are as bad as they sound. Though arguably this is not an exception, because the people who propose them are not in fact domain experts; politicians are domain experts in political tactics, like how to get elected and how to get legislation passed, but not in the world that policy acts upon. Perhaps no one could be. [3] This sense of "paradigm" was defined by Thomas Kuhn in his _Structure of Scientific Revolutions_ , but I also recommend his _Copernican Revolution_ , where you can see him at work developing the idea. [4] This is one reason people with a touch of Asperger's may have an advantage in discovering new ideas. They're always flying on instruments. [5] Hall, Rupert. _From Galileo to Newton._ Collins, 1963.
This book is particularly good at getting into contemporaries' heads. Thanks to Trevor Blackwell, Patrick Collison, Suhail Doshi, Daniel Gackle, Jessica Livingston, and Robert Morris for reading drafts of this..
2021年5月 有一种观点我始终不敢公开表达:当我认识的某位既精通某个领域又理性持重的人,提出一个听起来荒诞不经的想法时,我会极力避免说出"这绝对行不通"之类的话。 任何研究过思想史,尤其是科学史的人都知道,伟大的变革往往就是这样开始的。有人提出一个听起来疯狂的想法,多数人不屑一顾,随后这个想法逐渐征服世界。 大多数听起来不靠谱的想法确实糟糕,大可置之不理。但当这些想法来自理性的领域专家时,情况就不同了。如果提出想法的人足够理性,说明他清楚这个想法听起来多么不可思议。但他仍然选择提出来,这意味着他掌握着你不了解的信息。而如果他具备深厚的专业素养,这些信息很可能就来源于此。[1] 这类想法不仅不能轻易否定,反而极可能蕴含重大价值。当普通人提出看似荒谬的想法时,这种荒谬恰恰证明了其无知。但当理性的领域专家这么做时,情况就完全相反。这就像是一个高效市场:平均而言,那些看似最疯狂的想法一旦正确,将产生最深远的影响。因此,当你排除了"提出者能力不足"这个可能性后,想法看似荒谬的特质就从"平庸的证据"转变为"令人振奋的信号"。[2] 这类想法并非注定成功。但它们不需要百分百正确,只需具备足够高的预期价值——成为值得下注的赌局。我认为从整体来看确实如此。如果对所有由理性专家提出的"荒谬想法"都押注,最终很可能会获得净收益。 根源在于人类普遍的保守倾向。"范式"这个词虽然被滥用,但用在此处恰如其分。所有人都被当前范式束缚得太紧。即便是新思想的提出者,最初也会低估其价值。这意味着在公开提议之前,他们已对想法施加了过于严苛的自我审查。[3] 面对这类想法,明智的做法不是妄下断言,而是提出问题——因为这里存在真正的谜题:为何这位聪明理性的专家会提出看似荒谬的主张?是他错了,还是你错了?必有一方存在认知漏洞。如果是你存在盲区,这值得庆幸,因为这意味着你的世界观需要修补。即便错在对方,探究其错误根源同样富有价值——专家也会踏入的陷阱,同样值得你警惕。 这些道理似乎显而易见。但显然许多人并不像我这样畏惧否定新想法。他们为何如此?为何要冒着当下显得刻薄、未来沦为笑柄的风险,而不选择暂缓评判? 嫉妒是原因之一。若某人提出的激进想法最终成功,其声誉(可能还有财富)将成倍增长。有人会因此眼红,这种潜在的嫉妒会转化为"你必定错误"的执念。 另一个原因是,否定新想法是伪装高深的捷径。新想法初现时往往显得脆弱不堪,就像刚破壳的雏鸟;而传统智慧则如同展翅雄鹰。因此对新想法发起致命攻击易如反掌,在不理解这种不对称性的人眼中,攻击者会显得格外睿智。 这种现象因两种行为的不同回报而加剧:探索新想法的回报与成果价值挂钩。因此即便只有10%的成功概率,只要潜在收益超过十倍就值得尝试;而攻击新想法的回报却近乎恒定——无论攻击对象为何,这类批判看起来都同样"聪明"。 当人们与旧观念存在利益捆绑时,也会攻击新思想。例如达尔文最激烈的批评者中就不乏神职人员,这毫不奇怪——有人毕生事业都建立在某些观念上。当这些观念被宣称过时或错误时,他们自然会感到威胁。 最低级的否定是派系主义:仅因某个想法来自对立阵营就断然拒绝。而最不堪的,莫过于因提出者的身份而否定想法。 但导致理性人否定新想法的主因,其实与阻碍人们提出想法的是同一种力量:当前范式的无孔不入。它不仅影响我们的思考方式,更构成了思维的基本模块。能跳出当前范式的人凤毛麟角。即便是他们,最初通常也要压制自己的直觉——就像飞行员在云雾中必须信赖仪表而非平衡感。[4] 范式不仅定义当下思维,还会吞噬自身的发展轨迹,使我们对新想法的标准高得离谱。作为范式的继承者,我们总觉得现有体系完美无缺,甚至误以为它一经发现就被全盘接受——比如认为无论教会如何看待日心说,天文学家在哥白尼提出时就该立即信服。但事实远非如此:哥白尼于1532年发表日心说,直到十七世纪中叶科学界的主流意见才转向支持。[5] 很少有人明白新想法诞生时的孱弱模样。因此若想获得新思想,最宝贵的修行就是观察它们的原生状态。研读思想史,试着代入时人的视角:当某个新思想尚不完善,甚至提出者都半信半疑时,世界在他们眼中是何模样? 你不必止步于历史。此时此刻,无数重大新思想正在你周围诞生。只需寻找那些理性专家提出的、"错误"主张。 若你既睿智又善良,不仅会克制攻击的冲动,更会给予鼓励。孕育新思想是孤独的事业,唯有亲历者才懂得这种孤独。这些人需要你的支持。而给予帮助的同时,你很可能也会收获真知。 注释 [1] 这种专业素养可能来自其他领域。事实上,跨学科交叉往往特别具有前景。 [2] 该原则主要适用于数学、工程和硬科学领域。在政治等领域,疯狂想法通常确实糟糕——但这并非例外,因为提出者并非真正意义上的领域专家。政客精于选举和立法等政治策略,但对政策作用的世界缺乏专业认知,或许也没人能真正精通。 [3] 此处的"范式"概念源自托马斯·库恩《科学革命的结构》,推荐结合其《哥白尼革命》阅读,可见其思想发展轨迹。 [4] 这解释了为何轻度阿斯伯格特质者可能更具创新优势:他们始终依靠"仪表"飞行。 [5] 霍尔《从伽利略到牛顿》(1963)特别擅长还原历史当事人的思维状态。 致谢 特雷弗·布莱克韦尔、帕特里克·科里森、苏海尔·多希、丹尼尔·加克尔、杰西卡·利文斯顿和罗伯特·莫里斯审阅了本文草稿。.
May 2021 Noora Health, a nonprofit I've supported for years, just launched a new NFT. It has a dramatic name, _Save Thousands of Lives_, because that's what the proceeds will do. Noora has been saving lives for 7 years. They run programs in hospitals in South Asia to teach new mothers how to take care of their babies once they get home. They're in 165 hospitals now. And because they know the numbers before and after they start at a new hospital, they can measure the impact they have. It is massive. For every 1000 live births, they save 9 babies. This number comes from a _study_ of 133,733 families at 28 different hospitals that Noora conducted in collaboration with the Better Birth team at Ariadne Labs, a joint center for health systems innovation at Brigham and Women�s Hospital and Harvard T.H. Chan School of Public Health. Noora is so effective that even if you measure their costs in the most conservative way, by dividing their entire budget by the number of lives saved, the cost of saving a life is the lowest I've seen. $1,235. For this NFT, they're going to issue a public report tracking how this specific tranche of money is spent, and estimating the number of lives saved as a result. NFTs are a new territory, and this way of using them is especially new, but I'm excited about its potential. And I'm excited to see what happens with this particular auction, because unlike an NFT representing something that has already happened, this NFT gets better as the price gets higher. The reserve price was about $2.5 million, because that's what it takes for the name to be accurate: that's what it costs to save 2000 lives. But the higher the price of this NFT goes, the more lives will be saved. What a sentence to be able to write.
2021年5月 我支持多年的非营利组织Noora Health刚刚推出了一款新NFT。它有个震撼的名字——《拯救数千生命》(http://bit.ly/NooraNFT),因为拍卖所得将实现这个目标。 Noora已持续七年挽救生命。他们在南亚医院开展项目,教导新手妈妈们回家后如何照顾婴儿。目前项目覆盖165家医院。由于掌握每家新合作医院的前后数据,他们能精准测算干预效果——每1000名新生儿中就有9个生命被拯救。 这个数据源自Noora与布莱根妇女医院及哈佛陈曾熙公共卫生学院联合健康创新中心Ariadne Labs"更好分娩"团队合作的研究,该研究追踪了28家医院的133,733个家庭。 Noora的成效如此显著,即便用最保守的方式计算(总预算除以拯救生命数),每条生命的挽救成本仅1,235美元,这是我见过的最低数值。 本次NFT拍卖将发布专项财务报告,公开追踪资金使用情况并预估因此获救的生命数量。 NFT是新兴领域,这种应用方式更是创新,但其潜力令我振奋。这场拍卖尤其值得期待——与那些记录已发生事件的NFT不同,这款NFT的价值会随竞拍价攀升而增长。 起拍价设为约250万美元,因为这是实现"拯救两千生命"承诺所需的实际成本。而最终成交价每超出这个数字,就意味着更多生命将被挽救。能写下这样的句子,何其有幸。
May 2021 Most people think of nerds as quiet, diffident people. In ordinary social situations they are — as quiet and diffident as the star quarterback would be if he found himself in the middle of a physics symposium. And for the same reason: they are fish out of water. But the apparent diffidence of nerds is an illusion due to the fact that when non-nerds observe them, it's usually in ordinary social situations. In fact some nerds are quite fierce. The fierce nerds are a small but interesting group. They are as a rule extremely competitive — more competitive, I'd say, than highly competitive non-nerds. Competition is more personal for them. Partly perhaps because they're not emotionally mature enough to distance themselves from it, but also because there's less randomness in the kinds of competition they engage in, and they are thus more justified in taking the results personally. Fierce nerds also tend to be somewhat overconfident, especially when young. It might seem like it would be a disadvantage to be mistaken about one's abilities, but empirically it isn't. Up to a point, confidence is a self-fullfilling prophecy. Another quality you find in most fierce nerds is intelligence. Not all nerds are smart, but the fierce ones are always at least moderately so. If they weren't, they wouldn't have the confidence to be fierce. [1] There's also a natural connection between nerdiness and _independent-mindedness_. It's hard to be independent-minded without being somewhat socially awkward, because conventional beliefs are so often mistaken, or at least arbitrary. No one who was both independent-minded and ambitious would want to waste the effort it takes to fit in. And the independent-mindedness of the fierce nerds will obviously be of the _aggressive_ rather than the passive type: they'll be annoyed by rules, rather than dreamily unaware of them.
2021年5月 大多数人认为书呆子是安静怯懦的人。在普通社交场合确实如此——就像橄榄球明星四分卫突然置身物理学研讨会时那样手足无措。原因相同:他们都像离水之鱼。但书呆子表面的怯懦只是错觉,因为当普通人观察他们时,通常只见识到其社交场景的表现。事实上某些书呆子相当凶猛。
凶猛的书呆子虽属少数却值得玩味。他们往往极度争强好胜——我认为其竞争性甚至超过普通人群中的好胜者。竞争对他们而言更关乎个人尊严。部分原因或许是情感上不够成熟,难以超然物外;但更因为他们参与的竞争领域随机性较低,因此将结果视为个人能力的体现也更为合理。
这类书呆子还往往过度自信,年轻时尤甚。误判自身能力看似不利,但实证表明并非如此。在一定范围内,自信会成为自我实现的预言。
大多数凶猛书呆子还有个共同特质:聪慧。并非所有书呆子都聪明,但凶猛者至少具备中等以上智力。若非如此,他们也不会有凶猛行事的底气。[1]
I'm less sure why fierce nerds are impatient, but most seem to be. You notice it first in conversation, where they tend to interrupt you. This is merely annoying, but in the more promising fierce nerds it's connected to a deeper impatience about solving problems. Perhaps the competitiveness and impatience of fierce nerds are not separate qualities, but two manifestations of a single underlying drivenness. When you combine all these qualities in sufficient quantities, the result is quite formidable. The most vivid example of fierce nerds in action may be James Watson's _The Double Helix_. The first sentence of the book is "I have never seen Francis Crick in a modest mood," and the portrait he goes on to paint of Crick is the quintessential fierce nerd: brilliant, socially awkward, competitive, independent-minded, overconfident. But so is the implicit portrait he paints of himself. Indeed, his lack of social awareness makes both portraits that much more realistic, because he baldly states all sorts of opinions and motivations that a smoother person would conceal. And moreover it's clear from the story that Crick and Watson's fierce nerdiness was integral to their success. Their independent-mindedness caused them to consider approaches that most others ignored, their overconfidence allowed them to work on problems they only half understood (they were literally described as "clowns" by one eminent insider), and their impatience and competitiveness got them to the answer ahead of two other groups that would otherwise have found it within the next year, if not the next several months. [2] The idea that there could be fierce nerds is an unfamiliar one not just to many normal people but even to some young nerds. Especially early on, nerds spend so much of their time in ordinary social situations and so little doing real work that they get a lot more evidence of their awkwardness than their power.
书呆子特质与独立思考天然相关。若不显得些许社交笨拙,很难真正保持思想独立——因为传统观念常存在谬误或至少是武断的。既独立思考又胸怀大志者,绝不会浪费精力去迎合世俗。而凶猛书呆子的独立思考显然属于激进型而非被动型:他们会对规则感到恼怒,而非懵然不觉。
我不太确定为何凶猛书呆子普遍缺乏耐心,但事实如此。最直观体现在交谈中他们常打断别人。这固然恼人,但在更有潜力的凶猛书呆子身上,这种特质关联着解决问题的深层迫切感。或许他们的好胜心与急躁并非独立特质,而是同一种内在驱动力的两种表现。
当这些特质累积到一定程度,将造就非凡存在。詹姆斯·沃森《双螺旋》堪称展现凶猛书呆子的最佳范本。开篇首句"我从未见过弗朗西斯·克里克表现出谦虚",随后描绘的克里克形象正是典型凶猛书呆子:才华横溢、社交笨拙、争强好胜、思想独立、过度自信。而他笔下的自我形象同样如此。正是这种社交钝感让两个形象格外真实——他直言不讳地揭露了圆滑者会隐藏的种种想法与动机。更关键的是,故事清晰表明克里克与沃森的凶猛书呆子特质是其成功的关键。思想独立使他们探索主流忽视的路径,过度自信支撑他们研究半懂不懂的课题(某位权威人士直斥二人为"小丑"),急躁与好胜则让他们领先另外两个研究组数月乃至一年抢先破解谜题。[2]
"凶猛书呆子"的概念不仅对普通人陌生,甚至某些年轻书呆子也未曾察觉。尤其早期阶段,书呆子耗费大量时间在普通社交场景,真正投入事业的时间寥寥,因此对自身笨拙的认知远多于对力量的感知。或许有人读到此处会恍然:"嗯,这就是我"。此刻我要正告这些年轻的凶猛书呆子:
有个好消息,也有个坏消息。好消息是你们的凶猛特质将成为解决难题的利器。不仅是传统意义上的科技难题——随着时代发展,凭正确答案取胜的领域正持续扩展。近年财富积累也加入此列:美国八大富豪中,七位都是凶猛书呆子。
So there will be some who read this description of the fierce nerd and realize "Hmm, that's me." And it is to you, young fierce nerd, that I now turn. I have some good news, and some bad news. The good news is that your fierceness will be a great help in solving difficult problems. And not just the kind of scientific and technical problems that nerds have traditionally solved. As the world progresses, the number of things you can win at by getting the right answer increases. Recently _getting rich_ became one of them: 7 of the 8 richest people in America are now fierce nerds. Indeed, being a fierce nerd is probably even more helpful in business than in nerds' original territory of scholarship. Fierceness seems optional there. Darwin for example doesn't seem to have been especially fierce. Whereas it's impossible to be the CEO of a company over a certain size without being fierce, so now that nerds can win at business, fierce nerds will increasingly monopolize the really big successes. The bad news is that if it's not exercised, your fierceness will turn to bitterness, and you will become an intellectual playground bully: the grumpy sysadmin, the forum troll, the _hater_, the shooter down of _new ideas_. How do you avoid this fate? Work on ambitious projects. If you succeed, it will bring you a kind of satisfaction that neutralizes bitterness. But you don't need to have succeeded to feel this; merely working on hard projects gives most fierce nerds some feeling of satisfaction. And those it doesn't, it at least keeps busy. [3] Another solution may be to somehow turn off your fierceness, by devoting yourself to meditation or psychotherapy or something like that. Maybe that's the right answer for some people. I have no idea. But it doesn't seem the optimal solution to me. If you're given a sharp knife, it seems to me better to use it than to blunt its edge to avoid cutting yourself.
事实上,凶猛书呆子在商界的优势甚至超过学术领域。学术界的凶猛似乎非必需(例如达尔文就不算特别凶猛),但企业规模达到一定程度后,非凶猛者绝无可能担任CEO。既然书呆子能在商界获胜,凶猛者必将垄断真正巨大的成功。
坏消息是:若无处施展,你们的凶猛将化为怨毒,使你们沦为知识界的恶霸——暴躁的系统管理员、论坛喷子、仇恨者、新思想的扼杀者。
如何避免这种命运?投身雄心勃勃的事业。成功带来的满足感能中和怨毒。其实不必等到成功——对多数凶猛书呆子而言,仅挑战难题的过程就能带来满足。即便对此无感者,至少也能保持忙碌。[3]
另一种解法是通过冥想或心理治疗等方式熄灭凶猛本性。或许这对某些人有效(我无从判断),但在我看来并非最优解。若你手持利刃,比起磨钝刃口防割伤,不如学会驾驭它。
若选择雄心之路,你将顺风而行。当今是书呆子最好的时代。过去百年我们见证权力持续从交易者向技术者转移——从魅力型向能力型——我未见任何迹象表明这种趋势会终止。除非书呆子自己通过技术奇点终结这一切。
If you do choose the ambitious route, you'll have a tailwind behind you. There has never been a better time to be a nerd. In the past century we've seen a continuous transfer of power from dealmakers to technicians — from the charismatic to the competent — and I don't see anything on the horizon that will end it. At least not till the nerds end it themselves by bringing about the singularity. Notes [1] To be a nerd is to be socially awkward, and there are two distinct ways to do that: to be playing the same game as everyone else, but badly, and to be playing a different game. The smart nerds are the latter type. [2] The same qualities that make fierce nerds so effective can also make them very annoying. Fierce nerds would do well to remember this, and (a) try to keep a lid on it, and (b) seek out organizations and types of work where getting the right answer matters more than preserving social harmony. In practice that means small groups working on hard problems. Which fortunately is the most fun kind of environment anyway. [3] If success neutralizes bitterness, why are there some people who are at least moderately successful and yet still quite bitter? Because people's potential bitterness varies depending on how naturally bitter their personality is, and how ambitious they are: someone who's naturally very bitter will still have a lot left after success neutralizes some of it, and someone who's very ambitious will need proportionally more success to satisfy that ambition. So the worst-case scenario is someone who's both naturally bitter and extremely ambitious, and yet only moderately successful. Thanks to Trevor Blackwell, Steve Blank, Patrick Collison, Jessica Livingston, Amjad Masad, and Robert Morris for reading drafts of this.
[1] 书呆子的社交笨拙分两种:与他人玩同一游戏却玩不好,或根本玩着不同游戏。聪明的书呆子属于后者。
[2] 造就凶猛书呆子高效的特质也令其惹人生厌。他们最好牢记这点,并:(a) 适当收敛,(b) 选择重视正确答案甚于维系表面和谐的机构与工作。实践中这意味着专注解决难题的小型团队——所幸这本来就是最有趣的工作环境。
[3] 若成功可中和怨毒,为何有些至少中等成功者仍满怀怨怼?因为潜在怨毒量取决于:天生怨毒程度与野心大小。天性极怨毒者成功仅能抵消部分,极野心者需要等比更大的成功才能满足。
最糟情况是:天性怨毒又野心滔天,却仅获中等成功之人。
致谢 感谢Trevor Blackwell、Steve Blank、Patrick Collison、Jessica Livingston、Amjad Masad和Robert Morris审阅本文草稿。
April 2021 Every year since 1982, _Forbes_ magazine has published a list of the richest Americans. If we compare the 100 richest people in 1982 to the 100 richest in 2020, we notice some big differences. In 1982 the most common source of wealth was inheritance. Of the 100 richest people, 60 inherited from an ancestor. There were 10 du Pont heirs alone. By 2020 the number of heirs had been cut in half, accounting for only 27 of the biggest 100 fortunes. Why would the percentage of heirs decrease? Not because inheritance taxes increased. In fact, they decreased significantly during this period. The reason the percentage of heirs has decreased is not that fewer people are inheriting great fortunes, but that more people are making them. How are people making these new fortunes? Roughly 3/4 by starting companies and 1/4 by investing. Of the 73 new fortunes in 2020, 56 derive from founders' or early employees' equity (52 founders, 2 early employees, and 2 wives of founders), and 17 from managing investment funds. There were no fund managers among the 100 richest Americans in 1982. Hedge funds and private equity firms existed in 1982, but none of their founders were rich enough yet to make it into the top 100. Two things changed: fund managers discovered new ways to generate high returns, and more investors were willing to trust them with their money. [1] But the main source of new fortunes now is starting companies, and when you look at the data, you see big changes there too. People get richer from starting companies now than they did in 1982, because the companies do different things. In 1982, there were two dominant sources of new wealth: oil and real estate. Of the 40 new fortunes in 1982, at least 24 were due primarily to oil or real estate. Now only a small number are: of the 73 new fortunes in 2020, 4 were due to real estate and only 2 to oil.
自1982年起,《福布斯》杂志每年都会发布美国富豪榜。如果将1982年与2020年的百大富豪进行对比,我们会发现一些显著变化。
1982年,财富的最主要来源是继承。百大富豪中,有60人是从祖先那里继承了财富。仅杜邦家族就有10位继承人。到了2020年,继承人的数量减半,在百大富豪中仅占27席。
为何继承人比例会下降?并非因为遗产税增加——事实上,该时期遗产税大幅降低。继承人比例下降的真正原因,不是继承巨额财富的人变少,而是创造财富的人变多了。
这些新财富如何创造?大约四分之三通过创业,四分之一通过投资。2020年73位新晋富豪中,56位来自创始人或早期员工的股权(52位创始人、2位早期员工和2位创始人配偶),17位来自管理投资基金。
1982年的百大富豪中没有任何基金经理。虽然对冲基金和私募股权公司在当时已然存在,但其创始人尚未积累足够财富进入百强。两大变化促成了这一转变:基金经理发现了高回报的新方法,更多投资者愿意将资金托付给他们。[1]
By 2020 the biggest source of new wealth was what are sometimes called "tech" companies. Of the 73 new fortunes, about 30 derive from such companies. These are particularly common among the richest of the rich: 8 of the top 10 fortunes in 2020 were new fortunes of this type. Arguably it's slightly misleading to treat tech as a category. Isn't Amazon really a retailer, and Tesla a car maker? Yes and no. Maybe in 50 years, when what we call tech is taken for granted, it won't seem right to put these two businesses in the same category. But at the moment at least, there is definitely something they share in common that distinguishes them. What retailer starts AWS? What car maker is run by someone who also has a rocket company? The tech companies behind the top 100 fortunes also form a well-differentiated group in the sense that they're all companies that venture capitalists would readily invest in, and the others mostly not. And there's a reason why: these are mostly companies that win by having better technology, rather than just a CEO who's really driven and good at making deals. To that extent, the rise of the tech companies represents a qualitative change. The oil and real estate magnates of the 1982 Forbes 400 didn't win by making better technology. They won by being really driven and good at making deals. [2] And indeed, that way of getting rich is so old that it predates the Industrial Revolution. The courtiers who got rich in the (nominal) service of European royal houses in the 16th and 17th centuries were also, as a rule, really driven and good at making deals. People who don't look any deeper than the Gini coefficient look back on the world of 1982 as the good old days, because those who got rich then didn't get as rich. But if you dig into _how_ they got rich, the old days don't look so good. In 1982, 84% of the richest 100 people got rich by inheritance, extracting natural resources, or doing real estate deals.
但如今新财富的主要来源是创业。观察数据会发现,这一领域也发生了巨变。相比1982年,当今创业者能积累更多财富,因为他们从事的行业已然不同。
1982年,新财富的两大支柱是石油和房地产。当年40位新晋富豪中,至少有24位主要依靠这两大产业。而2020年的73位新晋富豪中,仅4位来自房地产,2位来自石油。
到2020年,新财富的最大源头是所谓的"科技"公司。约30位新晋富豪来自该领域。这种现象在顶级富豪中尤为明显:2020年十强富豪中,有8位属于此类科技新贵。
将科技单独归类或许略显牵强。亚马逊本质不是零售商吗?特斯拉不是汽车制造商吗?答案既是也非。或许五十年后,当现有科技成为基础设施时,将两者归为同类会显得不合时宜。但至少在当下,它们确实拥有某种共同特质。哪个零售商会创立AWS云计算?哪个车企老板会同时运营火箭公司?
从风险投资视角看,这些缔造百强富豪的科技公司确实自成一体——它们都是风投机构乐于投资的对象,而其他传统企业则大多不是。深层原因在于:这些公司主要凭借技术优势制胜,而非仅靠CEO的过人干劲和交易手腕。
就此而言,科技公司的崛起代表着质变。1982年《福布斯》400强中的石油大亨和地产巨头,并非依靠技术革新取胜,而是凭借超凡的驱动力和交易能力。[2]这种致富模式其实早在工业革命前就已存在——16至17世纪欧洲宫廷中发迹的权贵们,同样以这两项特质著称。
Is that really better than a world in which the richest people get rich by starting tech companies? Why are people starting so many more new companies than they used to, and why are they getting so rich from it? The answer to the first question, curiously enough, is that it's misphrased. We shouldn't be asking why people are starting companies, but why they're starting companies _again_. [3] In 1892, the _New York Herald Tribune_ compiled a list of all the millionaires in America. They found 4047 of them. How many had inherited their wealth then? Only about 20%, which is less than the proportion of heirs today. And when you investigate the sources of the new fortunes, 1892 looks even more like today. Hugh Rockoff found that "many of the richest ... gained their initial edge from the new technology of mass production." [4] So it's not 2020 that's the anomaly here, but 1982. The real question is why so few people had gotten rich from starting companies in 1982\. And the answer is that even as the _Herald Tribune_ 's list was being compiled, a wave of _consolidation_ was sweeping through the American economy. In the late 19th and early 20th centuries, financiers like J. P. Morgan combined thousands of smaller companies into a few hundred giant ones with commanding economies of scale. By the end of World War II, as Michael Lind writes, "the major sectors of the economy were either organized as government-backed cartels or dominated by a few oligopolistic corporations." [5] In 1960, most of the people who start startups today would have gone to work for one of them. You could get rich from starting your own company in 1890 and in 2020, but in 1960 it was not really a viable option. You couldn't break through the oligopolies to get at the markets.
那些只盯着基尼系数的人,常将1982年视为美好旧时光,因为当时的富豪财富规模较小。但若深究其财富来源,旧日景象并不美好。当年百强富豪中,84%通过继承、资源开采或房地产交易致富。这真的比当今科技创业者主导的财富图景更可取吗?
为何当今创业者数量激增,且能积累更庞大财富?第一个问题的答案颇具反讽:问题本身措辞有误。我们真正该问的不是"为何人们开始创业",而是"为何人们重新开始创业"。[3]
1892年,《纽约先驱论坛报》统计美国百万富翁时,共发现4047人。其中仅约20%继承财富,比例甚至低于当今。考察新财富来源时,1892年与当今更为相似。休·罗克夫研究发现:"许多顶级富豪...最初优势来自大规模生产的新技术。"[4]
因此异常值并非2020年,而是1982年。真正的问题是:为何1982年通过创业致富者如此之少?答案在于:就在《先驱论坛报》编制榜单时,一股兼并浪潮正席卷美国经济。19世纪末至20世纪初,J.P.摩根等金融家将数千家小企业合并为数百家具有规模效应的巨头。迈克尔·林德写道:"二战结束时,经济主要领域要么形成政府支持的卡特尔,要么被少数寡头垄断。"[5]
若在1960年,当今的创业者大多会去这些大公司任职。1890年和2020年都能通过创业致富,但在1960年这几乎不可行——寡头垄断封锁了市场通道。因此那个年代的精英之路不是创业,而是在现有企业中攀登晋升阶梯。[6]
雇员社会的确降低了经济不平等(及其他各类差异),但若以20世纪中叶为常态标准,这种认知其实极具误导性。J.P.摩根缔造的经济体系最终被证明只是一个阶段——1970年代起,它开始瓦解。
So the prestigious route in 1960 was not to start your own company, but to work your way up the corporate ladder at an existing one. [6] Making everyone a corporate employee decreased economic inequality (and every other kind of variation), but if your model of normal is the mid 20th century, you have a very misleading model in that respect. J. P. Morgan's economy turned out to be just a phase, and starting in the 1970s, it began to break up. Why did it break up? Partly senescence. The big companies that seemed models of scale and efficiency in 1930 had by 1970 become slack and bloated. By 1970 the rigid structure of the economy was full of cosy nests that various groups had built to insulate themselves from market forces. During the Carter administration the federal government realized something was amiss and began, in a process they called "deregulation," to roll back the policies that propped up the oligopolies. But it wasn't just decay from within that broke up J. P. Morgan's economy. There was also pressure from without, in the form of new technology, and particularly microelectronics. The best way to envision what happened is to imagine a pond with a crust of ice on top. Initially the only way from the bottom to the surface is around the edges. But as the ice crust weakens, you start to be able to punch right through the middle. The edges of the pond were pure tech: companies that actually described themselves as being in the electronics or software business. When you used the word "startup" in 1990, that was what you meant. But now startups are punching right through the middle of the ice crust and displacing incumbents like retailers and TV networks and car companies. [7] But though the breakup of J. P. Morgan's economy created a new world in the technological sense, it was a reversion to the norm in the social sense.
瓦解原因何在?部分源于体制老化。1930年代作为规模效率典范的大公司,到1970年代已变得臃肿低效。当时僵化的经济结构中,遍布各种利益集团为规避市场竞争而筑造的舒适巢穴。卡特政府时期,联邦政府意识到问题所在,通过"放松管制"逐步废除支撑寡头垄断的政策。
但J.P.摩根经济体系的崩溃不仅源于内部衰败,还有以微电子技术为代表的外部冲击。想象一个结冰的池塘:最初只能从边缘迂回,但随着冰层变薄,人们开始能直接破冰而出。
池塘边缘是纯科技公司——那些自称从事电子或软件业务的企业。1990年提及"初创企业"时,指的就是这类公司。而如今,初创企业正从冰层中央破冰而出,取代零售商、电视网络和车企等传统巨头。[7]
尽管J.P.摩根经济体系的瓦解在技术层面创造了新世界,在社会层面却是一种回归。若仅回溯至20世纪中叶,自主创业致富似乎是个新现象。但更长远看,这其实是历史常态。因此未来我们很可能会见证更多同类案例。事实上,随着创业门槛持续降低,创业者的数量与财富都将继续增长。
创业变易的部分原因在于社会认知。如今父母不会像上一代人那样对子女创业大惊小怪,创业知识也更为普及。但最主要原因在于成本降低——技术发展压低了产品开发与客户获取的成本。
创业成本下降改变了创始人与投资人的力量平衡。当创业意味着建造工厂时,必须获得投资人首肯。而如今投资人更需要创始人,加上风投资本供给增加,共同推高了估值。[8]
If you only look back as far as the mid 20th century, it seems like people getting rich by starting their own companies is a recent phenomenon. But if you look back further, you realize it's actually the default. So what we should expect in the future is more of the same. Indeed, we should expect both the number and wealth of founders to grow, because every decade it gets easier to start a startup. Part of the reason it's getting easier to start a startup is social. Society is (re)assimilating the concept. If you start one now, your parents won't freak out the way they would have a generation ago, and knowledge about how to do it is much more widespread. But the main reason it's easier to start a startup now is that it's cheaper. Technology has driven down the cost of both building products and acquiring customers. The decreasing cost of starting a startup has in turn changed the balance of power between founders and investors. Back when starting a startup meant building a factory, you needed investors' permission to do it at all. But now investors need founders more than founders need investors, and that, combined with the increasing amount of venture capital available, has driven up valuations. [8] So the decreasing cost of starting a startup increases the number of rich people in two ways: it means that more people start them, and that those who do can raise money on better terms. But there's also a third factor at work: the companies themselves are more valuable, because newly founded companies grow faster than they used to. Technology hasn't just made it cheaper to build and distribute things, but faster too. This trend has been running for a long time. IBM, founded in 1896, took 45 years to reach a billion 2020 dollars in revenue. Hewlett-Packard, founded in 1939, took 25 years. Microsoft, founded in 1975, took 13 years.
因此创业成本降低通过两种方式增加富豪数量:既让更多人投身创业,也让创业者能获得更优融资条件。
但还有第三重因素:企业本身价值提升,因为新兴公司的成长速度远超往昔。技术不仅降低了生产和分销成本,更大幅提速。
这一趋势由来已久。1896年创立的IBM耗时45年达到2020年币值的10亿美元营收;1939年创立的惠普耗时25年;1975年创立的微软耗时13年;如今高增长企业通常只需7-8年。[9]
快速增长对创始人股权价值产生双重效应。企业价值是营收与增长率的函数,因此公司增长越快,不仅更快达到10亿美元营收,其在该里程碑时的估值也远高于增长缓慢的企业。
这就是当今创始人能如此年轻就跻身顶级富豪的原因:创业初始成本低允许年轻人早早起步,而企业的高速成长意味着成功者短短数年后就能积累惊人财富。
Now the norm for fast-growing companies is 7 or 8 years. [9] Fast growth has a double effect on the value of founders' stock. The value of a company is a function of its revenue and its growth rate. So if a company grows faster, you not only get to a billion dollars in revenue sooner, but the company is more valuable when it reaches that point than it would be if it were growing slower. That's why founders sometimes get so rich so young now. The low initial cost of starting a startup means founders can start young, and the fast growth of companies today means that if they succeed they could be surprisingly rich just a few years later. It's easier now to start and grow a company than it has ever been. That means more people start them, that those who do get better terms from investors, and that the resulting companies become more valuable. Once you understand how these mechanisms work, and that startups were suppressed for most of the 20th century, you don't have to resort to some vague right turn the country took under Reagan to explain why America's Gini coefficient is increasing. Of course the Gini coefficient is increasing. With more people starting more valuable companies, how could it not be? Notes [1] Investment firms grew rapidly after a regulatory change by the Labor Department in 1978 allowed pension funds to invest in them, but the effects of this growth were not yet visible in the top 100 fortunes in 1982. [2] George Mitchell deserves mention as an exception. Though really driven and good at making deals, he was also the first to figure out how to use fracking to get natural gas out of shale. [3] When I say people are starting more companies, I mean the type of company meant to _grow_ very big. There has actually been a decrease in the last couple decades in the overall number of new companies. But the vast majority of companies are small retail and service businesses.
当今创办和壮大企业比历史上任何时候都更容易。这意味着更多创业者涌现、更优融资条件,以及更高企业估值。一旦理解这些机制,并认识到初创企业在20世纪大部分时期受到压制,就无需用"里根时代国家右转"这类模糊说法来解释美国基尼系数上升。基尼系数增长是必然——当更多人创建更高价值企业时,怎能不如此?
[1] 1978年美国劳工部法规修订允许养老基金投资于投资公司后,这类机构迅速扩张,但其影响在1982年百强富豪榜上尚未显现。
[2] 乔治·米切尔是个例外。除了过人干劲与交易能力,他还是页岩气水力压裂技术的首创者。
[3] 所谓"更多创业",特指旨在_快速壮大_的企业类型。过去二十年新企业总量实际是下降的,但绝大多数是小型零售和服务企业。"新企业减少"实质反映的是鞋店、理发店等小生意的减少。
人们有时会_混淆_"初创企业"的两种含义:(1)新成立企业;(2)专为快速成长设计的企业类型。统计数据显示的是第一种。
[4] 休·罗克夫,《镀金时代的巨额财富》,NBER工作论文14555号,2008年。
So what the statistics about the decreasing number of new businesses mean is that people are starting fewer shoe stores and barber shops. People sometimes get _confused_ when they see a graph labelled "startups" that's going down, because there are two senses of the word "startup": (1) the founding of a company, and (2) a particular type of company designed to grow big fast. The statistics mean startup in sense (1), not sense (2). [4] Rockoff, Hugh. "Great Fortunes of the Gilded Age." NBER Working Paper 14555, 2008. [5] Lind, Michael. _Land of Promise._ HarperCollins, 2012. It's also likely that the high tax rates in the mid 20th century deterred people from starting their own companies. Starting one's own company is risky, and when risk isn't rewarded, people opt for _safety_ instead. But it wasn't simply cause and effect. The oligopolies and high tax rates of the mid 20th century were all of a piece. Lower taxes are not just a cause of entrepreneurship, but an effect as well: the people getting rich in the mid 20th century from real estate and oil exploration lobbied for and got huge tax loopholes that made their effective tax rate much lower, and presumably if it had been more common to grow big companies by building new technology, the people doing that would have lobbied for their own loopholes as well. [6] That's why the people who did get rich in the mid 20th century so often got rich from oil exploration or real estate. Those were the two big areas of the economy that weren't susceptible to consolidation. [7] The pure tech companies used to be called "high technology" startups.
[5] 迈克尔·林德,《应许之地》,哈珀柯林斯,2012年。
20世纪中叶的高税率也可能抑制了创业意愿。创业本具风险,当风险缺乏回报时,人们会选择_安稳_路径。
但这并非简单因果关系。寡头垄断与高税率实为一体:降低税率不仅是创业活动的原因,也是其结果——20世纪中叶通过房地产和石油勘探致富的群体游说获得了巨大税收漏洞,使其实际税率远低于名义税率。若当时通过科技创新壮大企业更为普遍,该群体同样会争取自身税收优惠。
[6] 这解释了为何20世纪中叶的致富者多来自石油勘探或房地产——这是经济中少数未被垄断的领域。
[7] 纯科技公司曾被称为"高科技"初创企业。但随着企业能突破各行业壁垒,"高科技"一词已显得_过时_。
[8] 高估值意味着用较少股权换取既定资金,或以既定股权获得更多资金。典型初创企业会兼顾两者。保留更多股权显然能增加最终财富,但更多融资也应如此,因为:(a)促进公司成功;(b)延长下一轮融资间隔甚至避免需求。不过现实中常有资金损耗。
But now that startups can punch through the middle of the ice crust, we don't need a separate name for the edges, and the term "high-tech" has a decidedly _retro_ sound. [8] Higher valuations mean you either sell less stock to get a given amount of money, or get more money for a given amount of stock. The typical startup does some of each. Obviously you end up richer if you keep more stock, but you should also end up richer if you raise more money, because (a) it should make the company more successful, and (b) you should be able to last longer before the next round, or not even need one. Notice all those shoulds though. In practice a lot of money slips through them. It might seem that the huge rounds raised by startups nowadays contradict the claim that it has become cheaper to start one. But there's no contradiction here; the startups that raise the most are the ones doing it by choice, in order to grow faster, not the ones doing it because they need the money to survive. There's nothing like not needing money to make people offer it to you. You would think, after having been on the side of labor in its fight with capital for almost two centuries, that the far left would be happy that labor has finally prevailed. But none of them seem to be. You can almost hear them saying "No, no, not _that_ way." [9] IBM was created in 1911 by merging three companies, the most important of which was Herman Hollerith's Tabulating Machine Company, founded in 1896. In 1941 its revenues were $60 million. Hewlett-Packard's revenues in 1964 were $125 million. Microsoft's revenues in 1988 were $590 million. Thanks to Trevor Blackwell, Jessica Livingston, Bob Lesko, Robert Morris, Russ Roberts, and Alex Tabarrok for reading drafts of this, and to Jon Erlichman for growth data..
当今初创企业的巨额融资看似与"创业成本降低"矛盾,实则不然:那些融资最多的企业是主动选择加速成长,而非为生存被迫融资。没有什么比"不需要钱"更能吸引投资。
在与资本博弈近两个世纪后,激进左派本应乐见劳动方终占上风。但他们似乎都在说:"不,不该是_这种_方式。"
[9] IBM由三家公司于1911年合并成立,其中最重要的是1896年成立的霍列瑞斯制表机公司。1941年其营收为6000万美元。
惠普1964年营收1.25亿美元。
微软1988年营收5.9亿美元。
致谢 感谢特雷弗·布莱克韦尔、杰西卡·利文斯顿、鲍勃·莱斯科、罗伯特·莫里斯、拉斯·罗伯茨和亚历克斯·塔巴洛克审阅草稿,以及乔恩·埃尔利希曼提供的增长数据。
April 2021 When intellectuals talk about the death penalty, they talk about things like whether it's permissible for the state to take someone's life, whether the death penalty acts as a deterrent, and whether more death sentences are given to some groups than others. But in practice the debate about the death penalty is not about whether it's ok to kill murderers. It's about whether it's ok to kill innocent people, because at least 4% of people on death row are _innocent_. When I was a kid I imagined that it was unusual for people to be convicted of crimes they hadn't committed, and that in murder cases especially this must be very rare. Far from it. Now, thanks to organizations like the _Innocence Project_, we see a constant stream of stories about murder convictions being overturned after new evidence emerges. Sometimes the police and prosecutors were just very sloppy. Sometimes they were crooked, and knew full well they were convicting an innocent person. Kenneth Adams and three other men spent 18 years in prison on a murder conviction. They were exonerated after DNA testing implicated three different men, two of whom later confessed. The police had been told about the other men early in the investigation, but never followed up the lead. Keith Harward spent 33 years in prison on a murder conviction. He was convicted because "experts" said his teeth matched photos of bite marks on one victim. He was exonerated after DNA testing showed the murder had been committed by another man, Jerry Crotty. Ricky Jackson and two other men spent 39 years in prison after being convicted of murder on the testimony of a 12 year old boy, who later recanted and said he'd been coerced by police. Multiple people have confirmed the boy was elsewhere at the time.
The three men were exonerated after the county prosecutor dropped the charges, saying "The state is conceding the obvious." Alfred Brown spent 12 years in prison on a murder conviction, including 10 years on death row. He was exonerated after it was discovered that the assistant district attorney had concealed phone records proving he could not have committed the crimes. Glenn Ford spent 29 years on death row after having been convicted of murder. He was exonerated after new evidence proved he was not even at the scene when the murder occurred. The attorneys assigned to represent him had never tried a jury case before. Cameron Willingham was actually executed in 2004 by lethal injection. The "expert" who testified that he deliberately set fire to his house has since been discredited. A re-examination of the case ordered by the state of Texas in 2009 concluded that "a finding of arson could not be sustained." _Rich Glossip_ has spent 20 years on death row after being convicted of murder on the testimony of the actual killer, who escaped with a life sentence in return for implicating him. In 2015 he came within minutes of execution before it emerged that Oklahoma had been planning to kill him with an illegal combination of drugs. They still plan to go ahead with the execution, perhaps as soon as this summer, despite _new evidence_ exonerating him. I could go on. There are hundreds of similar cases. In Florida alone, 29 death row prisoners have been exonerated so far. Far from being rare, wrongful murder convictions are _very common_. Police are under pressure to solve a crime that has gotten a lot of attention.
When they find a suspect, they want to believe he's guilty, and ignore or even destroy evidence suggesting otherwise. District attorneys want to be seen as effective and tough on crime, and in order to win convictions are willing to manipulate witnesses and withhold evidence. Court-appointed defense attorneys are overworked and often incompetent. There's a ready supply of criminals willing to give false testimony in return for a lighter sentence, suggestible witnesses who can be made to say whatever police want, and bogus "experts" eager to claim that science proves the defendant is guilty. And juries want to believe them, since otherwise some terrible crime remains unsolved. This circus of incompetence and dishonesty is the real issue with the death penalty. We don't even reach the point where theoretical questions about the moral justification or effectiveness of capital punishment start to matter, because so many of the people sentenced to death are actually innocent. Whatever it means in theory, in practice capital punishment means killing innocent people. Thanks to Trevor Blackwell, Jessica Livingston, and Don Knight for reading drafts of this. Related:
Will Florida Kill an Innocent Man? Was Kevin Cooper Framed for Murder? Did Texas execute an innocent man?.
2021年4月 当知识分子讨论死刑时,他们谈论的是诸如国家是否有权剥夺一个人的生命、死刑是否能起到威慑作用,以及某些群体是否比其他群体更容易被判死刑等问题。但实际上,关于死刑的争论并不在于杀死杀人犯是否合理,而在于杀死无辜的人是否合理,因为死囚中至少有4%的人是_无辜的_。 我小时候以为,人们因未犯下的罪行而被定罪是罕见的事,尤其是在谋杀案中,这种情况一定非常少见。事实远非如此。如今,多亏了像_无辜计划_这样的组织,我们不断看到新的证据出现后谋杀定罪被推翻的故事。有时警察和检察官只是非常粗心大意。有时他们腐败堕落,完全清楚自己正在给一个无辜的人定罪。 肯尼斯·亚当斯和其他三名男子因谋杀罪在监狱中度过了18年。DNA检测指向另外三名男子后,他们被无罪释放,其中两人后来供认了罪行。警方在调查初期就被告知了这些人的存在,但从未跟进这条线索。 基思·哈沃德因谋杀罪在监狱中度过了33年。他被定罪是因为“专家”称他的牙齿与一名受害者身上的咬痕照片吻合。DNA检测显示谋杀是由另一名男子杰里·克罗蒂所为后,他被无罪释放。 里基·杰克逊和其他两名男子因一名12岁男孩的证词被判谋杀罪,在监狱中度过了39年。男孩后来翻供,称自己受到了警方的胁迫。多人证实男孩当时并不在场。县检察官撤销指控后,三人被无罪释放,并表示“州政府承认了显而易见的事实”。 阿尔弗雷德·布朗因谋杀罪在监狱中度过了12年,其中10年在死囚牢房中度过。助理地区检察官隐瞒了证明他不可能犯罪的电话记录被发现后,他被无罪释放。 格伦·福特因谋杀罪在死囚牢房中度过29年。新证据证明谋杀发生时他甚至不在现场后,他被无罪释放。指派为他辩护的律师此前从未处理过陪审团案件。 卡梅伦·托德·威林汉姆实际上已于2004年被注射死刑。作证称他故意纵火烧毁房屋的“专家”后来被揭穿不可信。2009年德克萨斯州下令重新审查此案,结论是“无法维持纵火的认定”。 _理查德·格洛西普_因实际杀人犯的证词被判谋杀罪,在死囚牢房中度过20年。杀人犯通过指证他换取无期徒刑。2015年,他距离被执行死刑仅剩几分钟时,人们发现俄克拉荷马州计划用非法药物组合处死他。尽管有_新证据_证明他无罪,他们仍计划继续执行死刑,可能就在今年夏天。 这样的案例不胜枚举。类似案件有数百起。仅在佛罗里达州,目前已有29名死囚被无罪释放。 错误的谋杀定罪绝非罕见,而是_非常普遍_。警方面临破案压力,尤其是那些备受关注的案件。当他们找到一个嫌疑人时,他们愿意相信他有罪,并忽视甚至销毁相反的证据。地区检察官希望被视为高效且严厉打击犯罪,为了赢得定罪,他们愿意操纵证人和隐瞒证据。法院指定的辩护律师工作过度,往往能力不足。有现成的罪犯愿意为减刑作伪证,易受影响的证人可以被诱导说出警方想要的任何话,还有急于声称科学证明被告有罪的虚假“专家”。陪审团也愿意相信他们,否则可怕的罪行将无法解决。 这种无能和不诚实的闹剧才是死刑的真正问题。我们甚至无法触及关于死刑道德合理性或有效性的理论问题,因为许多被判死刑的人实际上是无辜的。无论理论上如何定义,实践中死刑意味着杀死无辜的人。 感谢特雷弗·布莱克威尔、杰西卡·利文斯顿和唐·奈特阅读本文草稿。 相关阅读:
March 2021 I try to write using ordinary words and simple sentences. That kind of writing is easier to read, and the easier something is to read, the more deeply readers will engage with it. The less energy they expend on your prose, the more they'll have left for your ideas. And the further they'll read. Most readers' energy tends to flag part way through an article or essay. If the friction of reading is low enough, more keep going till the end. There's an Italian dish called _saltimbocca_ , which means "leap into the mouth." My goal when writing might be called _saltintesta_ : the ideas leap into your head and you barely notice the words that got them there. It's too much to hope that writing could ever be pure ideas. You might not even want it to be. But for most writers, most of the time, that's the goal to aim for. The gap between most writing and pure ideas is not filled with poetry. Plus it's more considerate to write simply. When you write in a fancy way to impress people, you're making them do extra work just so you can seem cool. It's like trailing a long train behind you that readers have to carry. And remember, if you're writing in English, that a lot of your readers won't be native English speakers. Their understanding of ideas may be way ahead of their understanding of English. So you can't assume that writing about a difficult topic means you can use difficult words. Of course, fancy writing doesn't just conceal ideas. It can also conceal the lack of them. That's why some people write that way, to conceal the fact that they have __nothing to say. Whereas writing simply keeps you honest. If you say nothing simply, it will be obvious to everyone, including you. Simple writing also lasts better.
2021年3月 我尝试用普通的词汇和简单的句式写作。 这样的文字更易阅读,而内容越容易理解,读者就越能深入思考。他们在文字上耗费的精力越少,留给思想的注意力就越多。 他们也会读得更远。大多数读者在阅读文章时往往半途而废。如果阅读阻力足够小,更多人会坚持读到结尾。 意大利有道名为"saltimbocca"的菜肴,意为"跳进嘴里"。我的写作目标或许可称为"saltintesta":让思想跃入你的脑海,而你几乎注意不到传递它们的文字。 指望写作能完全摆脱文字载体是不现实的。你甚至可能并不希望如此。但对大多数写作者而言,这始终是值得追求的目标。多数作品与纯粹思想之间的鸿沟里,填塞的并非诗意。 简单写作也是更体贴的选择。当你用花哨文风哗众取宠时,你是在强迫读者额外付出努力来成全你的虚荣。这就像拖着长长的裙摆,非要读者替你托着。 请记住,如果用英语写作,你的许多读者并非母语者。他们对思想的理解可能远胜于对英语的掌握。因此不能认为艰深的话题就必须搭配晦涩的词汇。
当然,华丽词藻不仅能掩盖思想,更能掩饰思想的匮乏。这正是某些人如此写作的原因——为了遮掩__空洞的内核。而简洁写作能保持诚实。若你言之无物,所有人——包括你自己——都会一目了然。
简洁的文字也更经得起时间考验。未来的读者处境与今日的异国读者相似:文化与语言都已变迁。在意这点并非虚荣,就像木匠追求椅子牢固无可厚非。
People reading your stuff in the future will be in much the same position as people from other countries reading it today. The culture and the language will have changed. It's not vain to care about that, any more than it's vain for a woodworker to build a chair to last. Indeed, lasting is not merely an accidental quality of chairs, or writing. It's a sign you did a good job. But although these are all real advantages of writing simply, none of them are why I do it. The main reason I write simply is that it offends me not to. When I write a sentence that seems too complicated, or that uses unnecessarily intellectual words, it doesn't seem fancy to me. It seems clumsy. There are of course times when you want to use a complicated sentence or fancy word for effect. But you should never do it by accident. The other reason my writing ends up being simple is the way I do it. I write the first draft fast, then spend days editing it, trying to get everything just right. Much of this editing is cutting, and that makes simple writing even simpler..
事实上,持久性并非椅子或文字的偶然属性。它是精工细作的证明。
尽管简洁写作有诸多好处,但这些都不是我的初衷。我坚持简练的根本原因,是繁复会触犯我的审美。当写下过于复杂的句子或故作高深的词汇时,我感受到的不是精致,而是笨拙。
当然,有时我们需要刻意使用复杂句式或华丽辞藻。但永远不该在无意中为之。
我的文字趋于简洁的另一个原因在于创作方式:快速完成初稿后,我会花数日编辑打磨。大量删减使简洁的文字愈发凝练。
March 2021 The secret curse of the nonprofit world is restricted donations. If you haven't been involved with nonprofits, you may never have heard this phrase before. But if you have been, it probably made you wince. Restricted donations mean donations where the donor limits what can be done with the money. This is common with big donations, perhaps the default. And yet it's usually a bad idea. Usually the way the donor wants the money spent is not the way the nonprofit would have chosen. Otherwise there would have been no need to restrict the donation. But who has a better understanding of where money needs to be spent, the nonprofit or the donor? If a nonprofit doesn't understand better than its donors where money needs to be spent, then it's incompetent and you shouldn't be donating to it at all. Which means a restricted donation is inherently suboptimal. It's either a donation to a bad nonprofit, or a donation for the wrong things. There are a couple exceptions to this principle. One is when the nonprofit is an umbrella organization. It's reasonable to make a restricted donation to a university, for example, because a university is only nominally a single nonprofit. Another exception is when the donor actually does know as much as the nonprofit about where money needs to be spent. The Gates Foundation, for example, has specific goals and often makes restricted donations to individual nonprofits to accomplish them. But unless you're a domain expert yourself or donating to an umbrella organization, your donation would do more good if it were unrestricted. If restricted donations do less good than unrestricted ones, why do donors so often make them? Partly because doing good isn't donors' only motive. They often have other motives as well — to make a mark, or to generate good publicity [1], or to comply with regulations or corporate policies.
2021年3月 非营利领域的隐秘诅咒是定向捐赠。若你未曾涉足非营利组织,或许从未听闻这个词;但若你身处其中,这个词很可能让你眉头紧锁。
定向捐赠意味着捐赠者对资金用途设限。大额捐赠常采用这种方式,甚至成为默认选项。然而这通常是个糟糕的主意——捐赠者指定的资金用途往往与受赠机构的选择背道而驰。若非如此,何必多此一举加以限制?但究竟谁更清楚资金应该投向何处:非营利组织还是捐赠者?
倘若一个非营利组织在资金分配上的判断力不及捐赠者,那它根本不配获得捐赠。
这意味着定向捐赠本质上就是次优选择:要么是捐给了糟糕的机构,要么是投向了错误的方向。
Many donors may simply never have considered the distinction between restricted and unrestricted donations. They may believe that donating money for some specific purpose is just how donation works. And to be fair, nonprofits don't try very hard to discourage such illusions. They can't afford to. People running nonprofits are almost always anxious about money. They can't afford to talk back to big donors. You can't expect candor in a relationship so asymmetric. So I'll tell you what nonprofits wish they could tell you. If you want to donate to a nonprofit, donate unrestricted. If you trust them to spend your money, trust them to decide how. Note [1] Unfortunately restricted donations tend to generate more publicity than unrestricted ones. "X donates money to build a school in Africa" is not only more interesting than "X donates money to Y nonprofit to spend as Y chooses," but also focuses more attention on X. Thanks to Chase Adam, Ingrid Bassett, Trevor Blackwell, and Edith Elliot for reading drafts of this..
此规则偶有例外。其一是当受赠方为伞形组织时,比如向大学进行定向捐赠就合乎情理,因为大学只是名义上的单一非营利实体。另一种情况是捐赠者确实具备与非营利组织同等的专业判断力,例如盖茨基金会有着明确目标,常通过定向捐赠驱动个别机构实现这些目标。但除非你本人是领域专家或捐赠对象是伞形组织,否则非定向捐赠能创造更大价值。
既然定向捐赠效果欠佳,为何捐赠者仍乐此不疲?部分原因在于"行善"并非唯一动机。标记个人印记、获取良好宣传[1]、遵守法规或企业政策等都可能是驱动力。许多捐赠者或许从未思考过定向与非定向捐赠的区别,认为"指定用途"就是捐赠的常态。平心而论,非营利机构也鲜少努力破除这种误解——它们承担不起这个代价。运营者总是为资金焦虑,根本不敢对大金主说半个不字。
在这种极度不对等的关系中,你很难期待坦诚相见。就让我来转述非营利组织想说却不敢说的话:若要捐赠,请选择非定向。既然信任他们支配资金,何不信任他们决策用途?
注释 [1] 可悲的是,定向捐赠往往比非定向更能博取关注。"X捐款在非洲建学校"不仅比"X捐款给Y机构自主支配"更具话题性,还能为捐赠者赢得更多聚光灯。
致谢 Chase Adam、Ingrid Bassett、Trevor Blackwell和Edith Elliot对本文草稿的审阅。
February 2021 Before college the two main things I worked on, outside of school, were writing and programming. I didn't write essays. I wrote what beginning writers were supposed to write then, and probably still are: short stories. My stories were awful. They had hardly any plot, just characters with strong feelings, which I imagined made them deep. The first programs I tried writing were on the IBM 1401 that our school district used for what was then called "data processing." This was in 9th grade, so I was 13 or 14. The school district's 1401 happened to be in the basement of our junior high school, and my friend Rich Draves and I got permission to use it. It was like a mini Bond villain's lair down there, with all these alien-looking machines � CPU, disk drives, printer, card reader � sitting up on a raised floor under bright fluorescent lights. The language we used was an early version of Fortran. You had to type programs on punch cards, then stack them in the card reader and press a button to load the program into memory and run it. The result would ordinarily be to print something on the spectacularly loud printer. I was puzzled by the 1401. I couldn't figure out what to do with it. And in retrospect there's not much I could have done with it. The only form of input to programs was data stored on punched cards, and I didn't have any data stored on punched cards. The only other option was to do things that didn't rely on any input, like calculate approximations of pi, but I didn't know enough math to do anything interesting of that type. So I'm not surprised I can't remember any programs I wrote, because they can't have done much. My clearest memory is of the moment I learned it was possible for programs not to terminate, when one of mine didn't. On a machine without time-sharing, this was a social as well as a technical error, as the data center manager's expression made clear. With microcomputers, everything changed.
上大学前,我在校外主要投入的两件事是写作和编程。我那时写的不是随笔,而是初学者"应该"写的短篇小说——这种观念至今可能仍未改变。我的小说糟糕透顶,几乎没有情节,只有情感强烈的角色,我天真地以为这样就能显得深刻。
Now you could have a computer sitting right in front of you, on a desk, that could respond to your keystrokes as it was running instead of just churning through a stack of punch cards and then stopping. [1] The first of my friends to get a microcomputer built it himself. It was sold as a kit by Heathkit. I remember vividly how impressed and envious I felt watching him sitting in front of it, typing programs right into the computer. Computers were expensive in those days and it took me years of nagging before I convinced my father to buy one, a TRS-80, in about 1980\. The gold standard then was the Apple II, but a TRS-80 was good enough. This was when I really started programming. I wrote simple games, a program to predict how high my model rockets would fly, and a word processor that my father used to write at least one book. There was only room in memory for about 2 pages of text, so he'd write 2 pages at a time and then print them out, but it was a lot better than a typewriter. Though I liked programming, I didn't plan to study it in college. In college I was going to study philosophy, which sounded much more powerful. It seemed, to my naive high school self, to be the study of the ultimate truths, compared to which the things studied in other fields would be mere domain knowledge. What I discovered when I got to college was that the other fields took up so much of the space of ideas that there wasn't much left for these supposed ultimate truths. All that seemed left for philosophy were edge cases that people in other fields felt could safely be ignored. I couldn't have put this into words when I was 18. All I knew at the time was that I kept taking philosophy courses and they kept being boring. So I decided to switch to AI.
我第一次尝试编程是在学校用来做"数据处理"的IBM 1401上。那时我九年级,十三四岁。这台机器恰好放在初中部地下室,我和朋友Rich Draves获准使用它。那里像迷你版邦德反派的老巢,各种外形奇特的机器——CPU、磁盘驱动器、打印机、读卡器——架设在抬高的地板上,沐浴在刺眼的荧光灯下。
AI was in the air in the mid 1980s, but there were two things especially that made me want to work on it: a novel by Heinlein called _The Moon is a Harsh Mistress_ , which featured an intelligent computer called Mike, and a PBS documentary that showed Terry Winograd using SHRDLU. I haven't tried rereading _The Moon is a Harsh Mistress_ , so I don't know how well it has aged, but when I read it I was drawn entirely into its world. It seemed only a matter of time before we'd have Mike, and when I saw Winograd using SHRDLU, it seemed like that time would be a few years at most. All you had to do was teach SHRDLU more words. There weren't any classes in AI at Cornell then, not even graduate classes, so I started trying to teach myself. Which meant learning Lisp, since in those days Lisp was regarded as the language of AI. The commonly used programming languages then were pretty primitive, and programmers' ideas correspondingly so. The default language at Cornell was a Pascal-like language called PL/I, and the situation was similar elsewhere. Learning Lisp expanded my concept of a program so fast that it was years before I started to have a sense of where the new limits were. This was more like it; this was what I had expected college to do. It wasn't happening in a class, like it was supposed to, but that was ok. For the next couple years I was on a roll. I knew what I was going to do. For my undergraduate thesis, I reverse-engineered SHRDLU. My God did I love working on that program. It was a pleasing bit of code, but what made it even more exciting was my belief � hard to imagine now, but not unique in 1985 � that it was already climbing the lower slopes of intelligence. I had gotten into a program at Cornell that didn't make you choose a major. You could take whatever classes you liked, and choose whatever you liked to put on your degree.
我们用的是早期Fortran语言。程序要打在穿孔卡片上,叠放进读卡器,按下按钮才能加载运行。结果通常是通过那台噪音惊人的打印机输出。这台机器让我困惑不已——我完全不知道能用它做什么。现在回想起来,确实也做不了什么:程序输入只能读取穿孔卡片上的数据,而我手头根本没有数据卡片;另一选择是编写不依赖输入的程序,比如计算圆周率近似值,但我的数学水平又不足以做出有趣的东西。难怪我记不起自己写过什么程序,因为它们实在乏善可陈。最清晰的记忆是某次程序陷入死循环,让我第一次意识到程序可能无法终止。在没有分时系统的年代,这种技术错误也会演变成社交灾难——数据中心管理员的表情说明了一切。
微电脑改变了一切。现在你可以把计算机放在桌上实时响应按键,而不是一次性处理整叠卡片后停止运行。[1]
I of course chose "Artificial Intelligence." When I got the actual physical diploma, I was dismayed to find that the quotes had been included, which made them read as scare-quotes. At the time this bothered me, but now it seems amusingly accurate, for reasons I was about to discover. I applied to 3 grad schools: MIT and Yale, which were renowned for AI at the time, and Harvard, which I'd visited because Rich Draves went there, and was also home to Bill Woods, who'd invented the type of parser I used in my SHRDLU clone. Only Harvard accepted me, so that was where I went. I don't remember the moment it happened, or if there even was a specific moment, but during the first year of grad school I realized that AI, as practiced at the time, was a hoax. By which I mean the sort of AI in which a program that's told "the dog is sitting on the chair" translates this into some formal representation and adds it to the list of things it knows. What these programs really showed was that there's a subset of natural language that's a formal language. But a very proper subset. It was clear that there was an unbridgeable gap between what they could do and actually understanding natural language. It was not, in fact, simply a matter of teaching SHRDLU more words. That whole way of doing AI, with explicit data structures representing concepts, was not going to work. Its brokenness did, as so often happens, generate a lot of opportunities to write papers about various band-aids that could be applied to it, but it was never going to get us Mike. So I looked around to see what I could salvage from the wreckage of my plans, and there was Lisp. I knew from experience that Lisp was interesting for its own sake and not just for its association with AI, even though that was the main reason people cared about it at the time. So I decided to focus on Lisp. In fact, I decided to write a book about Lisp hacking.
朋友中第一个拥有微电脑的人是自己组装的Heathkit套件。我至今记得看着他坐在机器前直接输入程序时,那种混合着震撼与嫉妒的感受。
It's scary to think how little I knew about Lisp hacking when I started writing that book. But there's nothing like writing a book about something to help you learn it. The book, _On Lisp_ , wasn't published till 1993, but I wrote much of it in grad school. Computer Science is an uneasy alliance between two halves, theory and systems. The theory people prove things, and the systems people build things. I wanted to build things. I had plenty of respect for theory � indeed, a sneaking suspicion that it was the more admirable of the two halves � but building things seemed so much more exciting. The problem with systems work, though, was that it didn't last. Any program you wrote today, no matter how good, would be obsolete in a couple decades at best. People might mention your software in footnotes, but no one would actually use it. And indeed, it would seem very feeble work. Only people with a sense of the history of the field would even realize that, in its time, it had been good. There were some surplus Xerox Dandelions floating around the computer lab at one point. Anyone who wanted one to play around with could have one. I was briefly tempted, but they were so slow by present standards; what was the point? No one else wanted one either, so off they went. That was what happened to systems work. I wanted not just to build things, but to build things that would last. In this dissatisfied state I went in 1988 to visit Rich Draves at CMU, where he was in grad school. One day I went to visit the Carnegie Institute, where I'd spent a lot of time as a kid. While looking at a painting there I realized something that might seem obvious, but was a big surprise to me. There, right on the wall, was something you could make that would last. Paintings didn't become obsolete. Some of the best ones were hundreds of years old. And moreover this was something you could make a living doing.
当时电脑价格昂贵,经过多年软磨硬泡,我才在1980年左右说服父亲买了台TRS-80。虽然Apple II是黄金标准,但TRS-80也够用了。这才真正开启我的编程生涯:写简单游戏、预测模型火箭飞行高度的程序,还有父亲用来写书(至少一本)的文字处理器。内存只能容纳约两页文本,所以他得写两页打印一次,但比起打字机已是巨大进步。
尽管热爱编程,我并没打算大学主修它。我计划攻读哲学——在高中生的天真想象中,这是研究终极真理的学科,其他领域不过是特定领域的知识。进入大学后才发现,其他学科已占据思想领域的大片疆土,留给所谓终极真理的空间所剩无几。哲学似乎只剩下其他学科认为可以安全忽略的边缘案例。
Not as easily as you could by writing software, of course, but I thought if you were really industrious and lived really cheaply, it had to be possible to make enough to survive. And as an artist you could be truly independent. You wouldn't have a boss, or even need to get research funding. I had always liked looking at paintings. Could I make them? I had no idea. I'd never imagined it was even possible. I knew intellectually that people made art � that it didn't just appear spontaneously � but it was as if the people who made it were a different species. They either lived long ago or were mysterious geniuses doing strange things in profiles in _Life_ magazine. The idea of actually being able to make art, to put that verb before that noun, seemed almost miraculous. That fall I started taking art classes at Harvard. Grad students could take classes in any department, and my advisor, Tom Cheatham, was very easy going. If he even knew about the strange classes I was taking, he never said anything. So now I was in a PhD program in computer science, yet planning to be an artist, yet also genuinely in love with Lisp hacking and working away at _On Lisp_. In other words, like many a grad student, I was working energetically on multiple projects that were not my thesis. I didn't see a way out of this situation. I didn't want to drop out of grad school, but how else was I going to get out? I remember when my friend Robert Morris got kicked out of Cornell for writing the internet worm of 1988, I was envious that he'd found such a spectacular way to get out of grad school. Then one day in April 1990 a crack appeared in the wall. I ran into professor Cheatham and he asked if I was far enough along to graduate that June.
18岁的我还无法清晰表述这种认知,只知道自己不断选修哲学课程却始终感到乏味。于是决定转向人工智能。
I didn't have a word of my dissertation written, but in what must have been the quickest bit of thinking in my life, I decided to take a shot at writing one in the 5 weeks or so that remained before the deadline, reusing parts of _On Lisp_ where I could, and I was able to respond, with no perceptible delay "Yes, I think so. I'll give you something to read in a few days." I picked applications of continuations as the topic. In retrospect I should have written about macros and embedded languages. There's a whole world there that's barely been explored. But all I wanted was to get out of grad school, and my rapidly written dissertation sufficed, just barely. Meanwhile I was applying to art schools. I applied to two: RISD in the US, and the Accademia di Belli Arti in Florence, which, because it was the oldest art school, I imagined would be good. RISD accepted me, and I never heard back from the Accademia, so off to Providence I went. I'd applied for the BFA program at RISD, which meant in effect that I had to go to college again. This was not as strange as it sounds, because I was only 25, and art schools are full of people of different ages. RISD counted me as a transfer sophomore and said I had to do the foundation that summer. The foundation means the classes that everyone has to take in fundamental subjects like drawing, color, and design. Toward the end of the summer I got a big surprise: a letter from the Accademia, which had been delayed because they'd sent it to Cambridge England instead of Cambridge Massachusetts, inviting me to take the entrance exam in Florence that fall. This was now only weeks away. My nice landlady let me leave my stuff in her attic. I had some money saved from consulting work I'd done in grad school; there was probably enough to last a year if I lived cheaply. Now all I had to do was learn Italian. Only _stranieri_ (foreigners) had to take this entrance exam.
1980年代中期,AI热潮涌动,但真正点燃我热情的是两件事:海因莱因小说《严厉的月亮》中名为迈克的智能计算机,以及PBS纪录片里Terry Winograd演示的SHRDLU系统。虽然不确定《严厉的月亮》是否经得起时间考验,但当时它让我完全沉浸其中,仿佛迈克这样的AI问世只是时间问题;而看到SHRDLU时,感觉这个时间最多不过几年——似乎只需教它更多单词就能实现。
当时康奈尔大学没有AI课程(连研究生课程都没有),我开始自学。这意味着要学Lisp——那时被视为AI语言的主流编程语言相当原始,程序员思维也相应受限。康奈尔主要使用类Pascal语言PL/I,其他学校情况类似。Lisp极大拓展了我对程序的认知,以至于多年后才摸清新边界。这才像话——这才是我期待大学带来的思维跃迁。虽然没通过正规课程实现,但无所谓。接下来几年我势如破竹,终于明确了自己要做什么。
In retrospect it may well have been a way of excluding them, because there were so many _stranieri_ attracted by the idea of studying art in Florence that the Italian students would otherwise have been outnumbered. I was in decent shape at painting and drawing from the RISD foundation that summer, but I still don't know how I managed to pass the written exam. I remember that I answered the essay question by writing about Cezanne, and that I cranked up the intellectual level as high as I could to make the most of my limited vocabulary. [2] I'm only up to age 25 and already there are such conspicuous patterns. Here I was, yet again about to attend some august institution in the hopes of learning about some prestigious subject, and yet again about to be disappointed. The students and faculty in the painting department at the Accademia were the nicest people you could imagine, but they had long since arrived at an arrangement whereby the students wouldn't require the faculty to teach anything, and in return the faculty wouldn't require the students to learn anything. And at the same time all involved would adhere outwardly to the conventions of a 19th century atelier. We actually had one of those little stoves, fed with kindling, that you see in 19th century studio paintings, and a nude model sitting as close to it as possible without getting burned. Except hardly anyone else painted her besides me. The rest of the students spent their time chatting or occasionally trying to imitate things they'd seen in American art magazines. Our model turned out to live just down the street from me. She made a living from a combination of modelling and making fakes for a local antique dealer. She'd copy an obscure old painting out of a book, and then he'd take the copy and maltreat it to make it look old. [3] While I was a student at the Accademia I started painting still lives in my bedroom at night.
本科论文我逆向工程了SHRDLU。天啊,我太爱这个项目了!代码本身令人愉悦,更让我兴奋的是(如今难以想象,但在1985年并非个例)——我坚信它正在攀登智能的初级台阶。
These paintings were tiny, because the room was, and because I painted them on leftover scraps of canvas, which was all I could afford at the time. Painting still lives is different from painting people, because the subject, as its name suggests, can't move. People can't sit for more than about 15 minutes at a time, and when they do they don't sit very still. So the traditional m.o. for painting people is to know how to paint a generic person, which you then modify to match the specific person you're painting. Whereas a still life you can, if you want, copy pixel by pixel from what you're seeing. You don't want to stop there, of course, or you get merely photographic accuracy, and what makes a still life interesting is that it's been through a head. You want to emphasize the visual cues that tell you, for example, that the reason the color changes suddenly at a certain point is that it's the edge of an object. By subtly emphasizing such things you can make paintings that are more realistic than photographs not just in some metaphorical sense, but in the strict information-theoretic sense. [4] I liked painting still lives because I was curious about what I was seeing. In everyday life, we aren't consciously aware of much we're seeing. Most visual perception is handled by low-level processes that merely tell your brain "that's a water droplet" without telling you details like where the lightest and darkest points are, or "that's a bush" without telling you the shape and position of every leaf. This is a feature of brains, not a bug. In everyday life it would be distracting to notice every leaf on every bush. But when you have to paint something, you have to look more closely, and when you do there's a lot to see. You can still be noticing new things after days of trying to paint something people usually take for granted, just as you can after days of trying to write an essay about something people usually take for granted.
我参加了康奈尔一个无需选定专业的特殊项目,可以自由选课并自定学位名称。当然,我选了"人工智能"。当拿到实体文凭时,发现引号被原样保留,看起来像讽刺性引用。当时很困扰,如今却觉得准确得有趣——原因我即将发现。
我申请了三所研究生院:当时以AI闻名的MIT和耶鲁,以及因Rich Draves就读而参观过的哈佛(Bill Woods也在那里——他发明的解析器类型正是我克隆SHRDLU时采用的)。只有哈佛录取了我。
This is not the only way to paint. I'm not 100% sure it's even a good way to paint. But it seemed a good enough bet to be worth trying. Our teacher, professor Ulivi, was a nice guy. He could see I worked hard, and gave me a good grade, which he wrote down in a sort of passport each student had. But the Accademia wasn't teaching me anything except Italian, and my money was running out, so at the end of the first year I went back to the US. I wanted to go back to RISD, but I was now broke and RISD was very expensive, so I decided to get a job for a year and then return to RISD the next fall. I got one at a company called Interleaf, which made software for creating documents. You mean like Microsoft Word? Exactly. That was how I learned that low end software tends to eat high end software. But Interleaf still had a few years to live yet. [5] Interleaf had done something pretty bold. Inspired by Emacs, they'd added a scripting language, and even made the scripting language a dialect of Lisp. Now they wanted a Lisp hacker to write things in it. This was the closest thing I've had to a normal job, and I hereby apologize to my boss and coworkers, because I was a bad employee. Their Lisp was the thinnest icing on a giant C cake, and since I didn't know C and didn't want to learn it, I never understood most of the software. Plus I was terribly irresponsible. This was back when a programming job meant showing up every day during certain working hours. That seemed unnatural to me, and on this point the rest of the world is coming around to my way of thinking, but at the time it caused a lot of friction. Toward the end of the year I spent much of my time surreptitiously working on _On Lisp_ , which I had by this time gotten a contract to publish. The good part was that I got paid huge amounts of money, especially by art student standards. In Florence, after paying my part of the rent, my budget for everything else had been $7 a day.
不记得具体时刻,但在研究生第一年,我意识到当时实践的AI是个骗局。我指的是那种被告知"狗坐在椅子上"就将其转化为形式化表示并加入知识库的程序。这类程序实际证明的只是自然语言中存在形式语言的子集——而且是非常有限的子集。它们与真正理解自然语言之间存在不可逾越的鸿沟。教SHRDLU更多单词根本不够。这种用显式数据结构表示概念的AI路径注定失败。就像常发生的那样,这种缺陷催生了许多修补性论文,但永远无法带我们抵达迈克。
Now I was getting paid more than 4 times that every hour, even when I was just sitting in a meeting. By living cheaply I not only managed to save enough to go back to RISD, but also paid off my college loans. I learned some useful things at Interleaf, though they were mostly about what not to do. I learned that it's better for technology companies to be run by product people than sales people (though sales is a real skill and people who are good at it are really good at it), that it leads to bugs when code is edited by too many people, that cheap office space is no bargain if it's depressing, that planned meetings are inferior to corridor conversations, that big, bureaucratic customers are a dangerous source of money, and that there's not much overlap between conventional office hours and the optimal time for hacking, or conventional offices and the optimal place for it. But the most important thing I learned, and which I used in both Viaweb and Y Combinator, is that the low end eats the high end: that it's good to be the "entry level" option, even though that will be less prestigious, because if you're not, someone else will be, and will squash you against the ceiling. Which in turn means that prestige is a danger sign. When I left to go back to RISD the next fall, I arranged to do freelance work for the group that did projects for customers, and this was how I survived for the next several years. When I came back to visit for a project later on, someone told me about a new thing called HTML, which was, as he described it, a derivative of SGML. Markup language enthusiasts were an occupational hazard at Interleaf and I ignored him, but this HTML thing later became a big part of my life. In the fall of 1992 I moved back to Providence to continue at RISD. The foundation had merely been intro stuff, and the Accademia had been a (very civilized) joke. Now I was going to see what real art school was like.
于是我在计划废墟中寻找 salvage,发现了Lisp。从经验中我知道Lisp本身就有趣,不仅因它与AI的关联——尽管这是当时人们关注它的主因。我决定专注Lisp,甚至要写本关于Lisp黑客的书。回想起来,动笔时我对Lisp黑客的理解少得可怕。但没有什么比写书更能促进学习。《On Lisp》直到1993年才出版,但大部分内容写于研究生时期。
But alas it was more like the Accademia than not. Better organized, certainly, and a lot more expensive, but it was now becoming clear that art school did not bear the same relationship to art that medical school bore to medicine. At least not the painting department. The textile department, which my next door neighbor belonged to, seemed to be pretty rigorous. No doubt illustration and architecture were too. But painting was post-rigorous. Painting students were supposed to express themselves, which to the more worldly ones meant to try to cook up some sort of distinctive signature style. A signature style is the visual equivalent of what in show business is known as a "schtick": something that immediately identifies the work as yours and no one else's. For example, when you see a painting that looks like a certain kind of cartoon, you know it's by Roy Lichtenstein. So if you see a big painting of this type hanging in the apartment of a hedge fund manager, you know he paid millions of dollars for it. That's not always why artists have a signature style, but it's usually why buyers pay a lot for such work. [6] There were plenty of earnest students too: kids who "could draw" in high school, and now had come to what was supposed to be the best art school in the country, to learn to draw even better. They tended to be confused and demoralized by what they found at RISD, but they kept going, because painting was what they did. I was not one of the kids who could draw in high school, but at RISD I was definitely closer to their tribe than the tribe of signature style seekers. I learned a lot in the color class I took at RISD, but otherwise I was basically teaching myself to paint, and I could do that for free. So in 1993 I dropped out. I hung around Providence for a bit, and then my college friend Nancy Parmet did me a big favor. A rent-controlled apartment in a building her mother owned in New York was becoming vacant.
计算机科学是理论与系统两部分的 uneasy alliance。理论派证明定理,系统派构建实物。我想成为构建者。虽然对理论充满敬意(暗自怀疑它更值得钦佩),但建造东西似乎刺激得多。
系统工作的致命缺陷是不持久。今天写的任何程序,无论多优秀,最多几十年就会过时。人们可能在脚注提及你的软件,但没人真正使用——实际上它会显得非常 feeble。只有了解领域历史的人才会知道它曾很出色。
Did I want it? It wasn't much more than my current place, and New York was supposed to be where the artists were. So yes, I wanted it! [7] Asterix comics begin by zooming in on a tiny corner of Roman Gaul that turns out not to be controlled by the Romans. You can do something similar on a map of New York City: if you zoom in on the Upper East Side, there's a tiny corner that's not rich, or at least wasn't in 1993. It's called Yorkville, and that was my new home. Now I was a New York artist � in the strictly technical sense of making paintings and living in New York. I was nervous about money, because I could sense that Interleaf was on the way down. Freelance Lisp hacking work was very rare, and I didn't want to have to program in another language, which in those days would have meant C++ if I was lucky. So with my unerring nose for financial opportunity, I decided to write another book on Lisp. This would be a popular book, the sort of book that could be used as a textbook. I imagined myself living frugally off the royalties and spending all my time painting. (The painting on the cover of this book, _ANSI Common Lisp_ , is one that I painted around this time.) The best thing about New York for me was the presence of Idelle and Julian Weber. Idelle Weber was a painter, one of the early photorealists, and I'd taken her painting class at Harvard. I've never known a teacher more beloved by her students. Large numbers of former students kept in touch with her, including me. After I moved to New York I became her de facto studio assistant. She liked to paint on big, square canvases, 4 to 5 feet on a side. One day in late 1994 as I was stretching one of these monsters there was something on the radio about a famous fund manager. He wasn't that much older than me, and was super rich. The thought suddenly occurred to me: why don't I become rich? Then I'll be able to work on whatever I want.
有段时间实验室出现过剩的Xerox Dandelion电脑,任何人都可以领一台玩。我短暂心动过,但以当时标准它们太慢了——有什么意义?最终无人认领的机器被处理掉。这就是系统工作的宿命。
Meanwhile I'd been hearing more and more about this new thing called the World Wide Web. Robert Morris showed it to me when I visited him in Cambridge, where he was now in grad school at Harvard. It seemed to me that the web would be a big deal. I'd seen what graphical user interfaces had done for the popularity of microcomputers. It seemed like the web would do the same for the internet. If I wanted to get rich, here was the next train leaving the station. I was right about that part. What I got wrong was the idea. I decided we should start a company to put art galleries online. I can't honestly say, after reading so many Y Combinator applications, that this was the worst startup idea ever, but it was up there. Art galleries didn't want to be online, and still don't, not the fancy ones. That's not how they sell. I wrote some software to generate web sites for galleries, and Robert wrote some to resize images and set up an http server to serve the pages. Then we tried to sign up galleries. To call this a difficult sale would be an understatement. It was difficult to give away. A few galleries let us make sites for them for free, but none paid us. Then some online stores started to appear, and I realized that except for the order buttons they were identical to the sites we'd been generating for galleries. This impressive-sounding thing called an "internet storefront" was something we already knew how to build. So in the summer of 1995, after I submitted the camera-ready copy of _ANSI Common Lisp_ to the publishers, we started trying to write software to build online stores. At first this was going to be normal desktop software, which in those days meant Windows software. That was an alarming prospect, because neither of us knew how to write Windows software or wanted to learn. We lived in the Unix world. But we decided we'd at least try writing a prototype store builder on Unix.
我想建造能持久的东西。
带着这种不满,1988年我去CMU拜访读研的Rich Draves。某天参观卡内基研究所(童年常去之地)时,看着墙上的画作突然顿悟(看似 obvious 却让我震惊):墙上挂着的正是能永恒存在之物。画作不会过时,最杰出的已有数百年历史。
Robert wrote a shopping cart, and I wrote a new site generator for stores � in Lisp, of course. We were working out of Robert's apartment in Cambridge. His roommate was away for big chunks of time, during which I got to sleep in his room. For some reason there was no bed frame or sheets, just a mattress on the floor. One morning as I was lying on this mattress I had an idea that made me sit up like a capital L. What if we ran the software on the server, and let users control it by clicking on links? Then we'd never have to write anything to run on users' computers. We could generate the sites on the same server we'd serve them from. Users wouldn't need anything more than a browser. This kind of software, known as a web app, is common now, but at the time it wasn't clear that it was even possible. To find out, we decided to try making a version of our store builder that you could control through the browser. A couple days later, on August 12, we had one that worked. The UI was horrible, but it proved you could build a whole store through the browser, without any client software or typing anything into the command line on the server. Now we felt like we were really onto something. I had visions of a whole new generation of software working this way. You wouldn't need versions, or ports, or any of that crap. At Interleaf there had been a whole group called Release Engineering that seemed to be at least as big as the group that actually wrote the software. Now you could just update the software right on the server. We started a new company we called Viaweb, after the fact that our software worked via the web, and we got $10,000 in seed funding from Idelle's husband Julian. In return for that and doing the initial legal work and giving us business advice, we gave him 10% of the company. Ten years later this deal became the model for Y Combinator's. We knew founders needed something like this, because we'd needed it ourselves.
而且这能谋生。当然不如写软件容易,但我想如果足够勤奋且生活简朴,应该能维持生计。作为艺术家还能真正独立——没有老板,甚至不需要研究经费。
At this stage I had a negative net worth, because the thousand dollars or so I had in the bank was more than counterbalanced by what I owed the government in taxes. (Had I diligently set aside the proper proportion of the money I'd made consulting for Interleaf? No, I had not.) So although Robert had his graduate student stipend, I needed that seed funding to live on. We originally hoped to launch in September, but we got more ambitious about the software as we worked on it. Eventually we managed to build a WYSIWYG site builder, in the sense that as you were creating pages, they looked exactly like the static ones that would be generated later, except that instead of leading to static pages, the links all referred to closures stored in a hash table on the server. It helped to have studied art, because the main goal of an online store builder is to make users look legit, and the key to looking legit is high production values. If you get page layouts and fonts and colors right, you can make a guy running a store out of his bedroom look more legit than a big company. (If you're curious why my site looks so old-fashioned, it's because it's still made with this software. It may look clunky today, but in 1996 it was the last word in slick.) In September, Robert rebelled. "We've been working on this for a month," he said, "and it's still not done." This is funny in retrospect, because he would still be working on it almost 3 years later. But I decided it might be prudent to recruit more programmers, and I asked Robert who else in grad school with him was really good. He recommended Trevor Blackwell, which surprised me at first, because at that point I knew Trevor mainly for his plan to reduce everything in his life to a stack of notecards, which he carried around with him. But Rtm was right, as usual. Trevor turned out to be a frighteningly effective hacker. It was a lot of fun working with Robert and Trevor.
我一直喜欢看画。我能画吗?毫无头绪。以前甚至觉得不可能。理性知道艺术是人创作的(不会凭空出现),但创作者仿佛是不同的物种——要么是古人,要么是《生活》杂志里做着古怪事情的神秘天才。真正能"创作艺术"这个想法近乎奇迹。
那年秋天我开始在哈佛修艺术课。研究生可以跨系选课,我的导师Tom Cheatham非常开明。就算知道我选这些奇怪课程,也从不过问。
They're the two most _independent-minded_ people I know, and in completely different ways. If you could see inside Rtm's brain it would look like a colonial New England church, and if you could see inside Trevor's it would look like the worst excesses of Austrian Rococo. We opened for business, with 6 stores, in January 1996. It was just as well we waited a few months, because although we worried we were late, we were actually almost fatally early. There was a lot of talk in the press then about ecommerce, but not many people actually wanted online stores. [8] There were three main parts to the software: the editor, which people used to build sites and which I wrote, the shopping cart, which Robert wrote, and the manager, which kept track of orders and statistics, and which Trevor wrote. In its time, the editor was one of the best general-purpose site builders. I kept the code tight and didn't have to integrate with any other software except Robert's and Trevor's, so it was quite fun to work on. If all I'd had to do was work on this software, the next 3 years would have been the easiest of my life. Unfortunately I had to do a lot more, all of it stuff I was worse at than programming, and the next 3 years were instead the most stressful. There were a lot of startups making ecommerce software in the second half of the 90s. We were determined to be the Microsoft Word, not the Interleaf. Which meant being easy to use and inexpensive. It was lucky for us that we were poor, because that caused us to make Viaweb even more inexpensive than we realized. We charged $100 a month for a small store and $300 a month for a big one. This low price was a big attraction, and a constant thorn in the sides of competitors, but it wasn't because of some clever insight that we set the price low. We had no idea what businesses paid for things. $300 a month seemed like a lot of money to us. We did a lot of things right by accident like that.
于是,我在计算机科学博士项目里计划成为艺术家,同时真心热爱Lisp黑客并埋头写《On Lisp》。像许多研究生一样,我精力充沛地投入多个非论文项目。
For example, we did what's now called "doing things that _don't scale_," although at the time we would have described it as "being so lame that we're driven to the most desperate measures to get users." The most common of which was building stores for them. This seemed particularly humiliating, since the whole raison d'etre of our software was that people could use it to make their own stores. But anything to get users. We learned a lot more about retail than we wanted to know. For example, that if you could only have a small image of a man's shirt (and all images were small then by present standards), it was better to have a closeup of the collar than a picture of the whole shirt. The reason I remember learning this was that it meant I had to rescan about 30 images of men's shirts. My first set of scans were so beautiful too. Though this felt wrong, it was exactly the right thing to be doing. Building stores for users taught us about retail, and about how it felt to use our software. I was initially both mystified and repelled by "business" and thought we needed a "business person" to be in charge of it, but once we started to get users, I was converted, in much the same way I was converted to _fatherhood_ once I had kids. Whatever users wanted, I was all theirs. Maybe one day we'd have so many users that I couldn't scan their images for them, but in the meantime there was nothing more important to do. Another thing I didn't get at the time is that _growth rate_ is the ultimate test of a startup. Our growth rate was fine. We had about 70 stores at the end of 1996 and about 500 at the end of 1997. I mistakenly thought the thing that mattered was the absolute number of users. And that is the thing that matters in the sense that that's how much money you're making, and if you're not making enough, you might go out of business. But in the long term the growth rate takes care of the absolute number.
我看不到出路。不想退学,但还有其他选择吗?记得1988年朋友Robert Morris因编写互联网蠕虫被康奈尔开除时,我甚至羡慕他找到如此 spectacular 的退学方式。
1990年4月某天,转机出现。偶遇Cheatham教授,他问我是否能在6月毕业。虽然论文一字未写,但我以生平最快的思维速度决定放手一搏——用剩余5周撰写,尽可能复用《On Lisp》内容,并毫不迟疑地回答:"是的,我想可以。几天内给您初稿。"
If we'd been a startup I was advising at Y Combinator, I would have said: Stop being so stressed out, because you're doing fine. You're growing 7x a year. Just don't hire too many more people and you'll soon be profitable, and then you'll control your own destiny. Alas I hired lots more people, partly because our investors wanted me to, and partly because that's what startups did during the Internet Bubble. A company with just a handful of employees would have seemed amateurish. So we didn't reach breakeven until about when Yahoo bought us in the summer of 1998. Which in turn meant we were at the mercy of investors for the entire life of the company. And since both we and our investors were noobs at startups, the result was a mess even by startup standards. It was a huge relief when Yahoo bought us. In principle our Viaweb stock was valuable. It was a share in a business that was profitable and growing rapidly. But it didn't feel very valuable to me; I had no idea how to value a business, but I was all too keenly aware of the near-death experiences we seemed to have every few months. Nor had I changed my grad student lifestyle significantly since we started. So when Yahoo bought us it felt like going from rags to riches. Since we were going to California, I bought a car, a yellow 1998 VW GTI. I remember thinking that its leather seats alone were by far the most luxurious thing I owned. The next year, from the summer of 1998 to the summer of 1999, must have been the least productive of my life. I didn't realize it at the time, but I was worn out from the effort and stress of running Viaweb. For a while after I got to California I tried to continue my usual m.o. of programming till 3 in the morning, but fatigue combined with Yahoo's prematurely aged _culture_ and grim cube farm in Santa Clara gradually dragged me down. After a few months it felt disconcertingly like working at Interleaf.
我选"continuation的应用"作为主题。事后看应该写宏和嵌入式语言——那有整个未被探索的世界。但当时只想毕业,仓促完成的论文勉强达标。
Yahoo had given us a lot of options when they bought us. At the time I thought Yahoo was so overvalued that they'd never be worth anything, but to my astonishment the stock went up 5x in the next year. I hung on till the first chunk of options vested, then in the summer of 1999 I left. It had been so long since I'd painted anything that I'd half forgotten why I was doing this. My brain had been entirely full of software and men's shirts for 4 years. But I had done this to get rich so I could paint, I reminded myself, and now I was rich, so I should go paint. When I said I was leaving, my boss at Yahoo had a long conversation with me about my plans. I told him all about the kinds of pictures I wanted to paint. At the time I was touched that he took such an interest in me. Now I realize it was because he thought I was lying. My options at that point were worth about $2 million a month. If I was leaving that kind of money on the table, it could only be to go and start some new startup, and if I did, I might take people with me. This was the height of the Internet Bubble, and Yahoo was ground zero of it. My boss was at that moment a billionaire. Leaving then to start a new startup must have seemed to him an insanely, and yet also plausibly, ambitious plan. But I really was quitting to paint, and I started immediately. There was no time to lose. I'd already burned 4 years getting rich. Now when I talk to founders who are leaving after selling their companies, my advice is always the same: take a vacation. That's what I should have done, just gone off somewhere and done nothing for a month or two, but the idea never occurred to me. So I tried to paint, but I just didn't seem to have any energy or ambition. Part of the problem was that I didn't know many people in California. I'd compounded this problem by buying a house up in the Santa Cruz Mountains, with a beautiful view but miles from anywhere.
同时我申请了两所艺术学院:美国的RISD和佛罗伦萨美术学院(因其历史最悠久而认为必然优秀)。RISD录取了我,佛罗伦萨音讯全无,于是前往普罗维登斯。
我申请的是RISD本科项目,相当于重读大学。这没听起来那么奇怪——我才25岁,而艺术学院本就年龄多元。RISD将我算作大二转学生,要求暑期先修基础课程(所有人必修的绘画、色彩、设计等)。
I stuck it out for a few more months, then in desperation I went back to New York, where unless you understand about rent control you'll be surprised to hear I still had my apartment, sealed up like a tomb of my old life. Idelle was in New York at least, and there were other people trying to paint there, even though I didn't know any of them. When I got back to New York I resumed my old life, except now I was rich. It was as weird as it sounds. I resumed all my old patterns, except now there were doors where there hadn't been. Now when I was tired of walking, all I had to do was raise my hand, and (unless it was raining) a taxi would stop to pick me up. Now when I walked past charming little restaurants I could go in and order lunch. It was exciting for a while. Painting started to go better. I experimented with a new kind of still life where I'd paint one painting in the old way, then photograph it and print it, blown up, on canvas, and then use that as the underpainting for a second still life, painted from the same objects (which hopefully hadn't rotted yet). Meanwhile I looked for an apartment to buy. Now I could actually choose what neighborhood to live in. Where, I asked myself and various real estate agents, is the Cambridge of New York? Aided by occasional visits to actual Cambridge, I gradually realized there wasn't one. Huh. Around this time, in the spring of 2000, I had an idea. It was clear from our experience with Viaweb that web apps were the future. Why not build a web app for making web apps? Why not let people edit code on our server through the browser, and then host the resulting applications for them? [9] You could run all sorts of services on the servers that these applications could use just by making an API call: making and receiving phone calls, manipulating images, taking credit card payments, etc. I got so excited about this idea that I couldn't think about anything else. It seemed obvious that this was the future.
夏末收到意外惊喜:因寄错地址(英国剑桥而非马萨诸塞剑桥)而迟到的佛罗伦萨美院来信,邀请我秋季参加入学考试。此时距考试仅剩几周。好心的房东让我把物品留在阁楼,我用研究生时期做咨询的积蓄(省着用大概能撑一年)踏上旅程,只剩意大利语要突击。
I didn't particularly want to start another company, but it was clear that this idea would have to be embodied as one, so I decided to move to Cambridge and start it. I hoped to lure Robert into working on it with me, but there I ran into a hitch. Robert was now a postdoc at MIT, and though he'd made a lot of money the last time I'd lured him into working on one of my schemes, it had also been a huge time sink. So while he agreed that it sounded like a plausible idea, he firmly refused to work on it. Hmph. Well, I'd do it myself then. I recruited Dan Giffin, who had worked for Viaweb, and two undergrads who wanted summer jobs, and we got to work trying to build what it's now clear is about twenty companies and several open source projects worth of software. The language for defining applications would of course be a dialect of Lisp. But I wasn't so naive as to assume I could spring an overt Lisp on a general audience; we'd hide the parentheses, like Dylan did. By then there was a name for the kind of company Viaweb was, an "application service provider," or ASP. This name didn't last long before it was replaced by "software as a service," but it was current for long enough that I named this new company after it: it was going to be called Aspra. I started working on the application builder, Dan worked on network infrastructure, and the two undergrads worked on the first two services (images and phone calls). But about halfway through the summer I realized I really didn't want to run a company � especially not a big one, which it was looking like this would have to be. I'd only started Viaweb because I needed the money. Now that I didn't need money anymore, why was I doing this? If this vision had to be realized as a company, then screw the vision. I'd build a subset that could be done as an open source project. Much to my surprise, the time I spent working on this stuff was not wasted after all.
只有外国人(stranieri)需要参加这个考试。现在想来可能是限制外国人的手段——否则想来佛罗伦萨学艺术的留学生会让意大利学生沦为少数派。得益于RISD暑期基础课,我的绘画水平尚可,但至今不知如何通过笔试——记得论述题我写的是塞尚,用尽有限词汇竭力拔高论述深度。[2]
After we started Y Combinator, I would often encounter startups working on parts of this new architecture, and it was very useful to have spent so much time thinking about it and even trying to write some of it. The subset I would build as an open source project was the new Lisp, whose parentheses I now wouldn't even have to hide. A lot of Lisp hackers dream of building a new Lisp, partly because one of the distinctive features of the language is that it has dialects, and partly, I think, because we have in our minds a Platonic form of Lisp that all existing dialects fall short of. I certainly did. So at the end of the summer Dan and I switched to working on this new dialect of Lisp, which I called Arc, in a house I bought in Cambridge. The following spring, lightning struck. I was invited to give a talk at a Lisp conference, so I gave one about how we'd used Lisp at Viaweb. Afterward I put a postscript file of this talk online, on paulgraham.com, which I'd created years before using Viaweb but had never used for anything. In one day it got 30,000 page views. What on earth had happened? The referring urls showed that someone had posted it on Slashdot. [10] Wow, I thought, there's an audience. If I write something and put it on the web, anyone can read it. That may seem obvious now, but it was surprising then. In the print era there was a narrow channel to readers, guarded by fierce monsters known as editors. The only way to get an audience for anything you wrote was to get it published as a book, or in a newspaper or magazine. Now anyone could publish anything. This had been possible in principle since 1993, but not many people had realized it yet. I had been intimately involved with building the infrastructure of the web for most of that time, and a writer as well, and it had taken me 8 years to realize it. Even then it took me several years to understand the implications.
25岁前的人生已显现明显模式:又一次准备进入 prestigious 学府学习 prestigious 学科,又一次即将失望。绘画系的师生都非常友善,但他们早已达成默契:学生不要求老师教学,老师也不要求学生学习,同时所有人表面遵守19世纪画室的传统。我们真有那种烧柴的小火炉(就像19世纪画室油画里的),裸体模特尽可能靠近它取暖——但除了我几乎没人画她。其他学生大多在聊天或偶尔模仿美国艺术杂志上的作品。
我的模特就住同条街上,靠做模特和为古董商造假维生。她会照着书临摹冷门古画,商人再对复制品做旧处理。[3]
It meant there would be a whole new generation of _essays_. [11] In the print era, the channel for publishing essays had been vanishingly small. Except for a few officially anointed thinkers who went to the right parties in New York, the only people allowed to publish essays were specialists writing about their specialties. There were so many essays that had never been written, because there had been no way to publish them. Now they could be, and I was going to write them. [12] I've worked on several different things, but to the extent there was a turning point where I figured out what to work on, it was when I started publishing essays online. From then on I knew that whatever else I did, I'd always write essays too. I knew that online essays would be a _marginal_ medium at first. Socially they'd seem more like rants posted by nutjobs on their GeoCities sites than the genteel and beautifully typeset compositions published in _The New Yorker_. But by this point I knew enough to find that encouraging instead of discouraging. One of the most conspicuous patterns I've noticed in my life is how well it has worked, for me at least, to work on things that weren't prestigious. Still life has always been the least prestigious form of painting. Viaweb and Y Combinator both seemed lame when we started them. I still get the glassy eye from strangers when they ask what I'm writing, and I explain that it's an essay I'm going to publish on my web site. Even Lisp, though prestigious intellectually in something like the way Latin is, also seems about as hip. It's not that unprestigious types of work are good per se. But when you find yourself drawn to some kind of work despite its current lack of prestige, it's a sign both that there's something real to be discovered there, and that you have the right kind of motives. Impure motives are a big danger for the ambitious.
在美院期间,我开始晚上在卧室画静物。画幅很小(房间本就狭小,而且我用得起的是边角料画布)。画静物与画人物不同——顾名思义,静物不会动。人物最多坐15分钟,还不停晃动,所以传统人物画法先掌握通用技法,再调整匹配具体对象;而静物可以(如果你愿意)像素级复制眼前所见。当然不能止步于此,否则只是照片级精确——静物的魅力在于经过大脑加工。你需要强化视觉线索(比如某处色彩突变其实是物体边缘),通过微妙强调这些,创作出比照片更真实的作品——不仅是隐喻意义上,严格的信息论意义上也是如此。[4]
If anything is going to lead you astray, it will be the desire to impress people. So while working on things that aren't prestigious doesn't guarantee you're on the right track, it at least guarantees you're not on the most common type of wrong one. Over the next several years I wrote lots of essays about all kinds of different topics. O'Reilly reprinted a collection of them as a book, called _Hackers & Painters_ after one of the essays in it. I also worked on spam filters, and did some more painting. I used to have dinners for a group of friends every thursday night, which taught me how to cook for groups. And I bought another building in Cambridge, a former candy factory (and later, twas said, porn studio), to use as an office. One night in October 2003 there was a big party at my house. It was a clever idea of my friend Maria Daniels, who was one of the thursday diners. Three separate hosts would all invite their friends to one party. So for every guest, two thirds of the other guests would be people they didn't know but would probably like. One of the guests was someone I didn't know but would turn out to like a lot: a woman called Jessica Livingston. A couple days later I asked her out. Jessica was in charge of marketing at a Boston investment bank. This bank thought it understood startups, but over the next year, as she met friends of mine from the startup world, she was surprised how different reality was. And how colorful their stories were. So she decided to compile a book of _interviews_ with startup founders. When the bank had financial problems and she had to fire half her staff, she started looking for a new job. In early 2005 she interviewed for a marketing job at a Boston VC firm. It took them weeks to make up their minds, and during this time I started telling her about all the things that needed to be fixed about venture capital.
我喜欢画静物因为对所见充满好奇。日常生活中,我们意识不到看到的许多细节——大部分视觉处理由底层进程完成,它只告诉大脑"那是水滴"而不说明最亮/最暗点的位置,或"那是灌木"而不描述每片叶子的形状位置。这是大脑特性而非缺陷——日常生活中注意每片叶子会分散注意力。但作画迫使你更仔细观察,从而发现无数细节。就像写文章剖析常见事物会有新发现一样,连续多日画习以为常的物体也会持续发现新细节。
这不是唯一的绘画方式,甚至不确定是否是好方法,但值得尝试。
They should make a larger number of smaller investments instead of a handful of giant ones, they should be funding younger, more technical founders instead of MBAs, they should let the founders remain as CEO, and so on. One of my tricks for writing essays had always been to give talks. The prospect of having to stand up in front of a group of people and tell them something that won't waste their time is a great spur to the imagination. When the Harvard Computer Society, the undergrad computer club, asked me to give a talk, I decided I would tell them how to start a startup. Maybe they'd be able to avoid the worst of the mistakes we'd made. So I gave this talk, in the course of which I told them that the best sources of seed funding were successful startup founders, because then they'd be sources of advice too. Whereupon it seemed they were all looking expectantly at me. Horrified at the prospect of having my inbox flooded by business plans (if I'd only known), I blurted out "But not me!" and went on with the talk. But afterward it occurred to me that I should really stop procrastinating about angel investing. I'd been meaning to since Yahoo bought us, and now it was 7 years later and I still hadn't done one angel investment. Meanwhile I had been scheming with Robert and Trevor about projects we could work on together. I missed working with them, and it seemed like there had to be something we could collaborate on. As Jessica and I were walking home from dinner on March 11, at the corner of Garden and Walker streets, these three threads converged. Screw the VCs who were taking so long to make up their minds. We'd start our own investment firm and actually implement the ideas we'd been talking about. I'd fund it, and Jessica could quit her job and work for it, and we'd get Robert and Trevor as partners too. [13] Once again, ignorance worked in our favor.
老师Ulivi教授很友善,看出我用功,在学生护照似的本子里给我打了高分。但美院只教会我意大利语,加上资金耗尽,第一年结束后我回到美国。
We had no idea how to be angel investors, and in Boston in 2005 there were no Ron Conways to learn from. So we just made what seemed like the obvious choices, and some of the things we did turned out to be novel. There are multiple components to Y Combinator, and we didn't figure them all out at once. The part we got first was to be an angel firm. In those days, those two words didn't go together. There were VC firms, which were organized companies with people whose job it was to make investments, but they only did big, million dollar investments. And there were angels, who did smaller investments, but these were individuals who were usually focused on other things and made investments on the side. And neither of them helped founders enough in the beginning. We knew how helpless founders were in some respects, because we remembered how helpless we'd been. For example, one thing Julian had done for us that seemed to us like magic was to get us set up as a company. We were fine writing fairly difficult software, but actually getting incorporated, with bylaws and stock and all that stuff, how on earth did you do that? Our plan was not only to make seed investments, but to do for startups everything Julian had done for us. YC was not organized as a fund. It was cheap enough to run that we funded it with our own money. That went right by 99% of readers, but professional investors are thinking "Wow, that means they got all the returns." But once again, this was not due to any particular insight on our part. We didn't know how VC firms were organized. It never occurred to us to try to raise a fund, and if it had, we wouldn't have known where to start. [14] The most distinctive thing about YC is the batch model: to fund a bunch of startups all at once, twice a year, and then to spend three months focusing intensively on trying to help them. That part we discovered by accident, not merely implicitly but explicitly due to our ignorance about investing.
我想回RISD,但已破产而RISD学费昂贵,决定工作一年再返校。我在文档软件公司Interleaf找到工作(类似Word?正是)。由此我学到低端软件往往吞噬高端软件,不过Interleaf还有几年寿命。[5]
Interleaf做了件大胆事:受Emacs启发,他们添加了脚本语言——甚至是Lisp方言。现在需要Lisp黑客来开发。这是我最接近正常工作的经历,在此向老板同事道歉——我是个糟糕员工。他们的Lisp像是巨型C蛋糕上的薄糖衣,由于我不懂也不想学C,始终不理解大部分软件。加上我极度不负责任——那时编程工作需要按时坐班,这让我觉得 unnatural(虽然如今世界正转向我的方式),当时造成许多摩擦。那年后期我常偷偷写《On Lisp》(已签出版合同)。
We needed to get experience as investors. What better way, we thought, than to fund a whole bunch of startups at once? We knew undergrads got temporary jobs at tech companies during the summer. Why not organize a summer program where they'd start startups instead? We wouldn't feel guilty for being in a sense fake investors, because they would in a similar sense be fake founders. So while we probably wouldn't make much money out of it, we'd at least get to practice being investors on them, and they for their part would probably have a more interesting summer than they would working at Microsoft. We'd use the building I owned in Cambridge as our headquarters. We'd all have dinner there once a week � on tuesdays, since I was already cooking for the thursday diners on thursdays � and after dinner we'd bring in experts on startups to give talks. We knew undergrads were deciding then about summer jobs, so in a matter of days we cooked up something we called the Summer Founders Program, and I posted an _announcement_ on my site, inviting undergrads to apply. I had never imagined that writing essays would be a way to get "deal flow," as investors call it, but it turned out to be the perfect source. [15] We got 225 applications for the Summer Founders Program, and we were surprised to find that a lot of them were from people who'd already graduated, or were about to that spring. Already this SFP thing was starting to feel more serious than we'd intended. We invited about 20 of the 225 groups to interview in person, and from those we picked 8 to fund. They were an impressive group. That first batch included reddit, Justin Kan and Emmett Shear, who went on to found Twitch, Aaron Swartz, who had already helped write the RSS spec and would a few years later become a martyr for open access, and Sam Altman, who would later become the second president of YC. I don't think it was entirely luck that the first batch was so good.
好处是报酬丰厚(以艺术生标准)。在佛罗伦萨时,扣除房租后我每日预算仅7美元;现在时薪超过四倍(开会坐着也有钱)。节俭生活不仅攒够返校费用,还还清了大学贷款。
You had to be pretty bold to sign up for a weird thing like the Summer Founders Program instead of a summer job at a legit place like Microsoft or Goldman Sachs. The deal for startups was based on a combination of the deal we did with Julian ($10k for 10%) and what Robert said MIT grad students got for the summer ($6k). We invested $6k per founder, which in the typical two-founder case was $12k, in return for 6%. That had to be fair, because it was twice as good as the deal we ourselves had taken. Plus that first summer, which was really hot, Jessica brought the founders free air conditioners. [16] Fairly quickly I realized that we had stumbled upon the way to scale startup funding. Funding startups in batches was more convenient for us, because it meant we could do things for a lot of startups at once, but being part of a batch was better for the startups too. It solved one of the biggest problems faced by founders: the isolation. Now you not only had colleagues, but colleagues who understood the problems you were facing and could tell you how they were solving them. As YC grew, we started to notice other advantages of scale. The alumni became a tight community, dedicated to helping one another, and especially the current batch, whose shoes they remembered being in. We also noticed that the startups were becoming one another's customers. We used to refer jokingly to the "YC GDP," but as YC grows this becomes less and less of a joke. Now lots of startups get their initial set of customers almost entirely from among their batchmates. I had not originally intended YC to be a full-time job. I was going to do three things: hack, write essays, and work on YC. As YC grew, and I grew more excited about it, it started to take up a lot more than a third of my attention. But for the first few years I was still able to work on other things. In the summer of 2006, Robert and I started working on a new version of Arc.
在Interleaf学到些有用经验(更多是反面教材):科技公司该由产品人而非销售人主导(虽然销售是 real skill);多人修改代码易产生bug;压抑的廉价办公室得不偿失;走廊谈话比正式会议高效;大官僚客户是危险收入来源;常规办公时间/地点与最佳编程时间/地点重合度很低。
最重要经验(后来用于Viaweb和YC)是"低端吞噬高端":成为"入门级"选项很有价值(即使不够 prestigious),否则别人会成为这个选项并将你挤压到天花板——这意味着 prestigious 反而是危险信号。
This one was reasonably fast, because it was compiled into Scheme. To test this new Arc, I wrote Hacker News in it. It was originally meant to be a news aggregator for startup founders and was called Startup News, but after a few months I got tired of reading about nothing but startups. Plus it wasn't startup founders we wanted to reach. It was future startup founders. So I changed the name to Hacker News and the topic to whatever engaged one's intellectual curiosity. HN was no doubt good for YC, but it was also by far the biggest source of stress for me. If all I'd had to do was select and help founders, life would have been so easy. And that implies that HN was a mistake. Surely the biggest source of stress in one's work should at least be something close to the core of the work. Whereas I was like someone who was in pain while running a marathon not from the exertion of running, but because I had a blister from an ill-fitting shoe. When I was dealing with some urgent problem during YC, there was about a 60% chance it had to do with HN, and a 40% chance it had do with everything else combined. [17] As well as HN, I wrote all of YC's internal software in Arc. But while I continued to work a good deal _in_ Arc, I gradually stopped working _on_ Arc, partly because I didn't have time to, and partly because it was a lot less attractive to mess around with the language now that we had all this infrastructure depending on it. So now my three projects were reduced to two: writing essays and working on YC. YC was different from other kinds of work I've done. Instead of deciding for myself what to work on, the problems came to me. Every 6 months there was a new batch of startups, and their problems, whatever they were, became our problems. It was very engaging work, because their problems were quite varied, and the good founders were very effective.
次年秋季回RISD前,我安排了为客服项目组做自由职业,这支撑了随后几年生活。后来有次回去做项目时,有人提到叫HTML的新事物(他描述为SGML的衍生品)。作为Interleaf员工,标记语言爱好者是职业危害,我没在意——但这个HTML后来成为我人生重要部分。
If you were trying to learn the most you could about startups in the shortest possible time, you couldn't have picked a better way to do it. There were parts of the job I didn't like. Disputes between cofounders, figuring out when people were lying to us, fighting with people who maltreated the startups, and so on. But I worked hard even at the parts I didn't like. I was haunted by something Kevin Hale once said about companies: "No one works harder than the boss." He meant it both descriptively and prescriptively, and it was the second part that scared me. I wanted YC to be good, so if how hard I worked set the upper bound on how hard everyone else worked, I'd better work very hard. One day in 2010, when he was visiting California for interviews, Robert Morris did something astonishing: he offered me unsolicited advice. I can only remember him doing that once before. One day at Viaweb, when I was bent over double from a kidney stone, he suggested that it would be a good idea for him to take me to the hospital. That was what it took for Rtm to offer unsolicited advice. So I remember his exact words very clearly. "You know," he said, "you should make sure Y Combinator isn't the last cool thing you do." At the time I didn't understand what he meant, but gradually it dawned on me that he was saying I should quit. This seemed strange advice, because YC was doing great. But if there was one thing rarer than Rtm offering advice, it was Rtm being wrong. So this set me thinking. It was true that on my current trajectory, YC would be the last thing I did, because it was only taking up more of my attention. It had already eaten Arc, and was in the process of eating essays too. Either YC was my life's work or I'd have to leave eventually. And it wasn't, so I would. In the summer of 2012 my mother had a stroke, and the cause turned out to be a blood clot caused by colon cancer.
1992年秋重返普罗维登斯继续RISD学业。基础课只是入门,佛罗伦萨美院是(非常文明的)笑话。现在要见识真正的艺术学院——可惜更像美院而非理想状态。当然更 organized 也更昂贵,但越来越清楚艺术学院与艺术的关系,不同于医学院与医学的关系(至少绘画系如此)。隔壁纺织系似乎很 rigorous,插画和建筑系可能也是,但绘画已是"后 rigorous"阶段——学生应该"表达自我",对世故者而言就是炮制某种独特风格。
The stroke destroyed her balance, and she was put in a nursing home, but she really wanted to get out of it and back to her house, and my sister and I were determined to help her do it. I used to fly up to Oregon to visit her regularly, and I had a lot of time to think on those flights. On one of them I realized I was ready to hand YC over to someone else. I asked Jessica if she wanted to be president, but she didn't, so we decided we'd try to recruit Sam Altman. We talked to Robert and Trevor and we agreed to make it a complete changing of the guard. Up till that point YC had been controlled by the original LLC we four had started. But we wanted YC to last for a long time, and to do that it couldn't be controlled by the founders. So if Sam said yes, we'd let him reorganize YC. Robert and I would retire, and Jessica and Trevor would become ordinary partners. When we asked Sam if he wanted to be president of YC, initially he said no. He wanted to start a startup to make nuclear reactors. But I kept at it, and in October 2013 he finally agreed. We decided he'd take over starting with the winter 2014 batch. For the rest of 2013 I left running YC more and more to Sam, partly so he could learn the job, and partly because I was focused on my mother, whose cancer had returned. She died on January 15, 2014. We knew this was coming, but it was still hard when it did. I kept working on YC till March, to help get that batch of startups through Demo Day, then I checked out pretty completely. (I still talk to alumni and to new startups working on things I'm interested in, but that only takes a few hours a week.) What should I do next? Rtm's advice hadn't included anything about that. I wanted to do something completely different, so I decided I'd paint. I wanted to see how good I could get if I really focused on it. So the day after I stopped working on YC, I started painting.
"独特风格"相当于演艺圈的"招牌动作"——立即标识作品归属。比如看到某种漫画风格的画,就知道是Roy Lichtenstein的。所以当对冲基金经理公寓挂着大幅这类作品,就知道他花了数百万美元。艺术家有 signature style 不总是为此,但买家重金购买通常正因如此。[6]
也有许多 earnest 的学生——高中时"会画画"的孩子,来到这所号称全美最好的艺术学院想画得更好。RISD现状让他们困惑沮丧,但坚持着,因为绘画是他们 identity 的一部分。我高中时不属于"会画画"的孩子,但在RISD绝对更接近他们而非 signature style 追求者群体。
I was rusty and it took a while to get back into shape, but it was at least completely engaging. [18] I spent most of the rest of 2014 painting. I'd never been able to work so uninterruptedly before, and I got to be better than I had been. Not good enough, but better. Then in November, right in the middle of a painting, I ran out of steam. Up till that point I'd always been curious to see how the painting I was working on would turn out, but suddenly finishing this one seemed like a chore. So I stopped working on it and cleaned my brushes and haven't painted since. So far anyway. I realize that sounds rather wimpy. But attention is a zero sum game. If you can choose what to work on, and you choose a project that's not the best one (or at least a good one) for you, then it's getting in the way of another project that is. And at 50 there was some opportunity cost to screwing around. I started writing essays again, and wrote a bunch of new ones over the next few months. I even wrote a couple that _weren't_ about startups. Then in March 2015 I started working on Lisp again. The distinctive thing about Lisp is that its core is a language defined by writing an interpreter in itself. It wasn't originally intended as a programming language in the ordinary sense. It was meant to be a formal model of computation, an alternative to the Turing machine. If you want to write an interpreter for a language in itself, what's the minimum set of predefined operators you need? The Lisp that John McCarthy invented, or more accurately discovered, is an answer to that question. [19] McCarthy didn't realize this Lisp could even be used to program computers till his grad student Steve Russell suggested it. Russell translated McCarthy's interpreter into IBM 704 machine language, and from that point Lisp started also to be a programming language in the ordinary sense.
在RISD的色彩课学到很多,但基本上我在自学绘画——这完全可以免费进行。于是1993年我退学了。在普罗维登斯逗留期间,大学好友Nancy Parmet帮了大忙:她母亲在纽约有栋 rent-controlled 公寓楼,其中一套将空出。我要吗?价格比当时住处略高,而纽约应该是艺术家的归宿。当然要![7]
But its origins as a model of computation gave it a power and elegance that other languages couldn't match. It was this that attracted me in college, though I didn't understand why at the time. McCarthy's 1960 Lisp did nothing more than interpret Lisp expressions. It was missing a lot of things you'd want in a programming language. So these had to be added, and when they were, they weren't defined using McCarthy's original axiomatic approach. That wouldn't have been feasible at the time. McCarthy tested his interpreter by hand-simulating the execution of programs. But it was already getting close to the limit of interpreters you could test that way � indeed, there was a bug in it that McCarthy had overlooked. To test a more complicated interpreter, you'd have had to run it, and computers then weren't powerful enough. Now they are, though. Now you could continue using McCarthy's axiomatic approach till you'd defined a complete programming language. And as long as every change you made to McCarthy's Lisp was a discoveredness-preserving transformation, you could, in principle, end up with a complete language that had this quality. Harder to do than to talk about, of course, but if it was possible in principle, why not try? So I decided to take a shot at it. It took 4 years, from March 26, 2015 to October 12, 2019. It was fortunate that I had a precisely defined goal, or it would have been hard to keep at it for so long. I wrote this new Lisp, called _Bel_, in itself in Arc. That may sound like a contradiction, but it's an indication of the sort of trickery I had to engage in to make this work. By means of an egregious collection of hacks I managed to make something close enough to an interpreter written in itself that could actually run. Not fast, but fast enough to test. I had to ban myself from writing essays during most of this time, or I'd never have finished.
就像《高卢英雄传》开场展现罗马高卢中一小块未被征服的角落,纽约地图也有类似区域:上东区有个叫约克维尔的小角落1993年还不算富裕。这里成了我的新家。现在我是"纽约艺术家"——严格技术意义上(在纽约生活并作画)。
我对资金感到 nervous,因为察觉到Interleaf在衰落。自由Lisp编程工作非常 rare,而我不想用其他语言编程(当时幸运的话是C++)。于是凭着对 financial opportunity 异常敏锐的嗅觉,我决定再写本Lisp书——面向大众的教科书。幻想靠版税节俭生活,全心投入绘画(《ANSI Common Lisp》封面画就是那时作品)。
In late 2015 I spent 3 months writing essays, and when I went back to working on Bel I could barely understand the code. Not so much because it was badly written as because the problem is so convoluted. When you're working on an interpreter written in itself, it's hard to keep track of what's happening at what level, and errors can be practically encrypted by the time you get them. So I said no more essays till Bel was done. But I told few people about Bel while I was working on it. So for years it must have seemed that I was doing nothing, when in fact I was working harder than I'd ever worked on anything. Occasionally after wrestling for hours with some gruesome bug I'd check Twitter or HN and see someone asking "Does Paul Graham still code?" Working on Bel was hard but satisfying. I worked on it so intensively that at any given time I had a decent chunk of the code in my head and could write more there. I remember taking the boys to the coast on a sunny day in 2015 and figuring out how to deal with some problem involving continuations while I watched them play in the tide pools. It felt like I was doing life right. I remember that because I was slightly dismayed at how novel it felt. The good news is that I had more moments like this over the next few years. In the summer of 2016 we moved to England. We wanted our kids to see what it was like living in another country, and since I was a British citizen by birth, that seemed the obvious choice. We only meant to stay for a year, but we liked it so much that we still live there. So most of Bel was written in England. In the fall of 2019, Bel was finally finished. Like McCarthy's original Lisp, it's a spec rather than an implementation, although like McCarthy's Lisp it's a spec expressed as code. Now that I could write essays again, I wrote a bunch about topics I'd had stacked up. I kept writing essays through 2020, but I also started to think about other things I could work on.
纽约对我最好的事是结识Idelle和Julian Weber。Idelle是早期照相写实主义画家,我在哈佛上过她的课——从没见过比她更受学生爱戴的老师。大量往届学生(包括我)与她保持联系。搬到纽约后,我成了她事实上的工作室助理。
How should I choose what to do? Well, how had I chosen what to work on in the past? I wrote an essay for myself to answer that question, and I was surprised how long and messy the answer turned out to be. If this surprised me, who'd lived it, then I thought perhaps it would be interesting to other people, and encouraging to those with similarly messy lives. So I wrote a more detailed version for others to read, and this is the last sentence of it. Notes [1] My experience skipped a step in the evolution of computers: time-sharing machines with interactive OSes. I went straight from batch processing to microcomputers, which made microcomputers seem all the more exciting. [2] Italian words for abstract concepts can nearly always be predicted from their English cognates (except for occasional traps like _polluzione_ ). It's the everyday words that differ. So if you string together a lot of abstract concepts with a few simple verbs, you can make a little Italian go a long way. [3] I lived at Piazza San Felice 4, so my walk to the Accademia went straight down the spine of old Florence: past the Pitti, across the bridge, past Orsanmichele, between the Duomo and the Baptistery, and then up Via Ricasoli to Piazza San Marco. I saw Florence at street level in every possible condition, from empty dark winter evenings to sweltering summer days when the streets were packed with tourists. [4] You can of course paint people like still lives if you want to, and they're willing. That sort of portrait is arguably the apex of still life painting, though the long sitting does tend to produce pained expressions in the sitters. [5] Interleaf was one of many companies that had smart people and built impressive technology, and yet got crushed by Moore's Law. In the 1990s the exponential growth in the power of commodity (i.e.
她喜欢在大幅方形画布(边长4-5英尺)上创作。1994年末某天,当我绷这种巨型画布时,收音机提到某著名基金经理——他只比我稍大却超级富有。突然灵光乍现:我为什么不致富?然后就能随心所欲地工作。
同时我越来越多地听说叫"万维网"的新事物。Robert Morris(当时在哈佛读研)在剑桥向我展示时,我就预感它会很重要——就像图形界面推动微电脑普及那样,网络将对互联网产生相同效应。
Intel) processors rolled up high-end, special-purpose hardware and software companies like a bulldozer. [6] The signature style seekers at RISD weren't specifically mercenary. In the art world, money and coolness are tightly coupled. Anything expensive comes to be seen as cool, and anything seen as cool will soon become equally expensive. [7] Technically the apartment wasn't rent-controlled but rent-stabilized, but this is a refinement only New Yorkers would know or care about. The point is that it was really cheap, less than half market price. [8] Most software you can launch as soon as it's done. But when the software is an online store builder and you're hosting the stores, if you don't have any users yet, that fact will be painfully obvious. So before we could launch publicly we had to launch privately, in the sense of recruiting an initial set of users and making sure they had decent-looking stores. [9] We'd had a code editor in Viaweb for users to define their own page styles. They didn't know it, but they were editing Lisp expressions underneath. But this wasn't an app editor, because the code ran when the merchants' sites were generated, not when shoppers visited them. [10] This was the first instance of what is now a familiar experience, and so was what happened next, when I read the comments and found they were full of angry people. How could I claim that Lisp was better than other languages? Weren't they all Turing complete? People who see the responses to essays I write sometimes tell me how sorry they feel for me, but I'm not exaggerating when I reply that it has always been like this, since the very beginning. It comes with the territory. An essay must tell readers things they _don't already know_, and some people dislike being told such things. [11] People put plenty of stuff on the internet in the 90s of course, but putting something online is not the same as publishing it online.
要致富就得赶上这班离站的列车。这部分判断正确,但想法错了:我们决定创立让画廊上网的公司。老实说(看过无数YC申请后),这虽非史上最糟创业点子,也名列前茅——高端画廊不想(至今仍不想)上网,这不是他们的销售方式。我写了生成画廊网站的软件,Robert写了调整图片大小的工具并搭建http服务器。我们试图签约画廊,用"艰难"形容都算轻描淡写——简直是白送都难。少数画廊让我们免费建站,但没人付费。
Publishing online means you treat the online version as the (or at least a) primary version. [12] There is a general lesson here that our experience with Y Combinator also teaches: Customs continue to constrain you long after the restrictions that caused them have disappeared. Customary VC practice had once, like the customs about publishing essays, been based on real constraints. Startups had once been much more expensive to start, and proportionally rare. Now they could be cheap and common, but the VCs' customs still reflected the old world, just as customs about writing essays still reflected the constraints of the print era. Which in turn implies that people who are independent-minded (i.e. less influenced by custom) will have an advantage in fields affected by rapid change (where customs are more likely to be obsolete). Here's an interesting point, though: you can't always predict which fields will be affected by rapid change. Obviously software and venture capital will be, but who would have predicted that essay writing would be? [13] Y Combinator was not the original name. At first we were called Cambridge Seed. But we didn't want a regional name, in case someone copied us in Silicon Valley, so we renamed ourselves after one of the coolest tricks in the lambda calculus, the Y combinator. I picked orange as our color partly because it's the warmest, and partly because no VC used it. In 2005 all the VCs used staid colors like maroon, navy blue, and forest green, because they were trying to appeal to LPs, not founders. The YC logo itself is an inside joke: the Viaweb logo had been a white V on a red circle, so I made the YC logo a white Y on an orange square. [14] YC did become a fund for a couple years starting in 2009, because it was getting so big I could no longer afford to fund it personally.
后来出现一些网店,我意识到除了下单按钮,它们与我们为画廊做的网站完全相同。这个听来 impressive 的"互联网店面"正是我们已掌握的技术。
于是1995年夏,向出版社提交《ANSI Common Lisp》终稿后,我们开始编写网店软件。最初计划是常规桌面软件(当时指Windows软件),这令人 alarm——我们都不懂也不想学Windows编程(活在Unix世界)。但决定至少尝试在Unix上写原型:Robert写购物车,我用Lisp写新的商店网站生成器。
But after Heroku got bought we had enough money to go back to being self-funded. [15] I've never liked the term "deal flow," because it implies that the number of new startups at any given time is fixed. This is not only false, but it's the purpose of YC to falsify it, by causing startups to be founded that would not otherwise have existed. [16] She reports that they were all different shapes and sizes, because there was a run on air conditioners and she had to get whatever she could, but that they were all heavier than she could carry now. [17] Another problem with HN was a bizarre edge case that occurs when you both write essays and run a forum. When you run a forum, you're assumed to see if not every conversation, at least every conversation involving you. And when you write essays, people post highly imaginative misinterpretations of them on forums. Individually these two phenomena are tedious but bearable, but the combination is disastrous. You actually have to respond to the misinterpretations, because the assumption that you're present in the conversation means that not responding to any sufficiently upvoted misinterpretation reads as a tacit admission that it's correct. But that in turn encourages more; anyone who wants to pick a fight with you senses that now is their chance. [18] The worst thing about leaving YC was not working with Jessica anymore. We'd been working on YC almost the whole time we'd known each other, and we'd neither tried nor wanted to separate it from our personal lives, so leaving was like pulling up a deeply rooted tree. [19] One way to get more precise about the concept of invented vs discovered is to talk about space aliens. Any sufficiently advanced alien civilization would certainly know about the Pythagorean theorem, for example. I believe, though with less certainty, that they would also know about the Lisp in McCarthy's 1960 paper.
我们在Robert剑桥公寓工作。他室友长期不在时,我就睡在那间房(莫名其妙只有床垫没床架)。某天早晨躺在这床垫上,一个想法让我像字母L般猛然坐起:何不让软件运行在服务器上,用户通过点击链接控制?这样无需在用户电脑装任何东西,直接在服务器生成并托管网站,用户只需浏览器。
But if so there's no reason to suppose that this is the limit of the language that might be known to them. Presumably aliens need numbers and errors and I/O too. So it seems likely there exists at least one path out of McCarthy's Lisp along which discoveredness is preserved. Thanks to Trevor Blackwell, John Collison, Patrick Collison, Daniel Gackle, Ralph Hazell, Jessica Livingston, Robert Morris, and Harj Taggar for reading drafts of this..
这种"网络应用"如今司空见惯,但当时连可行性都不明确。为验证,我们尝试制作可通过浏览器控制的商店构建器。8月12日,虽然界面丑陋,但证明了完全通过浏览器(无需客户端软件或服务器命令行)构建商店的可能性。
现在我们感到真正抓住了什么。仿佛看到新一代软件将如此运作:无需版本、端口等糟心事。在Interleaf,负责发布的"Release Engineering"
December 2020 As I was deciding what to write about next, I was surprised to find that two separate essays I'd been planning to write were actually the same. The first is about how to ace your Y Combinator interview. There has been so much nonsense written about this topic that I've been meaning for years to write something telling founders the truth. The second is about something politicians sometimes say � that the only way to become a billionaire is by exploiting people � and why this is mistaken. Keep reading, and you'll learn both simultaneously. I know the politicians are mistaken because it was my job to predict which people will become billionaires. I think I can truthfully say that I know as much about how to do this as anyone. If the key to becoming a billionaire � the defining feature of billionaires � was to exploit people, then I, as a professional billionaire scout, would surely realize this and look for people who would be good at it, just as an NFL scout looks for speed in wide receivers. But aptitude for exploiting people is not what Y Combinator looks for at all. In fact, it's the opposite of what they look for. I'll tell you what they do look for, by explaining how to convince Y Combinator to fund you, and you can see for yourself. What YC looks for, above all, is founders who understand some group of users and can make what they want. This is so important that it's YC's motto: "Make something people want." A big company can to some extent force unsuitable products on unwilling customers, but a startup doesn't have the power to do that. A startup must sing for its supper, by making things that genuinely delight its customers. Otherwise it will never get off the ground. Here's where things get difficult, both for you as a founder and for the YC partners trying to decide whether to fund you. In a market economy, it's hard to make something people want that they don't already have.
That's the great thing about market economies. If other people both knew about this need and were able to satisfy it, they already would be, and there would be no room for your startup. Which means the conversation during your YC interview will have to be about something new: either a new need, or a new way to satisfy one. And not just new, but uncertain. If it were certain that the need existed and that you could satisfy it, that certainty would be reflected in large and rapidly growing revenues, and you wouldn't be seeking seed funding. So the YC partners have to guess both whether you've discovered a real need, and whether you'll be able to satisfy it. That's what they are, at least in this part of their job: professional guessers. They have 1001 heuristics for doing this, and I'm not going to tell you all of them, but I'm happy to tell you the most important ones, because these can't be faked; the only way to "hack" them would be to do what you should be doing anyway as a founder. The first thing the partners will try to figure out, usually, is whether what you're making will ever be something a lot of people want. It doesn't have to be something a lot of people want now. The product and the market will both evolve, and will influence each other's evolution. But in the end there has to be something with a huge market. That's what the partners will be trying to figure out: is there a path to a huge market? [1] Sometimes it's obvious there will be a huge market. If _Boom_ manages to ship an airliner at all, international airlines will have to buy it. But usually it's not obvious. Usually the path to a huge market is by growing a small market. This idea is important enough that it's worth coining a phrase for, so let's call one of these small but growable markets a "larval market." The perfect example of a larval market might be Apple's market when they were founded in 1976.
In 1976, not many people wanted their own computer. But more and more started to want one, till now every 10 year old on the planet wants a computer (but calls it a "phone"). The ideal combination is the group of founders who are _"living in the future"_ in the sense of being at the leading edge of some kind of change, and who are building something they themselves want. Most super-successful startups are of this type. Steve Wozniak wanted a computer. Mark Zuckerberg wanted to engage online with his college friends. Larry and Sergey wanted to find things on the web. All these founders were building things they and their peers wanted, and the fact that they were at the leading edge of change meant that more people would want these things in the future. But although the ideal larval market is oneself and one's peers, that's not the only kind. A larval market might also be regional, for example. You build something to serve one location, and then expand to others. The crucial feature of the initial market is that it exist. That may seem like an obvious point, but the lack of it is the biggest flaw in most startup ideas. There have to be some people who want what you're building right now, and want it so urgently that they're willing to use it, bugs and all, even though you're a small company they've never heard of. There don't have to be many, but there have to be some. As long as you have some users, there are straightforward ways to get more: build new features they want, seek out more people like them, get them to refer you to their friends, and so on. But these techniques all require some initial seed group of users. So this is one thing the YC partners will almost certainly dig into during your interview.
Who are your first users going to be, and how do you know they want this? If I had to decide whether to fund startups based on a single question, it would be "How do you know people want this?" The most convincing answer is "Because we and our friends want it." It's even better when this is followed by the news that you've already built a prototype, and even though it's very crude, your friends are using it, and it's spreading by word of mouth. If you can say that and you're not lying, the partners will switch from default no to default yes. Meaning you're in unless there's some other disqualifying flaw. That is a hard standard to meet, though. Airbnb didn't meet it. They had the first part. They had made something they themselves wanted. But it wasn't spreading. So don't feel bad if you don't hit this gold standard of convincingness. If Airbnb didn't hit it, it must be too high. In practice, the YC partners will be satisfied if they feel that you have a deep understanding of your users' needs. And the Airbnbs did have that. They were able to tell us all about what motivated hosts and guests. They knew from first-hand experience, because they'd been the first hosts. We couldn't ask them a question they didn't know the answer to. We ourselves were not very excited about the idea as users, but we knew this didn't prove anything, because there were lots of successful startups we hadn't been excited about as users. We were able to say to ourselves "They seem to know what they're talking about. Maybe they're onto something. It's not growing yet, but maybe they can figure out how to make it grow during YC." Which they did, about three weeks into the batch. The best thing you can do in a YC interview is to teach the partners about your users. So if you want to prepare for your interview, one of the best ways to do it is to go talk to your users and find out exactly what they're thinking. Which is what you should be doing anyway.
This may sound strangely credulous, but the YC partners want to rely on the founders to tell them about the market. Think about how VCs typically judge the potential market for an idea. They're not ordinarily domain experts themselves, so they forward the idea to someone who is, and ask for their opinion. YC doesn't have time to do this, but if the YC partners can convince themselves that the founders both (a) know what they're talking about and (b) aren't lying, they don't need outside domain experts. They can use the founders themselves as domain experts when evaluating their own idea. This is why YC interviews aren't pitches. To give as many founders as possible a chance to get funded, we made interviews as short as we could: 10 minutes. That is not enough time for the partners to figure out, through the indirect evidence in a pitch, whether you know what you're talking about and aren't lying. They need to dig in and ask you questions. There's not enough time for sequential access. They need random access. [2] The worst advice I ever heard about how to succeed in a YC interview is that you should take control of the interview and make sure to deliver the message you want to. In other words, turn the interview into a pitch. ⟨elaborate expletive⟩. It is so annoying when people try to do that. You ask them a question, and instead of answering it, they deliver some obviously prefabricated blob of pitch. It eats up 10 minutes really fast. There is no one who can give you accurate advice about what to do in a YC interview except a current or former YC partner. People who've merely been interviewed, even successfully, have no idea of this, but interviews take all sorts of different forms depending on what the partners want to know about most. Sometimes they're all about the founders, other times they're all about the idea. Sometimes some very narrow aspect of the idea.
Founders sometimes walk away from interviews complaining that they didn't get to explain their idea completely. True, but they explained enough. Since a YC interview consists of questions, the way to do it well is to answer them well. Part of that is answering them candidly. The partners don't expect you to know everything. But if you don't know the answer to a question, don't try to bullshit your way out of it. The partners, like most experienced investors, are professional bullshit detectors, and you are (hopefully) an amateur bullshitter. And if you try to bullshit them and fail, they may not even tell you that you failed. So it's better to be honest than to try to sell them. If you don't know the answer to a question, say you don't, and tell them how you'd go about finding it, or tell them the answer to some related question. If you're asked, for example, what could go wrong, the worst possible answer is "nothing." Instead of convincing them that your idea is bullet-proof, this will convince them that you're a fool or a liar. Far better to go into gruesome detail. That's what experts do when you ask what could go wrong. The partners know that your idea is risky. That's what a good bet looks like at this stage: a tiny probability of a huge outcome. Ditto if they ask about competitors. Competitors are rarely what kills startups. Poor execution does. But you should know who your competitors are, and tell the YC partners candidly what your relative strengths and weaknesses are. Because the YC partners know that competitors don't kill startups, they won't hold competitors against you too much. They will, however, hold it against you if you seem either to be unaware of competitors, or to be minimizing the threat they pose. They may not be sure whether you're clueless or lying, but they don't need to be. The partners don't expect your idea to be perfect. This is seed investing. At this stage, all they can expect are promising hypotheses.
But they do expect you to be thoughtful and honest. So if trying to make your idea seem perfect causes you to come off as glib or clueless, you've sacrificed something you needed for something you didn't. If the partners are sufficiently convinced that there's a path to a big market, the next question is whether you'll be able to find it. That in turn depends on three things: the general qualities of the founders, their specific expertise in this domain, and the relationship between them. How determined are the founders? Are they good at building things? Are they resilient enough to keep going when things go wrong? How strong is their friendship? Though the Airbnbs only did ok in the idea department, they did spectacularly well in this department. The story of how they'd funded themselves by making Obama- and McCain-themed breakfast cereal was the single most important factor in our decision to fund them. They didn't realize it at the time, but what seemed to them an irrelevant story was in fact fabulously good evidence of their qualities as founders. It showed they were resourceful and determined, and could work together. It wasn't just the cereal story that showed that, though. The whole interview showed that they cared. They weren't doing this just for the money, or because startups were cool. The reason they were working so hard on this company was because it was their project. They had discovered an interesting new idea, and they just couldn't let it go. Mundane as it sounds, that's the most powerful motivator of all, not just in startups, but in most ambitious undertakings: to be _genuinely interested_ in what you're building. This is what really drives billionaires, or at least the ones who become billionaires from starting companies. The company is their project. One thing few people realize about billionaires is that all of them could have stopped sooner.
They could have gotten acquired, or found someone else to run the company. Many founders do. The ones who become really rich are the ones who keep working. And what makes them keep working is not just money. What keeps them working is the same thing that keeps anyone else working when they could stop if they wanted to: that there's nothing else they'd rather do. That, not exploiting people, is the defining quality of people who become billionaires from starting companies. So that's what YC looks for in founders: authenticity. People's motives for starting startups are usually mixed. They're usually doing it from some combination of the desire to make money, the desire to seem cool, genuine interest in the problem, and unwillingness to work for someone else. The last two are more powerful motivators than the first two. It's ok for founders to want to make money or to seem cool. Most do. But if the founders seem like they're doing it _just_ to make money or _just_ to seem cool, they're not likely to succeed on a big scale. The founders who are doing it for the money will take the first sufficiently large acquisition offer, and the ones who are doing it to seem cool will rapidly discover that there are much less painful ways of seeming cool. [3] Y Combinator certainly sees founders whose m.o. is to exploit people. YC is a magnet for them, because they want the YC brand. But when the YC partners detect someone like that, they reject them. If bad people made good founders, the YC partners would face a moral dilemma. Fortunately they don't, because bad people make bad founders. This exploitative type of founder is not going to succeed on a large scale, and in fact probably won't even succeed on a small one, because they're always going to be taking shortcuts. They see YC itself as a shortcut. Their exploitation usually begins with their own cofounders, which is disastrous, since the cofounders' relationship is the foundation of the company.
Then it moves on to the users, which is also disastrous, because the sort of early adopters a successful startup wants as its initial users are the hardest to fool. The best this kind of founder can hope for is to keep the edifice of deception tottering along until some acquirer can be tricked into buying it. But that kind of acquisition is never very big. [4] If professional billionaire scouts know that exploiting people is not the skill to look for, why do some politicians think this is the defining quality of billionaires? I think they start from the feeling that it's wrong that one person could have so much more money than another. It's understandable where that feeling comes from. It's in our DNA, and even in the DNA of other species. If they limited themselves to saying that it made them feel bad when one person had so much more money than other people, who would disagree? It makes me feel bad too, and I think people who make a lot of money have a moral obligation to use it for the common good. The mistake they make is to jump from feeling bad that some people are much richer than others to the conclusion that there's no legitimate way to make a very large amount of money. Now we're getting into statements that are not only falsifiable, but false. There are certainly some people who become rich by doing bad things. But there are also plenty of people who behave badly and don't make that much from it. There is no correlation � in fact, probably an inverse correlation � between how badly you behave and how much money you make. The greatest danger of this nonsense may not even be that it sends policy astray, but that it misleads ambitious people.
Can you imagine a better way to destroy social mobility than by telling poor kids that the way to get rich is by exploiting people, while the rich kids know, from having watched the preceding generation do it, how it's really done? I'll tell you how it's really done, so you can at least tell your own kids the truth. It's all about users. The most reliable way to become a billionaire is to start a company that _grows fast_, and the way to grow fast is to make what users want. Newly started startups have no choice but to delight users, or they'll never even get rolling. But this never stops being the lodestar, and bigger companies take their eye off it at their peril. Stop delighting users, and eventually someone else will. Users are what the partners want to know about in YC interviews, and what I want to know about when I talk to founders that we funded ten years ago and who are billionaires now. What do users want? What new things could you build for them? Founders who've become billionaires are always eager to talk about that topic. That's how they became billionaires. Notes [1] The YC partners have so much practice doing this that they sometimes see paths that the founders themselves haven't seen yet. The partners don't try to seem skeptical, as buyers in transactions often do to increase their leverage. Although the founders feel their job is to convince the partners of the potential of their idea, these roles are not infrequently reversed, and the founders leave the interview feeling their idea has more potential than they realized. [2] In practice, 7 minutes would be enough. You rarely change your mind at minute 8. But 10 minutes is socially convenient. [3] I myself took the first sufficiently large acquisition offer in my first startup, so I don't blame founders for doing this. There's nothing wrong with starting a startup to make money.
You need to make money somehow, and for some people startups are the most efficient way to do it. I'm just saying that these are not the startups that get really big. [4] Not these days, anyway. There were some big ones during the Internet Bubble, and indeed some big IPOs. Thanks to Trevor Blackwell, Jessica Livingston, Robert Morris, Geoff Ralston, and Harj Taggar for reading drafts of this..
2020年12月 当我正在思考下一篇写作主题时,意外发现原本计划撰写的两篇独立文章其实是同一主题。 第一篇是关于如何通过Y Combinator面试。这个话题充斥着太多荒谬言论,多年来我一直想向创业者揭示真相。 第二篇则针对政客们常说的"成为亿万富翁的唯一途径就是剥削他人"论调,解析其谬误所在。 继续阅读,你将同时理解这两点。 我确信政客们的观点是错误的,因为我的工作就是预测哪些人会成为亿万富翁。可以说,在这个领域我的认知深度不亚于任何人。如果成为亿万富翁的关键在于剥削他人,那么作为职业化的亿万富翁发掘者,我必然会寻找擅长此道之人,就像NFL球探会关注外接手的冲刺速度那样。 但Y Combinator寻找的绝非剥削他人的能力,恰恰相反。我将通过解释如何说服YC投资你,来展示他们真正看重什么。 YC最看重的是深刻理解特定用户群体并能满足其需求的创始人。这一理念如此重要,以至于成为YC的座右铭:"创造人们需要的东西"。 大公司或许能强行向不情愿的顾客推销不合适的产品,但初创企业没有这种权力。初创企业必须通过真正取悦客户来赢得生存空间,否则永远无法起步。 这对创始人和YC合伙人都是难题。在市场经济中,创造人们需要但尚未拥有的东西极为困难——这正是市场经济的精妙之处。如果某个需求已被广泛认知且能被满足,市场早就不存在空缺了。 因此YC面试必然围绕新事物展开:或是新需求,或是满足需求的新方式。而且必须是不确定的创新。如果需求确定存在且你能满足,这种确定性会直接体现为快速增长的营收,你就不需要种子资金了。 YC合伙人必须双重判断:你是否发现了真实需求?你能否满足它?这就是他们的专业所在——职业预测师。他们掌握1001种启发式方法,虽然不会全盘托出,但很乐意分享最关键的那些,因为这些无法伪造,"破解"的唯一方法就是做好创始人本分。 合伙人首要判断的是:你创造的东西最终能否被大众需要?不必是当下。产品与市场将互相塑造演化,但最终必须指向巨大市场。[1] 有时巨大市场显而易见。如果Boom公司能造出客机,国际航空公司必然采购。但通常路径是由小众市场扩展而来。这个概念如此重要,我们不妨称之为"幼虫市场"。 最典型的幼虫市场当属1976年苹果创立时的计算机市场。当时个人电脑需求有限,但逐渐扩展至今,全球十岁孩童都渴望拥有(尽管称之为"手机")。 最理想的组合是站在变革前沿"活在未来"的创始人,正在构建他们自己需要的东西。绝大多数超级成功的初创企业皆属此类:沃兹尼亚克需要电脑,扎克伯格想与大学好友在线互动,佩奇与布林要搜索网络内容。这些创始人都在为自己和同类人构建产品,而他们所处的变革前沿意味着未来会有更多人产生同样需求。 虽然最理想的幼虫市场是创始人自身及同行,但并非唯一类型。区域性市场也是可能路径——先服务特定地区再扩张。 初始市场的关键在于真实存在。这看似显而易见,却是多数创业构想的最大缺陷。必须存在迫切需要的用户群体,即使产品存在缺陷、公司籍籍无名也愿意使用。用户数量可以很少,但必须存在。只要有种子用户,通过添加功能、寻找相似人群、口碑传播等方式就能扩展。但所有方法都依赖初始用户群。 因此YC面试必定深挖这点:首批用户是谁?你如何确认他们的需求?如果只能提一个问题,那就是"你如何知道人们需要这个?" 最具说服力的回答是"因为我们和朋友需要"。如果还能展示正在传播的粗糙原型,合伙人就会将默认态度从"拒绝"转为"接受"——除非发现其他硬伤。 这个标准相当严苛。Airbnb当年都未达标——他们确实构建了自己需要的东西,但尚未形成传播效应。所以若达不到这个黄金标准也不必气馁。 实践中,只要创始人展现出对用户需求的深刻理解就能让合伙人满意。Airbnb团队正是如此:他们能详尽解析房东与房客的动机,源于亲身作为首批房东的经历。我们提的每个问题他们都有答案。虽然我们作为用户并不兴奋,但知道这不能说明什么——很多成功企业最初也未让我们兴奋。我们判断:"他们言之有物,或许发现了什么。虽然尚未增长,但可能在YC期间找到方法。"事实确实如此,三周后增长就开始了。 YC面试的最佳策略是向合伙人传授用户洞察。因此最佳准备方式就是与用户对话,精确把握他们的想法——这本就是创始人该做的事。 听起来可能有些轻信,但YC合伙人确实希望依赖创始人来理解市场。想想风投通常如何评估市场潜力?他们通常不是领域专家,所以会咨询专业人士。YC没时间这么做,但只要确认创始人(a)专业且(b)诚实,就不需要外部专家——创始人自己就是评估创意的领域专家。 因此YC面试不是路演。为给更多创始人机会,我们将面试压缩至10分钟。这么短时间无法通过路演间接证据判断创始人是否专业诚实,必须直接提问。没有时间顺序访问,需要随机访问。[2] 我听过最糟糕的面试建议是"控制面试节奏确保传达关键信息"——即把面试变成路演。⟨此处省略粗口⟩。当受访者回避问题转而背诵预制内容时,十分钟转瞬即逝。 只有现任或前任YC合伙人能提供准确面试建议。被面试者(即便成功者)并不了解:每次面试重点都不同,可能聚焦创始人、创意或某个具体环节。常有创始人抱怨没能完整阐述创意,但事实上他们已提供了足够信息。 既然YC面试由提问构成,制胜关键就是精彩作答。首要原则是坦诚。合伙人不期待你无所不知。若遇到不懂的问题,不要强行编造。合伙人如同资深投资者,都是职业"谎言探测仪",而你(但愿)只是业余"谎言制造者"。若识破你的谎言,他们甚至不会点破。所以诚实比推销更明智。遇到不懂的问题,直言不知并说明探索方法,或回答相关问题。 例如被问"可能失败的原因",最糟回答是"没有"。这不会证明创意无懈可击,反而暴露你是个傻瓜或骗子。专家被问及此时会详述各种可怕细节。合伙人清楚所有创意都有风险——好项目在这个阶段正是如此:微小概率可能成就巨大回报。 竞争对手问题同理。初创企业很少死于竞争,多因执行不力。但你必须清楚竞争对手,并坦诚分析优劣势。因为合伙人明白竞争不致命,不会因此否定你。但若你显得不了解对手或轻视威胁,他们会记上一笔——无论出于无知还是欺骗,结果都一样。 合伙人不期待完美创意。种子投资阶段只需要有潜力的假设。但他们期待你深思熟虑且诚实。若为显得完美而流于肤浅,就是得不偿失。 若合伙人确信存在通往大市场的路径,接下来判断你能否找到它。这取决于三点:创始人的综合素质、领域专长及团队关系。创始人有多坚定?构建能力如何?逆境中的韧性?团队友谊多牢固? Airbnb团队在创意环节只是及格,但在这个环节表现惊人。他们通过制作奥巴马/麦凯恩主题麦片筹集资金的故事,是我们决定投资的最重要因素。他们当时不知道,这个看似无关的故事实为创始人素质的绝佳证明:展现了机智、决心与协作能力。 整个面试都显示他们是真心投入——不为金钱或酷炫,而是因为这是他们的项目。他们发现了有趣的新点子,无法轻言放弃。 这听起来平凡,却是最强大的驱动力——不仅对初创企业,对任何雄心勃勃的事业都是如此:对你构建的事物怀有真挚兴趣。这才是真正驱动亿万富翁(至少那些通过创业成为亿万富翁的人)的力量。公司就是他们的项目。 关于亿万富翁,鲜为人知的是他们本都可以更早退出——通过被收购或聘请职业经理人。多数创始人确实如此。真正致富者是持续奋斗的人。驱使他们前进的不只是金钱,而是如同所有自愿坚持工作的人那样:没有更想做的事。 这才是创业成为亿万富翁者的核心特质——而非剥削他人。因此YC寻找的是真实的创始人。创业动机通常很复杂:金钱、酷炫形象、对问题的真诚兴趣、不愿为他人工作等因素交织。后两者比前两者更具驱动力。想赚钱或显得酷无可厚非,多数人皆如此。但若创始人显得只为这些,就很难取得大成功。为钱创业者会接受首个可观收购要约,为酷创业者很快会发现更轻松的耍帅方式。[3] YC确实会遇到剥削型创始人。他们被YC品牌吸引而来。但合伙人识别后会立即拒绝。如果恶人能成为优秀创始人,YC合伙人将面临道德困境。幸运的是他们不能——因为恶人就是差劲的创始人。这类剥削型创始人不会取得大成功,甚至小成就都难,因为他们总在寻找捷径。他们把YC本身也视为捷径。 他们的剥削通常始于联合创始人——这很致命,因为创始团队关系是公司根基。继而剥削用户——同样致命,因为成功初创企业需要的早期用户恰恰最难欺骗。这类创始人最多只能维持骗局,直到有收购方上当。但这种收购规模永远不会大。[4] 既然职业亿万富翁发掘者知道不该寻找剥削技能,为何某些政客认为这是亿万富翁的核心特质? 我认为他们始于"贫富悬殊令人不适"的感受。这种感受源自人类(甚至其他物种)的DNA。 若仅表达这种感受,谁会反对?我也感到不适,并且认为富人有责任将财富用于公益。但他们的错误在于从感受直接跳跃到"巨额财富必然来路不正"的结论——这个可证伪的论断本身就是错误的。 确实有人通过恶行致富,但更多作恶者并未获得多少财富。恶行与财富积累毫无关联——甚至可能负相关。 这种谬论的最大危害或许不是误导政策,而是误导有志青年。你能想象比这更破坏社会流动性的说教吗?一边告诉穷孩子致富要靠剥削,而富家子弟通过观察父辈早已知道真实路径? 让我告诉你真实路径,至少你可以告诉自己的孩子真相:一切围绕用户。成为亿万富翁最可靠的途径是创建快速增长的公司,而增长的关键在于满足用户需求。初创企业必须取悦用户才能起步,且这个准则永不过时。大公司若忽视这点就会危险——一旦停止取悦用户,终将被他人取代。 用户正是YC合伙人面试时最关注的,也是我与十年前投资、如今已成为亿万富翁的创始人交谈时的焦点:用户需要什么?你能为他们创造什么新事物?亿万富翁创始人总是热衷讨论这个话题——这正是他们成功的根源。 注释 [1] YC合伙人经验如此丰富,有时能发现创始人尚未察觉的市场路径。他们不会像交易中的买家那样故作怀疑来增加筹码。虽然创始人觉得需要说服合伙人,但角色经常反转——许多创始人离开时反而意识到自己创意的潜力比想象更大。 [2] 实际上7分钟足够。第8分钟很少改变决定。但10分钟更符合社交习惯。 [3] 我自己在首次创业时就接受了首个可观收购要约,所以不责怪创始人这么做。为赚钱创业没有错。人总要谋生,对某些人创业就是最高效的方式。只是这类企业通常不会做得特别大。 [4] 至少现在如此。互联网泡沫时期确实有过大规模收购和IPO。 致谢 感谢Trevor Blackwell、Jessica Livingston、Robert Morris、Geoff Ralston和Harj Taggar阅读本文草稿。.
December 2020 Jessica and I have certain words that have special significance when we're talking about startups. The highest compliment we can pay to founders is to describe them as "earnest." This is not by itself a guarantee of success. You could be earnest but incapable. But when founders are both formidable (another of our words) and earnest, they're as close to unstoppable as you get. Earnestness sounds like a boring, even Victorian virtue. It seems a bit of an anachronism that people in Silicon Valley would care about it. Why does this matter so much? When you call someone earnest, you're making a statement about their motives. It means both that they're doing something for the right reasons, and that they're trying as hard as they can. If we imagine motives as vectors, it means both the direction and the magnitude are right. Though these are of course related: when people are doing something for the right reasons, they try harder. [1] The reason motives matter so much in Silicon Valley is that so many people there have the wrong ones. Starting a successful startup makes you rich and famous. So a lot of the people trying to start them are doing it for those reasons. Instead of what? Instead of interest in the problem for its own sake. That is the root of earnestness. [2] It's also the hallmark of a nerd. Indeed, when people describe themselves as "x nerds," what they mean is that they're interested in x for its own sake, and not because it's cool to be interested in x, or because of what they can get from it. They're saying they care so much about x that they're willing to sacrifice seeming cool for its sake. A _genuine interest_ in something is a very powerful motivator � for some people, the most powerful motivator of all. [3] Which is why it's what Jessica and I look for in founders. But as well as being a source of strength, it's also a source of vulnerability. Caring constrains you.
杰西卡和我有一些在讨论初创企业时具有特殊意义的词汇。我们能给予创始人的最高赞誉就是形容他们"真挚"。这本身并不能保证成功——你可能真挚但能力不足。但当创始人既"强悍"(我们的另一个关键词)又真挚时,他们就近乎所向披靡了。
真挚听起来像是种乏味甚至过时的维多利亚时代美德。硅谷人士竟会重视这种品质似乎有些不合时宜。为何它如此重要?
当你称某人真挚时,你是在评价他们的动机。这既意味着他们做事的初衷正确,也意味着他们全力以赴。若将动机比作矢量,则说明其方向与强度俱佳。当然这两者相关:当人们出于正确理由做事时,自然会更加努力。[1]
动机在硅谷如此重要的原因在于,太多人怀揣错误动机。创立成功企业能带来财富与名声,因此许多创业者正是为此而来。而非什么?而非出于对问题本身的热爱。这才是真挚的本源。[2]
The earnest can't easily reply in kind to mocking banter, or put on a cool facade of nihil admirari. They care too much. They are doomed to be the straight man. That's a real disadvantage in your _teenage years_, when mocking banter and nihil admirari often have the upper hand. But it becomes an advantage later. It's a commonplace now that the kids who were nerds in high school become the cool kids' bosses later on. But people misunderstand why this happens. It's not just because the nerds are smarter, but also because they're more earnest. When the problems get harder than the fake ones you're given in high school, caring about them starts to matter. Does it always matter? Do the earnest always win? Not always. It probably doesn't matter much in politics, or in crime, or in certain types of business that are similar to crime, like gambling, personal injury law, patent trolling, and so on. Nor does it matter in academic fields at the more _bogus_ end of the spectrum. And though I don't know enough to say for sure, it may not matter in some kinds of humor: it may be possible to be completely cynical and still be very funny. [4] Looking at the list of fields I mentioned, there's an obvious pattern. Except possibly for humor, these are all types of work I'd avoid like the plague. So that could be a useful heuristic for deciding which fields to work in: how much does earnestness matter? Which can in turn presumably be inferred from the prevalence of nerds at the top. Along with "nerd," another word that tends to be associated with earnestness is "naive." The earnest often seem naive. It's not just that they don't have the motives other people have. They often don't fully grasp that such motives exist.
这也是书呆子的标志。当人们自称"X领域书呆子"时,他们想表达的是对X纯粹的兴趣,而非因关注X很酷或能从中获利。他们甘愿为热爱X而牺牲表面上的酷。
对事物的【纯粹兴趣】是最强大的驱动力——对某些人而言甚至是终极驱动力。[3]这正是我和杰西卡在创始人身上寻找的特质。但这种特质既是力量之源,也是脆弱之处。在意就意味着束缚。真挚者难以用戏谑还击嘲讽,也无法摆出"万物皆不足奇"的冷漠姿态。他们太过投入,注定成为认真的一方。这在【青少年时期】确实是劣势,因为那时嘲讽与冷漠往往占据上风。但日后这会转化为优势。
如今有个老生常谈:高中时的书呆子后来成了酷小孩的老板。但人们误解了其中缘由。不仅因为书呆子更聪明,更因为他们更真挚。当问题比中学作业更难时,投入程度就开始显现价值。
真挚永远重要吗?真挚者总能胜出?未必。在政治、犯罪或类似赌博、人身伤害诉讼、专利流氓等灰色商业领域,它可能无足轻重。在学术谱系中更【伪善】的领域同样如此。虽然我不够了解,但某些幽默类型或许也不需要真挚:完全玩世不恭的人可能非常风趣。[4]
观察上述领域会发现明显规律——除了幽默,这些都是我避之不及的工作类型。因此有个实用法则:选择真挚程度重要的领域。而该重要性又可通过顶尖人物中书呆子的比例来推断。
Or they may know intellectually that they do, but because they don't feel them, they forget about them. [5] It works to be slightly naive not just about motives but also, believe it or not, about the problems you're working on. Naive optimism can compensate for the bit rot that _rapid change_ causes in established beliefs. You plunge into some problem saying "How hard can it be?", and then after solving it you learn that it was till recently insoluble. Naivete is an obstacle for anyone who wants to seem sophisticated, and this is one reason would-be intellectuals find it so difficult to understand Silicon Valley. It hasn't been safe for such people to use the word "earnest" outside scare quotes since Oscar Wilde wrote "The Importance of Being Earnest" in 1895. And yet when you zoom in on Silicon Valley, right into _Jessica Livingston's brain_, that's what her x-ray vision is seeking out in founders. Earnestness! Who'd have guessed? Reporters literally can't believe it when founders making piles of money say that they started their companies to make the world better. The situation seems made for mockery. How can these founders be so naive as not to realize how implausible they sound? Though those asking this question don't realize it, that's not a rhetorical question. A lot of founders are faking it, of course, particularly the smaller fry, and the soon to be smaller fry. But not all of them. There are a significant number of founders who really are interested in the problem they're solving mainly for its own sake. Why shouldn't there be? We have no difficulty believing that people would be interested in history or math or even old bus tickets for their own sake. Why can't there be people interested in self-driving cars or social networks for their own sake? When you look at the question from this side, it seems obvious there would be.
与"书呆子"类似,"天真"也常与真挚关联。真挚者往往显得天真。他们不仅缺乏常人的动机,甚至常常意识不到这些动机的存在。或者理性上知道,但因自身缺乏这类感受而遗忘。[5]
适度的天真不仅适用于动机,信不信由你,对工作问题也同样有效。天真的乐观能抵消【快速变革】对既有观念的侵蚀。当你高喊"这能有多难"投身某个问题,解决后才知它不久前还被视为无解。
天真是追求世故者的障碍,这也解释了为何伪知识分子难以理解硅谷。自1895年王尔德写下《不可儿戏》后,"真挚"一词就难逃反讽用法。然而当你聚焦硅谷,直抵【杰西卡·利文斯顿的思维核心】,会发现她寻找的正是创始人身上的这种特质。真挚!谁能想到?当赚得盆满钵满的创始人说创业是为改变世界时,记者们简直难以置信。这场景简直是为嘲讽量身定制——这些创始人怎会天真到听不出自己多不可信?
提问者未曾意识到,这其实是个真问题。
当然许多创始人在伪装,尤其是小鱼小虾和即将沦为小鱼小虾之辈。但非全部。确实有相当数量的创始人纯粹是为解决问题本身而投入。
And isn't it likely that having a deep interest in something would be a source of great energy and resilience? It is in every other field. The question really is why we have a blind spot about business. And the answer to that is obvious if you know enough history. For most of history, making large amounts of money has not been very intellectually interesting. In preindustrial times it was never far from robbery, and some areas of business still retain that character, except using lawyers instead of soldiers. But there are other areas of business where the work is genuinely interesting. Henry Ford got to spend much of his time working on interesting technical problems, and for the last several decades the trend in that direction has been accelerating. It's much easier now to make a lot of money by working on something you're interested in than it was _50 years ago_. And that, rather than how fast they grow, may be the most important change that startups represent. Though indeed, the fact that the work is genuinely interesting is a big part of why it gets done so fast. [6] Can you imagine a more important change than one in the relationship between intellectual curiosity and money? These are two of the most powerful forces in the world, and in my lifetime they've become significantly more aligned. How could you not be fascinated to watch something like this happening in real time? I meant this essay to be about earnestness generally, and now I've gone and talked about startups again. But I suppose at least it serves as an example of an x nerd in the wild. Notes [1] It's interesting how many different ways there are _not_ to be earnest: to be cleverly cynical, to be superficially brilliant, to be conspicuously virtuous, to be cool, to be sophisticated, to be orthodox, to be a snob, to bully, to pander, to be on the make.
为何不能有?我们毫不怀疑有人会纯粹热爱历史、数学甚至旧车票。为何不能有人纯粹痴迷自动驾驶或社交网络?从这个角度看,答案显而易见。而对事物深度痴迷难道不是巨大能量与韧性的源泉吗?其他领域皆然。
真正的问题是我们对商业的盲区。若了解历史,答案显而易见:在大部分历史时期,赚大钱并非智力活动。前工业时代,致富总与劫掠相去不远,某些商业领域至今保留这种特质,只是用律师替代了士兵。
但商业中也有真正有趣的领域。亨利·福特当年就能将大量时间投入有趣的技术问题,近几十年来这种趋势正在加速。如今通过从事感兴趣之事致富比【50年前】容易得多。这或许才是初创企业代表的最重要变革,而非其增速。事实上,工作本身的有趣性正是其快速推进的主因。[6]
还有比智力好奇心与金钱关系变革更重要的事吗?这是世界上最强大的两股力量,而在我们有生之年,它们前所未有地趋于一致。目睹这种实时变革怎能不令人着迷?
本文本欲探讨广义的真挚,结果又绕回初创企业。但至少这算是个野生领域书呆子的鲜活案例。
This pattern suggests that earnestness is not one end of a continuum, but a target one can fall short of in multiple dimensions. Another thing I notice about this list is that it sounds like a list of the ways people behave on Twitter. Whatever else social media is, it's a vivid catalogue of ways not to be earnest. [2] People's motives are as mixed in Silicon Valley as anywhere else. Even the founders motivated mostly by money tend to be at least somewhat interested in the problem they're solving, and even the founders most interested in the problem they're solving also like the idea of getting rich. But there's great variation in the relative proportions of different founders' motivations. And when I talk about "wrong" motives, I don't mean morally wrong. There's nothing morally wrong with starting a startup to make money. I just mean that those startups don't do as well. [3] The most powerful motivator for most people is probably family. But there are some for whom intellectual curiosity comes first. In his (wonderful) autobiography, Paul Halmos says explicitly that for a mathematician, math must come before anything else, including family. Which at least implies that it did for him. [4] Interestingly, just as the word "nerd" implies earnestness even when used as a metaphor, the word "politics" implies the opposite. It's not only in actual politics that earnestness seems to be a handicap, but also in office politics and academic politics. [5] It's a bigger social error to seem naive in most European countries than it is in America, and this may be one of subtler reasons startups are less common there. Founder culture is completely at odds with sophisticated cynicism. The most earnest part of Europe is Scandinavia, and not surprisingly this is also the region with the highest number of successful startups per capita. [6] Much of business is schleps, and probably always will be. But even being a professor is largely schleps.
[1] 有趣的是,不真挚有无数种表现:精明世故、浮华炫技、道貌岸然、故作高冷、附庸风雅、因循守旧、势利眼、霸凌者、投机客、钻营家。这种模式暗示真挚并非连续谱的端点,而是可能从多维度偏离的靶心。
另值得注意的是,这份清单恰似推特用户行为大全。无论社交媒体本质为何,它确是不真挚行为的生动目录。
[2] 硅谷人士的动机与他处同样混杂。即便主要为钱创业的创始人,多少也对解决问题抱有兴趣;而最痴迷问题的创始人也喜欢致富概念。但不同创始人的动机比例差异巨大。
所谓"错误"动机无关道德。为赚钱创业并无道德问题,只是这类企业往往表现不佳。
[3] 对多数人最强的驱动力或许是家庭。但有些人将求知欲置于首位。保罗·哈尔莫斯在(精彩的)自传中直言,对数学家而言,数学必须高于一切——包括家庭。这至少暗示他本人如此。
It would be interesting to collect statistics about the schlep ratios of different jobs, but I suspect they'd rarely be less than 30%. Thanks to Trevor Blackwell, Patrick Collison, Suhail Doshi, Jessica Livingston, Mattias Ljungman, Harj Taggar, and Kyle Vogt for reading drafts of this..
[4] 有趣的是,正如"书呆子"即便作为隐喻也暗含真挚,"政治"一词则隐含相反意味。不仅在真实政坛,在办公室政治和学术政治中,真挚似乎都成劣势。
[5] 在多数欧洲国家,显得天真比在美国更严重的社会失误,这或许是当地初创企业较少的微妙原因之一。创始人文化与世故的犬儒主义完全相悖。
欧洲最真挚的地区是斯堪的纳维亚,这里的人均成功初创企业数量也最多。
[6] 商业多苦差,且可能永远如此。即便教授工作也大半是苦差。统计不同工作的苦差比例会很有趣,但我怀疑很少低于30%。
致谢 特雷弗·布莱克韦尔、帕特里克·科利森、苏海尔·多希、杰西卡·利文斯顿、马蒂亚斯·永曼、哈吉·塔加尔和凯尔·沃格特审阅了本文草稿。
December 2020 To celebrate Airbnb's IPO and to help future founders, I thought it might be useful to explain what was special about Airbnb. What was special about the Airbnbs was how earnest they were. They did nothing half-way, and we could sense this even in the interview. Sometimes after we interviewed a startup we'd be uncertain what to do, and have to talk it over. Other times we'd just look at one another and smile. The Airbnbs' interview was that kind. We didn't even like the idea that much. Nor did users, at that stage; they had no growth. But the founders seemed so full of energy that it was impossible not to like them. That first impression was not misleading. During the batch our nickname for Brian Chesky was The Tasmanian Devil, because like the cartoon character he seemed a tornado of energy. All three of them were like that. No one ever worked harder during YC than the Airbnbs did. When you talked to the Airbnbs, they took notes. If you suggested an idea to them in office hours, the next time you talked to them they'd not only have implemented it, but also implemented two new ideas they had in the process. "They probably have the best attitude of any startup we've funded" I wrote to Mike Arrington during the batch. They're still like that. Jessica and I had dinner with Brian in the summer of 2018, just the three of us. By this point the company is ten years old. He took a page of notes about ideas for new things Airbnb could do. What we didn't realize when we first met Brian and Joe and Nate was that Airbnb was on its last legs. After working on the company for a year and getting no growth, they'd agreed to give it one last shot. They'd try this Y Combinator thing, and if the company still didn't take off, they'd give up. Any normal person would have given up already. They'd been funding the company with credit cards.
为了庆祝Airbnb的上市并帮助未来的创业者,我认为解释Airbnb的独特之处或许会有所帮助。
Airbnb团队最特别的是他们的极度认真。他们做事从不半途而废,甚至在面试时我们就能感受到这一点。有时我们面试完一家初创公司后会犹豫不决,需要讨论一番;而有时我们只需相视一笑——Airbnb的面试就属于后者。当时我们并不太看好这个创意,用户反响也很冷淡,业务毫无增长迹象。但创始人们身上迸发的能量让人无法不喜欢他们。
第一印象没有骗人。在孵化期间,我们给Brian Chesky起了个绰号叫"塔斯马尼亚恶魔",因为他就像卡通角色那样永远活力四射。他们三人都如此。在YC历史上,没有哪支团队比Airbnb更拼命。每次交谈他们都会做笔记。如果你在办公时间提个建议,下次见面时他们不仅已经落实,还会额外实现两个衍生创意。"这可能是我们投资过态度最棒的团队,"我在孵化期间给Mike Arrington写信说道。
这种特质始终未变。2018年夏天,我和Jessica与Brian三人共进晚餐——那时公司已成立十年。他仍然记了满满一页纸,记录Airbnb可能拓展的新方向。
They had a _binder_ full of credit cards they'd maxed out. Investors didn't think much of the idea. One investor they met in a cafe walked out in the middle of meeting with them. They thought he was going to the bathroom, but he never came back. "He didn't even finish his smoothie," Brian said. And now, in late 2008, it was the worst recession in decades. The stock market was in free fall and wouldn't hit bottom for another four months. Why hadn't they given up? This is a useful question to ask. People, like matter, reveal their nature under extreme conditions. One thing that's clear is that they weren't doing this just for the money. As a money-making scheme, this was pretty lousy: a year's work and all they had to show for it was a binder full of maxed-out credit cards. So why were they still working on this startup? Because of the experience they'd had as the first hosts. When they first tried renting out airbeds on their floor during a design convention, all they were hoping for was to make enough money to pay their rent that month. But something surprising happened: they enjoyed having those first three guests staying with them. And the guests enjoyed it too. Both they and the guests had done it because they were in a sense forced to, and yet they'd all had a great experience. Clearly there was something new here: for hosts, a new way to make money that had literally been right under their noses, and for guests, a new way to travel that was in many ways better than hotels. That experience was why the Airbnbs didn't give up. They knew they'd discovered something. They'd seen a glimpse of the future, and they couldn't let it go. They knew that once people tried staying in what is now called "an airbnb," they would also realize that this was the future. But only if they tried it, and they weren't. That was the problem during Y Combinator: to get growth started.
初见Brian、Joe和Nate时,我们不知道Airbnb已濒临绝境。在经历一年毫无起色的运营后,他们约定这是最后一次尝试。如果参加YC后公司仍无起色,他们就放弃。
常人早就放弃了。他们一直用信用卡维持公司运转,有个塞满刷爆信用卡的活页夹。投资人对这个创意不屑一顾,有位在咖啡馆会面的投资人中途离席,再没回来。"他连奶昔都没喝完,"Brian说。而2008年底正值数十年来最严重的经济衰退,股市自由落体般下跌,四个月后才触底。
为什么他们没放弃?这个问题的答案很有启发性。就像物质在极端条件下会显现本质,人在绝境中也展露真性情。显然他们不是为了钱——作为赚钱计划这糟透了:一年努力只换来装满透支信用卡的活页夹。坚持的原因在于他们作为首批房东的体验。
最初在设计大会期间出租气垫床时,他们只求赚够当月房租。但意外发生了:他们享受与三位房客共处的时光,房客也很满意。虽然双方都是被逼无奈,却都获得了美妙体验。这里存在新事物:对房东是近在眼前的新收入来源,对房客则是全方位优于酒店的旅行方式。
Airbnb's goal during YC was to reach what we call ramen profitability, which means making enough money that the company can pay the founders' living expenses, if they live on ramen noodles. Ramen profitability is not, obviously, the end goal of any startup, but it's the most important threshold on the way, because this is the point where you're airborne. This is the point where you no longer need investors' permission to continue existing. For the Airbnbs, ramen profitability was $4000 a month: $3500 for rent, and $500 for food. They taped this goal to the mirror in the bathroom of their apartment. The way to get growth started in something like Airbnb is to focus on the hottest subset of the market. If you can get growth started there, it will spread to the rest. When I asked the Airbnbs where there was most demand, they knew from searches: New York City. So they focused on New York. They went there in person to visit their hosts and help them make their listings more attractive. A big part of that was better pictures. So Joe and Brian rented a professional camera and took pictures of the hosts' places themselves. This didn't just make the listings better. It also taught them about their hosts. When they came back from their first trip to New York, I asked what they'd noticed about hosts that surprised them, and they said the biggest surprise was how many of the hosts were in the same position they'd been in: they needed this money to pay their rent. This was, remember, the worst recession in decades, and it had hit New York first. It definitely added to the Airbnbs' sense of mission to feel that people needed them. In late January 2009, about three weeks into Y Combinator, their efforts started to show results, and their numbers crept upward. But it was hard to say for sure whether it was growth or just random fluctuation.
正是这段经历让Airbnb团队坚持下来。他们知道自己发现了什么,瞥见了未来图景,无法轻言放弃。
他们明白:只要人们尝试住在如今所谓的"Airbnb"里,就会意识到这是未来。但问题在于没人尝试——这就是YC期间要解决的增长难题。
他们在YC阶段的目标是实现"拉面盈利"(即收入能覆盖创始人基本生活开支)。虽然这不是创业的终极目标,却是最重要的里程碑,意味着公司能自主存活。对Airbnb团队来说,月入4000美元(3500房租+500食物)就是达标线,这个数字被贴在他们公寓浴室的镜子上。
对于Airbnb这类平台,启动增长的关键是聚焦需求最旺盛的市场细分。如果能在那里突破,就会蔓延到其他地区。当被问及哪里需求最大时,搜索数据告诉他们:纽约。于是他们亲赴纽约拜访房东,协助优化房源信息,其中重要环节是提升照片质量——Joe和Brian租了专业相机亲自为房东拍摄。
By February it was clear that it was real growth. They made $460 in fees in the first week of February, $897 in the second, and $1428 in the third. That was it: they were airborne. Brian sent me an email on February 22 announcing that they were ramen profitable and giving the last three weeks' numbers. "I assume you know what you've now set yourself up for next week," I responded. Brian's reply was seven words: "We are not going to slow down.".
这不仅改善了房源展示,更让他们深入理解房东群体。从纽约考察回来后,我问最意外的发现是什么,他们说是许多房东和自己当初处境相同:急需这笔钱交房租。别忘了当时正值经济危机,纽约首当其冲。这种"被需要"的感觉强化了他们的使命感。
2009年1月下旬,在YC进行约三周后,努力初见成效,数据缓慢攀升。起初难以分辨是真实增长还是随机波动,但到二月已确定是前者:二月第一周佣金收入460美元,第二周897美元,第三周1428美元——他们起飞了。Brian在2月22日发邮件宣布实现拉面盈利,并附上三周数据。
"你应该知道下周该做什么了,"我回复道。
Brian的答复只有七个字:"我们不会放缓脚步。"
November 2020 There are some kinds of work that you can't do well without thinking differently from your peers. To be a successful scientist, for example, it's not enough just to be correct. Your ideas have to be both correct and novel. You can't publish papers saying things other people already know. You need to say things no one else has realized yet. The same is true for investors. It's not enough for a public market investor to predict correctly how a company will do. If a lot of other people make the same prediction, the stock price will already reflect it, and there's no room to make money. The only valuable insights are the ones most other investors don't share. You see this pattern with startup founders too. You don't want to start a startup to do something that everyone agrees is a good idea, or there will already be other companies doing it. You have to do something that sounds to most other people like a bad idea, but that you know isn't � like writing software for a tiny computer used by a few thousand hobbyists, or starting a site to let people rent airbeds on strangers' floors. Ditto for essayists. An essay that told people things they already knew would be boring. You have to tell them something _new_. But this pattern isn't universal. In fact, it doesn't hold for most kinds of work. In most kinds of work � to be an administrator, for example � all you need is the first half. All you need is to be right. It's not essential that everyone else be wrong. There's room for a little novelty in most kinds of work, but in practice there's a fairly sharp distinction between the kinds of work where it's essential to be independent-minded, and the kinds where it's not. I wish someone had told me about this distinction when I was a kid, because it's one of the most important things to think about when you're deciding what kind of work you want to do.
有些工作,若不能以不同于同侪的方式思考,就无法出色完成。例如,要成为一名成功的科学家,仅仅正确是不够的。你的想法必须既正确又新颖。你不能发表重复他人已知观点的论文,而需要说出尚未被他人意识到的东西。
Do you want to do the kind of work where you can only win by thinking differently from everyone else? I suspect most people's unconscious mind will answer that question before their conscious mind has a chance to. I know mine does. Independent-mindedness seems to be more a matter of nature than nurture. Which means if you pick the wrong type of work, you're going to be unhappy. If you're naturally independent-minded, you're going to find it frustrating to be a middle manager. And if you're naturally conventional-minded, you're going to be sailing into a headwind if you try to do original research. One difficulty here, though, is that people are often mistaken about where they fall on the spectrum from conventional- to independent-minded. Conventional-minded people don't like to think of themselves as conventional-minded. And in any case, it genuinely feels to them as if they make up their own minds about everything. It's just a coincidence that their beliefs are identical to their peers'. And the independent-minded, meanwhile, are often unaware how different their ideas are from conventional ones, at least till they state them publicly. [1] By the time they reach adulthood, most people know roughly how smart they are (in the narrow sense of ability to solve pre-set problems), because they're constantly being tested and ranked according to it. But schools generally ignore independent-mindedness, except to the extent they try to suppress it. So we don't get anything like the same kind of feedback about how independent-minded we are. There may even be a phenomenon like Dunning-Kruger at work, where the most conventional-minded people are confident that they're independent-minded, while the genuinely independent-minded worry they might not be independent-minded enough. ___________ Can you make yourself more independent-minded? I think so.
投资者亦是如此。公开市场投资者仅正确预测公司表现是不够的。若多数人做出相同预测,股价早已反映这一预期,盈利空间便不复存在。唯有大多数投资者未察觉的洞见才有价值。
初创企业创始人同样遵循这一模式。若你创办的公司从事众人公认的好项目,必然已存在竞争者。你必须选择在多数人眼中看似糟糕、实则潜力巨大的方向——比如为几千名爱好者使用的微型电脑开发软件,或创建让人们租用陌生人家中气垫床的网站。
This quality may be largely inborn, but there seem to be ways to magnify it, or at least not to suppress it. One of the most effective techniques is one practiced unintentionally by most nerds: simply to be less aware what conventional beliefs are. It's hard to be a conformist if you don't know what you're supposed to conform to. Though again, it may be that such people already are independent-minded. A conventional-minded person would probably feel anxious not knowing what other people thought, and make more effort to find out. It matters a lot who you surround yourself with. If you're surrounded by conventional-minded people, it will constrain which ideas you can express, and that in turn will constrain which ideas you have. But if you surround yourself with independent-minded people, you'll have the opposite experience: hearing other people say surprising things will encourage you to, and to think of more. Because the independent-minded find it uncomfortable to be surrounded by conventional-minded people, they tend to self-segregate once they have a chance to. The problem with high school is that they haven't yet had a chance to. Plus high school tends to be an inward-looking little world whose inhabitants lack confidence, both of which magnify the forces of conformism. So high school is often a _bad time_ for the independent-minded. But there is some advantage even here: it teaches you what to avoid. If you later find yourself in a situation that makes you think "this is like high school," you know you should get out. [2] Another place where the independent- and conventional-minded are thrown together is in successful startups. The founders and early employees are almost always independent-minded; otherwise the startup wouldn't be successful. But conventional-minded people greatly outnumber independent-minded ones, so as the company grows, the original spirit of independent-mindedness is inevitably diluted.
文章作者也不例外。重复常识的论述必然乏味,唯有传递_新知_才有意义。
This causes all kinds of problems besides the obvious one that the company starts to suck. One of the strangest is that the founders find themselves able to speak more freely with founders of other companies than with their own employees. [3] Fortunately you don't have to spend all your time with independent-minded people. It's enough to have one or two you can talk to regularly. And once you find them, they're usually as eager to talk as you are; they need you too. Although universities no longer have the kind of monopoly they used to have on education, good universities are still an excellent way to meet independent-minded people. Most students will still be conventional-minded, but you'll at least find clumps of independent-minded ones, rather than the near zero you may have found in high school. It also works to go in the other direction: as well as cultivating a small collection of independent-minded friends, to try to meet as many different types of people as you can. It will decrease the influence of your immediate peers if you have several other groups of peers. Plus if you're part of several different worlds, you can often import ideas from one to another. But by different types of people, I don't mean demographically different. For this technique to work, they have to think differently. So while it's an excellent idea to go and visit other countries, you can probably find people who think differently right around the corner. When I meet someone who knows a lot about something unusual (which includes practically everyone, if you dig deep enough), I try to learn what they know that other people don't. There are almost always surprises here. It's a good way to make conversation when you meet strangers, but I don't do it to make conversation. I really want to know. You can expand the source of influences in time as well as space, by reading history.
但这一规律并非放之四海皆准。事实上,大多数工作并不适用。例如行政类工作,只需满足"正确"这一半要求即可,无需他人皆错。
多数工作允许少量创新,但实践中存在明确分界:一类工作必须以独立思考为根基,另一类则不必。
When I read history I do it not just to learn what happened, but to try to get inside the heads of people who lived in the past. How did things look to them? This is hard to do, but worth the effort for the same reason it's worth travelling far to triangulate a point. You can also take more explicit measures to prevent yourself from automatically adopting conventional opinions. The most general is to cultivate an attitude of skepticism. When you hear someone say something, stop and ask yourself "Is that true?" Don't say it out loud. I'm not suggesting that you impose on everyone who talks to you the burden of proving what they say, but rather that you take upon yourself the burden of evaluating what they say. Treat it as a puzzle. You know that some accepted ideas will later turn out to be wrong. See if you can guess which. The end goal is not to find flaws in the things you're told, but to find the new ideas that had been concealed by the broken ones. So this game should be an exciting quest for novelty, not a boring protocol for intellectual hygiene. And you'll be surprised, when you start asking "Is this true?", how often the answer is not an immediate yes. If you have any imagination, you're more likely to have too many leads to follow than too few. More generally your goal should be not to let anything into your head unexamined, and things don't always enter your head in the form of statements. Some of the most powerful influences are implicit. How do you even notice these? By standing back and watching how other people get their ideas. When you stand back at a sufficient distance, you can see ideas spreading through groups of people like waves. The most obvious are in fashion: you notice a few people wearing a certain kind of shirt, and then more and more, until half the people around you are wearing the same shirt.
若有人在我儿时指明这一区别该多好——它堪称职业选择时最关键的考量之一。你是否愿意从事唯有异于常人的思考才能胜出的领域?我猜多数人的潜意识会先于理性做出回答。至少我是如此。
You may not care much what you wear, but there are intellectual fashions too, and you definitely don't want to participate in those. Not just because you want sovereignty over your own thoughts, but because _unfashionable_ ideas are disproportionately likely to lead somewhere interesting. The best place to find undiscovered ideas is where no one else is looking. [4] ___________ To go beyond this general advice, we need to look at the internal structure of independent-mindedness � at the individual muscles we need to exercise, as it were. It seems to me that it has three components: fastidiousness about truth, resistance to being told what to think, and curiosity. Fastidiousness about truth means more than just not believing things that are false. It means being careful about degree of belief. For most people, degree of belief rushes unexamined toward the extremes: the unlikely becomes impossible, and the probable becomes certain. [5] To the independent-minded, this seems unpardonably sloppy. They're willing to have anything in their heads, from highly speculative hypotheses to (apparent) tautologies, but on subjects they care about, everything has to be labelled with a carefully considered degree of belief. [6] The independent-minded thus have a horror of ideologies, which require one to accept a whole collection of beliefs at once, and to treat them as articles of faith. To an independent-minded person that would seem revolting, just as it would seem to someone fastidious about food to take a bite of a submarine sandwich filled with a large variety of ingredients of indeterminate age and provenance. Without this fastidiousness about truth, you can't be truly independent-minded. It's not enough just to have resistance to being told what to think. Those kind of people reject conventional ideas only to replace them with the most random conspiracy theories.
独立思考的天性似乎更取决于禀赋而非培养。这意味着选错职业类型将导致痛苦:天生独立思考者在中层管理岗位会倍感压抑;而习惯从众者若强行从事原创研究,则如逆风航行。
棘手之处在于,人们常误判自己在"从众-独立"光谱上的位置。从众者不愿承认自己随波逐流,他们真诚地认为每个观点都源于自主判断——只是恰巧与同侪一致。而独立思考者往往意识不到自身观点多么离经叛道,直到公开表达时才恍然大悟。[1]
And since these conspiracy theories have often been manufactured to capture them, they end up being less independent-minded than ordinary people, because they're subject to a much more exacting master than mere convention. [7] Can you increase your fastidiousness about truth? I would think so. In my experience, merely thinking about something you're fastidious about causes that fastidiousness to grow. If so, this is one of those rare virtues we can have more of merely by wanting it. And if it's like other forms of fastidiousness, it should also be possible to encourage in children. I certainly got a strong dose of it from my father. [8] The second component of independent-mindedness, resistance to being told what to think, is the most visible of the three. But even this is often misunderstood. The big mistake people make about it is to think of it as a merely negative quality. The language we use reinforces that idea. You're _un_ conventional. You _don't_ care what other people think. But it's not just a kind of immunity. In the most independent-minded people, the desire not to be told what to think is a positive force. It's not mere skepticism, but an active _delight_ in ideas that subvert the conventional wisdom, the more counterintuitive the better. Some of the most novel ideas seemed at the time almost like practical jokes. Think how often your reaction to a novel idea is to laugh. I don't think it's because novel ideas are funny per se, but because novelty and humor share a certain kind of surprisingness. But while not identical, the two are close enough that there is a definite correlation between having a sense of humor and being independent-minded � just as there is between being humorless and being conventional-minded. [9] I don't think we can significantly increase our resistance to being told what to think.
成年时,多数人已大致知晓自己在解决预设问题方面的能力(即狭义智商),因为教育系统持续通过测试排名提供反馈。但学校通常忽视甚至压制独立思考特质,导致我们缺乏评估这项特质的可靠依据。
It seems the most innate of the three components of independent-mindedness; people who have this quality as adults usually showed all too visible signs of it as children. But if we can't increase our resistance to being told what to think, we can at least shore it up, by surrounding ourselves with other independent-minded people. The third component of independent-mindedness, curiosity, may be the most interesting. To the extent that we can give a brief answer to the question of where novel ideas come from, it's curiosity. That's what people are usually feeling before having them. In my experience, independent-mindedness and curiosity predict one another perfectly. Everyone I know who's independent-minded is deeply curious, and everyone I know who's conventional-minded isn't. Except, curiously, children. All small children are curious. Perhaps the reason is that even the conventional-minded have to be curious in the beginning, in order to learn what the conventions are. Whereas the independent-minded are the gluttons of curiosity, who keep eating even after they're full. [10] The three components of independent-mindedness work in concert: fastidiousness about truth and resistance to being told what to think leave space in your brain, and curiosity finds new ideas to fill it. Interestingly, the three components can substitute for one another in much the same way muscles can. If you're sufficiently fastidious about truth, you don't need to be as resistant to being told what to think, because fastidiousness alone will create sufficient gaps in your knowledge. And either one can compensate for curiosity, because if you create enough space in your brain, your discomfort at the resulting vacuum will add force to your curiosity. Or curiosity can compensate for them: if you're sufficiently curious, you don't need to clear space in your brain, because the new ideas you discover will push out the conventional ones you acquired by default.
这里可能存在邓宁-克鲁格效应:最从众的人自信拥有独立思考能力,而真正的独立思考者反而忧虑自己不够特立独行。
___________
Because the components of independent-mindedness are so interchangeable, you can have them to varying degrees and still get the same result. So there is not just a single model of independent-mindedness. Some independent-minded people are openly subversive, and others are quietly curious. They all know the secret handshake though. Is there a way to cultivate curiosity? To start with, you want to avoid situations that suppress it. How much does the work you're currently doing engage your curiosity? If the answer is "not much," maybe you should change something. The most important active step you can take to cultivate your curiosity is probably to seek out the topics that engage it. Few adults are equally curious about everything, and it doesn't seem as if you can choose which topics interest you. So it's up to you to _find_ them. Or invent them, if necessary. Another way to increase your curiosity is to indulge it, by investigating things you're interested in. Curiosity is unlike most other appetites in this respect: indulging it tends to increase rather than to sate it. Questions lead to more questions. Curiosity seems to be more individual than fastidiousness about truth or resistance to being told what to think. To the degree people have the latter two, they're usually pretty general, whereas different people can be curious about very different things. So perhaps curiosity is the compass here. Perhaps, if your goal is to discover novel ideas, your motto should not be "do what you love" so much as "do what you're curious about." Notes [1] One convenient consequence of the fact that no one identifies as conventional-minded is that you can say what you like about conventional-minded people without getting in too much trouble.
能否培养独立思考能力?我认为可以。这种特质或许先天为主,但确有方法放大它,至少避免压制它。
When I wrote _"The Four Quadrants of Conformism"_ I expected a firestorm of rage from the aggressively conventional-minded, but in fact it was quite muted. They sensed that there was something about the essay that they disliked intensely, but they had a hard time finding a specific passage to pin it on. [2] When I ask myself what in my life is like high school, the answer is Twitter. It's not just full of conventional-minded people, as anything its size will inevitably be, but subject to violent storms of conventional-mindedness that remind me of descriptions of Jupiter. But while it probably is a net loss to spend time there, it has at least made me think more about the distinction between independent- and conventional-mindedness, which I probably wouldn't have done otherwise. [3] The decrease in independent-mindedness in growing startups is still an open problem, but there may be solutions. Founders can delay the problem by making a conscious effort only to hire independent-minded people. Which of course also has the ancillary benefit that they have better ideas. Another possible solution is to create policies that somehow disrupt the force of conformism, much as control rods slow chain reactions, so that the conventional-minded aren't as dangerous. The physical separation of Lockheed's Skunk Works may have had this as a side benefit. Recent examples suggest employee forums like Slack may not be an unmitigated good. The most radical solution would be to grow revenues without growing the company.
最有效的方法恰是书呆子们无意实践的:减少对主流观念的认知。若不知该顺从什么,自然难以从众。当然,这类人可能本就具备独立思考基因——从众者若不知他人想法会焦虑不安,必会竭力打探。
社交圈至关重要。被从众者包围将限制你的表达,进而束缚你的思想;而与独立思考者为伍则相反:听到惊人言论会激发你表达更多创见。
You think hiring that junior PR person will be cheap, compared to a programmer, but what will be the effect on the average level of independent-mindedness in your company? (The growth in staff relative to faculty seems to have had a similar effect on universities.) Perhaps the rule about outsourcing work that's not your "core competency" should be augmented by one about outsourcing work done by people who'd ruin your culture as employees. Some investment firms already seem to be able to grow revenues without growing the number of employees. Automation plus the ever increasing articulation of the "tech stack" suggest this may one day be possible for product companies. [4] There are intellectual fashions in every field, but their influence varies. One of the reasons politics, for example, tends to be boring is that it's so extremely subject to them. The threshold for having opinions about politics is much _lower_ than the one for having opinions about set theory. So while there are some ideas in politics, in practice they tend to be swamped by waves of intellectual fashion. [5] The conventional-minded are often fooled by the strength of their opinions into believing that they're independent-minded. But strong convictions are not a sign of independent-mindedness. Rather the opposite. [6] Fastidiousness about truth doesn't imply that an independent-minded person won't be dishonest, but that he won't be deluded. It's sort of like the definition of a gentleman as someone who is never unintentionally rude. [7] You see this especially among political extremists. They think themselves nonconformists, but actually they're niche conformists.
由于独立思考者难以忍受从众环境,他们一旦有机会就会自我隔离。中学的问题在于这种机会尚未出现,加之校园是缺乏自信的封闭小世界,两者叠加放大了从众压力。因此中学对独立思考者往往是_噩梦_,但至少教会他们识别应回避的环境——日后若觉"此地宛如中学",便知该抽身而退。[2]
Their opinions may be different from the average person's, but they are often more influenced by their peers' opinions than the average person's are. [8] If we broaden the concept of fastidiousness about truth so that it excludes pandering, bogusness, and pomposity as well as falsehood in the strict sense, our model of independent-mindedness can expand further into the arts. [9] This correlation is far from perfect, though. G�del and Dirac don't seem to have been very strong in the humor department. But someone who is both "neurotypical" and humorless is very likely to be conventional-minded. [10] Exception: gossip. Almost everyone is curious about gossip. Thanks to Trevor Blackwell, Paul Buchheit, Patrick Collison, Jessica Livingston, Robert Morris, Harj Taggar, and Peter Thiel for reading drafts of this.
成功初创企业是另一处两类人被迫共处的场所。创始人及早期员工几乎都是独立思考者,否则企业难成功。但随着公司扩张,从众者数量优势必然稀释原创精神。这除了导致公司平庸化外,还引发诸多怪象:创始人发现与其他公司创始人交流反而比与自家员工更畅快。[3]
所幸你不必全天候与独立思考者为伴。定期与一两位交流足矣。一旦找到同类,他们通常同样渴望对话——正如你需要他们,他们也需
October 2020 One of the biggest things holding people back from doing great work is the fear of making something lame. And this fear is not an irrational one. Many great projects go through a stage early on where they don't seem very impressive, even to their creators. You have to push through this stage to reach the great work that lies beyond. But many people don't. Most people don't even reach the stage of making something they're embarrassed by, let alone continue past it. They're too frightened even to start. Imagine if we could turn off the fear of making something lame. Imagine how much more we'd do. Is there any hope of turning it off? I think so. I think the habits at work here are not very deeply rooted. Making new things is itself a new thing for us as a species. It has always happened, but till the last few centuries it happened so slowly as to be invisible to individual humans. And since we didn't need customs for dealing with new ideas, we didn't develop any. We just don't have enough experience with early versions of ambitious projects to know how to respond to them. We judge them as we would judge more finished work, or less ambitious projects. We don't realize they're a special case. Or at least, most of us don't. One reason I'm confident we can do better is that it's already starting to happen. There are already a few places that are living in the future in this respect. Silicon Valley is one of them: an unknown person working on a strange-sounding idea won't automatically be dismissed the way they would back home. In Silicon Valley, people have learned how dangerous that is. The right way to deal with new ideas is to treat them as a challenge to your imagination � not just to have lower standards, but to _switch polarity_ entirely, from listing the reasons an idea won't work to trying to think of ways it could. That's what I do when I meet people with new ideas.
阻碍人们做出伟大工作的最大障碍之一,是对创作出拙劣之物的恐惧。这种恐惧并非毫无来由。许多伟大的项目在早期阶段都显得平淡无奇,甚至连创作者自己都难以察觉其价值。你必须突破这个阶段,才能触及背后潜藏的伟大作品。但多数人未能做到——他们甚至尚未达到会为自己作品感到尴尬的阶段,更不用说跨越它。人们被恐惧束缚得连开始都不敢。
试想若能消除这种恐惧,我们的创造力将获得怎样的解放?
这种解放是否可能?我认为可以。这种心理习惯的根基其实并不深。
I've become quite good at it, but I've had a lot of practice. Being a partner at Y Combinator means being practically immersed in strange-sounding ideas proposed by unknown people. Every six months you get thousands of new ones thrown at you and have to sort through them, knowing that in a world with a power-law distribution of outcomes, it will be painfully obvious if you miss the needle in this haystack. Optimism becomes urgent. But I'm hopeful that, with time, this kind of optimism can become widespread enough that it becomes a social custom, not just a trick used by a few specialists. It is after all an extremely lucrative trick, and those tend to spread quickly. Of course, inexperience is not the only reason people are too harsh on early versions of ambitious projects. They also do it to seem clever. And in a field where the new ideas are risky, like startups, those who dismiss them are in fact more likely to be right. Just not when their predictions are _weighted by outcome_. But there is another more sinister reason people dismiss new ideas. If you try something ambitious, many of those around you will hope, consciously or unconsciously, that you'll fail. They worry that if you try something ambitious and succeed, it will put you above them. In some countries this is not just an individual failing but part of the national culture. I wouldn't claim that people in Silicon Valley overcome these impulses because they're morally better. [1] The reason many hope you'll succeed is that they hope to rise with you. For investors this incentive is particularly explicit. They want you to succeed because they hope you'll make them rich in the process. But many other people you meet can hope to benefit in some way from your success. At the very least they'll be able to say, when you're famous, that they've known you since way back.
对人类这个物种而言,创新本身仍是新鲜事物。虽然创新始终存在,但在过去几个世纪之前,其进程缓慢得难以被个体察觉。由于我们不需要应对新想法的社会习俗,相关规范便从未形成。
我们对雄心勃勃项目的雏形缺乏足够的认知经验,导致我们总是用评判成熟作品或普通项目的标准来苛责它们,未能意识到这些雏形的特殊性。
至少大多数人是如此。我对此保持乐观的原因之一,是改变已悄然发生。某些领域已率先迈入未来,硅谷便是典型:在这里,一个无名之辈提出的怪异构想不会像在其他地方那样遭到轻蔑否定。硅谷人早已领教过这种傲慢的代价。
But even if Silicon Valley's encouraging attitude is rooted in self-interest, it has over time actually grown into a sort of benevolence. Encouraging startups has been practiced for so long that it has become a custom. Now it just seems that that's what one does with startups. Maybe Silicon Valley is too optimistic. Maybe it's too easily fooled by impostors. Many less optimistic journalists want to believe that. But the lists of impostors they cite are suspiciously short, and plagued with asterisks. [2] If you use revenue as the test, Silicon Valley's optimism seems better tuned than the rest of the world's. And because it works, it will spread. There's a lot more to new ideas than new startup ideas, of course. The fear of making something lame holds people back in every field. But Silicon Valley shows how quickly customs can evolve to support new ideas. And that in turn proves that dismissing new ideas is not so deeply rooted in human nature that it can't be unlearnt. ___________ Unfortunately, if you want to do new things, you'll face a force more powerful than other people's skepticism: your own skepticism. You too will judge your early work too harshly. How do you avoid that? This is a difficult problem, because you don't want to completely eliminate your horror of making something lame. That's what steers you toward doing good work. You just want to turn it off temporarily, the way a painkiller temporarily turns off pain. People have already discovered several techniques that work. Hardy mentions two in _A Mathematician's Apology_ : > Good work is not done by "humble" men. It is one of the first duties of a professor, for example, in any subject, to exaggerate a little both the importance of his subject and his importance in it..
对待新思想的正确方式,是将其视为想象力的挑战——不仅要降低评判标准,更要彻底_转换极性_,从罗列失败理由转变为构想成功可能。这正是我面对创新者时的思考方式。经过YC合伙人的历练,这种思维已融入我的本能——每半年就要在上千个天马行空的构想中沙里淘金,深知在幂律分布的世界里,错过黄金创意的代价将无比惨痛。这种紧迫感让乐观主义成为生存必需。
我期待这种乐观精神终将演变为社会共识,而非少数专家的独门秘技。毕竟这是被验证过的致富之道,而这类方法向来传播迅猛。
当然,经验不足并非人们苛责雏形的唯一原因。有些人只为彰显聪明才智。在创业这类高风险领域,唱衰者反而更容易显得正确——除非用_结果权重_来衡量其预测准确性。
If you overestimate the importance of what you're working on, that will compensate for your mistakenly harsh judgment of your initial results. If you look at something that's 20% of the way to a goal worth 100 and conclude that it's 10% of the way to a goal worth 200, your estimate of its expected value is correct even though both components are wrong. It also helps, as Hardy suggests, to be slightly overconfident. I've noticed in many fields that the most successful people are slightly overconfident. On the face of it this seems implausible. Surely it would be optimal to have exactly the right estimate of one's abilities. How could it be an advantage to be mistaken? Because this error compensates for other sources of error in the opposite direction: being slightly overconfident armors you against both other people's skepticism and your own. Ignorance has a similar effect. It's safe to make the mistake of judging early work as finished work if you're a sufficiently lax judge of finished work. I doubt it's possible to cultivate this kind of ignorance, but empirically it's a real advantage, especially for the young. Another way to get through the lame phase of ambitious projects is to surround yourself with the right people � to create an eddy in the social headwind. But it's not enough to collect people who are always encouraging. You'd learn to discount that. You need colleagues who can actually tell an ugly duckling from a baby swan. The people best able to do this are those working on similar projects of their own, which is why university departments and research labs work so well. You don't need institutions to collect colleagues. They naturally coalesce, given the chance. But it's very much worth accelerating this process by seeking out other people trying to do new things. Teachers are in effect a special case of colleagues. It's a teacher's job both to see the promise of early work and to encourage you to continue.
但还存在更阴暗的动机:当你尝试宏图伟业时,周围人往往在潜意识里期待你的失败。他们恐惧你的成功会打破现有阶层。在某些国家,这不仅是个人缺陷,更已成为民族痼疾。
我并非认为硅谷人因道德高尚而克服了这种心理[1]。这里的特殊性在于,人们期待你成功是因为能共享红利。对投资者而言这种动机尤为直接——他们指望你带其致富。即便是普通相识者,也能从你的成功中分得声望红利。当你有朝一日功成名就,他们至少能炫耀"当年就认识你"。
尽管硅谷的鼓励文化植根于利益驱动,经年累月却演变为真正的善意。扶持初创企业已成为深入骨髓的社会习惯,就像呼吸般自然。
或许硅谷过于乐观?或许这里更容易被江湖骗子蒙蔽?许多持怀疑态度的记者热衷宣扬这种论调。但他们列出的骗子名单总是出奇地短,且满是星号标注的例外[2]。若以实际收益为衡量标准,硅谷的乐观主义显然比外界更精准。正因有效,这种文化终将蔓延。
But teachers who are good at this are unfortunately quite rare, so if you have the opportunity to learn from one, take it. [3] For some it might work to rely on sheer discipline: to tell yourself that you just have to press on through the initial crap phase and not get discouraged. But like a lot of "just tell yourself" advice, this is harder than it sounds. And it gets still harder as you get older, because your standards rise. The old do have one compensating advantage though: they've been through this before. It can help if you focus less on where you are and more on the rate of change. You won't worry so much about doing bad work if you can see it improving. Obviously the faster it improves, the easier this is. So when you start something new, it's good if you can spend a lot of time on it. That's another advantage of being young: you tend to have bigger blocks of time. Another common trick is to start by considering new work to be of a different, less exacting type. To start a painting saying that it's just a sketch, or a new piece of software saying that it's just a quick hack. Then you judge your initial results by a lower standard. Once the project is rolling you can sneakily convert it to something more. [4] This will be easier if you use a medium that lets you work fast and doesn't require too much commitment up front. It's easier to convince yourself that something is just a sketch when you're drawing in a notebook than when you're carving stone. Plus you get initial results faster. [5] [6] It will be easier to try out a risky project if you think of it as a way to learn and not just as a way to make something. Then even if the project truly is a failure, you'll still have gained by it.
创新远不止于创业领域。对拙劣作品的恐惧桎梏着所有行业的创造力。但硅谷证明,支持创新的文化习俗能够快速进化。这反过来印证了:对新思想的排斥并非人类不可更改的天性。
___________
遗憾的是,创新者面临的最大阻力并非外界质疑,而是自我怀疑。你同样会对自己早期作品过度苛责。如何规避这种陷阱?
If the problem is sharply enough defined, failure itself is knowledge: if the theorem you're trying to prove turns out to be false, or you use a structural member of a certain size and it fails under stress, you've learned something, even if it isn't what you wanted to learn. [7] One motivation that works particularly well for me is curiosity. I like to try new things just to see how they'll turn out. We started Y Combinator in this spirit, and it was one of main things that kept me going while I was working on _Bel_. Having worked for so long with various dialects of Lisp, I was very curious to see what its inherent shape was: what you'd end up with if you followed the axiomatic approach all the way. But it's a bit strange that you have to play mind games with yourself to avoid being discouraged by lame-looking early efforts. The thing you're trying to trick yourself into believing is in fact the truth. A lame-looking early version of an ambitious project truly is more valuable than it seems. So the ultimate solution may be to teach yourself that. One way to do it is to study the histories of people who've done great work. What were they thinking early on? What was the very first thing they did? It can sometimes be hard to get an accurate answer to this question, because people are often embarrassed by their earliest work and make little effort to publish it. (They too misjudge it.) But when you can get an accurate picture of the first steps someone made on the path to some great work, they're often pretty feeble. [8] Perhaps if you study enough such cases, you can teach yourself to be a better judge of early work. Then you'll be immune both to other people's skepticism and your own fear of making something lame. You'll see early work for what it is. Curiously enough, the solution to the problem of judging early work too harshly is to realize that our attitudes toward it are themselves early work.
这是个棘手难题,因为对拙劣作品的警惕本是指引你前行的罗盘。你需要的只是暂时关闭这种判断,就像止痛药暂时麻痹痛觉神经。
前人已总结出若干有效方法。哈代在《一个数学家的辩白》中提及两条:
> 伟大的工作从来不是由"谦逊"之人完成的。比如在任何学科领域,教授的首要职责之一,就是稍微夸大其研究领域的重要性,以及自己在该领域的重要性。
Holding everything to the same standard is a crude version 1. We're already evolving better customs, and we can already see signs of how big the payoff will be. Notes [1] This assumption may be too conservative. There is some evidence that historically the Bay Area has attracted a _different sort of person_ than, say, New York City. [2] One of their great favorites is Theranos. But the most conspicuous feature of Theranos's cap table is the absence of Silicon Valley firms. Journalists were fooled by Theranos, but Silicon Valley investors weren't. [3] I made two mistakes about teachers when I was younger. I cared more about professors' research than their reputations as teachers, and I was also wrong about what it meant to be a good teacher. I thought it simply meant to be good at explaining things. [4] Patrick Collison points out that you can go past treating something as a hack in the sense of a prototype and onward to the sense of the word that means something closer to a practical joke:.
如果你高估了手头工作的重要性,就能抵消对初期成果过于严苛的误判。假设某件事完成了通往100分目标的20%进度,你却判断为通往200分目标的10%进度——尽管两个要素都判断错误,但对其期望值的估算却是准确的。
正如哈代所言,保持适度自信也有帮助。我注意到在许多领域,最成功的人往往带着些许过度自信。表面看这似乎不合逻辑,毕竟对自身能力有精准评估才最理想。但为何判断偏差反而成为优势?因为这种误差能抵消其他方向的判断偏差:适度自信既能抵御他人的质疑,也能对抗自我怀疑。
无知同样具有类似效果。若你对成品作品的评判标准足够宽松,那么将早期作品误判为成品也无妨。虽然这种无知难以刻意培养,但实证表明它确实是种优势,尤其对年轻人而言。
度过雄心项目初期困境的另一方法,是置身于合适的群体中——在社会逆风中创造漩涡。但仅仅聚集一味鼓励你的人并不够,你会逐渐看穿这种安慰。你需要能真正辨识丑小鸭与幼天鹅的同伴,而最擅长此道的往往是从事类似项目的人,这正是大学院系和研究实验室高效运作的原因。其实无需专门机构来聚集同道,只要有机会,志同道合者自会汇聚。但主动寻找其他创新者来加速这个过程非常值得。
> I think there may be something related to being a hack that can be powerful � the idea of making the tenuousness and implausibility _a feature_. "Yes, it's a bit ridiculous, right? I'm just trying to see how far such a naive approach can get." YC seemed to me to have this characteristic.
教师本质上是特殊类型的同行。发现早期作品的潜力并鼓励你坚持,本就是教师的职责。可惜擅长此道的教师凤毛麟角,若遇良师,务必珍惜。
对某些人而言,纯粹依靠纪律或许有效:告诫自己必须熬过初期糟糕阶段,绝不气馁。但如同许多"自我说服"的建议,这远比听上去困难。随着年龄增长,标准提高,难度会更大。不过年长者有个补偿优势:他们经历过这种阶段。
少关注现状,多关注变化速率会有所帮助。若能看见进步,就不会过分纠结当下作品的拙劣。显然进步越快,这种心态越容易保持。因此开启新项目时,投入大块时间很有好处——这又是年轻人的优势所在。
[5] Much of the advantage of switching from physical to digital media is not the software per se but that it lets you start something new with little upfront commitment. [6] John Carmack adds:
另一个常见技巧是将新作品预设为要求更低的类型:把油画当作速写开始,或将新软件视为临时方案。这样就能用更低标准评判初期成果。等项目步入正轨,再悄然升级其定位。
使用能快速呈现、前期投入少的媒介会更轻松。在笔记本上涂鸦时说服自己"这只是速写",远比雕刻石像时容易,何况还能更快看到初期成果。
若将风险项目视为学习机会而非纯粹产出,尝试起来会更轻松。即使项目彻底失败,你仍有收获。当问题定义足够明确时,失败本身就是知识:若试图证明的定理被证伪,或某尺寸结构件在压力下失效,你获得的认知虽非初衷,但仍是收获。
> The value of a medium without a vast gulf between the early work and the final work is exemplified in game mods. The original Quake game was a golden age for mods, because everything was very flexible, but so crude due to technical limitations, that quick hacks to try out a gameplay idea weren't all _that_ far from the official game. Many careers were born from that, but as the commercial game quality improved over the years, it became almost a full time job to make a successful mod that would be appreciated by the community. This was dramatically reversed with Minecraft and later Roblox, where the entire esthetic of the experience was so explicitly crude that innovative gameplay concepts became the overriding value. These "crude" game mods by single authors are now often bigger deals than massive professional teams' work.
对我特别有效的动力是好奇心。我喜欢尝试新事物只为见证结果。我们怀着这种精神创立了Y Combinator,这也是我坚持完成《Bel》的主要动力。长期使用各种Lisp方言后,我极度好奇其本质形态:若将公理化方法贯彻到底,最终会得到什么。
但需要自我博弈来避免被拙劣的初期成果打击,这事本身就很奇怪。你试图说服自己相信的其实是真相——雄心项目难看的初版确实比表面更有价值。所以终极解决方案或许是让自己真正明白这一点。
研究伟人早期经历是个方法。他们初期有何想法?第一步做了什么?这个问题有时难获准确答案,因为人们常对早期作品感到难堪而不愿公开(他们也误判了价值)。但当你能准确还原伟人迈出的第一步时,往往会发现那些步伐相当蹒跚。
或许研究足够多案例后,你能培养出评判早期作品的更好眼光。届时你将免疫他人的质疑与自我怀疑,真正看清早期作品的本质。
[7] Lisa Randall suggests that we
奇妙的是,解决"对早期作品评判过严"这个问题的方法,在于意识到我们对待它的态度本身也是早期作品。用同一标准衡量一切只是粗糙的1.0版本。我们已在进化出更好的方式,且已能窥见其巨大回报的端倪。
注释 [1] 这个假设可能过于保守。有证据表明历史上湾区吸引的人才类型与纽约等城市不同。 [2] 媒体最爱炒作案例之一是Theranos。但Theranos融资表最显著特征正是缺少硅谷机构。记者被Theranos蒙骗时,硅谷投资者并未上当。 [3] 我年轻时对教师有两大误解:更关注教授的研究而非教学声誉,且误将"好老师"简单等同于"讲解清晰"。 [4] Patrick Collison指出,你可以超越将某物视为原型的概念,转而将其视为近乎恶作剧的存在。
我认为,或许与"临时拼凑"特质相关的某种力量在于——将那种脆弱性和不合理性转化为特色。"没错,这确实有点荒谬对吧?我只是想看看这种天真的方法能走多远。"在我看来,YC(Y Combinator)就具有这种特质。
> treat new things as experiments. That way there's no such thing as failing, since you learn something no matter what. You treat it like an experiment in the sense that if it really rules something out, you give up and move on, but if there's some way to vary it to make it work better, go ahead and do that
[5] 从实体媒介转向数字媒介的大部分优势并不在于软件本身,而在于它能让你以极低的前期投入开启新事物。
[6] 约翰·卡马克补充道:
> 早期作品与最终成果间不存在巨大鸿沟的媒介价值,在游戏模组中体现得淋漓尽致。初代《雷神之锤》是模组的黄金时代,因为所有元素都具有极高灵活性,但受限于技术水平又显得粗糙,以至于测试游戏创意的临时修改与官方版本差距并不悬殊。许多人的职业生涯由此起步,但随着商业游戏质量逐年提升,制作一个受社区认可的优质模组几乎成了全职工作。这种情况在《我的世界》和后来的《Roblox》中彻底逆转——这些游戏的整体美学风格刻意保持原始感,使得创新玩法成为核心价值。如今,单人制作的"粗糙"模组往往比专业团队的大制作更具影响力。
[8] Michael Nielsen points out that the internet has made this easier, because you can see programmers' first commits, musicians' first videos, and so on. Thanks to Trevor Blackwell, John Carmack, Patrick Collison, Jessica Livingston, Michael Nielsen, and Lisa Randall for reading drafts of this.
[7] 丽莎·兰道尔建议我们:
> 把新事物当作实验。这样就不存在失败,因为无论如何你都能有所收获。将其视为实验意味着:如果确实证明某条路行不通,你就放弃并转向;但如果存在改进空间,那就继续优化。
[8] 迈克尔·尼尔森指出,互联网使这一切变得更容易,因为你能看到程序员的第一行提交代码、音乐人的早期视频等等。
致谢 感谢特雷弗·布莱克威尔、约翰·卡马克、帕特里克·科里森、杰西卡·利文斯顿、迈克尔·尼尔森和丽莎·兰道尔审阅本文草稿。
August 2020 Some politicians are proposing to introduce wealth taxes in addition to income and capital gains taxes. Let's try modeling the effects of various levels of wealth tax to see what they would mean in practice for a startup founder. Suppose you start a successful startup in your twenties, and then live for another 60 years. How much of your stock will a wealth tax consume? If the wealth tax applies to all your assets, it's easy to calculate its effect. A wealth tax of 1% means you get to keep 99% of your stock each year. After 60 years the proportion of stock you'll have left will be .99^60, or .547. So a straight 1% wealth tax means the government will over the course of your life take 45% of your stock. (Losing shares does not, obviously, mean becoming _net_ poorer unless the value per share is increasing by less than the wealth tax rate.) Here's how much stock the government would take over 60 years at various levels of wealth tax: wealth tax| government takes ---|--- 0.1%| 6% 0.5%| 26% 1.0%| 45% 2.0%| 70% 3.0%| 84% 4.0%| 91% 5.0%| 95% A wealth tax will usually have a threshold at which it starts. How much difference would a high threshold make? To model that, we need to make some assumptions about the initial value of your stock and the growth rate. Suppose your stock is initially worth $2 million, and the company's trajectory is as follows: the value of your stock grows 3x for 2 years, then 2x for 2 years, then 50% for 2 years, after which you just get a typical public company growth rate, which we'll call 8%. [1] Suppose the wealth tax threshold is $50 million. How much stock does the government take now? wealth tax| government takes ---|--- 0.1%| 5% 0.5%| 23% 1.0%| 41% 2.0%| 65% 3.0%| 79% 4.0%| 88% 5.0%| 93% It may at first seem surprising that such apparently small tax rates produce such dramatic effects.
一些政客提议在所得税和资本利得税之外开征财富税。让我们尝试模拟不同等级财富税的影响,看看它们对初创公司创始人的实际意义。
假设你在二十多岁时创立了一家成功的初创公司,之后又活了60年。财富税会消耗你多少股份?
如果财富税适用于你所有的资产,其影响很容易计算。1%的财富税意味着你每年只能保留99%的股份。60年后,你剩余的股份比例将是0.99的60次方,即0.547。因此,1%的直接财富税意味着政府将在你的一生中拿走你45%的股份。
(显然,股份的减少并不意味着净财富的减少,除非每股价值的增长低于财富税率。)
以下是不同等级财富税在60年内政府将拿走的股份比例:
财富税 | 政府拿走比例 ---|--- 0.1% | 6% 0.5% | 26% 1.0% | 45% 2.0% | 70% 3.0% | 84% 4.0% | 91% 5.0% | 95%
A 2% wealth tax with a $50 million threshold takes about two thirds of a successful founder's stock. The reason wealth taxes have such dramatic effects is that they're applied over and over to the same money. Income tax happens every year, but only to that year's income. Whereas if you live for 60 years after acquiring some asset, a wealth tax will tax that same asset 60 times. A wealth tax compounds. Note [1] In practice, eventually some of this 8% would come in the form of dividends, which are taxed as income at issue, so this model actually represents the most optimistic case for the founder..
财富税通常会有一个起征点。高起征点会带来多大差异?为了模拟这一点,我们需要对你的股份初始价值和增长率做一些假设。
假设你的股份初始价值为200万美元,公司的发展轨迹如下:股份价值在前两年增长3倍,接下来两年增长2倍,随后两年增长50%,之后以典型的上市公司增长率(我们设为8%)增长。[1] 假设财富税的起征点为5000万美元。现在政府会拿走多少股份?
财富税 | 政府拿走比例 ---|--- 0.1% | 5% 0.5% | 23% 1.0% | 41% 2.0% | 65% 3.0% | 79% 4.0% | 88% 5.0% | 93%
乍一看,如此小的税率竟能产生如此显著的效果,可能令人惊讶。2%的财富税加上5000万美元的起征点,会拿走成功创始人约三分之二的股份。
财富税之所以有如此显著的效果,是因为它们对同一笔资金反复征收。所得税每年征收,但只针对当年的收入。而如果你在获得某项资产后又活了60年,财富税将对同一项资产征收60次。财富税是复利式的。
[1] 实际上,这8%的增长最终会有一部分以股息的形式发放,股息在发放时会被作为收入征税,因此这个模型实际上代表了创始人最乐观的情况。
July 2020 | "Few people are capable of expressing with equanimity opinions which differ from the prejudices of their social environment. Most people are even incapable of forming such opinions." � Einstein
There has been a lot of talk about privilege lately. Although the concept is overused, there is something to it, and in particular to the idea that privilege makes you blind � that you can't see things that are visible to someone whose life is very different from yours. But one of the most pervasive examples of this kind of blindness is one that I haven't seen mentioned explicitly. I'm going to call it _orthodox privilege_ : The more conventional-minded someone is, the more it seems to them that it's safe for everyone to express their opinions. It's safe for _them_ to express their opinions, because the source of their opinions is whatever it's currently acceptable to believe. So it seems to them that it must be safe for everyone. They literally can't imagine a true statement that would get you in trouble. And yet at every point in history, there _were_ true things that would get you in trouble to say. Is ours the first where this isn't so? What an amazing coincidence that would be. Surely it should at least be the default assumption that our time is not unique, and that there are true things you can't say now, just as there have always been. You would think. But even in the face of such overwhelming historical evidence, most people will go with their gut on this one. In the most extreme cases, people suffering from orthodox privilege will not only deny that there's anything true that you can't say, but will accuse you of heresy merely for saying there is. Though if there's more than one heresy current in your time, these accusations will be weirdly non-deterministic: you must either be an xist or a yist. Frustrating as it is to deal with these people, it's important to realize that they're in earnest.
They're not pretending they think it's impossible for an idea to be both unorthodox and true. The world really looks that way to them. Indeed, this is a uniquely tenacious form of privilege. People can overcome the blindness induced by most forms of privilege by learning more about whatever they're not. But they can't overcome orthodox privilege just by learning more. They'd have to become more independent-minded. If that happens at all, it doesn't happen on the time scale of one conversation. It may be possible to convince some people that orthodox privilege must exist even though they can't sense it, just as one can with, say, dark matter. There may be some who could be convinced, for example, that it's very unlikely that this is the first point in history at which there's nothing true you can't say, even if they can't imagine specific examples. But in general I don't think it will work to say "check your privilege" about this type of privilege, because those in its demographic don't realize they're in it. It doesn't seem to conventional-minded people that they're conventional-minded. It just seems to them that they're right. Indeed, they tend to be particularly sure of it. Perhaps the solution is to appeal to politeness. If someone says they can hear a high-pitched noise that you can't, it's only polite to take them at their word, instead of demanding evidence that's impossible to produce, or simply denying that they hear anything. Imagine how rude that would seem. Similarly, if someone says they can think of things that are true but that cannot be said, it's only polite to take them at their word, even if you can't think of any yourself. Thanks to Sam Altman, Trevor Blackwell, Patrick Collison, Antonio Garcia-Martinez, Jessica Livingston, Robert Morris, Michael Nielsen, Geoff Ralston, Max Roser, and Harj Taggar for reading drafts of this..
2020年7月 | "很少有人能够心平气和地表达与社会环境偏见相左的观点。大多数人甚至无法形成这样的观点。" ——爱因斯坦
近来关于特权的讨论甚嚣尘上。尽管这个概念被过度使用,但其中确有真知灼见,尤其是特权使人盲目这一观点——你看不见那些生活与你迥异之人能轻易察觉的事物。 然而这种盲目性最普遍的表现形式之一,却鲜少被明确提及。我称之为_正统特权_:一个人的思维越符合主流,就越会觉得所有人都能安全表达观点。 _他们_当然能安全表达观点,因为其观点来源本就是当下公认的准则。于是他们认定所有人都该如此。这些人根本无法想象,说出真相竟会招致祸端。 但历史每个时期都存在过因言获罪的真相。难道唯独我们这个时代例外?若真如此,那该是多么惊人的巧合。 至少我们应当默认:这个时代并非特例,正如历史上每个时期那样,此刻也存在不可言说的真相。按理说本该如此。但即便面对压倒性的历史证据,多数人仍会凭直觉否认这点。 最极端情况下,正统特权者不仅否认存在不可言说的真相,更会因你提出这个概念而直接指控你散布异端邪说。不过若同时存在多种"异端",这些指控就会陷入诡异的自相矛盾:你非此即彼必属某类异端。 虽然与这些人打交道令人沮丧,但必须认识到他们是真心实意。他们并非假装不相信存在既非正统又属真实的观点——他们的世界观确实如此。 事实上,这是种尤为顽固的特权形态。人们通常能通过了解自身不具备的特权来克服认知盲区,但正统特权无法通过简单学习来破除。唯有培养独立思维才能突破桎梏——即便可能,也绝非一次谈话就能实现。 或许可以像说服人们相信暗物质存在那样,让某些人接受正统特权的客观存在。比如让他们明白:人类历史首次出现"所有真相皆可直言"的概率微乎其微——即便他们想不出具体例证。 但笼统地要求"检视你的特权"恐怕收效甚微,因为这个特权群体根本意识不到自身处境。循规蹈矩者从不觉得自己墨守成规,他们只坚信自己正确无误——且往往格外笃定。 或许解决之道在于诉诸礼节。若有人说听见你听不见的高频噪音,礼貌的做法是采信其言,而非强求对方提供无法呈现的证据,或断然否认其感受。将心比心便知后者何其无礼。同理,当某人声称知道某些不可言说的真相时,即便你毫无头绪,保持礼貌的基本修养就是相信其所言非虚。 致谢:感谢Sam Altman、Trevor Blackwell、Patrick Collison、Antonio Garcia-Martinez、Jessica Livingston、Robert Morris、Michael Nielsen、Geoff Ralston、Max Roser和Harj Taggar审阅本文草稿。
July 2020 One of the most revealing ways to classify people is by the degree and aggressiveness of their conformism. Imagine a Cartesian coordinate system whose horizontal axis runs from conventional-minded on the left to independent-minded on the right, and whose vertical axis runs from passive at the bottom to aggressive at the top. The resulting four quadrants define four types of people. Starting in the upper left and going counter-clockwise: aggressively conventional-minded, passively conventional-minded, passively independent-minded, and aggressively independent-minded. I think that you'll find all four types in most societies, and that which quadrant people fall into depends more on their own personality than the beliefs prevalent in their society. [1] Young children offer some of the best evidence for both points. Anyone who's been to primary school has seen the four types, and the fact that school rules are so arbitrary is strong evidence that which quadrant people fall into depends more on them than the rules. The kids in the upper left quadrant, the aggressively conventional-minded ones, are the tattletales. They believe not only that rules must be obeyed, but that those who disobey them must be punished. The kids in the lower left quadrant, the passively conventional-minded, are the sheep. They're careful to obey the rules, but when other kids break them, their impulse is to worry that those kids will be punished, not to ensure that they will. The kids in the lower right quadrant, the passively independent-minded, are the dreamy ones. They don't care much about rules and probably aren't 100% sure what the rules even are. And the kids in the upper right quadrant, the aggressively independent-minded, are the naughty ones. When they see a rule, their first impulse is to question it. Merely being told what to do makes them inclined to do the opposite.
对人进行分类最具启发性的方式之一,是根据他们从众的程度和激进程度。想象一个笛卡尔坐标系:横轴左侧代表传统思维,右侧代表独立思维;纵轴底部代表被动,顶部代表激进。由此形成的四个象限定义了四种类型的人。从左上角开始逆时针方向依次是:激进的传统思维者、被动的传统思维者、被动的独立思维者,以及激进的独立思维者。
我认为在大多数社会中都能找到这四种类型,而人们所处的象限更多取决于他们的个性,而非社会盛行的信仰。[1]
幼儿为这两点提供了最佳证据之一。任何上过小学的人都见过这四种类型,而学校规则如此随意的事实强有力地证明,人们所处的象限更多取决于他们自身,而非规则。
When measuring conformism, of course, you have to say with respect to what, and this changes as kids get older. For younger kids it's the rules set by adults. But as kids get older, the source of rules becomes their peers. So a pack of teenagers who all flout school rules in the same way are not independent-minded; rather the opposite. In adulthood we can recognize the four types by their distinctive calls, much as you could recognize four species of birds. The call of the aggressively conventional-minded is "Crush !" (It's rather alarming to see an exclamation point after a variable, but that's the whole problem with the aggressively conventional-minded.) The call of the passively conventional-minded is "What will the neighbors think?" The call of the passively independent-minded is "To each his own." And the call of the aggressively independent-minded is "Eppur si muove." The four types are not equally common. There are more passive people than aggressive ones, and far more conventional-minded people than independent-minded ones. So the passively conventional-minded are the largest group, and the aggressively independent-minded the smallest. Since one's quadrant depends more on one's personality than the nature of the rules, most people would occupy the same quadrant even if they'd grown up in a quite different society. Princeton professor Robert George recently wrote: > I sometimes ask students what their position on slavery would have been had they been white and living in the South before abolition. Guess what? They all would have been abolitionists! They all would have bravely spoken out against slavery, and worked tirelessly against it..
左上象限的孩子,即激进的传统思维者,是那些打小报告的人。他们不仅认为必须遵守规则,还认为违反规则的人必须受到惩罚。
左下象限的孩子,是被动的传统思维者,也就是“羊群”。他们会小心遵守规则,但当其他孩子违反规则时,他们的第一反应是担心那些孩子会受到惩罚,而不是确保惩罚被执行。
右下象限的孩子,是被动的独立思维者,是那些爱做梦的人。他们不太在乎规则,甚至可能对规则的具体内容都不完全清楚。
而右上象限的孩子,是激进的独立思维者,也就是那些淘气鬼。当他们看到一条规则时,第一反应是质疑它。仅仅被告知该做什么,就会让他们倾向于反其道而行之。
He's too polite to say so, but of course they wouldn't. And indeed, our default assumption should not merely be that his students would, on average, have behaved the same way people did at the time, but that the ones who are aggressively conventional-minded today would have been aggressively conventional-minded then too. In other words, that they'd not only not have fought against slavery, but that they'd have been among its staunchest defenders. I'm biased, I admit, but it seems to me that aggressively conventional-minded people are responsible for a disproportionate amount of the trouble in the world, and that a lot of the customs we've evolved since the Enlightenment have been designed to protect the rest of us from them. In particular, the retirement of the concept of heresy and its replacement by the principle of freely debating all sorts of different ideas, even ones that are currently considered unacceptable, without any punishment for those who try them out to see if they work. [2] Why do the independent-minded need to be protected, though? Because they have all the new ideas. To be a successful scientist, for example, it's not enough just to be right. You have to be right when everyone else is wrong. Conventional-minded people can't do that. For similar reasons, all successful startup CEOs are not merely independent-minded, but aggressively so. So it's no coincidence that societies prosper only to the extent that they have customs for keeping the conventional-minded at bay. [3] In the last few years, many of us have noticed that the customs protecting free inquiry have been weakened. Some say we're overreacting � that they haven't been weakened very much, or that they've been weakened in the service of a greater good. The latter I'll dispose of immediately. When the conventional-minded get the upper hand, they always say it's in the service of a greater good. It just happens to be a different, incompatible greater good each time.
当然,衡量从众性时必须明确“相对于什么”,而这会随着孩子年龄的增长而变化。对年幼的孩子来说,规则由成人制定;但随着年龄增长,规则的来源变成了同龄人。因此,一群以同样方式藐视校规的青少年并不具备独立思维,恰恰相反。
成年后,我们可以通过他们独特的“叫声”来识别这四种类型,就像识别四种鸟类一样。激进传统思维者的“叫声”是“打倒!”(在变量后看到感叹号相当令人不安,但这正是激进传统思维者的问题所在。)被动传统思维者的“叫声”是“邻居们会怎么想?”被动独立思维者的“叫声”是“各有所好。”而激进独立思维者的“叫声”是“但它确实在动。”(Eppur si muove)
这四种类型的分布并不均匀。被动者多于激进者,传统思维者远多于独立思维者。因此,被动传统思维者是最大的群体,而激进独立思维者是最小的。
由于一个人所处的象限更多取决于其个性而非规则的性质,即使在一个截然不同的社会中长大,大多数人仍会处于相同的象限。
As for the former worry, that the independent-minded are being oversensitive, and that free inquiry hasn't been shut down that much, you can't judge that unless you are yourself independent-minded. You can't know how much of the space of ideas is being lopped off unless you have them, and only the independent-minded have the ones at the edges. Precisely because of this, they tend to be very sensitive to changes in how freely one can explore ideas. They're the canaries in this coalmine. The conventional-minded say, as they always do, that they don't want to shut down the discussion of all ideas, just the bad ones. You'd think it would be obvious just from that sentence what a dangerous game they're playing. But I'll spell it out. There are two reasons why we need to be able to discuss even "bad" ideas. The first is that any process for deciding which ideas to ban is bound to make mistakes. All the more so because no one intelligent wants to undertake that kind of work, so it ends up being done by the stupid. And when a process makes a lot of mistakes, you need to leave a margin for error. Which in this case means you need to ban fewer ideas than you'd like to. But that's hard for the aggressively conventional-minded to do, partly because they enjoy seeing people punished, as they have since they were children, and partly because they compete with one another. Enforcers of orthodoxy can't allow a borderline idea to exist, because that gives other enforcers an opportunity to one-up them in the moral purity department, and perhaps even to turn enforcer upon them. So instead of getting the margin for error we need, we get the opposite: a race to the bottom in which any idea that seems at all bannable ends up being banned. [4] The second reason it's dangerous to ban the discussion of ideas is that ideas are more closely related than they look. Which means if you restrict the discussion of some topics, it doesn't only affect those topics.
普林斯顿大学教授罗伯特·乔治最近写道:
> 我有时会问学生,如果他们生活在废除奴隶制前的南方且是白人,会对奴隶制持什么立场。猜猜怎么着?他们都会是废奴主义者!他们都会勇敢地反对奴隶制,并不懈地为之奋斗。
他太客气了没有明说,但显然他们不会。事实上,我们的默认假设不该仅仅是他的学生平均而言会与当时的人们行为一致,更该是那些如今咄咄逼人的守旧派,放在当年也会同样咄咄逼人。换言之,他们不仅不会反抗奴隶制,反而会成为最顽固的捍卫者。
我承认我有偏见,但在我看来,世界上绝大多数麻烦都源于这些咄咄逼人的守旧派。启蒙运动后形成的许多习俗,本质上都是为了保护我们其他人免受其害——尤其是用"自由辩论所有观点"的原则取代"异端"概念,允许人们尝试甚至挑战当下被视为禁忌的思想而不受惩罚。[2]
The restrictions propagate back into any topic that yields implications in the forbidden ones. And that is not an edge case. The best ideas do exactly that: they have consequences in fields far removed from their origins. Having ideas in a world where some ideas are banned is like playing soccer on a pitch that has a minefield in one corner. You don't just play the same game you would have, but on a different shaped pitch. You play a much more subdued game even on the ground that's safe. In the past, the way the independent-minded protected themselves was to congregate in a handful of places � first in courts, and later in universities � where they could to some extent make their own rules. Places where people work with ideas tend to have customs protecting free inquiry, for the same reason wafer fabs have powerful air filters, or recording studios good sound insulation. For the last couple centuries at least, when the aggressively conventional-minded were on the rampage for whatever reason, universities were the safest places to be. That may not work this time though, due to the unfortunate fact that the latest wave of intolerance began in universities. It began in the mid 1980s, and by 2000 seemed to have died down, but it has recently flared up again with the arrival of social media. This seems, unfortunately, to have been an own goal by Silicon Valley. Though the people who run Silicon Valley are almost all independent-minded, they've handed the aggressively conventional-minded a tool such as they could only have dreamed of. On the other hand, perhaps the decline in the spirit of free inquiry within universities is as much the symptom of the departure of the independent-minded as the cause. People who would have become professors 50 years ago have other options now. Now they can become quants or start startups. You have to be independent-minded to succeed at either of those.
但为何独立思考者需要保护?因为所有新思想都源自他们。以科学家为例,仅仅正确是不够的,你必须在所有人都错误时仍能坚持真理。守旧派永远做不到这点。同理,所有成功的初创公司CEO不仅独立思考,更是 aggressively so(激进地如此)。因此社会繁荣程度与其遏制守旧派力量的习俗强度成正比,绝非偶然。[3]
近几年,许多人注意到保护自由探索的习俗正在弱化。有人说我们反应过度——认为削弱程度有限,或是为了更高利益。后者不值一驳:每当守旧派占据上风,他们永远宣称是为了更高利益,只不过每次这个"更高利益"都彼此矛盾。
至于前者——认为独立思考者过于敏感,自由探索并未严重受限——除非你本身具备独立思考能力,否则根本无从判断。你无法感知思想疆域被割让了多少,因为只有独立思考者才能触及边缘地带。正因如此,他们对思想探索的自由度变化极度敏感,就像煤矿中的金丝雀。
守旧派照例宣称:他们只想禁止"坏思想"的讨论。单是这句话就暴露了他们正在玩火。我们需要讨论"坏思想"有两个关键原因:
If these people had been professors, they'd have put up a stiffer resistance on behalf of academic freedom. So perhaps the picture of the independent-minded fleeing declining universities is too gloomy. Perhaps the universities are declining because so many have already left. [5] Though I've spent a lot of time thinking about this situation, I can't predict how it plays out. Could some universities reverse the current trend and remain places where the independent-minded want to congregate? Or will the independent-minded gradually abandon them? I worry a lot about what we might lose if that happened. But I'm hopeful long term. The independent-minded are good at protecting themselves. If existing institutions are compromised, they'll create new ones. That may require some imagination. But imagination is, after all, their specialty. Notes [1] I realize of course that if people's personalities vary in any two ways, you can use them as axes and call the resulting four quadrants personality types. So what I'm really claiming is that the axes are orthogonal and that there's significant variation in both. [2] The aggressively conventional-minded aren't responsible for all the trouble in the world. Another big source of trouble is the sort of charismatic leader who gains power by appealing to them. They become much more dangerous when such leaders emerge. [3] I never worried about writing things that offended the conventional-minded when I was running Y Combinator. If YC were a cookie company, I'd have faced a difficult moral choice. Conventional-minded people eat cookies too. But they don't start successful startups. So if I deterred them from applying to YC, the only effect was to save us work reading applications. [4] There has been progress in one area: the punishments for talking about banned ideas are less severe than in the past.
第一,任何思想审查机制都必然犯错。更糟的是,聪明人根本不愿从事这种工作,最终由愚蠢者操刀。当机制错误率极高时,就必须预留容错空间——这意味着实际禁止的思想应该比你想禁的少得多。但咄咄逼人的守旧派做不到这点,部分因为他们自幼就热衷看人受罚,部分因为他们彼此竞争。正统卫道士不能容忍任何边缘思想存在,否则就给同行留下了在道德纯洁性上攀比的机会,甚至可能反噬自身。于是我们非但没有获得必要的容错空间,反而陷入一场逐底竞赛:但凡能禁的思想终将被禁。[4]
第二,思想间的关联远比表面紧密。限制某些话题的讨论会产生涟漪效应,波及所有与之存在逻辑关联的领域。而这绝非边缘情况——最卓越的思想往往能在遥远领域引发变革。在存在思想禁区的世界思考,就像在埋着地雷的球场踢球:你不仅无法按照原定战术比赛,即使在安全区域也会畏首畏尾。
历史上,独立思考者通过聚集在特定场所自我保护——先是宫廷,后是大学——这些地方能一定程度自定规则。正如晶圆厂需要强力空气过滤器,录音室需要隔音设备,思想工作场所自然衍生出保护自由探索的习俗。至少过去两百年间,当守旧派因故肆虐时,大学始终是最安全的避风港。
但这次可能失效了——不幸的是,最新一波压制思潮恰恰发源于大学。它始于1980年代中期,2000年前后看似消退,却随着社交媒体卷土重来。这似乎是硅谷的乌龙球:尽管硅谷掌舵者几乎都是独立思考者,他们却给守旧派送上了梦寐以求的武器。
There's little danger of being killed, at least in richer countries. The aggressively conventional-minded are mostly satisfied with getting people fired. [5] Many professors are independent-minded � especially in math, the hard sciences, and engineering, where you have to be to succeed. But students are more representative of the general population, and thus mostly conventional-minded. So when professors and students are in conflict, it's not just a conflict between generations but also between different types of people. Thanks to Sam Altman, Trevor Blackwell, Nicholas Christakis, Patrick Collison, Sam Gichuru, Jessica Livingston, Patrick McKenzie, Geoff Ralston, and Harj Taggar for reading drafts of this.
German Translation | Korean Translation Serbian Translation.
但或许大学自由探索精神的衰败,与其说是原因不如说是结果。五十年前会成为教授的人,如今有了新选择——他们可以成为量化分析师或创办初创公司,这两条路都需独立思考能力。若这些人留在学界,本会为学术自由筑起更坚固的防线。因此将大学衰落归咎于独立思考者逃离可能因果倒置——或许正是因为他们大规模撤离,大学才加速沉沦。[5]
尽管长期思考这个问题,我仍无法预测结局。某些大学能否逆转趋势,继续保持对独立思考者的吸引力?抑或后者将逐渐弃之而去?若后者成真,我们将失去什么?这个念头令我忧心忡忡。
但我长期仍抱希望。独立思考者善于自我保护。当现有机构沦陷时,他们会创造新天地。这需要想象力——而恰巧,这正是他们的专长。
注释 [1] 当然,只要人群在任意两个维度存在差异,都能划分出四类人格。我真正的论点是这两个维度正交且变异显著。 [2] 守旧派并非所有麻烦的根源。另一大祸源是那些利用他们获取权力的魅力型领袖。 [3] 执掌YC时,我从不担心触怒守旧派。若YC是饼干公司,我将面临道德困境——毕竟守旧派也吃饼干。但他们从不会创办成功企业,因此吓退他们反而省去了审阅申请的麻烦。 [4] 唯一进步是:对禁忌思想的惩罚比古代温和。至少在富裕国家,鲜有生命危险,守旧派满足于让人失业。 [5] 许多教授(尤其数学、硬科学和工程领域)本就是独立思考者——这些领域必须如此才能成功。但学生更接近大众平均水平,多为守旧派。因此师生冲突不仅是代际矛盾,更是人格类型的碰撞。
April 2020 I recently saw a _video_ of TV journalists and politicians confidently saying that the coronavirus would be no worse than the flu. What struck me about it was not just how mistaken they seemed, but how daring. How could they feel safe saying such things? The answer, I realized, is that they didn't think they could get caught. They didn't realize there was any danger in making false predictions. These people constantly make false predictions, and get away with it, because the things they make predictions about either have mushy enough outcomes that they can bluster their way out of trouble, or happen so far in the future that few remember what they said. An epidemic is different. It falsifies your predictions rapidly and unequivocally. But epidemics are rare enough that these people clearly didn't realize this was even a possibility. Instead they just continued to use their ordinary m.o., which, as the epidemic has made clear, is to talk confidently about things they don't understand. An event like this is thus a uniquely powerful way of taking people's measure. As Warren Buffett said, "It's only when the tide goes out that you learn who's been swimming naked." And the tide has just gone out like never before. Now that we've seen the results, let's remember what we saw, because this is the most accurate test of credibility we're ever likely to have. I hope.
2020年4月 我最近看到一段_视频_,电视记者和政治人物信誓旦旦地宣称新冠病毒不会比流感更严重。最令我震惊的不仅是他们的荒谬论断,更是他们肆无忌惮的态度。他们怎敢如此大放厥词? 我意识到,答案在于他们认为自己不会被揭穿。这些人根本没意识到虚假预测会带来任何风险。他们常年发表错误预言却总能全身而退——要么因为预测对象的结果模糊不清,让他们能靠诡辩脱身;要么因为事件发生在遥远的未来,没几人会记得他们说过什么。 但流行病截然不同。它能迅速且毫不含糊地证伪你的预言。 然而这类危机实在罕见,这些人显然没意识到存在被当场打脸的可能。他们依然沿用惯用伎俩——正如疫情所揭示的——就是对自己不懂的事物夸夸其谈。 因此这类事件成了检验人性的绝佳试金石。正如沃伦·巴菲特所言:"只有当潮水退去,才知道谁在裸泳。"而这次退潮的力度前所未有。 既然真相已然显现,让我们牢记眼前的景象——因为这很可能是我们此生所能获得的最可信度测试。但愿如此。
February 2020 What should an essay be? Many people would say persuasive. That's what a lot of us were taught essays should be. But I think we can aim for something more ambitious: that an essay should be useful. To start with, that means it should be correct. But it's not enough merely to be correct. It's easy to make a statement correct by making it vague. That's a common flaw in academic writing, for example. If you know nothing at all about an issue, you can't go wrong by saying that the issue is a complex one, that there are many factors to be considered, that it's a mistake to take too simplistic a view of it, and so on. Though no doubt correct, such statements tell the reader nothing. Useful writing makes claims that are as strong as they can be made without becoming false. For example, it's more useful to say that Pike's Peak is near the middle of Colorado than merely somewhere in Colorado. But if I say it's in the exact middle of Colorado, I've now gone too far, because it's a bit east of the middle. Precision and correctness are like opposing forces. It's easy to satisfy one if you ignore the other. The converse of vaporous academic writing is the bold, but false, rhetoric of demagogues. Useful writing is bold, but true. It's also two other things: it tells people something important, and that at least some of them didn't already know. Telling people something they didn't know doesn't always mean surprising them. Sometimes it means telling them something they knew unconsciously but had never put into words. In fact those may be the more valuable insights, because they tend to be more fundamental. Let's put them all together. Useful writing tells people something true and important that they didn't already know, and tells them as unequivocally as possible. Notice these are all a matter of degree. For example, you can't expect an idea to be novel to everyone.
一篇文章应该是什么样的?许多人会说是要有说服力。这正是我们大多数人被教导的文章应有的样子。但我认为我们可以追求更宏大的目标:文章应当是有用的。
首先,这意味着它必须是正确的。但仅仅正确还不够。通过模糊表述来确保正确性很容易,这是学术写作中常见的缺陷。例如,如果你对某个问题一无所知,你可以说这个问题很复杂,需要考虑许多因素,过于简单化的观点是错误的,等等,这样你就不会出错。
虽然这些陈述无疑是正确的,但它们对读者毫无意义。有用的写作会提出尽可能强烈但不失真实的观点。
例如,说派克峰位于科罗拉多州中部附近,比仅仅说它在科罗拉多州某处更有用。但如果我说它正好位于科罗拉多州的正中心,那就过头了,因为它实际上稍微偏东一些。
精确性和正确性就像对立的力量。如果你忽略其中一个,就很容易满足另一个。与空洞的学术写作相反的是煽动者大胆但虚假的言辞。有用的写作既大胆又真实。
它还有另外两个特点:告诉人们一些重要的事情,并且至少是其中一些人还不知道的事情。
Any insight that you have will probably have already been had by at least one of the world's 7 billion people. But it's sufficient if an idea is novel to a lot of readers. Ditto for correctness, importance, and strength. In effect the four components are like numbers you can multiply together to get a score for usefulness. Which I realize is almost awkwardly reductive, but nonetheless true. _____ How can you ensure that the things you say are true and novel and important? Believe it or not, there is a trick for doing this. I learned it from my friend Robert Morris, who has a horror of saying anything dumb. His trick is not to say anything unless he's sure it's worth hearing. This makes it hard to get opinions out of him, but when you do, they're usually right. Translated into essay writing, what this means is that if you write a bad sentence, you don't publish it. You delete it and try again. Often you abandon whole branches of four or five paragraphs. Sometimes a whole essay. You can't ensure that every idea you have is good, but you can ensure that every one you publish is, by simply not publishing the ones that aren't. In the sciences, this is called publication bias, and is considered bad. When some hypothesis you're exploring gets inconclusive results, you're supposed to tell people about that too. But with essay writing, publication bias is the way to go. My strategy is loose, then tight. I write the first draft of an essay fast, trying out all kinds of ideas. Then I spend days rewriting it very carefully. I've never tried to count how many times I proofread essays, but I'm sure there are sentences I've read 100 times before publishing them. When I proofread an essay, there are usually passages that stick out in an annoying way, sometimes because they're clumsily written, and sometimes because I'm not sure they're true.
告诉人们他们不知道的事情并不总是意味着让他们感到惊讶。有时这意味着说出他们潜意识里知道但从未用语言表达出来的东西。事实上,这些可能是更有价值的见解,因为它们往往更根本。
让我们把这些综合起来。有用的写作告诉人们一些他们还不知道的真实且重要的事情,并尽可能明确地表达出来。
注意,这些都是程度问题。例如,你不能指望一个想法对所有人来说都是新颖的。任何你想到的见解,全球70亿人中可能至少已经有人想到过。但只要这个想法对许多读者来说是新颖的,就足够了。
正确性、重要性和强度也是如此。实际上,这四个组成部分就像可以相乘的数字,最终得出一个有用性的分数。我意识到这种说法几乎有些过于简化,但确实是事实。
如何确保你说的事情是真实、新颖且重要的?信不信由你,有一个技巧可以实现这一点。我是从我的朋友罗伯特·莫里斯那里学到的,他非常害怕说任何愚蠢的话。他的技巧是,除非他确定某件事值得一听,否则他不会说出来。这使得从他那里获取意见很困难,但一旦你得到了,这些意见通常是对的。
在文章写作中,这意味着如果你写了一个糟糕的句子,你就不要发表它。你删掉它,然后重写。通常你会放弃整段四五个段落。有时甚至是整篇文章。
The annoyance starts out unconscious, but after the tenth reading or so I'm saying "Ugh, that part" each time I hit it. They become like briars that catch your sleeve as you walk past. Usually I won't publish an essay till they're all gone � till I can read through the whole thing without the feeling of anything catching. I'll sometimes let through a sentence that seems clumsy, if I can't think of a way to rephrase it, but I will never knowingly let through one that doesn't seem correct. You never have to. If a sentence doesn't seem right, all you have to do is ask why it doesn't, and you've usually got the replacement right there in your head. This is where essayists have an advantage over journalists. You don't have a deadline. You can work for as long on an essay as you need to get it right. You don't have to publish the essay at all, if you can't get it right. Mistakes seem to lose courage in the face of an enemy with unlimited resources. Or that's what it feels like. What's really going on is that you have different expectations for yourself. You're like a parent saying to a child "we can sit here all night till you eat your vegetables." Except you're the child too. I'm not saying no mistake gets through. For example, I added condition (c) in _"A Way to Detect Bias"_ after readers pointed out that I'd omitted it. But in practice you can catch nearly all of them. There's a trick for getting importance too. It's like the trick I suggest to young founders for getting startup ideas: to make something you yourself want. You can use yourself as a proxy for the reader. The reader is not completely unlike you, so if you write about topics that seem important to you, they'll probably seem important to a significant number of readers as well. Importance has two factors. It's the number of people something matters to, times how much it matters to them.
你无法确保你想到的每一个想法都是好的,但你可以通过不发表那些不好的想法,确保你发表的每一个想法都是好的。
在科学领域,这被称为“发表偏倚”,被认为是不好的。当你探索的某个假设得出不确定的结果时,你也应该告诉人们这一点。但在文章写作中,发表偏倚是正确的做法。
我的策略是先宽松,后严格。我会快速写完文章的初稿,尝试各种想法。然后花几天时间非常仔细地重写。
我从未数过自己校对文章的次数,但我敢肯定,有些句子在发表前我已经读了100遍。当我校对一篇文章时,通常会有一些段落显得特别刺眼,有时是因为它们写得笨拙,有时是因为我不确定它们是否正确。这种不适感最初是无意识的,但在读了十遍左右后,每次读到这些地方我都会说:“唉,又是这部分。”它们就像你走过时会钩住袖子的荆棘。通常,我不会发表一篇文章,直到所有这些“荆棘”都被清除——直到我能通读全文而没有任何“钩住”的感觉。
有时,如果我想不出更好的表达方式,我会让一个看起来笨拙的句子通过,但我绝不会故意让一个看起来不正确的句子通过。你永远不必这样做。如果一个句子看起来不对,你只需要问自己为什么不对,通常你脑子里就已经有了替代方案。
这就是文章作者比记者有优势的地方。你没有截稿日期。你可以花尽可能多的时间来完善一篇文章。如果你无法把它写好,你完全可以不发表。在拥有无限资源的对手面前,错误似乎会失去勇气。或者至少感觉上是这样。实际上发生的是你对自己的期望不同了。你就像一个家长对孩子说:“我们可以整晚坐在这里,直到你吃完蔬菜。”只不过你同时也是那个孩子。
Which means of course that it's not a rectangle, but a sort of ragged comb, like a Riemann sum. The way to get novelty is to write about topics you've thought about a lot. Then you can use yourself as a proxy for the reader in this department too. Anything you notice that surprises you, who've thought about the topic a lot, will probably also surprise a significant number of readers. And here, as with correctness and importance, you can use the Morris technique to ensure that you will. If you don't learn anything from writing an essay, don't publish it. You need humility to measure novelty, because acknowledging the novelty of an idea means acknowledging your previous ignorance of it. Confidence and humility are often seen as opposites, but in this case, as in many others, confidence helps you to be humble. If you know you're an expert on some topic, you can freely admit when you learn something you didn't know, because you can be confident that most other people wouldn't know it either. The fourth component of useful writing, strength, comes from two things: thinking well, and the skillful use of qualification. These two counterbalance each other, like the accelerator and clutch in a car with a manual transmission. As you try to refine the expression of an idea, you adjust the qualification accordingly. Something you're sure of, you can state baldly with no qualification at all, as I did the four components of useful writing. Whereas points that seem dubious have to be held at arm's length with perhapses. As you refine an idea, you're pushing in the direction of less qualification. But you can rarely get it down to zero. Sometimes you don't even want to, if it's a side point and a fully refined version would be too long. Some say that qualifications weaken writing. For example, that you should never begin a sentence in an essay with "I think," because if you're saying it, then of course you think it.
我并不是说不会有错误漏网。例如,在《一种检测偏见的方法》中,我在读者指出遗漏后添加了条件(c)。但在实践中,你几乎可以抓住所有错误。
还有一个技巧可以确保重要性。这就像我给年轻创始人的建议,让他们找到创业点子:做你自己想要的东西。你可以把自己当作读者的代表。读者和你并非完全不同,所以如果你写的是对你来说重要的话题,它们对相当多的读者来说可能也很重要。
重要性有两个因素。一是它关乎多少人,二是它对这些人有多重要。当然,这意味着它不是矩形,而是一种参差不齐的梳子,就像黎曼和。
获得新颖性的方法是写你思考了很多的话题。然后你也可以把自己当作读者的代表。任何让你感到惊讶的事情——作为对这个话题思考很多的人——也可能让相当多的读者感到惊讶。在这里,就像在正确性和重要性方面一样,你可以使用莫里斯技巧来确保这一点。如果你从写作中没有学到任何东西,就不要发表它。
你需要谦逊来衡量新颖性,因为承认一个想法的新颖性意味着承认你之前对它一无所知。自信和谦逊通常被视为对立面,但在这种情况下,就像在许多其他情况下一样,自信有助于你保持谦逊。如果你知道自己是某个话题的专家,你可以自由地承认你学到了新东西,因为你可以确信大多数其他人也不知道它。
有用写作的第四个组成部分——强度,来自两件事:良好的思考和熟练地使用限定词。这两者相互平衡,就像手动挡汽车中的油门和离合器。当你试图完善一个想法的表达时,你会相应地调整限定词。对于你确信的事情,你可以毫不修饰地直接陈述,就像我对有用写作的四个组成部分所做的那样。而那些看起来可疑的观点,则可能需要用“或许”之类的词保持距离。
And it's true that "I think x" is a weaker statement than simply "x." Which is exactly why you need "I think." You need it to express your degree of certainty. But qualifications are not scalars. They're not just experimental error. There must be 50 things they can express: how broadly something applies, how you know it, how happy you are it's so, even how it could be falsified. I'm not going to try to explore the structure of qualification here. It's probably more complex than the whole topic of writing usefully. Instead I'll just give you a practical tip: Don't underestimate qualification. It's an important skill in its own right, not just a sort of tax you have to pay in order to avoid saying things that are false. So learn and use its full range. It may not be fully half of having good ideas, but it's part of having them. There's one other quality I aim for in essays: to say things as simply as possible. But I don't think this is a component of usefulness. It's more a matter of consideration for the reader. And it's a practical aid in getting things right; a mistake is more obvious when expressed in simple language. But I'll admit that the main reason I write simply is not for the reader's sake or because it helps get things right, but because it bothers me to use more or fancier words than I need to. It seems inelegant, like a program that's too long. I realize florid writing works for some people. But unless you're sure you're one of them, the best advice is to write as simply as you can. _____ I believe the formula I've given you, importance + novelty + correctness + strength, is the recipe for a good essay. But I should warn you that it's also a recipe for making people mad. The root of the problem is novelty. When you tell people something they didn't know, they don't always thank you for it. Sometimes the reason people don't know something is because they don't want to know it.
当你完善一个想法时,你是在朝着减少限定词的方向努力。但你很少能把它降到零。有时你甚至不想这样做,如果这是一个次要观点,而完全完善的版本会太长。
有人说限定词会削弱写作。例如,你不应该在文章中以“我认为”开头,因为如果你在说它,那么显然你是这么想的。确实,“我认为x”是一个比简单的“x”更弱的陈述。这正是你需要“我认为”的原因。你需要它来表达你的确定程度。
但限定词不仅仅是标量。它们不仅仅是实验误差。它们可以表达至少50种东西:某事的适用范围、你是如何知道的、你对它如此感到高兴的程度,甚至它如何可能被证伪。我不打算在这里探讨限定词的结构。它可能比整个“如何写出有用的文章”的主题更复杂。相反,我只给你一个实用的建议:不要低估限定词。它本身就是一项重要的技能,而不仅仅是为了避免说错话而必须支付的某种“税”。所以学习并充分利用它的全部范围。它可能不是拥有好想法的一半,但它是拥有好想法的一部分。
我在文章中追求的另一个品质是:尽可能简单地表达事情。但我不认为这是有用性的组成部分。这更多是对读者的考虑。而且它也是把事情做对的实际帮助;用简单的语言表达时,错误会更明显。但我承认,我写得简单的主要原因不是为了读者,也不是因为它有助于把事情做对,而是因为使用比需要更多或更花哨的词汇让我感到不舒服。这似乎不优雅,就像一个太长的程序。
我知道华丽的写作对某些人有效。但除非你确定你是其中之一,否则最好的建议是尽可能简单地写作。
我相信我给你的公式——重要性+新颖性+正确性+强度——是一篇好文章的配方。但我应该警告你,它也是让人生气的配方。
Usually because it contradicts some cherished belief. And indeed, if you're looking for novel ideas, popular but mistaken beliefs are a good place to find them. Every popular mistaken belief creates a _dead zone_ of ideas around it that are relatively unexplored because they contradict it. The strength component just makes things worse. If there's anything that annoys people more than having their cherished assumptions contradicted, it's having them flatly contradicted. Plus if you've used the Morris technique, your writing will seem quite confident. Perhaps offensively confident, to people who disagree with you. The reason you'll seem confident is that you are confident: you've cheated, by only publishing the things you're sure of. It will seem to people who try to disagree with you that you never admit you're wrong. In fact you constantly admit you're wrong. You just do it before publishing instead of after. And if your writing is as simple as possible, that just makes things worse. Brevity is the diction of command. If you watch someone delivering unwelcome news from a position of inferiority, you'll notice they tend to use lots of words, to soften the blow. Whereas to be short with someone is more or less to be rude to them. It can sometimes work to deliberately phrase statements more weakly than you mean. To put "perhaps" in front of something you're actually quite sure of. But you'll notice that when writers do this, they usually do it with a wink. I don't like to do this too much. It's cheesy to adopt an ironic tone for a whole essay. I think we just have to face the fact that elegance and curtness are two names for the same thing. You might think that if you work sufficiently hard to ensure that an essay is correct, it will be invulnerable to attack. That's sort of true. It will be invulnerable to valid attacks. But in practice that's little consolation.
问题的根源在于新颖性。当你告诉人们他们不知道的事情时,他们并不总是感谢你。有时人们不知道某件事是因为他们不想知道。通常是因为它与某些珍视的信念相矛盾。事实上,如果你在寻找新颖的想法,流行但错误的信念是一个很好的来源。每一个流行的错误信念都会在其周围创造一个思想的“死区”,因为这些思想与它相矛盾,所以相对未被探索。
强度这个组成部分只会让事情变得更糟。如果说有什么比珍视的假设被反驳更让人恼火,那就是被直截了当地反驳。
此外,如果你使用了莫里斯技巧,你的写作会显得非常自信。对于不同意你观点的人来说,这种自信可能令人不快。你显得自信的原因是你确实自信:你“作弊”了,只发表你确信的东西。对于那些试图不同意你的人来说,你似乎从不承认自己错了。事实上,你一直在承认自己错了。你只是在发表之前这样做,而不是之后。
如果你的写作尽可能简单,这只会让事情变得更糟。简洁是命令的措辞。如果你观察一个地位较低的人传达不受欢迎的消息,你会注意到他们倾向于使用大量词汇来缓和打击。而对某人简短或多或少是对他们无礼。
有时可以故意把陈述表达得比你实际意思更弱。在你实际上非常确定的事情前面加上“或许”。但你会注意到,当作家这样做时,他们通常是带着一种暗示。
我不喜欢过多地这样做。整篇文章采用讽刺的语气很俗气。我认为我们不得不面对这样一个事实:优雅和简略是同一事物的两个名称。
In fact, the strength component of useful writing will make you particularly vulnerable to misrepresentation. If you've stated an idea as strongly as you could without making it false, all anyone has to do is to exaggerate slightly what you said, and now it is false. Much of the time they're not even doing it deliberately. One of the most surprising things you'll discover, if you start writing essays, is that people who disagree with you rarely disagree with what you've actually written. Instead they make up something you said and disagree with that. For what it's worth, the countermove is to ask someone who does this to quote a specific sentence or passage you wrote that they believe is false, and explain why. I say "for what it's worth" because they never do. So although it might seem that this could get a broken discussion back on track, the truth is that it was never on track in the first place. Should you explicitly forestall likely misinterpretations? Yes, if they're misinterpretations a reasonably smart and well-intentioned person might make. In fact it's sometimes better to say something slightly misleading and then add the correction than to try to get an idea right in one shot. That can be more efficient, and can also model the way such an idea would be discovered. But I don't think you should explicitly forestall intentional misinterpretations in the body of an essay. An essay is a place to meet honest readers. You don't want to spoil your house by putting bars on the windows to protect against dishonest ones. The place to protect against intentional misinterpretations is in end-notes. But don't think you can predict them all. People are as ingenious at misrepresenting you when you say something they don't want to hear as they are at coming up with rationalizations for things they want to do but know they shouldn't.
你可能会认为,如果你足够努力地确保一篇文章是正确的,它就会无懈可击。这在某种程度上是对的。它将无懈可击于有效的攻击。但在实践中,这没什么安慰作用。
事实上,有用写作的强度部分会让你特别容易被曲解。如果你尽可能强烈地表达一个想法而不失真实,那么任何人只需要稍微夸大你说的话,它就会变成假的。
很多时候,他们甚至不是故意的。如果你开始写文章,你会发现最令人惊讶的事情之一是,那些不同意你的人很少不同意你实际写的内容。相反,他们会编造一些你说过的话,然后不同意它。
值得一提的是,应对方法是让这样做的人引用他们认为错误的你写的具体句子或段落,并解释为什么。我说“值得一提的是”是因为他们从不这样做。所以,尽管这看起来可以让偏离轨道的讨论回到正轨,但事实是它从一开始就没有在轨道上。
你应该明确地预防可能的误解吗?是的,如果这些误解是一个相当聪明且善意的人可能会犯的。事实上,有时说一些稍微误导的话然后添加修正,比试图一次性把想法表达正确更好。这可能更高效,也可以模拟这种想法被发现的方式。
但我认为你不应该在文章正文中明确预防故意的曲解。文章是与诚实读者相遇的地方。你不想通过在窗户上安装栏杆来防止不诚实的人破坏你的房子。防止故意曲解的地方是尾注。但不要以为你能预测所有的曲解。当你说出他们不想听的话时,人们在曲解你时的创造力,就像他们在为自己想做但知道不应该做的事情找理由时一样。我怀疑这是同一种技能。
I suspect it's the same skill. _____ As with most other things, the way to get better at writing essays is to practice. But how do you start? Now that we've examined the structure of useful writing, we can rephrase that question more precisely. Which constraint do you relax initially? The answer is, the first component of importance: the number of people who care about what you write. If you narrow the topic sufficiently, you can probably find something you're an expert on. Write about that to start with. If you only have ten readers who care, that's fine. You're helping them, and you're writing. Later you can expand the breadth of topics you write about. The other constraint you can relax is a little surprising: publication. Writing essays doesn't have to mean publishing them. That may seem strange now that the trend is to publish every random thought, but it worked for me. I wrote what amounted to essays in notebooks for about 15 years. I never published any of them and never expected to. I wrote them as a way of figuring things out. But when the web came along I'd had a lot of practice. Incidentally, _Steve Wozniak_ did the same thing. In high school he designed computers on paper for fun. He couldn't build them because he couldn't afford the components. But when Intel launched 4K DRAMs in 1975, he was ready. _____ How many essays are there left to write though? The answer to that question is probably the most exciting thing I've learned about essay writing. Nearly all of them are left to write. Although _the essay_ is an old form, it hasn't been assiduously cultivated. In the print era, publication was expensive, and there wasn't enough demand for essays to publish that many. You could publish essays if you were already well known for writing something else, like novels. Or you could write book reviews that you took over to express your own ideas.
与大多数其他事情一样,提高文章写作水平的方法是练习。但你如何开始?既然我们已经研究了有用写作的结构,我们可以更准确地重新表述这个问题。你最初放松哪个约束?答案是,重要性的第一个组成部分:关心你写的内容的人数。
如果你把话题范围缩得足够小,你可能会找到一些你擅长的事情。从写这些开始。如果只有十个读者关心,那也没关系。你是在帮助他们,同时你也在写作。以后你可以扩大写作话题的范围。
你可以放松的另一个约束有点令人惊讶:发表。写文章不一定意味着发表它们。现在流行的趋势是发表每一个随机的想法,这可能看起来很奇怪,但对我来说很有效。我在笔记本上写了相当于文章的东西大约15年。我从未发表过任何一篇,也从未期望发表。我写它们是为了理清思路。但当网络出现时,我已经有了很多练习。
顺便说一句,史蒂夫·沃兹尼亚克也做了同样的事情。高中时,他为了乐趣在纸上设计计算机。他无法建造它们,因为他买不起零件。但当英特尔在1975年推出4K DRAM时,他已经准备好了。
不过,还有多少文章可以写?这个问题的答案可能是我关于文章写作学到的最令人兴奋的事情。几乎所有的文章都还有待书写。
尽管文章是一种古老的形式,但它并没有被勤奋地培育。在印刷时代,出版成本高昂,而对文章的需求不足以出版那么多。如果你因为写小说等其他作品而已经出名,你可以发表文章。或者你可以写书评来表达自己的想法。但并没有一条直接成为文章作家的路径。这意味着很少有人写文章,而那些写了的文章往往局限于狭窄的主题范围。
But there was not really a direct path to becoming an essayist. Which meant few essays got written, and those that did tended to be about a narrow range of subjects. Now, thanks to the internet, there's a path. Anyone can publish essays online. You start in obscurity, perhaps, but at least you can start. You don't need anyone's permission. It sometimes happens that an area of knowledge sits quietly for years, till some change makes it explode. Cryptography did this to number theory. The internet is doing it to the essay. The exciting thing is not that there's a lot left to write, but that there's a lot left to discover. There's a certain kind of idea that's best discovered by writing essays. If most essays are still unwritten, most such ideas are still undiscovered. Notes [1] Put railings on the balconies, but don't put bars on the windows. [2] Even now I sometimes write essays that are not meant for publication. I wrote several to figure out what Y Combinator should do, and they were really helpful. Thanks to Trevor Blackwell, Daniel Gackle, Jessica Livingston, and Robert Morris for reading drafts of this.
现在,多亏了互联网,有了一条路径。任何人都可以在网上发表文章。你开始时可能默默无闻,但至少你可以开始。你不需要任何人的许可。
有时,一个知识领域会安静多年,直到某些变化让它爆发。密码学对数论就是这样做的。互联网正在对文章这样做。
令人兴奋的不是还有很多文章可以写,而是还有很多东西可以发现。有一种想法最适合通过写文章来发现。如果大多数文章还没有被写出来,那么大多数这样的想法也还没有被发现。
[1] 在阳台上安装栏杆,但不要在窗户上安装栏杆。
[2] 即使现在,我有时也会写一些不打算发表的文章。我写了几篇来弄清楚Y Combinator应该做什么,它们真的很有帮助。
感谢 特雷弗·布莱克威尔、丹尼尔·加克尔、杰西卡·利文斯顿和罗伯特·莫里斯阅读了本文的草稿。
January 2020 _(I originally intended this for startup founders, who are often surprised by the attention they get as their companies grow, but it applies equally to anyone who becomes famous.)_ If you become sufficiently famous, you'll acquire some fans who like you too much. These people are sometimes called "fanboys," and though I dislike that term, I'm going to have to use it here. We need some word for them, because this is a distinct phenomenon from someone simply liking your work. A fanboy is obsessive and uncritical. Liking you becomes part of their identity, and they create an image of you in their own head that is much better than reality. Everything you do is good, because you do it. If you do something bad, they find a way to see it as good. And their love for you is not, usually, a quiet, private one. They want everyone to know how great you are. Well, you may be thinking, I could do without this kind of obsessive fan, but I know there are all kinds of people in the world, and if this is the worst consequence of fame, that's not so bad. Unfortunately this is not the worst consequence of fame. As well as fanboys, you'll have haters. A hater is obsessive and uncritical. Disliking you becomes part of their identity, and they create an image of you in their own head that is much worse than reality. Everything you do is bad, because you do it. If you do something good, they find a way to see it as bad. And their dislike for you is not, usually, a quiet, private one. They want everyone to know how awful you are. If you're thinking of checking, I'll save you the trouble. The second and fifth paragraphs are identical except for "good" being switched to "bad" and so on. I spent years puzzling about haters. What are they, and where do they come from? Then one day it dawned on me. Haters are just fanboys with the sign switched. Note that by haters, I don't simply mean trolls.
I'm not talking about people who say bad things about you and then move on. I'm talking about the much smaller group of people for whom this becomes a kind of obsession and who do it repeatedly over a long period. Like fans, haters seem to be an automatic consequence of fame. Anyone sufficiently famous will have them. And like fans, haters are energized by the fame of whoever they hate. They hear a song by some pop singer. They don't like it much. If the singer were an obscure one, they'd just forget about it. But instead they keep hearing her name, and this seems to drive some people crazy. Everyone's always going on about this singer, but she's no good! She's a fraud! That word "fraud" is an important one. It's the spectral signature of a hater to regard the object of their hatred as a _fraud_. They can't deny their fame. Indeed, their fame is if anything exaggerated in the hater's mind. They notice every mention of the singer's name, because every mention makes them angrier. In their own minds they exaggerate both the singer's fame and her lack of talent, and the only way to reconcile those two ideas is to conclude that she has tricked everyone. What sort of people become haters? Can anyone become one? I'm not sure about this, but I've noticed some patterns. Haters are generally losers in a very specific sense: although they are occasionally talented, they have never achieved much. And indeed, anyone successful enough to have achieved significant fame would be unlikely to regard another famous person as a fraud on that account, because anyone famous knows how random fame is. But haters are not always complete losers. They are not always the proverbial guy living in his mom's basement. Many are, but some have some amount of talent. In fact I suspect that a sense of frustrated talent is what drives some people to become haters.
They're not just saying "It's unfair that so-and-so is famous," but "It's unfair that so-and-so is famous, and not me." Could a hater be cured if they achieved something impressive? My guess is that's a moot point, because they _never will_. I've been able to observe for long enough that I'm fairly confident the pattern works both ways: not only do people who do great work never become haters, haters never do great work. Although I dislike the word "fanboy," it's evocative of something important about both haters and fanboys. It implies that the fanboy is so slavishly predictable in his admiration that he's diminished as a result, that he's less than a man. Haters seem even more diminished. I can imagine being a fanboy. I can think of people whose work I admire so much that I could abase myself before them out of sheer gratitude. If P. G. Wodehouse were still alive, I could see myself being a Wodehouse fanboy. But I could not imagine being a hater. Knowing that haters are just fanboys with the sign bit flipped makes it much easier to deal with them. We don't need a separate theory of haters. We can just use existing techniques for dealing with obsessive fans. The most important of which is simply not to think much about them. If you're like most people who become famous enough to acquire haters, your initial reaction will be one of mystification. Why does this guy seem to have it in for me? Where does his obsessive energy come from, and what makes him so appallingly nasty? What did I do to set him off? Is it something I can fix? The mistake here is to think of the hater as someone you have a dispute with. When you have a dispute with someone, it's usually a good idea to try to understand why they're upset and then fix things if you can. Disputes are distracting. But it's a false analogy to think of a hater as someone you have a dispute with. It's an understandable mistake, if you've never encountered haters before.
But when you realize that you're dealing with a hater, and what a hater is, it's clear that it's a waste of time even to think about them. If you have obsessive fans, do you spend any time wondering what makes them love you so much? No, you just think "some people are kind of crazy," and that's the end of it. Since haters are equivalent to fanboys, that's the way to deal with them too. There may have been something that set them off. But it's not something that would have set off a normal person, so there's no reason to spend any time thinking about it. It's not you, it's them. Notes [1] There are of course some people who are genuine frauds. How can you distinguish between x calling y a fraud because x is a hater, and because y is a fraud? Look at neutral opinion. Actual frauds are usually pretty conspicuous. Thoughtful people are rarely taken in by them. So if there are some thoughtful people who like y, you can usually assume y is not a fraud. [2] I would make an exception for teenagers, who sometimes act in such extreme ways that they are literally not themselves. I can imagine a teenage kid being a hater and then growing out of it. But not anyone over 25. [3] I have a much worse memory for misdeeds than my wife Jessica, who is a connoisseur of character, but I don't wish it were better. Most disputes are a waste of time even if you're in the right, and it's easy to bury the hatchet with someone if you can't remember why you were mad at them. [4] A competent hater will not merely attack you individually but will try to get mobs after you. In some cases you may want to refute whatever bogus claim they made in order to do so.
But err on the side of not, because ultimately it probably won't matter. Thanks to Austen Allred, Trevor Blackwell, Patrick Collison, Christine Ford, Daniel Gackle, Jessica Livingston, Robert Morris, Elon Musk, Harj Taggar, and Peter Thiel for reading drafts of this.
Japanese Translation | Arabic Translation Polish Translation.
2020年1月 (本文原本是为初创公司创始人而写,他们常因公司发展壮大后受到的关注感到惊讶,但同样适用于任何成名之人。) 当你足够出名时,就会吸引一些过度喜爱你的粉丝。这些人有时被称为"脑残粉"——尽管我讨厌这个词,但在此不得不使用它。我们需要一个特定词汇来描述这种现象,因为这不同于单纯欣赏你作品的人。 脑残粉的特征是痴迷且不加批判。对你的喜爱成为他们身份认同的一部分,他们在脑海中塑造的形象远优于现实。你的一切行为都是好的,因为是你所为。即便你做了糟糕的事,他们也会设法将其合理化。通常,这种爱慕并非安静私密,他们渴望向全世界宣告你的伟大。 你或许会想:没有这种狂热粉丝也无妨,反正世上本就形形色色的人都有。如果这就是成名的最大代价,倒也不算太糟。 可惜这并非最糟的部分。与脑残粉相伴而来的,还有仇恨者。 仇恨者同样痴迷且不加批判。厌恶你成为他们身份认同的一部分,他们在脑海中塑造的形象远比现实恶劣。你的一切行为都是坏的,因为是你所为。即便你做了好事,他们也会设法将其污名化。通常,这种憎恶并非安静私密,他们渴望向全世界宣告你的不堪。 为免你反复核对,我直接说明:第二段与第五段除"好/坏"等词反转外完全一致。 我曾花费数年思索仇恨者现象:他们究竟是什么?从何而来?直到某天豁然开朗:仇恨者不过是符号反转的脑残粉。 请注意,我所说的仇恨者并非单纯指网络喷子。不是那些随口诋毁你后就转移目标的人,而是指极少数将仇恨发展为长期执念的群体。 如同粉丝,仇恨者似乎是名声的必然衍生品。任何足够出名的人都难逃此劫。仇恨者也像粉丝那样,因所恨之人的名声而亢奋。当他们听到某流行歌手的作品,若歌手籍籍无名,他们转头便忘;但若该歌手名声显赫,持续听到其名字就会让某些人发狂——所有人都对这徒有虚名的骗子赞不绝口! "骗子"这个关键词至关重要。仇恨者的典型特征就是将被憎恨者视为欺诈者。他们无法否认对方的名气,甚至会在脑中将其夸大。每个提及该歌手名字的瞬间都加剧他们的愤怒。通过同时夸大其名声与无能,唯一能调和这对矛盾的结论就是:此人欺骗了全世界。 什么样的人会成为仇恨者?任何人都可能吗?虽不确定,但我注意到某些模式。仇恨者通常是特定意义上的失败者:他们或许偶有才华,却从未取得实质性成就。事实上,任何足够成功获得盛名之人,不太可能因名声本身就将其他名人视为骗子——因为成名者深知名声的随机性。 但仇恨者未必全是彻头彻尾的失败者。不全是传说中蜗居母亲地下室的那种人。有些确实如此,但另一些确有一定才华。我怀疑正是这种才能未被赏识的挫败感,驱使某些人成为仇恨者。他们呐喊的不仅是"某某成名太不公平",更是"该成名的是我而非ta"。 若仇恨者取得惊人成就能被治愈吗?我想这纯属假设,因为他们永远做不到。长期观察让我确信这种模式双向成立:不仅成大事者从不会变成仇恨者,仇恨者也永远做不出伟大成就。尽管厌恶"脑残粉"这个词,但它精准捕捉到两者共性——暗示崇拜者因盲目追捧而自我矮化,丧失独立人格。 仇恨者的自我矮化更为严重。我能想象成为脑残粉:若P.G.伍德豪斯仍在世,我或许会沦为他的狂热信徒。但成为仇恨者?这完全超出我的想象。 明白仇恨者只是极性相反的脑残粉后,应对之道便清晰起来。我们无需另建理论体系,直接套用应对狂热粉丝的方法即可。 最关键的是不要过度关注。若你像多数招致仇恨的名人那样,最初会感到困惑:这人为何针对我?其执念从何而来?为何如此恶毒?我做了什么激怒他?能否补救? 误区在于将仇恨者视为纠纷对象。解决纠纷时,理解对方诉求并尝试修正确实明智。但与仇恨者的关系绝非此类。若你从未遭遇仇恨者,这种误解情有可原。一旦认清其本质,就会明白纠结于此纯属浪费时间。你会纠结狂热粉丝为何爱你吗?当然不,顶多感叹"有些人就是疯狂"便作罢。 既然仇恨者等同于脑残粉,就该以同样方式对待。或许确有导火索,但正常人都不会被其触发,何必费神深究?问题不在你,而在他们。 注释 [1] 当然存在真正的骗子。如何区分"因仇恨者心理指控他人行骗"与"对方确系骗子"?观察中立观点即可。真正的欺诈通常相当明显,明智者很少上当。若有理性之人认可y,基本可判定y非骗子。 [2] 青少年例外,他们有时行为极端到判若两人。我设想青少年可能经历仇恨者阶段而后成长蜕变。但25岁以上者绝无可能。 [3] 我对恶行的记忆力远逊于妻子杰西卡(她堪称性格鉴赏家),但我不愿改善这点。多数纠纷纵使占理也是浪费时间,若记不清愤怒缘由,和解反而更易达成。 [4] 专业的仇恨者不仅个人攻击,更会煽动群体围攻。某些情况下或需驳斥其不实指控。但宁可选择忽略,因最终多半无关紧要。 致谢:感谢奥斯汀·奥尔雷德、特雷弗·布莱克韦尔、帕特里克·科里森、克里斯汀·福特、丹尼尔·加克尔、杰西卡·利文斯顿、罗伯特·莫里斯、埃隆·马斯克、哈吉·塔加尔与彼得·蒂尔审阅本文草稿。
January 2020 When I was young, I thought old people had everything figured out. Now that I'm old, I know this isn't true. I constantly feel like a noob. It seems like I'm always talking to some startup working in a new field I know nothing about, or reading a book about a topic I don't understand well enough, or visiting some new country where I don't know how things work. It's not pleasant to feel like a noob. And the word "noob" is certainly not a compliment. And yet today I realized something encouraging about being a noob: the more of a noob you are locally, the less of a noob you are globally. For example, if you stay in your home country, you'll feel less of a noob than if you move to Farawavia, where everything works differently. And yet you'll know more if you move. So the feeling of being a noob is inversely correlated with actual ignorance. But if the feeling of being a noob is good for us, why do we dislike it? What evolutionary purpose could such an aversion serve? I think the answer is that there are two sources of feeling like a noob: being stupid, and doing something novel. Our dislike of feeling like a noob is our brain telling us "Come on, come on, figure this out." Which was the right thing to be thinking for most of human history. The life of hunter-gatherers was complex, but it didn't change as much as life does now. They didn't suddenly have to figure out what to do about cryptocurrency. So it made sense to be biased toward competence at existing problems over the discovery of new ones. It made sense for humans to dislike the feeling of being a noob, just as, in a world where food was scarce, it made sense for them to dislike the feeling of being hungry. Now that too much food is more of a problem than too little, our dislike of feeling hungry leads us astray. And I think our dislike of feeling like a noob does too.
年轻时,我以为年长者早已洞悉一切。如今自己年岁渐长,才明白事实并非如此。
我时常感觉自己是个新手。似乎总在接触陌生领域——与某个新兴行业的初创公司交谈,阅读一知半解的学科书籍,或是造访某个运作规则全然陌生的国家。
这种新手体验并不愉快。"菜鸟"一词显然不是褒奖。但今天我意识到一个令人振奋的事实:你在局部领域越是生疏,在全局层面就越发老练。
譬如固守故土时,你的不适感远低于移居法拉瓦维亚(那里一切规则迥异)。但正是通过迁移,你才真正拓展认知。因此新手感受与实际无知程度呈反比。
若新手体验有益,为何我们本能抗拒?这种厌恶感在进化层面有何意义?
我认为答案在于:新手感受有两个源头——愚钝,或探索新知。我们对此的排斥,实则是大脑在催促"快弄明白这个"。这在人类历史长河中曾是合理反应。狩猎采集生活虽复杂,但变迁速度远不及现代。他们无需突然研究加密货币对策。因此优先掌握现存问题而非探索未知,在当时是明智策略。正如食物匮乏时代,厌恶饥饿感具有生存意义。
Though it feels unpleasant, and people will sometimes ridicule you for it, the more you feel like a noob, the better.
Japanese Translation | Arabic Translation French Translation | Korean Translation Polish Translation | Chinese Translation Serbian Translation | French Translation.
December 2019 There are two distinct ways to be politically moderate: on purpose and by accident. Intentional moderates are trimmers, deliberately choosing a position mid-way between the extremes of right and left. Accidental moderates end up in the middle, on average, because they make up their own minds about each question, and the far right and far left are roughly equally wrong. You can distinguish intentional from accidental moderates by the distribution of their opinions. If the far left opinion on some matter is 0 and the far right opinion 100, an intentional moderate's opinion on every question will be near 50. Whereas an accidental moderate's opinions will be scattered over a broad range, but will, like those of the intentional moderate, average to about 50. Intentional moderates are similar to those on the far left and the far right in that their opinions are, in a sense, not their own. The defining quality of an ideologue, whether on the left or the right, is to acquire one's opinions in bulk. You don't get to pick and choose. Your opinions about taxation can be predicted from your opinions about sex. And although intentional moderates might seem to be the opposite of ideologues, their beliefs (though in their case the word "positions" might be more accurate) are also acquired in bulk. If the median opinion shifts to the right or left, the intentional moderate must shift with it. Otherwise they stop being moderate. Accidental moderates, on the other hand, not only choose their own answers, but choose their own questions. They may not care at all about questions that the left and right both think are terribly important. So you can only even measure the politics of an accidental moderate from the intersection of the questions they care about and those the left and right care about, and this can sometimes be vanishingly small.
政治温和派有两种截然不同的类型:刻意为之型与偶然形成型。刻意温和派是骑墙者,刻意选择左右极端之间的中间立场;偶然温和派则因对每个问题独立判断,而极左与极右往往同样荒谬,最终其观点平均落在中间位置。
通过观点分布可区分二者。若某议题极左立场为0分、极右为100分,刻意温和派在所有问题上的立场都接近50分;而偶然温和派的观点会广泛分散,但平均值同样约为50分。
刻意温和派与极左极右派存在共性:其观点在某种意义上并非自主形成。意识形态者(无论左右)的本质特征在于批量获取观点——你无法自主挑选,从你对性的态度就能预测你对税收的看法。尽管刻意温和派看似与意识形态者对立,但其信念(或更准确地说"立场")同样是批量获得的。若舆论中位数左右偏移,刻意温和派必须随之移动,否则就不再温和。
It is not merely a manipulative rhetorical trick to say "if you're not with us, you're against us," but often simply false. Moderates are sometimes derided as cowards, particularly by the extreme left. But while it may be accurate to call intentional moderates cowards, openly being an accidental moderate requires the most courage of all, because you get attacked from both right and left, and you don't have the comfort of being an orthodox member of a large group to sustain you. Nearly all the most impressive people I know are accidental moderates. If I knew a lot of professional athletes, or people in the entertainment business, that might be different. Being on the far left or far right doesn't affect how fast you run or how well you sing. But someone who works with ideas has to be independent-minded to do it well. Or more precisely, you have to be independent-minded about the ideas you work with. You could be mindlessly doctrinaire in your politics and still be a good mathematician. In the 20th century, a lot of very smart people were Marxists � just no one who was smart about the subjects Marxism involves. But if the ideas you use in your work intersect with the politics of your time, you have two choices: be an accidental moderate, or be mediocre. Notes [1] It's possible in theory for one side to be entirely right and the other to be entirely wrong. Indeed, ideologues must always believe this is the case. But historically it rarely has been. [2] For some reason the far right tend to ignore moderates rather than despise them as backsliders. I'm not sure why. Perhaps it means that the far right is less ideological than the far left. Or perhaps that they are more confident, or more resigned, or simply more disorganized. I just don't know. [3] Having heretical opinions doesn't mean you have to express them openly.
偶然温和派则不仅自主选择答案,还自主选择议题。他们可能完全不在意左右派都认为至关重要的问题。因此只能通过他们与左右派共同关注的议题交集来测量其政治倾向,而这个交集有时微乎其微。
"不站队就是反对"不仅是操纵话术,更常是彻底谬误。
温和派常被讥为懦夫(尤其被极左抨击),但只有刻意温和派配得上这个评价。公开成为偶然温和派需要最大勇气——你将遭受左右夹击,且无法从大群体正统成员的归属感中获得慰藉。
我认识的所有杰出人物几乎都是偶然温和派。若我认识许多职业运动员或演艺人士,情况或许不同——极左或极右立场不影响奔跑速度或歌唱水平。但从事思想工作的人必须保持独立思考才能卓越。
It may be _easier to have them_ if you don't. Thanks to Austen Allred, Trevor Blackwell, Patrick Collison, Jessica Livingston, Amjad Masad, Ryan Petersen, and Harj Taggar for reading drafts of this.
更准确地说,必须对工作涉及的观念保持独立思维。你可以在政治上盲目教条,同时仍是优秀数学家。二十世纪许多绝顶聪明者都是马克思主义者——只是没有精通马克思主义相关领域的人。但若工作理念与时代政治存在交集,你只有两种选择:成为偶然温和派,或沦为平庸之辈。
[1] 理论上可能存在一方完全正确而另一方完全错误的情况,意识形态者必然坚信如此。但历史上极少出现。 [2] 极右派往往忽视而非鄙视温和派,原因不明。或许表明极右意识形态性较弱,或更自信/更认命/更缺乏组织性。 [3] 持有异端观点不意味着必须公开表达,有时【保持沉默】反而更容易坚持己见。
感谢Austen Allred、Trevor Blackwell、Patrick Collison、Jessica Livingston、Amjad Masad、Ryan Petersen和Harj Taggar审阅本文草稿。
December 2019 I've seen the same pattern in many different fields: even though lots of people have worked hard in the field, only a small fraction of the space of possibilities has been explored, because they've all worked on similar things. Even the smartest, most imaginative people are surprisingly conservative when deciding what to work on. People who would never dream of being fashionable in any other way get sucked into working on fashionable problems. If you want to try working on unfashionable problems, one of the best places to look is in fields that people think have already been fully explored: essays, Lisp, venture funding � you may notice a pattern here. If you can find a new approach into a big but apparently played out field, the value of whatever you discover will be _multiplied_ by its enormous surface area. The best protection against getting drawn into working on the same things as everyone else may be to _genuinely love_ what you're doing. Then you'll continue to work on it even if you make the same mistake as other people and think that it's too marginal to matter.
Japanese Translation | Arabic Translation French Translation
我在许多不同领域都观察到相同的模式:尽管无数人在该领域辛勤耕耘,但由于大家都在研究相似的内容,可能性空间中只有极小部分被真正探索过。
即便最聪明、最具想象力的人在选题时也出奇地保守。那些在其他方面绝不随波逐流的人,却会不自觉地被卷入时髦问题的研究中。
若想尝试研究非热门问题,最佳切入点之一正是那些被认为已被彻底开发的领域:散文、Lisp语言、风险投资——你或许已注意到其中的规律。若能在一个庞大但看似穷尽的领域开辟新路径,你所发现的任何价值都将因其广阔的应用面而呈几何级增长。
抵御跟风研究的最佳方法,或许是真正热爱你正在从事的工作。这样即使你和其他人犯了同样的错误——认为这个课题过于边缘而无足轻重——你仍会坚持深耕下去。
December 2019 The most damaging thing you learned in school wasn't something you learned in any specific class. It was learning to get good grades. When I was in college, a particularly earnest philosophy grad student once told me that he never cared what grade he got in a class, only what he learned in it. This stuck in my mind because it was the only time I ever heard anyone say such a thing. For me, as for most students, the measurement of what I was learning completely dominated actual learning in college. I was fairly earnest; I was genuinely interested in most of the classes I took, and I worked hard. And yet I worked by far the hardest when I was studying for a test. In theory, tests are merely what their name implies: tests of what you've learned in the class. In theory you shouldn't have to prepare for a test in a class any more than you have to prepare for a blood test. In theory you learn from taking the class, from going to the lectures and doing the reading and/or assignments, and the test that comes afterward merely measures how well you learned. In practice, as almost everyone reading this will know, things are so different that hearing this explanation of how classes and tests are meant to work is like hearing the etymology of a word whose meaning has changed completely. In practice, the phrase "studying for a test" was almost redundant, because that was when one really studied. The difference between diligent and slack students was that the former studied hard for tests and the latter didn't. No one was pulling all-nighters two weeks into the semester. Even though I was a diligent student, almost all the work I did in school was aimed at getting a good grade on something. To many people, it would seem strange that the preceding sentence has a "though" in it.
你在学校学到最具破坏性的一课,并非来自任何特定课程,而是学会了如何取得好成绩。
大学时期,一位异常认真的哲学系研究生曾告诉我,他从不关心某门课的成绩,只在乎自己学到了什么。这句话令我记忆犹新,因为这是我唯一一次听到有人这么说。
对我和大多数学生而言,大学里衡量学习成果的标尺完全凌驾于真实学习之上。我算是相当认真的学生:对多数课程怀有真诚兴趣,也勤奋用功。但最拼命用功的时刻,永远是在备考期间。
理论上,考试正如其名——是对课程所学内容的检验。理论上你无需专门备考,就像体检前无需特别准备一样。理论上你通过上课、听讲、阅读和作业来学习知识,随后的考试只是衡量学习效果的标尺。
Aren't I merely stating a tautology? Isn't that what a diligent student is, a straight-A student? That's how deeply the conflation of learning with grades has infused our culture. Is it so bad if learning is conflated with grades? Yes, it is bad. And it wasn't till decades after college, when I was running Y Combinator, that I realized how bad it is. I knew of course when I was a student that studying for a test is far from identical with actual learning. At the very least, you don't retain knowledge you cram into your head the night before an exam. But the problem is worse than that. The real problem is that most tests don't come close to measuring what they're supposed to. If tests truly were tests of learning, things wouldn't be so bad. Getting good grades and learning would converge, just a little late. The problem is that nearly all tests given to students are terribly hackable. Most people who've gotten good grades know this, and know it so well they've ceased even to question it. You'll see when you realize how naive it sounds to act otherwise. Suppose you're taking a class on medieval history and the final exam is coming up. The final exam is supposed to be a test of your knowledge of medieval history, right? So if you have a couple days between now and the exam, surely the best way to spend the time, if you want to do well on the exam, is to read the best books you can find about medieval history. Then you'll know a lot about it, and do well on the exam. No, no, no, experienced students are saying to themselves. If you merely read good books on medieval history, most of the stuff you learned wouldn't be on the test. It's not good books you want to read, but the lecture notes and assigned reading in this class. And even most of that you can ignore, because you only have to worry about the sort of thing that could turn up as a test question. You're looking for sharply-defined chunks of information.
现实中——正如几乎所有读者都心知肚明的——实际情况与此大相径庭,听到这种关于考试本质的解释,就像在听某个词义已彻底改变的词源故事。"为考试复习"这个说法几乎是冗余的,因为这才是真正用功的时刻。勤奋学生与懒散学生的区别,在于前者会为考试拼命复习,后者则不会。没人会在开学两周后就熬夜苦读。
尽管我是个勤奋学生,但我在校期间几乎所有努力都指向同一个目标:在某件事上取得好成绩。
对许多人而言,前文出现"尽管"二字会显得奇怪。这难道不是同义反复吗?勤奋学生不就是全优生吗?这正是"学习等同于成绩"的观念在我们文化中根深蒂固的明证。
将学习与成绩混为一谈真有那么糟糕?是的,确实很糟。直到大学毕业数十年后,在运营Y Combinator时,我才真正意识到其危害程度。
If one of the assigned readings has an interesting digression on some subtle point, you can safely ignore that, because it's not the sort of thing that could be turned into a test question. But if the professor tells you that there were three underlying causes of the Schism of 1378, or three main consequences of the Black Death, you'd better know them. And whether they were in fact the causes or consequences is beside the point. For the purposes of this class they are. At a university there are often copies of old exams floating around, and these narrow still further what you have to learn. As well as learning what kind of questions this professor asks, you'll often get actual exam questions. Many professors re-use them. After teaching a class for 10 years, it would be hard not to, at least inadvertently. In some classes, your professor will have had some sort of political axe to grind, and if so you'll have to grind it too. The need for this varies. In classes in math or the hard sciences or engineering it's rarely necessary, but at the other end of the spectrum there are classes where you couldn't get a good grade without it. Getting a good grade in a class on x is so different from learning a lot about x that you have to choose one or the other, and you can't blame students if they choose grades. Everyone judges them by their grades � graduate programs, employers, scholarships, even their own parents. I liked learning, and I really enjoyed some of the papers and programs I wrote in college. But did I ever, after turning in a paper in some class, sit down and write another just for fun? Of course not. I had things due in other classes. If it ever came to a choice of learning or grades, I chose grades. I hadn't come to college to do badly. Anyone who cares about getting good grades has to play this game, or they'll be surpassed by those who do.
学生时代我当然知道,为考试复习与真实学习相去甚远。至少,考前突击的知识很难长久留存。但问题远比这严重——真正的问题在于,多数考试根本测不出它们宣称要测量的内容。
如果考试真能检验学习效果,情况还不至于如此糟糕。取得好成绩与真实学习虽有时差,终会趋于一致。问题在于,几乎所有学生面对的考试都存在严重漏洞。多数成绩优异者心知肚明,甚至已对此习以为常。当你意识到反其道而行之有多么天真时,就会明白这一点。
假设你正在修读中世纪史课程,期末考试临近。这场考试本应检验你对中世纪史的掌握程度,对吧?那么在考前这几天,要取得好成绩,最佳方式理应是阅读能找到的最好的中世纪史著作。这样你就能掌握大量知识,考试自然出色。
不,不,不——经验丰富的学生会在心里摇头。如果只是阅读优质的中世纪史著作,你学到的多数内容根本不会出现在考卷上。你需要研读的不是学术专著,而是本课程的讲义和指定读物。即便如此,其中大部分也可忽略——你只需关注可能转化为考题的信息点。你要寻找的是边界清晰的知识点。如果某篇指定读物对某个微妙问题展开有趣探讨,你大可跳过,因为这不可能成为考题。但若教授强调1378年教会大分裂的三个根本原因,或黑死病的三大影响,你必须牢记。至于这些是否确为原因或影响并不重要——在这门课的语境下,它们就是标准答案。
And at elite universities, that means nearly everyone, since someone who didn't care about getting good grades probably wouldn't be there in the first place. The result is that students compete to maximize the difference between learning and getting good grades. Why are tests so bad? More precisely, why are they so hackable? Any experienced programmer could answer that. How hackable is software whose author hasn't paid any attention to preventing it from being hacked? Usually it's as porous as a colander. Hackable is the default for any test imposed by an authority. The reason the tests you're given are so consistently bad � so consistently far from measuring what they're supposed to measure � is simply that the people creating them haven't made much effort to prevent them from being hacked. But you can't blame teachers if their tests are hackable. Their job is to teach, not to create unhackable tests. The real problem is grades, or more precisely, that grades have been overloaded. If grades were merely a way for teachers to tell students what they were doing right and wrong, like a coach giving advice to an athlete, students wouldn't be tempted to hack tests. But unfortunately after a certain age grades become more than advice. After a certain age, whenever you're being taught, you're usually also being judged. I've used college tests as an example, but those are actually the least hackable. All the tests most students take their whole lives are at least as bad, including, most spectacularly of all, the test that gets them into college. If getting into college were merely a matter of having the quality of one's mind measured by admissions officers the way scientists measure the mass of an object, we could tell teenage kids "learn a lot" and leave it at that. You can tell how bad college admissions are, as a test, from how unlike high school that sounds.
大学里常流传往届试题,这进一步缩小了学习范围。你不仅能摸清教授的命题风格,甚至可能遇到原题重现。许多教授会重复使用试题——连续十年讲授同一门课,想完全不重复都难,至少会无意中重复。
某些课程中,教授可能抱有某种政治立场,这时你也必须迎合。这种需求因课而异:数学、自然科学或工程类课程很少需要,但有些课程若不如此就难获高分。
在X课程取得高分与深入学习X学科差异如此之大,以至于你必须二选一。而当学生选择追求成绩时,你无法责备他们——研究生项目、雇主、奖学金甚至父母,所有人都在用成绩评判他们。
我热爱学习,大学期间某些论文和程序确实带给我快乐。但交完某门课的论文后,我可曾纯粹出于兴趣再写一篇?当然没有——其他课程的作业还在等着。当学习与成绩冲突时,我选择成绩。我来大学可不是为了表现糟糕。
In practice, the freakishly specific nature of the stuff ambitious kids have to do in high school is directly proportionate to the hackability of college admissions. The classes you don't care about that are mostly memorization, the random "extracurricular activities" you have to participate in to show you're "well-rounded," the standardized tests as artificial as chess, the "essay" you have to write that's presumably meant to hit some very specific target, but you're not told what. As well as being bad in what it does to kids, this test is also bad in the sense of being very hackable. So hackable that whole industries have grown up to hack it. This is the explicit purpose of test-prep companies and admissions counsellors, but it's also a significant part of the function of private schools. Why is this particular test so hackable? I think because of what it's measuring. Although the popular story is that the way to get into a good college is to be really smart, admissions officers at elite colleges neither are, nor claim to be, looking only for that. What are they looking for? They're looking for people who are not simply smart, but admirable in some more general sense. And how is this more general admirableness measured? The admissions officers feel it. In other words, they accept who they like. So what college admissions is a test of is whether you suit the taste of some group of people. Well, of course a test like that is going to be hackable. And because it's both very hackable and there's (thought to be) a lot at stake, it's hacked like nothing else. That's why it distorts your life so much for so long. It's no wonder high school students often feel alienated. The shape of their lives is completely artificial. But wasting your time is not the worst thing the educational system does to you. The worst thing it does is to train you that the way to win is by hacking bad tests.
任何在意成绩的人都不得不参与这场游戏,否则就会被参与者超越。在精英大学,这意味着几乎所有人——毕竟,不在乎成绩的人最初就不会来到这里。结果就是,学生们竞相扩大"真实学习"与"获取高分"之间的差距。
为何考试如此糟糕?更准确地说,为何它们如此容易被钻空子?任何有经验的程序员都能回答:如果开发者根本没考虑防漏洞措施,软件会有多脆弱?通常就像漏勺般千疮百孔。
对权威强加的测试而言,"可钻空子"是默认状态。你面对的考试之所以始终糟糕——始终远离其声称要测量的目标——根本原因在于出题者并未真正努力防止漏洞利用。
但不能因此责备教师。他们的职责是教学,而非设计无漏洞的考试。真正的问题在于成绩,或者说成绩被赋予了过多功能。如果成绩只是教师指导学生改进的工具,就像教练给运动员的建议,学生就不会想钻空子。但不幸的是,超过某个年龄后,成绩就不再只是建议——每当接受教育时,你通常也在被评判。
This is a much subtler problem that I didn't recognize until I saw it happening to other people. When I started advising startup founders at Y Combinator, especially young ones, I was puzzled by the way they always seemed to make things overcomplicated. How, they would ask, do you raise money? What's the trick for making venture capitalists want to invest in you? The best way to make VCs want to invest in you, I would explain, is to actually be a good investment. Even if you could trick VCs into investing in a bad startup, you'd be tricking yourselves too. You're investing time in the same company you're asking them to invest money in. If it's not a good investment, why are you even doing it? Oh, they'd say, and then after a pause to digest this revelation, they'd ask: What makes a startup a good investment? So I would explain that what makes a startup promising, not just in the eyes of investors but in fact, is _growth_. Ideally in revenue, but failing that in usage. What they needed to do was get lots of users. How does one get lots of users? They had all kinds of ideas about that. They needed to do a big launch that would get them "exposure." They needed influential people to talk about them. They even knew they needed to launch on a tuesday, because that's when one gets the most attention. No, I would explain, that is not how to get lots of users. The way you get lots of users is to make the product really great. Then people will not only use it but recommend it to their friends, so your growth will be exponential once you _get it started_. At this point I've told the founders something you'd think would be completely obvious: that they should make a good company by making a good product.
我以大学考试为例,但它们其实是最不易钻空子的。多数学生一生中参加的所有考试至少同样糟糕,其中最突出的莫过于大学入学考试。如果大学录取只是招生官像科学家测量物体质量那样评估心智品质,我们大可以告诉青少年"多学习"就够了。从高中生活与这种理想状态的差距,就能看出大学招生作为测试有多糟糕。现实中,雄心勃勃的高中生被迫完成的那些怪异任务,与大学招生的可钻空子程度直接相关:那些全靠死记硬背的无趣课程,为显示"全面发展"而参加的随机"课外活动",像国际象棋般人为设计的标准化考试,以及那篇必须写却不知评判标准的"申请文书"。
这套制度不仅毒害青少年,作为测试也极易被钻空子——漏洞大到催生出完整产业链。考试辅导机构和升学顾问公开以此为业,私立学校也将其作为重要职能。
为何这项测试特别容易被钻空子?我认为根源在于其测量对象。尽管流行说法是"进入好大学就要非常聪明",但精英大学的招生官既不(也无法)仅凭此筛选。他们在寻找什么?是那些不仅聪明,而且在更广泛意义上令人欣赏的人。这种"广泛意义上的优秀"如何衡量?招生官凭感觉判断——换言之,他们录取自己喜欢的人。
因此大学招生本质上测试的是:你是否符合某群人的口味。这种测试当然容易被钻空子。而由于它既极易操作又(被认为)事关重大,其被钻空子的程度无与伦比。这就是为什么它会长期严重扭曲你的人生。
And yet their reaction would be something like the reaction many physicists must have had when they first heard about the theory of relativity: a mixture of astonishment at its apparent genius, combined with a suspicion that anything so weird couldn't possibly be right. Ok, they would say, dutifully. And could you introduce us to such-and-such influential person? And remember, we want to launch on Tuesday. It would sometimes take founders years to grasp these simple lessons. And not because they were lazy or stupid. They just seemed blind to what was right in front of them. Why, I would ask myself, do they always make things so complicated? And then one day I realized this was not a rhetorical question. Why did founders tie themselves in knots doing the wrong things when the answer was right in front of them? Because that was what they'd been trained to do. Their education had taught them that the way to win was to hack the test. And without even telling them they were being trained to do this. The younger ones, the recent graduates, had never faced a non-artificial test. They thought this was just how the world worked: that the first thing you did, when facing any kind of challenge, was to figure out what the trick was for hacking the test. That's why the conversation would always start with how to raise money, because that read as the test. It came at the end of YC. It had numbers attached to it, and higher numbers seemed to be better. It must be the test. There are certainly big chunks of the world where the way to win is to hack the test. This phenomenon isn't limited to schools. And some people, either due to ideology or ignorance, claim that this is true of startups too. But it isn't. In fact, one of the most striking things about startups is the degree to which you win by simply doing good work.
高中生常感到疏离并不奇怪——他们的生活形态完全是人为设计的。
但教育体系对你所做最恶劣之事,不是浪费时间,而是训练你通过钻空子来赢得糟糕的测试。这个更隐蔽的问题,直到我看见它发生在别人身上才意识到。
在Y Combinator指导初创创始人(尤其是年轻人)时,他们总把事情过度复杂化的方式令我困惑。他们会问:如何融资?让风投愿意投资的诀窍是什么?我会解释:让风投想投资你的最佳方式,就是真正成为优质项目。即使你能骗风投投资烂项目,其实也是在骗自己——你在用时间投资自己寻求融资的公司。如果这不是好投资,你为何要做?
"哦,"他们会说,消化片刻后又问:那什么才算好项目?
There are edge cases, as there are in anything, but in general you win by getting users, and what users care about is whether the product does what they want. Why did it take me so long to understand why founders made startups overcomplicated? Because I hadn't realized explicitly that schools train us to win by hacking bad tests. And not just them, but me! I'd been trained to hack bad tests too, and hadn't realized it till decades later. I had lived as if I realized it, but without knowing why. For example, I had avoided working for big companies. But if you'd asked why, I'd have said it was because they were bogus, or bureaucratic. Or just yuck. I never understood how much of my dislike of big companies was due to the fact that you win by hacking bad tests. Similarly, the fact that the tests were unhackable was a lot of what attracted me to startups. But again, I hadn't realized that explicitly. I had in effect achieved by successive approximations something that may have a closed-form solution. I had gradually undone my training in hacking bad tests without knowing I was doing it. Could someone coming out of school banish this demon just by knowing its name, and saying begone? It seems worth trying. Merely talking explicitly about this phenomenon is likely to make things better, because much of its power comes from the fact that we take it for granted. After you've noticed it, it seems the elephant in the room, but it's a pretty well camouflaged elephant. The phenomenon is so old, and so pervasive. And it's simply the result of neglect. No one meant things to be this way. This is just what happens when you combine learning with grades, competition, and the naive assumption of unhackability. It was mind-blowing to realize that two of the things I'd puzzled about the most � the bogusness of high school, and the difficulty of getting founders to see the obvious � both had the same cause.
于是我解释:初创公司的真正价值(不仅在投资人眼中,事实上也是如此)在于增长——最好是收入增长,退而求其次是用户增长。他们需要争取大量用户。
如何获取大量用户?他们总有各种奇思妙想:需要盛大发布来获得"曝光";需要意见领袖推荐;甚至知道要在周二发布,因为那天关注度最高。
不,我会解释:这不是获取用户的方式。真正的方法是打造卓越产品。这样用户不仅会使用,还会推荐给朋友,一旦启动增长就会呈指数级上升。
至此,我已向创始人阐明了看似不言而喻的道理:要创建好公司,就该做出好产品。但他们的反应,想必如同物理学家初闻相对论:既惊叹其看似天才的洞见,又怀疑如此怪异的理论不可能正确。"好的,"他们会顺从地答应,接着问:"能引荐某位意见领袖吗?记得我们要在周二发布。"
It's rare for such a big block to slide into place so late. Usually when that happens it has implications in a lot of different areas, and this case seems no exception. For example, it suggests both that education could be done better, and how you might fix it. But it also suggests a potential answer to the question all big companies seem to have: how can we be more like a startup? I'm not going to chase down all the implications now. What I want to focus on here is what it means for individuals. To start with, it means that most ambitious kids graduating from college have something they may want to unlearn. But it also changes how you look at the world. Instead of looking at all the different kinds of work people do and thinking of them vaguely as more or less appealing, you can now ask a very specific question that will sort them in an interesting way: to what extent do you win at this kind of work by hacking bad tests? It would help if there was a way to recognize bad tests quickly. Is there a pattern here? It turns out there is. Tests can be divided into two kinds: those that are imposed by authorities, and those that aren't. Tests that aren't imposed by authorities are inherently unhackable, in the sense that no one is claiming they're tests of anything more than they actually test. A football match, for example, is simply a test of who wins, not which team is better. You can tell that from the fact that commentators sometimes say afterward that the better team won. Whereas tests imposed by authorities are usually proxies for something else. A test in a class is supposed to measure not just how well you did on that particular test, but how much you learned in the class. While tests that aren't imposed by authorities are inherently unhackable, those imposed by authorities have to be made unhackable. Usually they aren't. So as a first approximation, bad tests are roughly equivalent to tests imposed by authorities.
有时创始人需要数年才能领悟这些简单道理。并非因为他们懒惰或愚蠢——他们只是对眼前的事实视而不见。
为何他们总把事情复杂化?某天我突然意识到,这不是反问句。
为何创始人在答案显而易见时仍纠缠于错误方法?因为这是他们被训练出的思维模式。教育体系教会他们:获胜之道就是钻测试的空子。这种训练甚至是潜移默化的——年轻的应届毕业生从未面对过非人为设计的测试。他们以为世界本就如此:面对任何挑战,首先要找出钻空子的窍门。所以对话总是从"如何融资"开始,因为在他们看来这就是测试——YC孵化结束时的考核,附着可量化的数字,数字越大似乎越好。这一定是测试。
世界上确实存在许多需要通过钻空子获胜的领域,这种现象不仅限于学校。有些人出于意识形态或无知,声称初创公司也是如此。但事实并非如此。实际上,初创领域最显著的特点恰恰在于:你完全可以通过踏实工作获胜。虽然像所有领域一样存在边界案例,但通常你通过获取用户获胜,而用户只关心产品是否满足需求。
You might actually like to win by hacking bad tests. Presumably some people do. But I bet most people who find themselves doing this kind of work don't like it. They just take it for granted that this is how the world works, unless you want to drop out and be some kind of hippie artisan. I suspect many people implicitly assume that working in a field with bad tests is the price of making lots of money. But that, I can tell you, is false. It used to be true. In the mid-twentieth century, when the economy was _composed of oligopolies_, the only way to the top was by playing their game. But it's not true now. There are now ways to get rich by doing good work, and that's part of the reason people are so much more excited about getting rich than they used to be. When I was a kid, you could either become an engineer and make cool things, or make lots of money by becoming an "executive." Now you can make lots of money by making cool things. Hacking bad tests is becoming less important as the link between work and authority erodes. The erosion of that link is one of the most important trends happening now, and we see its effects in almost every kind of work people do. Startups are one of the most visible examples, but we see much the same thing in writing. Writers no longer have to submit to publishers and editors to reach readers; now they can go direct. The more I think about this question, the more optimistic I get. This seems one of those situations where we don't realize how much something was holding us back until it's eliminated. And I can foresee the whole bogus edifice crumbling. Imagine what happens as more and more people start to ask themselves if they want to win by hacking bad tests, and decide that they don't. The kinds of work where you win by hacking bad tests will be starved of talent, and the kinds where you win by doing good work will see an influx of the most ambitious people.
为何我花了这么久才明白创始人复杂化问题的原因?因为我没明确意识到:学校训练我们通过钻空子赢得糟糕测试。不仅训练了他们,也训练了我!我也被如此训练过,只是数十年后才发现。
我的生活方式仿佛已意识到这点,却不明白原因。例如我始终避免为大公司工作。若被问及原因,我会说因为它们虚伪、官僚或令人厌恶。但从没意识到,我对大公司的反感很大程度上源于其"通过钻空子获胜"的机制。
同理,测试无法被钻空子这一特质,正是吸引我投身初创领域的重要原因——但同样,我并未明确意识到这点。
我实际上通过逐步逼近的方式,达成了某种可能存在简洁解的问题:在不知不觉中,逐渐消除了"钻空子应对糟糕测试"的思维定式。刚毕业的人能否通过认知并驱除这种思维定式来摆脱它?值得尝试。
And as hacking bad tests shrinks in importance, education will evolve to stop training us to do it. Imagine what the world could look like if that happened. This is not just a lesson for individuals to unlearn, but one for society to unlearn, and we'll be amazed at the energy that's liberated when we do. Notes [1] If using tests only to measure learning sounds impossibly utopian, that is already the way things work at Lambda School. Lambda School doesn't have grades. You either graduate or you don't. The only purpose of tests is to decide at each stage of the curriculum whether you can continue to the next. So in effect the whole school is pass/fail. [2] If the final exam consisted of a long conversation with the professor, you could prepare for it by reading good books on medieval history. A lot of the hackability of tests in schools is due to the fact that the same test has to be given to large numbers of students. [3] Learning is the naive algorithm for getting good grades. [4] _Hacking_ has multiple senses. There's a narrow sense in which it means to compromise something. That's the sense in which one hacks a bad test. But there's another, more general sense, meaning to find a surprising solution to a problem, often by thinking differently about it. Hacking in this sense is a wonderful thing. And indeed, some of the hacks people use on bad tests are impressively ingenious; the problem is not so much the hacking as that, because the tests are hackable, they don't test what they're meant to. [5] The people who pick startups at Y Combinator are similar to admissions officers, except that instead of being arbitrary, their acceptance criteria are trained by a very tight feedback loop.
仅仅明确讨论这种现象就可能改善现状,因为其力量很大程度上源于我们的习以为常。一旦注意到它,就会觉得它如同房间里的大象——只是这头大象伪装得极好。这种现象如此古老而普遍,纯粹是长期放任的结果。没人刻意设计这种局面——当学习与成绩、竞争以及"测试不可被钻空子"的天真假设结合时,就会自然产生这种结果。
当我意识到两个长期困惑的问题——高中的虚伪性,以及让创始人看清简单事实的困难度——竟有相同根源时,震撼无以复加。如此重大的认知拼图在人生后期才归位实属罕见。
通常这种情况会引发多领域连锁反应,这次也不例外。例如它既暗示教育体系可以改进,也指出了改进方向;同时为所有大公司共有的疑问"如何像初创公司那样运作"提供了潜在答案。不过此刻我想聚焦于它对个人的意义。
首先,这意味着多数雄心勃勃的大学毕业生可能需要摒弃某些思维习惯。但它也改变了你观察世界的视角:面对形形色色的工作,不再模糊地判断吸引力高低,而是可以提出一个精准问题来有趣地分类——这种工作能在多大程度上通过钻空子获胜?
If you accept a bad startup or reject a good one, you will usually know it within a year or two at the latest, and often within a month. [6] I'm sure admissions officers are tired of reading applications from kids who seem to have no personality beyond being willing to seem however they're supposed to seem to get accepted. What they don't realize is that they are, in a sense, looking in a mirror. The lack of authenticity in the applicants is a reflection of the arbitrariness of the application process. A dictator might just as well complain about the lack of authenticity in the people around him. [7] By good work, I don't mean morally good, but good in the sense in which a good craftsman does good work. [8] There are borderline cases where it's hard to say which category a test falls in. For example, is raising venture capital like college admissions, or is it like selling to a customer? [9] Note that a good test is merely one that's unhackable. Good here doesn't mean morally good, but good in the sense of working well. The difference between fields with bad tests and good ones is not that the former are bad and the latter are good, but that the former are bogus and the latter aren't. But those two measures are not unrelated. As Tara Ploughman said, the path from good to evil goes through bogus. [10] People who think the recent increase in _economic inequality_ is due to changes in tax policy seem very naive to anyone with experience in startups.
如果能快速识别糟糕测试会很有帮助。是否存在识别模式?确实存在。
测试可分为两类:权威强加的与非权威强加的。后者本质上无法被钻空子,因为没人声称它们能测量超出实际测试范围的内容。例如足球比赛只检验谁获胜,而非哪支队伍更强——从赛后评论员有时说"强队获胜"就能看出这点。而权威强加的测试通常是他事物的代理变量——课堂测试本应测量的不仅是当次测试表现,还包括课程学习效果。非权威测试天然防钻空子,权威测试则需要人为设计防钻空子机制(通常并未设计)。因此粗略来说,糟糕测试≈权威强加的测试。
或许有人确实喜欢通过钻空子获胜——确实存在这种人。但我敢说多数从事这类工作的人并非出于喜爱,只是默认这就是世界运行的方式,除非你选择退出当个嬉皮士匠人。
许多人可能默认:在存在糟糕测试的领域工作是赚大钱必须付出的代价。但我可以告诉你,这是错的。过去确实如此——二十世纪中叶当经济被寡头垄断时,唯有遵守游戏规则才能登上顶峰。但如今不同了:现在完全可以通过踏实工作致富,这正是人们对致富空前热情的部分原因。我小时候,你要么成为工程师创造酷炫产品,要么成为"高管"赚大钱。如今你可以通过创造酷炫产品赚大钱。
Different people are getting rich now than used to, and they're getting much richer than mere tax savings could make them. [11] Note to tiger parents: you may think you're training your kids to win, but if you're training them to win by hacking bad tests, you are, as parents so often do, training them to fight the last war. Thanks to Austen Allred, Trevor Blackwell, Patrick Collison, Jessica Livingston, Robert Morris, and Harj Taggar for reading drafts of this.
Russian Translation | Arabic Translation Swedish Translation.
随着工作与权威之间纽带的弱化,钻空子的重要性正在降低。这种弱化是当下最重要的趋势之一,几乎在所有工作领域都能看到其影响。初创公司是最显著的例子,但写作领域同样如此——作家不再需要屈服于出版商和编辑就能触达读者,现在可以直接面对市场。
越是思考这个问题,我就越乐观。这属于那种直到枷锁解除,我们才意识到其束缚有多强的情境。我能预见整个虚伪体系土崩瓦解的景象——当越来越多人开始自问"是否想通过钻空子获胜"并选择否定答案时,依赖钻空子的领域将面临人才流失,而依靠踏实工作的领域将迎来最具雄心者的涌入。随着钻空子重要性降低,教育体系也将进化,不再训练我们这种思维。想象那将造就怎样的世界。
这不仅是个人需要摒弃的一课,更是社会需要摒弃的一课。当我们真正做到时,将被释放出的巨大能量所震撼。
注释 [1] 若"考试仅用于测量学习效果"听起来像乌托邦,这已是Lambda学校的运作方式。该校没有成绩,只有毕业与否。测试唯一目的是判断学生能否进入下一阶段,实质上是全员通过制。 [7] "踏实工作"指匠人式的专业工作,无关道德评判。 [10] 认为近期经济不平等加剧源于税收政策变化的人,在初创从业者眼中天真得可笑——如今致富的群体与过去不同,其财富规模远超税收优惠能解释的范围。 [11] 虎爸虎妈们注意:你可能以为在训练孩子获胜,但若训练的是钻空子能力,你正如多数家长那样,在训练孩子打上一场战争。
December 2019 Before I had kids, I was afraid of having kids. Up to that point I felt about kids the way the young Augustine felt about living virtuously. I'd have been sad to think I'd never have children. But did I want them now? No. If I had kids, I'd become a parent, and parents, as I'd known since I was a kid, were uncool. They were dull and responsible and had no fun. And while it's not surprising that kids would believe that, to be honest I hadn't seen much as an adult to change my mind. Whenever I'd noticed parents with kids, the kids seemed to be terrors, and the parents pathetic harried creatures, even when they prevailed. When people had babies, I congratulated them enthusiastically, because that seemed to be what one did. But I didn't feel it at all. "Better you than me," I was thinking. Now when people have babies I congratulate them enthusiastically and I mean it. Especially the first one. I feel like they just got the best gift in the world. What changed, of course, is that I had kids. Something I dreaded turned out to be wonderful. Partly, and I won't deny it, this is because of serious chemical changes that happened almost instantly when our first child was born. It was like someone flipped a switch. I suddenly felt protective not just toward our child, but toward all children. As I was driving my wife and new son home from the hospital, I approached a crosswalk full of pedestrians, and I found myself thinking "I have to be really careful of all these people. Every one of them is someone's child!" So to some extent you can't trust me when I say having kids is great. To some extent I'm like a religious cultist telling you that you'll be happy if you join the cult too � but only because joining the cult will alter your mind in a way that will make you happy to be a cult member. But not entirely. There were some things about having kids that I clearly got wrong before I had them.
For example, there was a huge amount of selection bias in my observations of parents and children. Some parents may have noticed that I wrote "Whenever I'd noticed parents with kids." Of course the times I noticed kids were when things were going wrong. I only noticed them when they made noise. And where was I when I noticed them? Ordinarily I never went to places with kids, so the only times I encountered them were in shared bottlenecks like airplanes. Which is not exactly a representative sample. Flying with a toddler is something very few parents enjoy. What I didn't notice, because they tend to be much quieter, were all the great moments parents had with kids. People don't talk about these much � the magic is hard to put into words, and all other parents know about them anyway � but one of the great things about having kids is that there are so many times when you feel there is nowhere else you'd rather be, and nothing else you'd rather be doing. You don't have to be doing anything special. You could just be going somewhere together, or putting them to bed, or pushing them on the swings at the park. But you wouldn't trade these moments for anything. One doesn't tend to associate kids with peace, but that's what you feel. You don't need to look any further than where you are right now. Before I had kids, I had moments of this kind of peace, but they were rarer. With kids it can happen several times a day. My other source of data about kids was my own childhood, and that was similarly misleading. I was pretty bad, and was always in trouble for something or other. So it seemed to me that parenthood was essentially law enforcement. I didn't realize there were good times too. I remember my mother telling me once when I was about 30 that she'd really enjoyed having me and my sister. My god, I thought, this woman is a saint.
She not only endured all the pain we subjected her to, but actually enjoyed it? Now I realize she was simply telling the truth. She said that one reason she liked having us was that we'd been interesting to talk to. That took me by surprise when I had kids. You don't just love them. They become your friends too. They're really interesting. And while I admit small children are disastrously fond of repetition (anything worth doing once is worth doing fifty times) it's often genuinely fun to play with them. That surprised me too. Playing with a 2 year old was fun when I was 2 and definitely not fun when I was 6. Why would it become fun again later? But it does. There are of course times that are pure drudgery. Or worse still, terror. Having kids is one of those intense types of experience that are hard to imagine unless you've had them. But it is not, as I implicitly believed before having kids, simply your DNA heading for the lifeboats. Some of my worries about having kids were right, though. They definitely make you less productive. I know having kids makes some people get their act together, but if your act was already together, you're going to have less time to do it in. In particular, you're going to have to work to a schedule. Kids have schedules. I'm not sure if it's because that's how kids are, or because it's the only way to integrate their lives with adults', but once you have kids, you tend to have to work on their schedule. You will have chunks of time to work. But you can't let work spill promiscuously through your whole life, like I used to before I had kids. You're going to have to work at the same time every day, whether inspiration is flowing or not, and there are going to be times when you have to stop, even if it is. I've been able to adapt to working this way. Work, like love, finds a way. If there are only certain times it can happen, it happens at those times.
So while I don't get as much done as before I had kids, I get enough done. I hate to say this, because being ambitious has always been a part of my identity, but having kids may make one less ambitious. It hurts to see that sentence written down. I squirm to avoid it. But if there weren't something real there, why would I squirm? The fact is, once you have kids, you're probably going to care more about them than you do about yourself. And attention is a zero-sum game. Only one idea at a time can be the _top idea in your mind_. Once you have kids, it will often be your kids, and that means it will less often be some project you're working on. I have some hacks for sailing close to this wind. For example, when I write essays, I think about what I'd want my kids to know. That drives me to get things right. And when I was writing _Bel_, I told my kids that once I finished it I'd take them to Africa. When you say that sort of thing to a little kid, they treat it as a promise. Which meant I had to finish or I'd be taking away their trip to Africa. Maybe if I'm really lucky such tricks could put me net ahead. But the wind is there, no question. On the other hand, what kind of wimpy ambition do you have if it won't survive having kids? Do you have so little to spare? And while having kids may be warping my present judgement, it hasn't overwritten my memory. I remember perfectly well what life was like before. Well enough to miss some things a lot, like the ability to take off for some other country at a moment's notice. That was so great. Why did I never do that? See what I did there? The fact is, most of the freedom I had before kids, I never used. I paid for it in loneliness, but I never used it. I had plenty of happy times before I had kids. But if I count up happy moments, not just potential happiness but actual happy moments, there are more after kids than before.
Now I practically have it on tap, almost any bedtime. People's experiences as parents vary a lot, and I know I've been lucky. But I think the worries I had before having kids must be pretty common, and judging by other parents' faces when they see their kids, so must the happiness that kids bring. Note [1] Adults are sophisticated enough to see 2 year olds for the fascinatingly complex characters they are, whereas to most 6 year olds, 2 year olds are just defective 6 year olds. Thanks to Trevor Blackwell, Jessica Livingston, and Robert Morris for reading drafts of this.
2019年12月 在拥有孩子之前,我曾对养育孩子充满恐惧。那时的感受就像年轻时的奥古斯丁对道德生活的态度——想到永远不会有孩子会让我悲伤,但此刻是否想要?绝不。 成为父母意味着要变成我童年印象中那种无趣的大人:沉闷、肩负责任、毫无乐趣。虽然孩子产生这种想法很正常,但成年后我的见闻并未改变这一认知。每当看到带孩子的家长,孩子们总像小恶魔,父母则显得狼狈不堪,即使他们最终掌控局面。 过去当别人喜得贵子时,我会热情祝贺——因为这是社交礼仪,但内心真实想法是:"幸好不是我"。如今我依然会热情祝贺新生儿父母,但这次真心实意,尤其是对初为父母者。他们仿佛获得了世间最珍贵的礼物。 改变源于我自己成为父亲。曾经恐惧的事情竟如此美好。 不可否认,这种转变部分源于第一个孩子出生时瞬间发生的化学变化。就像有人按下了开关,我突然对所有孩子都产生了保护欲。当开车接妻儿出院时,看到满人行横道的行人,我竟想着:"必须小心驾驶——每个路人都是别人家的孩子啊!" 所以当我说养育孩子很棒时,某种程度上你该保持怀疑。这就像邪教徒向你保证入教就会幸福——只不过是因为入教改变了你的思维方式。但我的体验并非完全失真,有些认知误区确实在亲身经历后才被纠正。 比如过去观察家长和孩子时存在严重的选择偏差。注意我的用词是"每当看到带孩子的家长"——我只会注意到失控的场面。只有在孩子吵闹时才会引起我的注意,而这些观察场景多在飞机等封闭空间,这显然不能代表常态。很少有父母会享受带幼儿乘机的过程。 那些安静的美好时刻往往被忽视。父母们很少谈论这些难以言传的魔法时刻:仅仅是共同出行、哄睡或在公园荡秋千,就会让你觉得此刻即是永恒。这种满足感难以置换。孩子竟能与宁静相关联,但这种确存在。 成为父亲前,这种宁静时刻屈指可数;现在每天都能体验多次。另一个错误认知来自我的童年记忆——总因调皮惹祸,使我误以为育儿就是执法行为,完全忽略了其中的欢乐。 三十岁时母亲曾说养育我和妹妹是段愉快经历,当时我觉得她简直是圣人。如今才明白她只是陈述事实。她说喜欢与我们交谈的时光,这点在我成为父亲后深有体会。孩子不仅是爱的对象,更会成为有趣的朋友。虽然幼儿热衷重复(值得做一次的事就值得做五十次),但陪伴玩耍确实充满乐趣——这令我惊讶,因为六岁时我觉得两岁幼童很无趣,为何成年后反而乐在其中? 当然育儿生活也有枯燥甚至恐怖的时刻。这种强烈体验难以凭空想象,但绝非我原先认为的"基因自救行为"。 部分担忧确实成真:孩子必然降低工作效率。虽然有人因此变得更高效,但对原本自律的人意味着时间紧缩。你必须适应孩子的作息表——不确定这是天性使然还是为了配合成人生活,但你的工作必须按他们的时间安排进行。 我学会了在这种模式下工作。就像爱情,工作自会找到出路。虽然产出不如从前,但已足够。不得不承认,养育孩子可能削弱野心——写下这句话令我如坐针毡,但回避正说明其真实性。事实是,孩子的优先级总会超过你自己。注意力是零和游戏,你脑海中的首要念头往往会是他们而非工作项目。 我找到些折中方法:比如写作时思考"希望孩子了解什么",这促使我更严谨;撰写《Bel》时向孩子承诺完稿后带他们去非洲——对孩子而言这就是铁誓,迫使我必须完成以免剥夺他们的期待。或许这些技巧能让我因祸得福,但影响确实存在。 反过来说,若你的野心连养育孩子都经受不住,这种抱负是否太过脆弱? 虽然现状可能影响判断,但记忆不会骗人。我清楚记得从前的生活——比如随时飞往异国的自由,那种感觉太棒了。但讽刺的是,这种自由多数时候只存在于想象,最终兑换成的是孤独。 有孩子前的快乐时光并不少,但若统计真实发生的幸福时刻,成为父亲后反而更多。现在几乎每个睡前时光都能随时提取幸福。 每个人的育儿体验各异,我承认自己幸运。但我相信那些曾经的担忧具有普遍性,而其他父母见到孩子时的神情说明,他们获得的幸福也同样真实。 注 [1] 成年人能欣赏两岁幼儿的复杂魅力,而六岁儿童往往只把他们看作有缺陷的同类。 致谢 感谢Trevor Blackwell、Jessica Livingston和Robert Morris阅读本文草稿。
November 2019 Everyone knows that to do great work you need both natural ability and determination. But there's a third ingredient that's not as well understood: an obsessive interest in a particular topic. To explain this point I need to burn my reputation with some group of people, and I'm going to choose bus ticket collectors. There are people who collect old bus tickets. Like many collectors, they have an obsessive interest in the minutiae of what they collect. They can keep track of distinctions between different types of bus tickets that would be hard for the rest of us to remember. Because we don't care enough. What's the point of spending so much time thinking about old bus tickets? Which leads us to the second feature of this kind of obsession: there is no point. A bus ticket collector's love is disinterested. They're not doing it to impress us or to make themselves rich, but for its own sake. When you look at the lives of people who've done great work, you see a consistent pattern. They often begin with a bus ticket collector's obsessive interest in something that would have seemed pointless to most of their contemporaries. One of the most striking features of Darwin's book about his voyage on the Beagle is the sheer depth of his interest in natural history. His curiosity seems infinite. Ditto for Ramanujan, sitting by the hour working out on his slate what happens to series. It's a mistake to think they were "laying the groundwork" for the discoveries they made later. There's too much intention in that metaphor. Like bus ticket collectors, they were doing it because they liked it. But there is a difference between Ramanujan and a bus ticket collector. Series matter, and bus tickets don't. If I had to put the recipe for genius into one sentence, that might be it: to have a disinterested obsession with something that matters. Aren't I forgetting about the other two ingredients? Less than you might think.
众所周知,要做出伟大的工作,既需要天赋也需要毅力。但还有第三个要素未被充分理解:对某个特定主题的痴迷兴趣。
为了说明这一点,我需要得罪某个群体,这次我选择公交车票收藏家。有些人专门收藏旧公交车票。和许多收藏家一样,他们对收藏品的细枝末节有着病态的执着。他们能分辨不同车票类型的细微差别,而这些区别对我们普通人来说可能根本记不住——因为我们不够在乎。花这么多时间研究旧车票有什么意义?
这就引出了这种痴迷的第二个特征:它本就没有意义。公交车票收藏家的热爱是无功利性的。他们这么做不是为了打动谁或发财,纯粹出于热爱本身。
An obsessive interest in a topic is both a proxy for ability and a substitute for determination. Unless you have sufficient mathematical aptitude, you won't find series interesting. And when you're obsessively interested in something, you don't need as much determination: you don't need to push yourself as hard when curiosity is pulling you. An obsessive interest will even bring you luck, to the extent anything can. Chance, as Pasteur said, favors the prepared mind, and if there's one thing an obsessed mind is, it's prepared. The disinterestedness of this kind of obsession is its most important feature. Not just because it's a filter for earnestness, but because it helps you discover new ideas. The paths that lead to new ideas tend to look unpromising. If they looked promising, other people would already have explored them. How do the people who do great work discover these paths that others overlook? The popular story is that they simply have better vision: because they're so talented, they see paths that others miss. But if you look at the way great discoveries are made, that's not what happens. Darwin didn't pay closer attention to individual species than other people because he saw that this would lead to great discoveries, and they didn't. He was just really, really interested in such things. Darwin couldn't turn it off. Neither could Ramanujan. They didn't discover the hidden paths that they did because they seemed promising, but because they couldn't help it. That's what allowed them to follow paths that someone who was merely ambitious would have ignored. What rational person would decide that the way to write great novels was to begin by spending several years creating an imaginary elvish language, like Tolkien, or visiting every household in southwestern Britain, like Trollope? No one, including Tolkien and Trollope.
观察那些做出伟大成就者的生平,你会发现一个共同模式。他们往往始于某种在同时代人看来毫无意义的痴迷,就像公交车票收藏家那样。达尔文在《小猎犬号航海记》中展现出的对自然史的狂热就令人震惊——他的好奇心似乎永无止境。拉马努金也是如此,他能连续数小时在黑板上演算级数的性质。
若认为这些人是在为日后的发现"打基础",那就错了。这种说法太过功利。和公交车票收藏家一样,他们这么做纯粹因为喜欢。
但拉马努金与公交车票收藏家存在本质区别:级数研究有意义,而车票收藏没有。
The bus ticket theory is similar to Carlyle's famous definition of genius as an infinite capacity for taking pains. But there are two differences. The bus ticket theory makes it clear that the source of this infinite capacity for taking pains is not infinite diligence, as Carlyle seems to have meant, but the sort of infinite interest that collectors have. It also adds an important qualification: an infinite capacity for taking pains about something that matters. So what matters? You can never be sure. It's precisely because no one can tell in advance which paths are promising that you can discover new ideas by working on what you're interested in. But there are some heuristics you can use to guess whether an obsession might be one that matters. For example, it's more promising if you're creating something, rather than just consuming something someone else creates. It's more promising if something you're interested in is difficult, especially if it's _more difficult for other people_ than it is for you. And the obsessions of talented people are more likely to be promising. When talented people become interested in random things, they're not truly random. But you can never be sure. In fact, here's an interesting idea that's also rather alarming if it's true: it may be that to do great work, you also have to waste a lot of time. In many different areas, reward is proportionate to risk. If that rule holds here, then the way to find paths that lead to truly great work is to be willing to expend a lot of effort on things that turn out to be every bit as unpromising as they seem. I'm not sure if this is true. On one hand, it seems surprisingly difficult to waste your time so long as you're working hard on something interesting. So much of what you do ends up being useful.
如果要用一句话概括天才的配方,那可能是:对重要事物保持无功利性的痴迷。
难道我忽略了另外两个要素?其实不然。对某个领域的痴迷既是能力的证明,也是毅力的替代品。除非具备足够的数学天赋,否则你不会觉得级数有趣。而当你对某件事物痴迷时,就不需要太多意志力——当好奇心牵引着你时,根本不需要自我鞭策。
痴迷甚至能带来好运,如果运气真的存在的话。正如巴斯德所说,机遇偏爱有准备的头脑,而痴迷者最不缺的就是准备。
But on the other hand, the rule about the relationship between risk and reward is so powerful that it seems to hold wherever risk occurs. _Newton's_ case, at least, suggests that the risk/reward rule holds here. He's famous for one particular obsession of his that turned out to be unprecedentedly fruitful: using math to describe the world. But he had two other obsessions, alchemy and theology, that seem to have been complete wastes of time. He ended up net ahead. His bet on what we now call physics paid off so well that it more than compensated for the other two. But were the other two necessary, in the sense that he had to take big risks to make such big discoveries? I don't know. Here's an even more alarming idea: might one make all bad bets? It probably happens quite often. But we don't know how often, because these people don't become famous. It's not merely that the returns from following a path are hard to predict. They change dramatically over time. 1830 was a really good time to be obsessively interested in natural history. If Darwin had been born in 1709 instead of 1809, we might never have heard of him. What can one do in the face of such uncertainty? One solution is to hedge your bets, which in this case means to follow the obviously promising paths instead of your own private obsessions. But as with any hedge, you're decreasing reward when you decrease risk. If you forgo working on what you like in order to follow some more conventionally ambitious path, you might miss something wonderful that you'd otherwise have discovered. That too must happen all the time, perhaps even more often than the genius whose bets all fail. The other solution is to let yourself be interested in lots of different things. You don't decrease your upside if you switch between equally genuine interests based on which seems to be working so far.
这种无功利性正是痴迷最重要的特征。它不仅是真诚的过滤器,更是发现新思想的助燃剂。
通往新思想的路径往往看似毫无前景。若它们看起来有希望,早就有别人探索过了。那些做出伟大工作的人如何发现被他人忽视的路径?流行的说法是他们拥有更好的眼光:因为天赋异禀,所以能看到别人错过的路。但考察伟大发现的诞生过程,事实并非如此。达尔文比其他人在物种研究上投入更多关注,并非因为他预见到这会带来伟大发现而别人没看到——他只是对这些事物怀有纯粹的热爱。
达尔文停不下来。拉马努金也是。他们发现隐秘路径不是因为那些路径看起来有希望,而是因为他们无法抗拒这种探索。正是这种特质让他们走上了野心家绝不会选择的路。
But there is a danger here too: if you work on too many different projects, you might not get deeply enough into any of them. One interesting thing about the bus ticket theory is that it may help explain why different types of people excel at different kinds of work. Interest is much more unevenly distributed than ability. If natural ability is all you need to do great work, and natural ability is evenly distributed, you have to invent elaborate theories to explain the skewed distributions we see among those who actually do great work in various fields. But it may be that much of the skew has a simpler explanation: different people are interested in different things. The bus ticket theory also explains why people are less likely to do great work after they have children. Here interest has to compete not just with external obstacles, but with another interest, and one that for most people is extremely powerful. It's harder to find time for work after you have kids, but that's the easy part. The real change is that you don't want to. But the most exciting implication of the bus ticket theory is that it suggests ways to encourage great work. If the recipe for genius is simply natural ability plus hard work, all we can do is hope we have a lot of ability, and work as hard as we can. But if interest is a critical ingredient in genius, we may be able, by cultivating interest, to cultivate genius. For example, for the very ambitious, the bus ticket theory suggests that the way to do great work is to relax a little. Instead of gritting your teeth and diligently pursuing what all your peers agree is the most promising line of research, maybe you should try doing something just for fun. And if you're stuck, that may be the vector along which to break out.
哪个理性的人会认为,写出伟大小说的方法应该像托尔金那样先花几年编造精灵语,或者像特罗洛普那样走访英国西南部每户人家?没人会这么想——包括托尔金和特罗洛普自己。
"公交车票理论"与卡莱尔对天才的著名定义——"无限忍受痛苦的能力"相似,但有两点不同。该理论明确指出,这种无限能力的源泉不是卡莱尔所指的无限勤奋,而是收藏家式的无限兴趣;同时补充了关键限定:对重要事物的无限投入。
那么什么才重要?你永远无法确定。正因为没人能预判哪些路径有前景,追随兴趣才可能发现新思想。
不过有些经验法则可供参考:创造比消费更有前景;你感兴趣的事物若具有难度(尤其对他人比你更难)更有前景;天才的痴迷领域往往更具潜力——当聪明人对随机事物产生兴趣时,这种随机性并不真正随机。
I've always liked _Hamming's_ famous double-barrelled question: what are the most important problems in your field, and why aren't you working on one of them? It's a great way to shake yourself up. But it may be overfitting a bit. It might be at least as useful to ask yourself: if you could take a year off to work on something that probably wouldn't be important but would be really interesting, what would it be? The bus ticket theory also suggests a way to avoid slowing down as you get older. Perhaps the reason people have fewer new ideas as they get older is not simply that they're losing their edge. It may also be because once you become established, you can no longer mess about with irresponsible side projects the way you could when you were young and no one cared what you did. The solution to that is obvious: remain irresponsible. It will be hard, though, because the apparently random projects you take up to stave off decline will read to outsiders as evidence of it. And you yourself won't know for sure that they're wrong. But it will at least be more fun to work on what you want. It may even be that we can cultivate a habit of intellectual bus ticket collecting in kids. The usual plan in education is to start with a broad, shallow focus, then gradually become more specialized. But I've done the opposite with my kids. I know I can count on their school to handle the broad, shallow part, so I take them deep. When they get interested in something, however random, I encourage them to go preposterously, bus ticket collectorly, deep. I don't do this because of the bus ticket theory. I do it because I want them to feel the joy of learning, and they're never going to feel that about something I'm making them learn. It has to be something they're interested in. I'm just following the path of least resistance; depth is a byproduct.
但你永远无法确定。事实上,有个有趣却令人不安的观点:要做伟大工作,可能必须浪费大量时间。
在许多领域,回报与风险成正比。若这条法则在此适用,那么发现通往伟大工作的路径,就意味着甘愿在看似毫无希望的事物上投入巨大精力。
我不确定这是否正确。一方面,只要你在认真研究感兴趣的事物,似乎很难真正浪费时间——你的多数努力终将产生价值。但另一方面,风险与回报的关系法则如此强大,似乎适用于所有风险领域。至少牛顿的案例支持这点:他以数学描述世界的痴迷带来了空前成果,但他对炼金术和神学的同等痴迷却纯属浪费时间。最终他仍是赢家——在物理学上的巨大成功足以弥补另两个领域的徒劳。但后两者是否必要?是否必须承担巨大风险才能做出重大发现?我不得而知。
But if in trying to show them the joy of learning I also end up training them to go deep, so much the better. Will it have any effect? I have no idea. But that uncertainty may be the most interesting point of all. There is so much more to learn about how to do great work. As old as human civilization feels, it's really still very young if we haven't nailed something so basic. It's exciting to think there are still discoveries to make about discovery. If that's the sort of thing you're interested in. Notes [1] There are other types of collecting that illustrate this point better than bus tickets, but they're also more popular. It seemed just as well to use an inferior example rather than offend more people by telling them their hobby doesn't matter. [2] I worried a little about using the word "disinterested," since some people mistakenly believe it means not interested. But anyone who expects to be a genius will have to know the meaning of such a basic word, so I figure they may as well start now. [3] Think how often genius must have been nipped in the bud by people being told, or telling themselves, to stop messing about and be responsible. Ramanujan's mother was a huge enabler. Imagine if she hadn't been. Imagine if his parents had made him go out and get a job instead of sitting around at home doing math. On the other hand, anyone quoting the preceding paragraph to justify not getting a job is probably mistaken. [4] 1709 Darwin is to time what the _Milanese Leonardo_ is to space. [5] "An infinite capacity for taking pains" is a paraphrase of what Carlyle wrote. What he wrote, in his _History of Frederick the Great_ , was "... it is the fruit of 'genius' (which means transcendent capacity of taking trouble, first of all)...." Since the paraphrase seems the name of the idea at this point, I kept it. Carlyle's _History_ was published in 1858.
更令人不安的是:有人可能全盘皆输吗?这或许经常发生,只是我们无从知晓——因为这些人不会青史留名。
不仅回报难以预测,其价值还会随时间剧变。1830年正是痴迷自然史的黄金时代。若达尔文生于1709年而非1809年,我们可能永远不会听说他。
面对这种不确定性该怎么办?一种对策是分散下注,即选择明显有前景的路径而非个人兴趣。但如同所有对冲策略,降低风险的同时也减少了回报。若为常规野心放弃真正热爱的事物,你可能错过本该发现的精彩。这种情况必然时常发生,或许比全盘皆输的天才更常见。
In 1785 H�rault de S�chelles quoted Buffon as saying "Le g�nie n'est qu'une plus grande aptitude � la patience." (Genius is only a greater aptitude for patience.) [6] Trollope was establishing the system of postal routes. He himself sensed the obsessiveness with which he pursued this goal. > It is amusing to watch how a passion will grow upon a man. During those two years it was the ambition of my life to cover the country with rural letter-carriers..
另一种对策是培养多元兴趣。在同等真诚的兴趣间切换不会降低上限。但这也存在危险:项目过多可能导致每个领域都钻研不足。
"公交车票理论"有趣之处在于,它或许能解释为何不同类型的人擅长不同工作。兴趣的分布比能力不均衡得多。若仅需天赋就能成就伟业,而天赋分布均匀,就必须编造复杂理论来解释各领域成就者的偏态分布。但或许答案很简单:不同人对不同事物感兴趣。
该理论也解释了为何人们在有孩子后更难做出伟大工作。这时兴趣不仅要对抗外部阻碍,还要与另一种更强大的兴趣竞争。找时间工作变难了,但真正的改变是你不再那么想工作。
Even Newton occasionally sensed the degree of his obsessiveness. After computing pi to 15 digits, he wrote in a letter to a friend:
最令人振奋的启示在于:我们可以借此培育伟大工作。若天才配方只是天赋加努力,我们只能指望自己天赋异禀并拼命工作。但若兴趣是关键要素,那么培养兴趣或许就能培养天才。
比如对野心家而言,这个理论建议稍微放松。与其咬牙追逐同行公认最有前景的研究方向,不如尝试做些纯粹有趣的事。陷入困境时,这可能是突破的方向。
我一直喜欢汉明的著名双管问题:你领域最重要的问题是什么?为何没在研究其中一个?这是自我警醒的好方法。但它可能有点过拟合。或许同样该问:如果休假一年研究可能不重要但极其有趣的事,你会选什么?
该理论还提出了避免思维僵化的方法。人们年长后缺乏新想法,或许不仅因为能力衰退,还因为成名后不能再像年轻时那样随心所欲地探索旁支——那时没人在意你做什么。
> I am ashamed to tell you to how many figures I carried these computations, having no other business at the time.
解决方法显而易见:保持"不负责任"。虽然很难——那些抵御衰退的随机项目在外人看来正是衰退的证据,连你自己都无法确定他们错了。但至少,研究心之所向更有乐趣。
我们甚至可以在孩子身上培养"智力车票收藏"的习惯。传统教育主张先广后专,我对子女却反其道而行。学校会负责广博的部分,我则带他们深入。
只要他们对某事物产生兴趣(无论多随机),我就鼓励他们像车票收藏家那样荒谬地深入。这么做不是因为这个理论,而是想让他们体验学习的快乐——被迫学习的东西永远不会带来这种感受。必须是自己感兴趣的事物。我只是顺势而为,深度是副产品。但若在展示学习乐趣的同时也培养了他们深入钻研的能力,那就更好了。
Incidentally, Ramanujan was also a compulsive calculator. As Kanigel writes in his excellent biography:
这会有效果吗?我不知道。但这种不确定性或许正是最有趣之处。关于如何成就伟业,我们还有太多要学习。人类文明看似古老,但若连如此基础的问题都未解决,其实仍很年轻。想到关于"发现"本身仍有待发现,就令人兴奋——当然,前提是你对这类事情感兴趣。
注释 [1] 有些收藏类型比车票更能说明问题,但也更主流。选用次优例子总比冒犯更多人、说他们的爱好不重要要好。 [2] 我曾犹豫是否用"disinterested"一词,因有人误以为它指"不感兴趣"。但想成为天才的人总该认识这种基础词汇。 [3] 想想有多少天才因被劝说(或自我告诫)"别不务正业"而夭折。拉马努金的母亲是重要推手。若他父母逼他外出打工而非在家研究数学呢?当然,引用这段为不找工作辩护的人可能搞错了。 [4] 1709年的达尔文,犹如空间维度上的"米兰的达芬奇"。 [5] "无限忍受痛苦的能力"是卡莱尔原意的转述。他在《腓特烈大帝史》中写道:"...这是'天才'的果实(首先意味着超越常人的吃苦能力)..."因转述已成通用表述,故沿用。卡莱尔的著作出版于1858年。1785年埃罗·德·塞谢尔引用布丰名言:"天才不过是更善于忍耐。" [6] 特罗洛普当时正在建立乡村邮递系统。他本人也察觉到自己对此的痴迷:"看着激情如何支配一个人很有趣。那两年间,让全国遍布乡村邮差成了我的人生抱负。"
牛顿偶尔也会意识到自己的痴迷程度。在将圆周率计算到小数点后15位时,他在给朋友的信中写道:
> One Ramanujan scholar, B. M. Wilson, later told how Ramanujan's research into number theory was often "preceded by a table of numerical results, carried usually to a length from which most of us would shrink."
> 我羞于告诉你我计算到了多少位数,当时实在无事可做。
值得一提的是,拉马努金也是个强迫症般的计算狂。正如卡尼格尔在其优秀传记中所写:
> 拉马努金的研究学者B·M·威尔逊后来提到,这位数学家对数论的研究往往"始于一份冗长的数值结果表,其详尽程度令我们大多数人望而却步"。
[7] Working to understand the natural world counts as creating rather than consuming. Newton tripped over this distinction when he chose to work on theology. His beliefs did not allow him to see it, but chasing down paradoxes in nature is fruitful in a way that chasing down paradoxes in sacred texts is not. [8] How much of people's propensity to become interested in a topic is inborn? My experience so far suggests the answer is: most of it. Different kids get interested in different things, and it's hard to make a child interested in something they wouldn't otherwise be. Not in a way that sticks. The most you can do on behalf of a topic is to make sure it gets a fair showing � to make it clear to them, for example, that there's more to math than the dull drills they do in school. After that it's up to the child. Thanks to Marc Andreessen, Trevor Blackwell, Patrick Collison, Kevin Lacker, Jessica Livingston, Jackie McDonough, Robert Morris, Lisa Randall, Zak Stone, and _my 7 year old_ for reading drafts of this.
Spanish Translation | Russian Translation Korean Translation | Armenian Translation
[7] 探索自然规律属于创造而非消耗行为。 牛顿研究神学时曾在这个分野失足。他的信仰蒙蔽了双眼——追寻自然界的悖论能结出硕果,而钻研经文中的矛盾却徒劳无功。
[8] 人们对某个领域产生兴趣的天性有多少是与生俱来的?我的观察表明:绝大部分都是。不同的孩子会迷恋不同事物,你很难让孩子对他们本无兴趣的东西产生持久热情。家长最多能确保某个领域得到公平展示——比如让孩子明白,数学远不止学校里那些枯燥练习。之后便取决于孩子自己了。
致谢 感谢马克·安德森、特雷弗·布莱克韦尔、帕特里克·科里森、凯文·拉克尔、杰西卡·利文斯顿、杰基·麦克多诺、罗伯特·莫里斯、丽莎·兰道尔、扎克·斯通以及我7岁的孩子阅读本文草稿。
November 2019 If you discover something new, there's a significant chance you'll be accused of some form of heresy. To discover new things, you have to work on ideas that are good but non-obvious; if an idea is obviously good, other people are probably already working on it. One common way for a good idea to be non-obvious is for it to be hidden in the shadow of some mistaken assumption that people are very attached to. But anything you discover from working on such an idea will tend to contradict the mistaken assumption that was concealing it. And you will thus get a lot of heat from people attached to the mistaken assumption. Galileo and Darwin are famous examples of this phenomenon, but it's probably always an ingredient in the resistance to new ideas. So it's particularly dangerous for an organization or society to have a culture of pouncing on heresy. When you suppress heresies, you don't just prevent people from contradicting the mistaken assumption you're trying to protect. You also suppress any idea that implies indirectly that it's false. Every cherished mistaken assumption has a dead zone of unexplored ideas around it. And the more preposterous the assumption, the bigger the dead zone it creates. There is a positive side to this phenomenon though. If you're looking for new ideas, one way to find them is by _looking for heresies_. When you look at the question this way, the depressingly large dead zones around mistaken assumptions become excitingly large mines of new ideas.
Japanese Translation | Russian Translation Simplified Chinese Translation
2019年11月 当你发现新事物时,很有可能会被指控为某种异端邪说。 要发现新事物,你必须研究那些优秀但不显而易见的想法;如果一个想法明显优秀,其他人可能已经在研究它了。一个好想法不显而易见的一个常见原因是,它隐藏在人们非常依恋的某些错误假设的阴影中。但你在研究这样的想法时发现的任何东西,往往会与隐藏它的错误假设相矛盾。因此,你会受到那些依恋错误假设的人们的猛烈抨击。伽利略和达尔文是这种现象的著名例子,但它可能始终是新思想遭遇阻力的一个因素。 因此,一个组织或社会如果有一种揪住异端不放的文化,就特别危险。当你压制异端时,你不仅阻止人们反驳你试图保护的错误假设,还会压制任何间接暗示它是错误的想法。 每一个被珍视的错误假设周围都有一个未被探索的想法的死区。假设越是荒谬,它创造的死区就越大。 不过,这种现象也有积极的一面。如果你在寻找新想法,一种方法是_寻找异端邪说_。当你从这个角度看问题时,那些围绕错误假设的、令人沮丧的巨大死区就变成了令人兴奋的新想法宝库。
September 2017 The most valuable insights are both general and surprising. F = ma for example. But general and surprising is a hard combination to achieve. That territory tends to be picked clean, precisely because those insights are so valuable. Ordinarily, the best that people can do is one without the other: either surprising without being general (e.g. gossip), or general without being surprising (e.g. platitudes). Where things get interesting is the moderately valuable insights. You get those from small additions of whichever quality was missing. The more common case is a small addition of generality: a piece of gossip that's more than just gossip, because it teaches something interesting about the world. But another less common approach is to focus on the most general ideas and see if you can find something new to say about them. Because these start out so general, you only need a small delta of novelty to produce a useful insight. A small delta of novelty is all you'll be able to get most of the time. Which means if you take this route, your ideas will seem a lot like ones that already exist. Sometimes you'll find you've merely rediscovered an idea that did already exist. But don't be discouraged. Remember the huge multiplier that kicks in when you do manage to think of something even a little new. Corollary: the more general the ideas you're talking about, the less you should worry about repeating yourself. If you write enough, it's inevitable you will. Your brain is much the same from year to year and so are the stimuli that hit it. I feel slightly bad when I find I've said something close to what I've said before, as if I were plagiarizing myself. But rationally one shouldn't. You won't say something exactly the same way the second time, and that variation increases the chance you'll get that tiny but critical delta of novelty.
最具价值的洞见往往兼具普适性与反常识性。比如F=ma。但普适又反常识的组合很难达成——正因为这类洞见如此珍贵,相关领域早被发掘殆尽。
通常人们至多只能做到其中一点:要么反常识却缺乏普适性(如八卦),要么普适却毫无新意(如陈词滥调)。
真正耐人寻味的是那些中等价值的洞见。它们诞生于对缺失特质的微量补充:更常见的是增添些许普适性——一则超越八卦本身的流言,因其揭示了世界的某个有趣面向;另一种更罕见的路径,则是聚焦最普适的概念,探寻能否赋予其新意。由于起点本身极具普适性,只需微量的创新增量就能催生有用洞见。
微量创新往往是常态。这意味着选择这条路径时,你的想法会与既有观点高度相似。有时你甚至会发现自己只是重新发现了现存理论。但别气馁——当你真的捕捉到哪怕一丝新意时,记住那个巨大的乘数效应。
And of course, ideas beget ideas. (That sounds _familiar_.) An idea with a small amount of novelty could lead to one with more. But only if you keep going. So it's doubly important not to let yourself be discouraged by people who say there's not much new about something you've discovered. "Not much new" is a real achievement when you're talking about the most general ideas. It's not true that there's nothing new under the sun. There are some domains where there's almost nothing new. But there's a big difference between nothing and almost nothing, when it's multiplied by the area under the sun. Thanks to Sam Altman, Patrick Collison, and Jessica Livingston for reading drafts of this.
推论:讨论的概念越普适,就越不必担心自我重复。持续写作必然导致观点复现。我们的大脑年复一年相差无几,接收的刺激也大抵相同。当我发现自己重复类似观点时,总隐约感到自我剽窃的愧疚,但这其实毫无必要。二次阐述绝不会完全雷同,而正是这些细微差异,可能孕育关键的新意增量。
当然,思想会催生思想(这说法似曾相识)。含有些微新意的想法可能引燃更多创新——但前提是持续探索。因此当他人指摘你的发现"缺乏新意"时,万不可因此却步。在讨论最普适的概念时,"略有新意"已是实在的成就。
"日光之下无新事"并非真理。某些领域确实鲜有创新,但当"近乎没有"乘以"日光之下的广阔天地","全无"与"近乎没有"便有天壤之别。
致谢 感谢Sam Altman、Patrick Collison和Jessica Livingston审阅本文草稿。
January 2017 Because biographies of famous scientists tend to edit out their mistakes, we underestimate the degree of risk they were willing to take. And because anything a famous scientist did that wasn't a mistake has probably now become the conventional wisdom, those choices don't seem risky either. Biographies of Newton, for example, understandably focus more on physics than alchemy or theology. The impression we get is that his unerring judgment led him straight to truths no one else had noticed. How to explain all the time he spent on alchemy and theology? Well, smart people are often kind of crazy. But maybe there is a simpler explanation. Maybe the smartness and the craziness were not as separate as we think. Physics seems to us a promising thing to work on, and alchemy and theology obvious wastes of time. But that's because we know how things turned out. In Newton's day the three problems seemed roughly equally promising. No one knew yet what the payoff would be for inventing what we now call physics; if they had, more people would have been working on it. And alchemy and theology were still then in the category Marc Andreessen would describe as "huge, if true." Newton made three bets. One of them worked. But they were all risky.
由于名人科学家的传记往往会删去他们的错误,我们低估了他们愿意承担的风险程度。而著名科学家所做的任何非错误之事,如今很可能已成为传统智慧,那些选择看起来也就不再冒险。
例如,牛顿的传记理所当然地更侧重于物理学,而非炼金术或神学。我们得到的印象是,他精准无误的判断力直接引领他发现了无人注意的真理。那么如何解释他花在炼金术和神学上的所有时间呢?嗯,聪明人往往有点疯狂。
但或许有一个更简单的解释。也许聪明与疯狂并不像我们以为的那样泾渭分明。在我们看来,物理学是值得投入的领域,而炼金术和神明显然是浪费时间。但那是因为我们已知事情的结果。在牛顿的时代,这三个领域的前景看起来大致相当。当时无人知晓发明我们现在称为物理学的领域会带来什么回报;如果知道,就会有更多人投身其中。而炼金术和神学在当时仍属于马克·安德森所说的“若成真,影响巨大”的范畴。
牛顿下了三个赌注。其中一个成功了。但它们全都充满风险。
January 2017 People who are powerful but uncharismatic will tend to be disliked. Their power makes them a target for criticism that they don't have the charisma to disarm. That was Hillary Clinton's problem. It also tends to be a problem for any CEO who is more of a builder than a schmoozer. And yet the builder-type CEO is (like Hillary) probably the best person for the job. I don't think there is any solution to this problem. It's human nature. The best we can do is to recognize that it's happening, and to understand that being a magnet for criticism is sometimes a sign not that someone is the wrong person for a job, but that they're the right one.
2017年1月 有权势但缺乏魅力的人往往容易招致厌恶。他们的权势使其成为众矢之的,却又缺乏化解批评的个人魅力。这正是希拉里·克林顿的困境所在。对于任何更擅长实干而非交际的CEO而言,这也往往是个难题。然而这类实干型CEO(如同希拉里)很可能恰恰是最适合该职位的人选。 我认为这个问题无解。此乃人性使然。我们最多只能意识到这种现象的存在,并理解招致批评有时并非意味着某人不适合某个职位,反而可能证明他们正是最合适的人选。
November 2016 If you're a California voter, there is an important proposition on your ballot this year: Proposition 62, which bans the death penalty. When I was younger I used to think the debate about the death penalty was about when it's ok to take a human life. Is it ok to kill a killer? But that is not the issue here. The real world does not work like the version I was shown on TV growing up. The police often arrest the wrong person. Defendants' lawyers are often incompetent. And prosecutors are often motivated more by publicity than justice. In the real world, about 4% of people sentenced to death are innocent. So this is not about whether it's ok to kill killers. This is about whether it's ok to kill innocent people. A child could answer that one for you. This year, in California, you have a chance to end this, by voting yes on Proposition 62. But beware, because there is another proposition, Proposition 66, whose goal is to make it easier to execute people. So yes on 62, no on 66. It's time.
如果你是加利福尼亚州的选民,今年你的选票上有一项重要的提案:第62号提案,该提案旨在废除死刑。
年轻时,我曾以为关于死刑的争论是关于何时可以结束一个人的生命。杀死一个杀人犯可以吗?
现实世界并不像我成长过程中在电视上看到的那样。警察常常抓错人,被告的律师往往能力不足,而检察官的动机更多是追求曝光度而非正义。
在现实世界中,约4%被判处死刑的人是无辜的。因此,这不是关于是否可以杀死杀人犯的问题,而是关于是否可以杀死无辜者的问题。
连孩子都能回答这个问题。
今年,在加利福尼亚州,你有机会通过投票支持第62号提案来终结这一切。但要注意,还有另一项提案——第66号提案,其目的是让处决变得更加容易。所以,请支持62号,反对66号。
April 2016 _(This is a talk I gave at an event called Opt412 in Pittsburgh. Much of it will apply to other towns. But not all, because as I say in the talk, Pittsburgh has some important advantages over most would-be startup hubs.)_ What would it take to make Pittsburgh into a startup hub, like Silicon Valley? I understand Pittsburgh pretty well, because I grew up here, in Monroeville. And I understand Silicon Valley pretty well because that's where I live now. Could you get that kind of startup ecosystem going here? When I agreed to speak here, I didn't think I'd be able to give a very optimistic talk. I thought I'd be talking about what Pittsburgh could do to become a startup hub, very much in the subjunctive. Instead I'm going to talk about what Pittsburgh can do. What changed my mind was an article I read in, of all places, the _New York Times_ food section. The title was " _Pittsburgh's Youth-Driven Food Boom_." To most people that might not even sound interesting, let alone something related to startups. But it was electrifying to me to read that title. I don't think I could pick a more promising one if I tried. And when I read the article I got even more excited. It said "people ages 25 to 29 now make up 7.6 percent of all residents, up from 7 percent about a decade ago." Wow, I thought, Pittsburgh could be the next Portland. It could become the cool place all the people in their twenties want to go live. When I got here a couple days ago, I could feel the difference. I lived here from 1968 to 1984. I didn't realize it at the time, but during that whole period the city was in free fall. On top of the flight to the suburbs that happened everywhere, the steel and nuclear businesses were both dying. Boy are things different now. It's not just that downtown seems a lot more prosperous. There is an energy here that was not here when I was a kid.
如何将匹兹堡打造成创业中心(第一部分,共两部分)
(本文是我在匹兹堡Opt412活动上的演讲。大部分内容适用于其他城市,但并非全部——正如我在演讲中所说,匹兹堡相比大多数潜在创业中心具有重要优势。)
When I was a kid, this was a place young people left. Now it's a place that attracts them. What does that have to do with startups? Startups are made of people, and the average age of the people in a typical startup is right in that 25 to 29 bracket. I've seen how powerful it is for a city to have those people. Five years ago they shifted the center of gravity of Silicon Valley from the peninsula to San Francisco. Google and Facebook are on the peninsula, but the next generation of big winners are all in SF. The reason the center of gravity shifted was the talent war, for programmers especially. Most 25 to 29 year olds want to live in the city, not down in the boring suburbs. So whether they like it or not, founders know they have to be in the city. I know multiple founders who would have preferred to live down in the Valley proper, but who made themselves move to SF because they knew otherwise they'd lose the talent war. So being a magnet for people in their twenties is a very promising thing to be. It's hard to imagine a place becoming a startup hub without also being that. When I read that statistic about the increasing percentage of 25 to 29 year olds, I had exactly the same feeling of excitement I get when I see a startup's graphs start to creep upward off the x axis. Nationally the percentage of 25 to 29 year olds is 6.8%. That means you're .8% ahead. The population is 306,000, so we're talking about a surplus of about 2500 people. That's the population of a small town, and that's just the surplus. So you have a toehold. Now you just have to expand it. And though "youth-driven food boom" may sound frivolous, it is anything but. Restaurants and cafes are a big part of the personality of a city. Imagine walking down a street in Paris. What are you walking past? Little restaurants and cafes. Imagine driving through some depressing random exurb. What are you driving past? Starbucks and McDonalds and Pizza Hut.
要让匹兹堡成为硅谷那样的创业中心需要什么?我对匹兹堡非常了解,因为我在这里的莫农加希拉长大。我也很了解硅谷,因为我现在就住在那里。这里能建立起那样的创业生态系统吗?
当初答应来演讲时,我以为自己给不出太乐观的展望。我原以为会以假设语气谈论匹兹堡"可能"采取的措施,但现在我要说的是匹兹堡"可以"做什么。
改变我想法的是一篇刊登在《纽约时报》美食版的文章,标题是《匹兹堡青年驱动的美食热潮》。对多数人来说这听起来可能无趣,更别说联想到创业。但那个标题让我无比振奋——简直想不出比这更有希望的标题了。读完文章后我更激动了:25-29岁人群占比从十年前的7%升至7.6%。天啊,匹兹堡可能成为下一个波特兰,成为年轻人向往的酷炫城市。
As Gertrude Stein said, there is no there there. You could be anywhere. These independent restaurants and cafes are not just feeding people. They're making there be a there here. So here is my first concrete recommendation for turning Pittsburgh into the next Silicon Valley: do everything you can to encourage this youth-driven food boom. What could the city do? Treat the people starting these little restaurants and cafes as your users, and go ask them what they want. I can guess at least one thing they might want: a fast permit process. San Francisco has left you a huge amount of room to beat them in that department. I know restaurants aren't the prime mover though. The prime mover, as the Times article said, is cheap housing. That's a big advantage. But that phrase "cheap housing" is a bit misleading. There are plenty of places that are cheaper. What's special about Pittsburgh is not that it's cheap, but that it's a cheap place you'd actually want to live. Part of that is the buildings themselves. I realized a long time ago, back when I was a poor twenty-something myself, that the best deals were places that had once been rich, and then became poor. If a place has always been rich, it's nice but too expensive. If a place has always been poor, it's cheap but grim. But if a place was once rich and then got poor, you can find palaces for cheap. And that's what's bringing people here. When Pittsburgh was rich, a hundred years ago, the people who lived here built big solid buildings. Not always in the best taste, but definitely solid. So here is another piece of advice for becoming a startup hub: don't destroy the buildings that are bringing people here. When cities are on the way back up, like Pittsburgh is now, developers race to tear down the old buildings. Don't let that happen. Focus on historic preservation. Big real estate development projects are not what's bringing the twenty-somethings here.
几天前抵达时,我感受到了变化。1968-1984年我住在这里,当时没意识到这座城市正处于自由落体状态——除了普遍的郊区化浪潮,钢铁和核工业都在衰亡。如今截然不同:不仅市中心更繁荣,这里还焕发着我童年时没有的活力。过去这里是年轻人逃离的地方,现在却吸引着他们。
这与创业有何关联?初创企业由人构成,其核心群体正是25-29岁的年轻人。我见证过这类人群对城市的重塑力:五年前他们将硅谷重心从半岛转移到旧金山。谷歌和脸书仍在半岛,但新一代赢家都在旧金山——因为人才争夺战,尤其是程序员。多数年轻人想住在都市而非无聊的郊区,因此创始人不得不迁就。我认识多位偏爱半岛却被迫搬到旧金山的创始人。
因此,吸引年轻人是非常有前景的优势。很难想象一个非年轻化城市能成为创业中心。看到25-29岁人口增长数据时,我的兴奋感如同看到初创企业的增长曲线突破X轴。
They're the opposite of the new restaurants and cafes; they subtract personality from the city. The empirical evidence suggests you cannot be too strict about historic preservation. The tougher cities are about it, the better they seem to do. But the appeal of Pittsburgh is not just the buildings themselves. It's the neighborhoods they're in. Like San Francisco and New York, Pittsburgh is fortunate in being a pre-car city. It's not too spread out. Because those 25 to 29 year olds do not like driving. They prefer walking, or bicycling, or taking public transport. If you've been to San Francisco recently you can't help noticing the huge number of bicyclists. And this is not just a fad that the twenty-somethings have adopted. In this respect they have discovered a better way to live. The beards will go, but not the bikes. Cities where you can get around without driving are just better period. So I would suggest you do everything you can to capitalize on this. As with historic preservation, it seems impossible to go too far. Why not make Pittsburgh the most bicycle and pedestrian friendly city in the country? See if you can go so far that you make San Francisco seem backward by comparison. If you do, it's very unlikely you'll regret it. The city will seem like a paradise to the young people you want to attract. If they do leave to get jobs elsewhere, it will be with regret at leaving behind such a place. And what's the downside? Can you imagine a headline "City ruined by becoming too bicycle-friendly?" It just doesn't happen. So suppose cool old neighborhoods and cool little restaurants make this the next Portland. Will that be enough? It will put you in a way better position than Portland itself, because Pittsburgh has something Portland lacks: a first-rate research university. CMU plus little cafes means you have more than hipsters drinking lattes. It means you have hipsters drinking lattes while talking about distributed systems.
全美该年龄段占比6.8%,匹兹堡领先0.8%。以30.6万人口计算,意味着约2500人的净流入——相当于一个小镇的规模。这还只是净增数,你们已占据立足点,现在只需扩大优势。
"青年美食热潮"看似轻浮实则至关重要。餐厅咖啡馆构成城市个性:想象巴黎街景——小餐馆咖啡馆林立;再想象沉闷的远郊——只有连锁快餐店。正如格特鲁德·斯坦所说,那里没有"那里"。独立餐饮不仅满足口腹,更塑造城市灵魂。
因此我的首个具体建议是:全力支持这场青年美食热潮。市政府能做什么?把这些创业者视为用户,询问他们的需求。我至少能猜到一个:快速审批流程。旧金山在这方面给你们留足了超越空间。
Now you're getting really close to San Francisco. In fact you're better off than San Francisco in one way, because CMU is downtown, but Stanford and Berkeley are out in the suburbs. What can CMU do to help Pittsburgh become a startup hub? Be an even better research university. CMU is one of the best universities in the world, but imagine what things would be like if it were the very best, and everyone knew it. There are a lot of ambitious people who must go to the best place, wherever it is. If CMU were it, they would all come here. There would be kids in Kazakhstan dreaming of one day living in Pittsburgh. Being that kind of talent magnet is the most important contribution universities can make toward making their city a startup hub. In fact it is practically the only contribution they can make. But wait, shouldn't universities be setting up programs with words like "innovation" and "entrepreneurship" in their names? No, they should not. These kind of things almost always turn out to be disappointments. They're pursuing the wrong targets. The way to get innovation is not to aim for innovation but to aim for something more specific, like better batteries or better 3D printing. And the way to learn about entrepreneurship is to do it, which you _can't in school_. I know it may disappoint some administrators to hear that the best thing a university can do to encourage startups is to be a great university. It's like telling people who want to lose weight that the way to do it is to eat less. But if you want to know where startups come from, look at the empirical evidence. Look at the histories of the most successful startups, and you'll find they grow organically out of a couple of founders building something that starts as an interesting side project. Universities are great at bringing together founders, but beyond that the best thing they can do is get out of the way.
但餐饮并非核心驱动力。《纽约时报》指出,真正动力是廉价住房——这个表述不够准确。匹兹堡的特殊性不在于低价,而在于"值得居住的低价"。部分原因在于建筑本身:我年轻时就知道,最佳选择是曾经富裕后衰落的区域。这里百年前繁荣时建造的坚固建筑(虽审美未必最佳)正吸引着人们。因此第二个建议:保护这些吸引人才的建筑。城市复兴时,开发商总想拆除旧建筑,必须阻止这种行为。历史保护再严格都不为过——越严格的城市发展越好。
匹兹堡的魅力还在于社区布局。像旧金山和纽约一样,它是前汽车时代的紧凑城市。25-29岁人群讨厌开车,偏爱步行、骑行或公交。旧金山满街骑行者不是暂时风尚,而是更好的生活方式——胡须会过时,单车不会。建议全力发展这方面优势,让匹兹堡成为全美最友好的骑行步行城市。这样做绝无风险,只会让城市对年轻人更具吸引力。
For example, by not claiming ownership of "intellectual property" that students and faculty develop, and by having liberal rules about deferred admission and leaves of absence. In fact, one of the most effective things a university could do to encourage startups is an elaborate form of getting out of the way invented by Harvard. Harvard used to have exams for the fall semester after Christmas. At the beginning of January they had something called "Reading Period" when you were supposed to be studying for exams. And Microsoft and Facebook have something in common that few people realize: they were both started during Reading Period. It's the perfect situation for producing the sort of side projects that turn into startups. The students are all on campus, but they don't have to do anything because they're supposed to be studying for exams. Harvard may have closed this window, because a few years ago they moved exams before Christmas and shortened reading period from 11 days to 7. But if a university really wanted to help its students start startups, the empirical evidence, weighted by market cap, suggests the best thing they can do is literally nothing. The culture of Pittsburgh is another of its strengths. It seems like a city has to be socially liberal to be a startup hub, and it's pretty clear why. A city has to tolerate strangeness to be a home for startups, because startups are so strange. And you can't choose to allow just the forms of strangeness that will turn into big startups, because they're all intermingled. You have to tolerate all strangeness. That immediately rules out _big chunks of the US_. I'm optimistic it doesn't rule out Pittsburgh. One of the things I remember from growing up here, though I didn't realize at the time that there was anything unusual about it, is how well people got along. I'm still not sure why.
假设酷炫的老社区和小餐馆真使这里成为下一个波特兰,这就够了吗?匹兹堡还有波特兰缺乏的优势:顶尖研究型大学CMU。咖啡馆加CMU意味着这里不仅有喝拿铁的潮人,更有讨论分布式系统的极客——这已非常接近旧金山。实际上某方面更优:CMU位于市中心,而斯坦福和伯克利都在郊区。
CMU如何助力?成为更顶尖的研究型大学。若能成为公认的世界第一,全球雄心勃勃的人才都会涌来,连哈萨克斯坦的孩子都会梦想定居匹兹堡。大学对创业生态的最大贡献就是吸引人才——几乎是唯一贡献。
那些标榜"创新""创业"的大学项目往往令人失望。创新不是目标而是结果,应聚焦具体领域如电池或3D打印技术。创业只能通过实践学习。大学最该做的是不干涉:不抢占师生知识产权,放宽延期入学和休学政策。哈佛曾有的"阅读期"(考试前自主复习期)意外催生了微软和脸书——学生聚集校园却无需上课,正是孕育创业项目的完美时机。
Maybe one reason was that everyone felt like an immigrant. When I was a kid in Monroeville, people didn't call themselves American. They called themselves Italian or Serbian or Ukranian. Just imagine what it must have been like here a hundred years ago, when people were pouring in from twenty different countries. Tolerance was the only option. What I remember about the culture of Pittsburgh is that it was both tolerant and pragmatic. That's how I'd describe the culture of Silicon Valley too. And it's not a coincidence, because Pittsburgh was the Silicon Valley of its time. This was a city where people built new things. And while the things people build have changed, the spirit you need to do that kind of work is the same. So although an influx of latte-swilling hipsters may be annoying in some ways, I would go out of my way to encourage them. And more generally to tolerate strangeness, even unto the degree wacko Californians do. For Pittsburgh that is a conservative choice: it's a return to the city's roots. Unfortunately I saved the toughest part for last. There is one more thing you need to be a startup hub, and Pittsburgh hasn't got it: investors. Silicon Valley has a big investor community because it's had 50 years to grow one. New York has a big investor community because it's full of people who like money a lot and are quick to notice new ways to get it. But Pittsburgh has neither of these. And the cheap housing that draws other people here has no effect on investors. If an investor community grows up here, it will happen the same way it did in Silicon Valley: slowly and organically. So I would not bet on having a big investor community in the short term. But fortunately there are three trends that make that less necessary than it used to be. One is that startups are increasingly cheap to start, so you just don't need as much outside money as you used to.
匹兹堡的文化是另一优势。创业中心需要社会开明,因为初创企业本质怪异,而各种"怪异"又相互交织。这直接排除了美国许多地区,但匹兹堡有希望。我成长于此的记忆是人们的融洽相处——可能因为大家都自视为移民(当年人们自称意大利人、塞尔维亚人而非美国人)。这种包容与务实正是硅谷的特质,也是匹兹堡作为昔日"硅谷"的精神遗产。
尽管拿铁潮人在某些方面令人厌烦,仍应尽力吸引他们。广义上要包容怪异,哪怕达到加州疯子的程度——对匹兹堡这是保守选择,是回归本源。
最后是最棘手的问题:匹兹堡缺乏投资者群体。硅谷用50年培育了投资生态,纽约则有嗜钱如命的金融文化。廉价住房对投资者没有吸引力。投资社区只能像硅谷那样缓慢有机生长。但三个趋势降低了短期需求:创业成本降低、Kickstarter等平台加速盈利、YC等孵化器提供全球融资渠道。
The second is that thanks to things like Kickstarter, a startup can get to revenue faster. You can put something on Kickstarter from anywhere. The third is programs like Y Combinator. A startup from anywhere in the world can go to YC for 3 months, pick up funding, and then return home if they want. My advice is to make Pittsburgh a great place for startups, and gradually more of them will stick. Some of those will succeed; some of their founders will become investors; and still more startups will stick. This is not a fast path to becoming a startup hub. But it is at least a path, which is something few other cities have. And it's not as if you have to make painful sacrifices in the meantime. Think about what I've suggested you should do. Encourage local restaurants, save old buildings, take advantage of density, make CMU the best, promote tolerance. These are the things that make Pittsburgh good to live in now. All I'm saying is that you should do even more of them. And that's an encouraging thought. If Pittsburgh's path to becoming a startup hub is to be even more itself, then it has a good chance of succeeding. In fact it probably has the best chance of any city its size. It will take some effort, and a lot of time, but if any city can do it, Pittsburgh can. Thanks to Charlie Cheever and Jessica Livingston for reading drafts of this, and to Meg Cheever for organizing Opt412 and inviting me to speak..
建议先打造适合创业的环境,自然会有更多企业扎根。部分成功者将成为投资者,吸引更多创业者。这不是快速通道,但已是大多数城市没有的优势。而且实施这些建议无需痛苦牺牲——鼓励本地餐饮、保护老建筑、利用密度优势、提升CMU、促进包容,这些本就能提升城市宜居度。只需做得更多。
这是个鼓舞人心的结论:如果匹兹堡的创业之路是"做更好的自己",那么它成功概率很大——在同规模城市中可能最高。这需要努力和时间,但如果有城市能做到,那就是匹兹堡。
感谢查理·奇弗、杰西卡·利文斯顿审阅草稿,感谢梅格·奇弗组织Opt412并邀请我演讲。
January 2016 One advantage of being old is that you can see change happen in your lifetime. A lot of the change I've seen is fragmentation. US politics is much more polarized than it used to be. Culturally we have ever less common ground. The creative class flocks to a handful of happy cities, abandoning the rest. And increasing economic inequality means the spread between rich and poor is growing too. I'd like to propose a hypothesis: that all these trends are instances of the same phenomenon. And moreover, that the cause is not some force that's pulling us apart, but rather the erosion of forces that had been pushing us together. Worse still, for those who worry about these trends, the forces that were pushing us together were an anomaly, a one-time combination of circumstances that's unlikely to be repeated — and indeed, that we would not want to repeat. The two forces were war (above all World War II), and the rise of large corporations. The effects of World War II were both economic and social. Economically, it decreased variation in income. Like all modern armed forces, America's were socialist economically. From each according to his ability, to each according to his need. More or less. Higher ranking members of the military got more (as higher ranking members of socialist societies always do), but what they got was fixed according to their rank. And the flattening effect wasn't limited to those under arms, because the US economy was conscripted too. Between 1942 and 1945 all wages were set by the National War Labor Board. Like the military, they defaulted to flatness. And this national standardization of wages was so pervasive that its effects could still be seen years after the war ended. [1] Business owners weren't supposed to be making money either. FDR said "not a single war millionaire" would be permitted. To ensure that, any increase in a company's profits over prewar levels was taxed at 85%.
年长者的一大优势是能亲眼见证时代变迁。在我目睹的诸多变化中,"碎片化"尤为显著。美国政治比以往更加两极分化,文化领域的共同根基日益稀薄,创意阶层涌向少数幸福城市而抛弃其他地区。日益加剧的经济不平等则意味着贫富差距持续扩大。我想提出一个假说:这些趋势实为同一现象的不同表现。究其根源,并非某种分裂力量在作祟,而是曾经推动社会聚合的力量正在消退。
更令人忧心的是,对那些关注这些趋势的人而言,昔日推动社会聚合的力量本身是反常的——它们是特定历史条件的偶然结合,既难以重现,亦非我们所愿。
And when what was left after corporate taxes reached individuals, it was taxed again at a marginal rate of 93%. [2] Socially too the war tended to decrease variation. Over 16 million men and women from all sorts of different backgrounds were brought together in a way of life that was literally uniform. Service rates for men born in the early 1920s approached 80%. And working toward a common goal, often under stress, brought them still closer together. Though strictly speaking World War II lasted less than 4 years for the US, its effects lasted longer. Wars make central governments more powerful, and World War II was an extreme case of this. In the US, as in all the other Allied countries, the federal government was slow to give up the new powers it had acquired. Indeed, in some respects the war didn't end in 1945; the enemy just switched to the Soviet Union. In tax rates, federal power, defense spending, conscription, and nationalism, the decades after the war looked more like wartime than prewar peacetime. [3] And the social effects lasted too. The kid pulled into the army from behind a mule team in West Virginia didn't simply go back to the farm afterward. Something else was waiting for him, something that looked a lot like the army. If total war was the big political story of the 20th century, the big economic story was the rise of a new kind of company. And this too tended to produce both social and economic cohesion. [4] The 20th century was the century of the big, national corporation. General Electric, General Foods, General Motors. Developments in finance, communications, transportation, and manufacturing enabled a new type of company whose goal was above all scale. Version 1 of this world was low-res: a Duplo world of a few giant companies dominating each big market. [5] The late 19th and early 20th centuries had been a time of consolidation, led especially by J. P. Morgan.
这两股力量分别是战争(尤其是第二次世界大战)与大型企业的崛起。
二战的影响兼具经济与社会双重维度。经济上,它压缩了收入差距。与所有现代军队类似,美军实行的是经济上的社会主义制度——各尽所能,按需分配(大体如此)。高级军官虽享有更多待遇(正如社会主义社会中的上位者惯常所为),但所得皆按军衔严格固定。这种扁平化效应不仅限于军队,因为美国国民经济同样被征用:1942至1945年间,所有工资标准皆由国家战时劳工委员会制定。与军队模式如出一辙,他们默认采用平均主义原则。这种全国性的工资标准化影响深远,甚至在战后多年仍清晰可辨[1]。
企业主亦被禁止牟利。罗斯福宣称"决不允许出现战争暴发户"。为确保这点,企业利润超过战前水平的增量部分课以85%重税。而公司税后利润分配到个人时,还需缴纳高达93%的边际税率[2]。
Thousands of companies run by their founders were merged into a couple hundred giant ones run by professional managers. Economies of scale ruled the day. It seemed to people at the time that this was the final state of things. John D. Rockefeller said in 1880 > The day of combination is here to stay. Individualism has gone, never to return..
在社会层面,战争同样消弭差异。超过1600万来自不同背景的男女被纳入高度统一的军事化生活。1920年代早期出生的男性服役率接近80%。为共同目标奋斗的经历(往往伴随着高压环境),使他们产生更紧密的联结。
尽管严格来说美国参战不足四年,其影响却持久不衰。战争强化中央集权,二战将此推向极致。与其他盟国相同,美国联邦政府迟迟不愿放弃新获得的权力。某些层面上,战争在1945年并未真正结束——只是敌人换成了苏联。从税率、联邦权力、国防开支、征兵制到民族主义,战后数十年更近似战时状态而非战前和平年代[3]。社会影响同样延续:西弗吉尼亚州赶骡队的农家子弟入伍后,等待他的归宿绝非简单回归农田,而是某个与军队高度相似的崭新世界。
He turned out to be mistaken, but he seemed right for the next hundred years. The consolidation that began in the late 19th century continued for most of the 20th. By the end of World War II, as Michael Lind writes, "the major sectors of the economy were either organized as government-backed cartels or dominated by a few oligopolistic corporations." For consumers this new world meant the same choices everywhere, but only a few of them. When I grew up there were only 2 or 3 of most things, and since they were all aiming at the middle of the market there wasn't much to differentiate them. One of the most important instances of this phenomenon was in TV. Here there were 3 choices: NBC, CBS, and ABC. Plus public TV for eggheads and communists. The programs that the 3 networks offered were indistinguishable. In fact, here there was a triple pressure toward the center. If one show did try something daring, local affiliates in conservative markets would make them stop. Plus since TVs were expensive, whole families watched the same shows together, so they had to be suitable for everyone. And not only did everyone get the same thing, they got it at the same time. It's difficult to imagine now, but every night tens of millions of families would sit down together in front of their TV set watching the same show, at the same time, as their next door neighbors. What happens now with the Super Bowl used to happen every night. We were literally in sync. [6] In a way mid-century TV culture was good. The view it gave of the world was like you'd find in a children's book, and it probably had something of the effect that (parents hope) children's books have in making people behave better. But, like children's books, TV was also misleading. Dangerously misleading, for adults. In his autobiography, Robert MacNeil talks of seeing gruesome images that had just come in from Vietnam and thinking, we can't show these to families while they're having dinner.
若说全面战争是20世纪的政治主旋律,那么经济领域的主线则是新型企业的崛起——这股力量同样促进着社会经济凝聚[4]。
20世纪属于庞大的全国性企业:通用电气、通用食品、通用汽车。金融、通信、运输与制造业的发展催生出以规模扩张为核心的新型公司。这个世界的1.0版本像素粗糙:如同乐高得宝积木般,每个主要市场都由少数巨头主宰[5]。
19世纪末至20世纪初是兼并重组时代,J.P.摩根堪称领军人物。数以千计的创始人型企业被合并为数百家由职业经理人掌舵的巨头。规模经济大行其道,时人皆视此为终极形态。约翰·D·洛克菲勒在1880年断言:
I know how pervasive the common culture was, because I tried to opt out of it, and it was practically impossible to find alternatives. When I was 13 I realized, more from internal evidence than any outside source, that the ideas we were being fed on TV were crap, and I stopped watching it. [7] But it wasn't just TV. It seemed like everything around me was crap. The politicians all saying the same things, the consumer brands making almost identical products with different labels stuck on to indicate how prestigious they were meant to be, the balloon-frame houses with fake "colonial" skins, the cars with several feet of gratuitous metal on each end that started to fall apart after a couple years, the "red delicious" apples that were red but only nominally apples. And in retrospect, it _was_ crap. [8] But when I went looking for alternatives to fill this void, I found practically nothing. There was no Internet then. The only place to look was in the chain bookstore in our local shopping mall. [9] There I found a copy of _The Atlantic_. I wish I could say it became a gateway into a wider world, but in fact I found it boring and incomprehensible. Like a kid tasting whisky for the first time and pretending to like it, I preserved that magazine as carefully as if it had been a book. I'm sure I still have it somewhere. But though it was evidence that there was, somewhere, a world that wasn't red delicious, I didn't find it till college. It wasn't just as consumers that the big companies made us similar. They did as employers too. Within companies there were powerful forces pushing people toward a single model of how to look and act. IBM was particularly notorious for this, but they were only a little more extreme than other big companies. And the models of how to look and act varied little between companies. Meaning everyone within this world was expected to seem more or less the same.
> 企业联合的时代永驻,个人主义一去不返。
事实证明他错了,但这个错误持续了将近一百年才被察觉。
始于19世纪末的行业整合贯穿了20世纪大部分时间。正如迈克尔·林德所写,到二战结束时,"经济的主要领域要么被组织成政府支持的卡特尔,要么被少数寡头垄断企业掌控"。
And not just those in the corporate world, but also everyone who aspired to it — which in the middle of the 20th century meant most people who weren't already in it. For most of the 20th century, working-class people tried hard to look middle class. You can see it in old photos. Few adults aspired to look dangerous in 1950. But the rise of national corporations didn't just compress us culturally. It compressed us economically too, and on both ends. Along with giant national corporations, we got giant national labor unions. And in the mid 20th century the corporations cut deals with the unions where they paid over market price for labor. Partly because the unions were monopolies. [10] Partly because, as components of oligopolies themselves, the corporations knew they could safely pass the cost on to their customers, because their competitors would have to as well. And partly because in mid-century most of the giant companies were still focused on finding new ways to milk economies of scale. Just as startups rightly pay AWS a premium over the cost of running their own servers so they can focus on growth, many of the big national corporations were willing to pay a premium for labor. [11] As well as pushing incomes up from the bottom, by overpaying unions, the big companies of the 20th century also pushed incomes down at the top, by underpaying their top management. Economist J. K. Galbraith wrote in 1967 that "There are few corporations in which it would be suggested that executive salaries are at a maximum." [12] To some extent this was an illusion. Much of the de facto pay of executives never showed up on their income tax returns, because it took the form of perks.
对消费者而言,这个新世界意味着各地选择相同且有限。在我成长的时代,大多数商品只有两三种品牌,由于它们都瞄准市场中间群体,彼此间几乎毫无差异。
这种现象最典型的体现是电视行业。当时只有三个选择:NBC、CBS和ABC,再加上为书呆子和共产主义者准备的公共电视台。三大电视网播出的节目如出一辙。实际上,这里存在三重向心力:如果某节目尝试创新,保守地区的附属台就会施压叫停;加之电视机价格昂贵,全家老小共同观看,内容必须老少咸宜。
The higher the rate of income tax, the more pressure there was to pay employees upstream of it. (In the UK, where taxes were even higher than in the US, companies would even pay their kids' private school tuitions.) One of the most valuable things the big companies of the mid 20th century gave their employees was job security, and this too didn't show up in tax returns or income statistics. So the nature of employment in these organizations tended to yield falsely low numbers about economic inequality. But even accounting for that, the big companies paid their best people less than market price. There was no market; the expectation was that you'd work for the same company for decades if not your whole career. [13] Your work was so illiquid there was little chance of getting market price. But that same illiquidity also encouraged you not to seek it. If the company promised to employ you till you retired and give you a pension afterward, you didn't want to extract as much from it this year as you could. You needed to take care of the company so it could take care of you. Especially when you'd been working with the same group of people for decades. If you tried to squeeze the company for more money, you were squeezing the organization that was going to take care of _them_. Plus if you didn't put the company first you wouldn't be promoted, and if you couldn't switch ladders, promotion on this one was the only way up. [14] To someone who'd spent several formative years in the armed forces, this situation didn't seem as strange as it does to us now. From their point of view, as big company executives, they were high-ranking officers. They got paid a lot more than privates. They got to have expense account lunches at the best restaurants and fly around on the company's Gulfstreams. It probably didn't occur to most of them to ask if they were being paid market price. The ultimate way to get market price is to work for yourself, by starting your own company.
不仅内容相同,观看时间也完全同步。如今难以想象的是,每晚数百万家庭会与邻居同时打开电视收看相同节目。如今超级碗的盛况,当年每晚都在上演。我们确实生活在同步节奏中。[6]
某种意义上,世纪中叶的电视文化有其积极面。它呈现的世界观如同儿童读物,或许确实产生了类似(父母期望中)童书教化人心的效果。但就像童书一样,电视也造成误导——对成年人而言是危险的误导。罗伯特·麦克尼尔在自传中谈到,当他看到刚从越南传回的惨烈画面时,第一反应是"我们不能在家庭晚餐时间播放这些"。
我深知主流文化的强大渗透力,因为我曾试图逃离却徒劳无功。十三岁时,我通过内在判断(而非外界影响)意识到电视灌输的理念全是垃圾,从此拒绝观看。[7]但问题不止于电视。周遭一切似乎都粗制滥造:政客们千篇一律的演说,不同品牌贴着不同标签却本质雷同的商品,披着伪"殖民风格"外衣的轻木框架房屋,两端装着多余金属板几年就散架的汽车,徒有"红"字却毫无苹果味的"蛇果"。如今回望,那确实是个垃圾遍地的时代。[8]
That seems obvious to any ambitious person now. But in the mid 20th century it was an alien concept. Not because starting one's own company seemed too ambitious, but because it didn't seem ambitious enough. Even as late as the 1970s, when I grew up, the ambitious plan was to get lots of education at prestigious institutions, and then join some other prestigious institution and work one's way up the hierarchy. Your prestige was the prestige of the institution you belonged to. People did start their own businesses of course, but educated people rarely did, because in those days there was practically zero concept of starting what we now call a _startup_: a business that starts small and grows big. That was much harder to do in the mid 20th century. Starting one's own business meant starting a business that would start small and stay small. Which in those days of big companies often meant scurrying around trying to avoid being trampled by elephants. It was more prestigious to be one of the executive class riding the elephant. By the 1970s, no one stopped to wonder where the big prestigious companies had come from in the first place. It seemed like they'd always been there, like the chemical elements. And indeed, there was a double wall between ambitious kids in the 20th century and the origins of the big companies. Many of the big companies were roll-ups that didn't have clear founders. And when they did, the founders didn't seem like us. Nearly all of them had been uneducated, in the sense of not having been to college. They were what Shakespeare called rude mechanicals. College trained one to be a member of the professional classes. Its graduates didn't expect to do the sort of grubby menial work that Andrew Carnegie or Henry Ford started out doing. [15] And in the 20th century there were more and more college graduates. They increased from about 2% of the population in 1900 to about 25% in 2000.
当我试图寻找替代品填补精神空缺时,几乎一无所获。那时没有互联网,唯一的选择是商场连锁书店。[9]我在那里发现一本《大西洋月刊》。虽然它最终未能成为通往广阔世界的窗口(坦白说当时觉得既无聊又难懂),但我像小孩假装喜欢威士忌般珍视它,保存之精心堪比典籍。这本杂志证明世界上确实存在非"蛇果"的天地,不过直到大学我才真正找到它。
大公司不仅通过消费产品塑造同质化,作为雇主同样如此。企业内部存在强大力量,将员工推向统一的行为范式。IBM在这方面臭名昭著,但其他大公司也不过五十步笑百步。更关键的是,各公司间的行为范式差异极小,意味着整个体系期待每个人都表现得大同小异。不仅企业界如此,所有向往其中的人——在20世纪中叶即指大多数圈外人——都受此约束。整个20世纪,工人阶级都竭力模仿中产做派,老照片清晰印证这点:1950年几乎没有成年人追求叛逆形象。
但全国性企业的崛起不仅带来文化压缩,经济层面同样产生双向挤压。
In the middle of the century our two big forces intersect, in the form of the GI Bill, which sent 2.2 million World War II veterans to college. Few thought of it in these terms, but the result of making college the canonical path for the ambitious was a world in which it was socially acceptable to work for Henry Ford, but not to be Henry Ford. [16] I remember this world well. I came of age just as it was starting to break up. In my childhood it was still dominant. Not quite so dominant as it had been. We could see from old TV shows and yearbooks and the way adults acted that people in the 1950s and 60s had been even more conformist than us. The mid-century model was already starting to get old. But that was not how we saw it at the time. We would at most have said that one could be a bit more daring in 1975 than 1965. And indeed, things hadn't changed much yet. But change was coming soon. And when the Duplo economy started to disintegrate, it disintegrated in several different ways at once. Vertically integrated companies literally dis-integrated because it was more efficient to. Incumbents faced new competitors as (a) markets went global and (b) technical innovation started to trump economies of scale, turning size from an asset into a liability. Smaller companies were increasingly able to survive as formerly narrow channels to consumers broadened. Markets themselves started to change faster, as whole new categories of products appeared. And last but not least, the federal government, which had previously smiled upon J. P. Morgan's world as the natural state of things, began to realize it wasn't the last word after all. What J. P. Morgan was to the horizontal axis, Henry Ford was to the vertical. He wanted to do everything himself. The giant plant he built at River Rouge between 1917 and 1928 literally took in iron ore at one end and sent cars out the other. 100,000 people worked there. At the time it seemed the future.
伴随巨型企业出现的是强大的全国性工会。20世纪中叶,企业向工会支付高于市场价的工资——部分因为工会垄断劳动力[10],部分由于寡头企业知道能将成本转嫁给消费者(毕竟竞争对手也会如此),更因为当时大公司仍专注于挖掘规模经济红利。就像初创企业愿意溢价使用AWS以专注发展,许多全国性企业也愿意为劳动力支付溢价。[11]
20世纪的大公司既通过高薪拉高底层收入,也通过低薪压制高层收入。经济学家加尔布雷斯1967年写道:"几乎没有公司会认为高管工资已达到上限。"[12]
But that is not how car companies operate today. Now much of the design and manufacturing happens in a long supply chain, whose products the car companies ultimately assemble and sell. The reason car companies operate this way is that it works better. Each company in the supply chain focuses on what they know best. And they each have to do it well or they can be swapped out for another supplier. Why didn't Henry Ford realize that networks of cooperating companies work better than a single big company? One reason is that supplier networks take a while to evolve. In 1917, doing everything himself seemed to Ford the only way to get the scale he needed. And the second reason is that if you want to solve a problem using a network of cooperating companies, you have to be able to coordinate their efforts, and you can do that much better with computers. Computers reduce the transaction costs that Coase argued are the raison d'etre of corporations. That is a fundamental change. In the early 20th century, big companies were synonymous with efficiency. In the late 20th century they were synonymous with inefficiency. To some extent this was because the companies themselves had become sclerotic. But it was also because our standards were higher. It wasn't just within existing industries that change occurred. The industries themselves changed. It became possible to make lots of new things, and sometimes the existing companies weren't the ones who did it best. Microcomputers are a classic example. The market was pioneered by upstarts like Apple. When it got big enough, IBM decided it was worth paying attention to. At the time IBM completely dominated the computer industry. They assumed that all they had to do, now that this market was ripe, was to reach out and pick it. Most people at the time would have agreed with them. But what happened next illustrated how much more complicated the world had become. IBM did launch a microcomputer.
某种程度上这是假象。高管实际报酬大多从未出现在税单上,而是以福利形式存在。所得税率越高,这种上游支付压力越大。(在英国,公司甚至会支付高管子女的私立学费。)20世纪中叶大公司提供的最有价值福利是工作保障,这同样不体现在税收统计中。因此这类组织的雇佣性质会低估经济不平等程度。但即便考虑这些因素,大公司支付顶尖人才的报酬仍低于市场价——因为根本不存在真正市场,默认你要为同一家公司工作数十年乃至整个职业生涯。[13]
工作流动性极差自然难获市场价,但同样也让人放弃追求。当公司承诺终身雇佣并提供养老金时,你不会榨取当年最大收益。你需要呵护公司,它才会庇护你——尤其当你与同一群人共事数十年时。若你试图压榨公司,就是在伤害未来照顾这些同僚的组织。更何况,不把公司利益置于首位就难获晋升,而在无法跳槽的情况下,晋升是唯一上升通道。[14]
对经历过军旅生涯的人而言,这种模式并不陌生。在他们眼中,作为大公司高管就像高级军官:薪水远高于列兵,能在顶级餐厅签单消费,乘坐公司湾流飞机。多数人根本不会质疑自己是否获得市场价报酬。
Though quite successful, it did not crush Apple. But even more importantly, IBM itself ended up being supplanted by a supplier coming in from the side — from software, which didn't even seem to be the same business. IBM's big mistake was to accept a non-exclusive license for DOS. It must have seemed a safe move at the time. No other computer manufacturer had ever been able to outsell them. What difference did it make if other manufacturers could offer DOS too? The result of that miscalculation was an explosion of inexpensive PC clones. Microsoft now owned the PC standard, and the customer. And the microcomputer business ended up being Apple vs Microsoft. Basically, Apple bumped IBM and then Microsoft stole its wallet. That sort of thing did not happen to big companies in mid-century. But it was going to happen increasingly often in the future. Change happened mostly by itself in the computer business. In other industries, legal obstacles had to be removed first. Many of the mid-century oligopolies had been anointed by the federal government with policies (and in wartime, large orders) that kept out competitors. This didn't seem as dubious to government officials at the time as it sounds to us. They felt a two-party system ensured sufficient competition in politics. It ought to work for business too. Gradually the government realized that anti-competitive policies were doing more harm than good, and during the Carter administration it started to remove them. The word used for this process was misleadingly narrow: deregulation. What was really happening was de-oligopolization. It happened to one industry after another. Two of the most visible to consumers were air travel and long-distance phone service, which both became dramatically cheaper after deregulation. Deregulation also contributed to the wave of hostile takeovers in the 1980s.
获取市场价的终极方式是创业。这对当今有志者显而易见,但在20世纪中叶却属异端——并非因为创业太激进,而是显得不够抱负。即便在我成长的1970年代,成功路径仍是:名校深造→加入知名机构→逐级攀登。你的声望完全依附于机构声望。当然有人创业,但受教育阶层极少参与,因为当时完全不存在如今"初创企业"(从小做大)的概念。创业意味着永远小打小闹,在大公司时代如同蝼蚁避象。成为骑象的精英阶层才更体面。
到1970年代,已无人追问这些巨头从何而来。它们仿佛元素般永恒存在。20世纪的雄心青年与公司起源之间隔着双重屏障:许多大公司是并购产物,没有明确创始人;即便有,创始人也与精英教育绝缘——他们多是莎士比亚笔下的"粗鄙匠人"。大学培养的是专业阶层,其毕业生不屑于从事卡内基或福特发迹时的脏活累活。[15]
In the old days the only limit on the inefficiency of companies, short of actual bankruptcy, was the inefficiency of their competitors. Now companies had to face absolute rather than relative standards. Any public company that didn't generate sufficient returns on its assets risked having its management replaced with one that would. Often the new managers did this by breaking companies up into components that were more valuable separately. [17] Version 1 of the national economy consisted of a few big blocks whose relationships were negotiated in back rooms by a handful of executives, politicians, regulators, and labor leaders. Version 2 was higher resolution: there were more companies, of more different sizes, making more different things, and their relationships changed faster. In this world there were still plenty of back room negotiations, but more was left to market forces. Which further accelerated the fragmentation. It's a little misleading to talk of versions when describing a gradual process, but not as misleading as it might seem. There was a lot of change in a few decades, and what we ended up with was qualitatively different. The companies in the S&P 500 in 1958 had been there an average of 61 years. By 2012 that number was 18 years. [18] The breakup of the Duplo economy happened simultaneously with the spread of computing power. To what extent were computers a precondition? It would take a book to answer that. Obviously the spread of computing power was a precondition for the rise of startups. I suspect it was for most of what happened in finance too. But was it a precondition for globalization or the LBO wave? I don't know, but I wouldn't discount the possibility. It may be that the refragmentation was driven by computers in the way the industrial revolution was driven by steam engines. Whether or not computers were a precondition, they have certainly accelerated it.
20世纪大学生比例从1900年的2%升至2000年的25%。世纪中叶,《退伍军人权利法案》将220万二战老兵送入大学,使两大力量交汇。很少有人意识到:将大学设为雄心标配的结果,是形成"为亨利·福特工作体面,成为亨利·福特却不体面"的价值观。[16]
我对这个世界记忆犹新——它在我成年时开始瓦解,但童年仍居主导。通过老电视节目、年鉴和成人举止,我们能看出1950-60年代的人比我们更循规蹈矩。世纪中叶模式已然老化,但当时我们至多认为1975年比1965年稍显开放,实质变化尚未发生。
剧变即将来临。当积木经济开始瓦解时,呈现多维度崩塌:垂直整合企业因效率问题主动拆分;随着(a)市场全球化(b)技术创新战胜规模经济,既得利益者面临新竞争,规模由资产变累赘;通往消费者的渠道拓宽使小公司存活率提升;全新产品品类加速市场迭代;最重要的是,曾将摩根世界视为常态的联邦政府,终于意识到这并非终极形态。
The new fluidity of companies changed people's relationships with their employers. Why climb a corporate ladder that might be yanked out from under you? Ambitious people started to think of a career less as climbing a single ladder than as a series of jobs that might be at different companies. More movement (or even potential movement) between companies introduced more competition in salaries. Plus as companies became smaller it became easier to estimate how much an employee contributed to the company's revenue. Both changes drove salaries toward market price. And since people vary dramatically in productivity, paying market price meant salaries started to diverge. By no coincidence it was in the early 1980s that the term "yuppie" was coined. That word is not much used now, because the phenomenon it describes is so taken for granted, but at the time it was a label for something novel. Yuppies were young professionals who made lots of money. To someone in their twenties today, this wouldn't seem worth naming. Why wouldn't young professionals make lots of money? But until the 1980s, being underpaid early in your career was part of what it meant to be a professional. Young professionals were paying their dues, working their way up the ladder. The rewards would come later. What was novel about yuppies was that they wanted market price for the work they were doing now. The first yuppies did not work for startups. That was still in the future. Nor did they work for big companies. They were professionals working in fields like law, finance, and consulting. But their example rapidly inspired their peers. Once they saw that new BMW 325i, they wanted one too. Underpaying people at the beginning of their career only works if everyone does it. Once some employer breaks ranks, everyone else has to, or they can't get good people.
如果说J.P.摩根代表横向整合,亨利·福特就是垂直整合的化身。1917-1928年建成的荣格工厂,一端输入铁矿砂,另一端驶出汽车,十万工人在此劳作。这曾代表未来,却非当今车企运营模式。如今设计和制造分散于供应链,车企只负责最终组装销售。这种模式更高效:每家企业专注所长,表现不佳即遭替换。
为何福特没意识到企业网络比单体巨兽更高效?首先,供应链网络需要演化时间——1917年自建全链似乎是获取规模的唯一途径;其次,协调企业网络需要计算机辅助。计算机降低了科斯所说的交易成本,这一根本变革使20世纪初象征效率的大公司,到世纪末成为低效代名词。部分源于企业自身僵化,更多源于我们标准提高。
变革不仅发生在既有行业内部,行业本身也在更替。大量新产品成为可能,而现有企业往往不是最佳创造者。
And once started this process spreads through the whole economy, because at the beginnings of people's careers they can easily switch not merely employers but industries. But not all young professionals benefitted. You had to produce to get paid a lot. It was no coincidence that the first yuppies worked in fields where it was easy to measure that. More generally, an idea was returning whose name sounds old-fashioned precisely because it was so rare for so long: that you could make your fortune. As in the past there were multiple ways to do it. Some made their fortunes by creating wealth, and others by playing zero-sum games. But once it became possible to make one's fortune, the ambitious had to decide whether or not to. A physicist who chose physics over Wall Street in 1990 was making a sacrifice that a physicist in 1960 didn't have to think about. The idea even flowed back into big companies. CEOs of big companies make more now than they used to, and I think much of the reason is prestige. In 1960, corporate CEOs had immense prestige. They were the winners of the only economic game in town. But if they made as little now as they did then, in real dollar terms, they'd seem like small fry compared to professional athletes and whiz kids making millions from startups and hedge funds. They don't like that idea, so now they try to get as much as they can, which is more than they had been getting. [19] Meanwhile a similar fragmentation was happening at the other end of the economic scale. As big companies' oligopolies became less secure, they were less able to pass costs on to customers and thus less willing to overpay for labor. And as the Duplo world of a few big blocks fragmented into many companies of different sizes — some of them overseas — it became harder for unions to enforce their monopolies. As a result workers' wages also tended toward market price. Which (inevitably, if unions had been doing their job) tended to be lower.
微机是经典案例。苹果等新锐开创市场后,主宰计算机产业的IBM认为可以轻松收割。多数人当时认同这点,但随后发展揭示世界的复杂程度:IBM微机虽成功却未碾碎苹果;更关键的是,IBM最终被侧翼杀入的软件供应商取代——微软通过非独家DOS授权引发廉价PC克隆狂潮,最终夺得行业标准。简言之,苹果撞倒IBM,微软顺手牵羊。这类事件在世纪中叶的巨头间闻所未闻,却将成为未来常态。
计算机行业的变革自发产生,其他行业则需先破除法律障碍。许多世纪中叶的寡头垄断依赖联邦政府政策(及战时大订单)排除竞争者。当时官员不觉得这有问题,他们认为两党制能确保政治竞争,商业也该如此。
Perhaps dramatically so, if automation had decreased the need for some kind of work. And just as the mid-century model induced social as well as economic cohesion, its breakup brought social as well as economic fragmentation. People started to dress and act differently. Those who would later be called the "creative class" became more mobile. People who didn't care much for religion felt less pressure to go to church for appearances' sake, while those who liked it a lot opted for increasingly colorful forms. Some switched from meat loaf to tofu, and others to Hot Pockets. Some switched from driving Ford sedans to driving small imported cars, and others to driving SUVs. Kids who went to private schools or wished they did started to dress "preppy," and kids who wanted to seem rebellious made a conscious effort to look disreputable. In a hundred ways people spread apart. [20] Almost four decades later, fragmentation is still increasing. Has it been net good or bad? I don't know; the question may be unanswerable. Not entirely bad though. We take for granted the forms of fragmentation we like, and worry only about the ones we don't. But as someone who caught the tail end of mid-century _conformism_, I can tell you it was no utopia. [21] My goal here is not to say whether fragmentation has been good or bad, just to explain why it's happening. With the centripetal forces of total war and 20th century oligopoly mostly gone, what will happen next? And more specifically, is it possible to reverse some of the fragmentation we've seen? If it is, it will have to happen piecemeal. You can't reproduce mid-century cohesion the way it was originally produced. It would be insane to go to war just to induce more national unity.
随着政府意识到反竞争政策弊大于利,卡特政府时期开始解除管制。"放松管制"这个术语其实窄化了实质——这是"去寡头化"运动。航空旅行和长途电话服务是最明显的受益领域,价格在管制解除后大幅下降。
放松管制也助推1980年代敌意收购潮。过去企业效率的唯一约束是竞争对手同样低效,现在则面临绝对标准。任何上市公司若资产回报不足,管理层就可能被替换。新管理者常通过拆分公司释放价值。[17]
国民经济1.0版本由少数大集团构成,其关系由高管、政客、监管者和工会领袖在密室协商。2.0版本分辨率更高:更多不同规模的企业生产更差异化产品,关系变更更快。虽然密室谈判仍在,但更多交由市场决定——这进一步加速了碎片化。
And once you understand the degree to which the economic history of the 20th century was a low-res version 1, it's clear you can't reproduce that either. 20th century cohesion was something that happened at least in a sense naturally. The war was due mostly to external forces, and the Duplo economy was an evolutionary phase. If you want cohesion now, you'd have to induce it deliberately. And it's not obvious how. I suspect the best we'll be able to do is address the symptoms of fragmentation. But that may be enough. The form of fragmentation people worry most about lately is _economic inequality_, and if you want to eliminate that you're up against a truly formidable headwind that has been in operation since the stone age. Technology. Technology is a lever. It magnifies work. And the lever not only grows increasingly long, but the rate at which it grows is itself increasing. Which in turn means the variation in the amount of wealth people can create has not only been increasing, but accelerating. The unusual conditions that prevailed in the mid 20th century masked this underlying trend. The ambitious had little choice but to join large organizations that made them march in step with lots of other people — literally in the case of the armed forces, figuratively in the case of big corporations. Even if the big corporations had wanted to pay people proportionate to their value, they couldn't have figured out how. But that constraint has gone now. Ever since it started to erode in the 1970s, we've seen the underlying forces at work again. [22] Not everyone who gets rich now does it by creating wealth, certainly. But a significant number do, and the Baumol Effect means all their peers get dragged along too. [23] And as long as it's possible to get rich by creating wealth, the default tendency will be for economic inequality to increase. Even if you eliminate all the other ways to get rich.
用"版本"描述渐变过程略有误导,但20世纪后几十年的剧变确实造就了质变。1958年标普500成分股平均存续61年,到2012年仅为18年。[18]
积木经济瓦解与计算力普及同步发生。计算机在多大程度上是前提条件?这需要专著探讨。显然计算力是初创企业崛起的前提,我猜测也是金融领域多数变革的基础。但它是否全球化或杠杆收购的前提?虽不确定,但可能性不容忽视。或许碎片化复兴与计算机的关系,正如工业革命与蒸汽机。无论是否前提,计算机确实加速了这一进程。
企业流动性改变改变了员工关系。当企业阶梯可能突然抽离时,有志者开始将职业视为跨公司的跃迁而非单线攀登。更多流动(或潜在流动)带来薪资竞争,加之企业规模缩小使个人贡献更易量化,两者共同推动薪资趋向市场价。由于个体生产力差异巨大,按市场价支付自然导致收入分化。
You can mitigate this with subsidies at the bottom and taxes at the top, but unless taxes are high enough to discourage people from creating wealth, you're always going to be fighting a losing battle against increasing variation in productivity. [24] That form of fragmentation, like the others, is here to stay. Or rather, back to stay. Nothing is forever, but the tendency toward fragmentation should be more forever than most things, precisely because it's not due to any particular cause. It's simply a reversion to the mean. When Rockefeller said individualism was gone, he was right for a hundred years. It's back now, and that's likely to be true for longer. I worry that if we don't acknowledge this, we're headed for trouble. If we think 20th century cohesion disappeared because of few policy tweaks, we'll be deluded into thinking we can get it back (minus the bad parts, somehow) with a few countertweaks. And then we'll waste our time trying to eliminate fragmentation, when we'd be better off thinking about how to mitigate its consequences. Notes [1] Lester Thurow, writing in 1975, said the wage differentials prevailing at the end of World War II had become so embedded that they "were regarded as 'just' even after the egalitarian pressures of World War II had disappeared. Basically, the same differentials exist to this day, thirty years later." But Goldin and Margo think market forces in the postwar period also helped preserve the wartime compression of wages — specifically increased demand for unskilled workers, and oversupply of educated ones. (Oddly enough, the American custom of having employers pay for health insurance derives from efforts by businesses to circumvent NWLB wage controls in order to attract workers.) [2] As always, tax rates don't tell the whole story. There were lots of exemptions, especially for individuals.
"雅皮士"一词在1980年代初出现绝非偶然。这个如今司空见惯到无需提及的词汇,当时却标志着新现象:高收入的年轻专业人士。对当今二十多岁的青年,这根本不值得命名——年轻专业人士不该高收入吗?但1980年代前,职业生涯早期低薪正是专业身份的组成部分。雅皮士的新颖之处在于要求当前工作的市场价。
首批雅皮士并非初创企业员工(那属于未来),也不效力大公司,而是律师、金融、咨询等领域的专业人士。但他们的示范效应迅速蔓延——当同事看到新买的宝马325i,自然心生向往。早期职业低薪的前提是全员遵守,一旦有雇主破例,其他人被迫跟进。这个进程会席卷整个经济,因为职业初期不仅容易更换雇主,更能跨行业流动。
And in World War II the tax codes were so new that the government had little acquired immunity to tax avoidance. If the rich paid high taxes during the war it was more because they wanted to than because they had to. After the war, federal tax receipts as a percentage of GDP were about the same as they are now. In fact, for the entire period since the war, tax receipts have stayed close to 18% of GDP, despite dramatic changes in tax rates. The lowest point occurred when marginal income tax rates were highest: 14.1% in 1950. Looking at the data, it's hard to avoid the conclusion that tax rates have had little effect on what people actually paid. [3] Though in fact the decade preceding the war had been a time of unprecedented federal power, in response to the Depression. Which is not entirely a coincidence, because the Depression was one of the causes of the war. In many ways the New Deal was a sort of dress rehearsal for the measures the federal government took during wartime. The wartime versions were much more drastic and more pervasive though. As Anthony Badger wrote, "for many Americans the decisive change in their experiences came not with the New Deal but with World War II." [4] I don't know enough about the origins of the world wars to say, but it's not inconceivable they were connected to the rise of big corporations.
但并非所有年轻人都受益。高薪必须基于产出——首批雅皮士恰巧集中在产出易量化的领域。
更广泛地说,一个听起来过时的观念正在回归:致富可能。与过去相同,途径多种多样:有的创造财富,有的玩零和游戏。但一旦致富成为可能,有志者就必须做出选择。1990年选择物理而非华尔街的学者,正在做出1960年代学者无需考虑的牺牲。
这个观念甚至反噬大公司。如今CEO薪资暴涨,我认为主因是声望机制变化——1960年企业CEO是经济游戏唯一赢家,享有至高声望。若按当时实际薪资水平,他们在如今靠初创企业或对冲基金赚取数百万的运动员和天才少年面前将黯然失色。为免于此,CEO们竭力争取更高报酬。[19]
If that were the case, 20th century cohesion would have a single cause. [5] More precisely, there was a bimodal economy consisting, in Galbraith's words, of "the world of the technically dynamic, massively capitalized and highly organized corporations on the one hand and the hundreds of thousands of small and traditional proprietors on the other." Money, prestige, and power were concentrated in the former, and there was near zero crossover. [6] I wonder how much of the decline in families eating together was due to the decline in families watching TV together afterward. [7] I know when this happened because it was the season Dallas premiered. Everyone else was talking about what was happening on Dallas, and I had no idea what they meant. [8] I didn't realize it till I started doing research for this essay, but the meretriciousness of the products I grew up with is a well-known byproduct of oligopoly. When companies can't compete on price, they compete on tailfins. [9] Monroeville Mall was at the time of its completion in 1969 the largest in the country. In the late 1970s the movie _Dawn of the Dead_ was shot there. Apparently the mall was not just the location of the movie, but its inspiration; the crowds of shoppers drifting through this huge mall reminded George Romero of zombies. My first job was scooping ice cream in the Baskin-Robbins. [10] Labor unions were exempted from antitrust laws by the Clayton Antitrust Act in 1914 on the grounds that a person's work is not "a commodity or article of commerce." I wonder if that means service companies are also exempt. [11] The relationships between unions and unionized companies can even be symbiotic, because unions will exert political pressure to protect their hosts.
经济光谱另一端同样在分化。随着寡头垄断弱化,大公司更难转嫁成本,支付超额工资的意愿降低。当积木世界碎裂为不同规模企业(部分在海外),工会更难维持垄断。结果工人工资也趋向市场价——若工会曾有效履职,这个价格必然更低。若叠加自动化减少需求,降幅可能非常可观。
正如世纪中叶模式同时带来社会和经济凝聚力,其瓦解也引发双重碎片化。人们开始差异化着装行事,后来被称为"创意阶层"的群体流动性增强。对宗教无感者不再为形象去教堂,虔诚者则选择更狂热的形态。有人改吃 tofu,有人选择 Hot Pockets;有人开进口小车,有人选SUV;私立学校学生(或向往者)穿"预科生"风格,追求叛逆者刻意衣衫不整。百种方式,各奔东西。[20]
According to Michael Lind, when politicians tried to attack the A&P supermarket chain because it was putting local grocery stores out of business, "A&P successfully defended itself by allowing the unionization of its workforce in 1938, thereby gaining organized labor as a constituency." I've seen this phenomenon myself: hotel unions are responsible for more of the political pressure against Airbnb than hotel companies. [12] Galbraith was clearly puzzled that corporate executives would work so hard to make money for other people (the shareholders) instead of themselves. He devoted much of _The New Industrial State_ to trying to figure this out. His theory was that professionalism had replaced money as a motive, and that modern corporate executives were, like (good) scientists, motivated less by financial rewards than by the desire to do good work and thereby earn the respect of their peers. There is something in this, though I think lack of movement between companies combined with self-interest explains much of observed behavior. [13] Galbraith (p. 94) says a 1952 study of the 800 highest paid executives at 300 big corporations found that three quarters of them had been with their company for more than 20 years. [14] It seems likely that in the first third of the 20th century executive salaries were low partly because companies then were more dependent on banks, who would have disapproved if executives got too much. This was certainly true in the beginning. The first big company CEOs were J. P. Morgan's hired hands. Companies didn't start to finance themselves with retained earnings till the 1920s. Till then they had to pay out their earnings in dividends, and so depended on banks for capital for expansion. Bankers continued to sit on corporate boards till the Glass-Steagall act in 1933. By mid-century big companies funded 3/4 of their growth from earnings.
近四十年后,碎片化仍在加剧。这是好是坏?或许无解,但绝非全坏。我们总将喜欢的碎片化视为理所当然,只担忧不喜欢的部分。但作为亲历世纪中叶[循规蹈矩]尾声的人,我可以作证那绝非乌托邦。[21]
本文目标并非评判碎片化好坏,而是解释其成因。随着总体战和20世纪寡头垄断这两种向心力式微,未来会怎样?更具体地说,能否逆转部分碎片化?
若可能,也只会零敲碎打。我们无法复制世纪中叶的凝聚力形成机制——为促进国家团结而发动战争简直疯狂;一旦理解20世纪经济史本质上是低分辨率的1.0版本,就更清楚其不可复制性。
But the early years of bank dependence, reinforced by the financial controls of World War II, must have had a big effect on social conventions about executive salaries. So it may be that the lack of movement between companies was as much the effect of low salaries as the cause. Incidentally, the switch in the 1920s to financing growth with retained earnings was one cause of the 1929 crash. The banks now had to find someone else to lend to, so they made more margin loans. [15] Even now it's hard to get them to. One of the things I find hardest to get into the heads of would-be startup founders is how important it is to do certain kinds of menial work early in the life of a company. Doing _things that don't scale_ is to how Henry Ford got started as a high-fiber diet is to the traditional peasant's diet: they had no choice but to do the right thing, while we have to make a conscious effort. [16] Founders weren't celebrated in the press when I was a kid. "Our founder" meant a photograph of a severe-looking man with a walrus mustache and a wing collar who had died decades ago. The thing to be when I was a kid was an _executive_. If you weren't around then it's hard to grasp the cachet that term had. The fancy version of everything was called the "executive" model. [17] The wave of hostile takeovers in the 1980s was enabled by a combination of circumstances: court decisions striking down state anti-takeover laws, starting with the Supreme Court's 1982 decision in Edgar v.
20世纪的凝聚力在某种意义上自然形成。战争主要源于外力,积木经济则是进化阶段。若想重建凝聚力,必须有意识引导——而这绝非易事。我们最多只能缓解碎片化的症状,但这可能已足够。
近来最受关注的碎片化形式是[经济不平等],若想消除它,你将面对自石器时代就存在的强劲逆风:技术。
技术是杠杆,能放大工作成果。这个杠杆不仅越来越长,其增长速率本身也在加快。这意味着人们创造财富的差异不仅在扩大,更在加速扩大。20世纪中叶的特殊条件掩盖了这个趋势——有志者只能加入大组织,与众人统一步调(军队是字面意义,企业是比喻意义)。即便大公司想按价值付薪,也无力测算。如今约束已消失,自1970年代开始侵蚀以来,底层力量重新显现。[22]
MITE Corp.; the Reagan administration's comparatively sympathetic attitude toward takeovers; the Depository Institutions Act of 1982, which allowed banks and savings and loans to buy corporate bonds; a new SEC rule issued in 1982 (rule 415) that made it possible to bring corporate bonds to market faster; the creation of the junk bond business by Michael Milken; a vogue for conglomerates in the preceding period that caused many companies to be combined that never should have been; a decade of inflation that left many public companies trading below the value of their assets; and not least, the increasing complacency of managements. [18] Foster, Richard. "Creative Destruction Whips through Corporate America." Innosight, February 2012. [19] CEOs of big companies may be overpaid. I don't know enough about big companies to say. But it is certainly not impossible for a CEO to make 200x as much difference to a company's revenues as the average employee. Look at what Steve Jobs did for Apple when he came back as CEO. It would have been a good deal for the board to give him 95% of the company. Apple's market cap the day Steve came back in July 1997 was 1.73 billion. 5% of Apple now (January 2016) would be worth about 30 billion. And it would not be if Steve hadn't come back; Apple probably wouldn't even exist anymore. Merely including Steve in the sample might be enough to answer the question of whether public company CEOs in the aggregate are overpaid. And that is not as facile a trick as it might seem, because the broader your holdings, the more the aggregate is what you care about. [20] The late 1960s were famous for social upheaval. But that was more rebellion (which can happen in any era if people are provoked sufficiently) than fragmentation. You're not seeing fragmentation unless you see people breaking off to both left and right. [21] Globally the trend has been in the other direction.
当然,并非所有当代富豪都靠创造财富致富。但相当数量确实如此,而鲍莫尔效应会带动整个群体。[23]只要创造财富能致富,经济不平等就会自然加剧——即便禁止其他致富途径。你可以通过补贴底层和征税顶层来缓解,但只要税率不足以抑制创造财富,与生产力差异扩大化的对抗就注定失败。[24]
这种碎片化与其他形式一样,将会持续。更准确地说,是回归持续。虽然永恒不存在,但碎片化趋势将比其他事物更接近永恒——正因它没有特定成因,只是均值回归。洛克菲勒说个人主义消亡时,他对了一百年。如今个人主义归来,这个状态可能持续更久。
While the US is becoming more fragmented, the world as a whole is becoming less fragmented, and mostly in good ways. [22] There were a handful of ways to make a fortune in the mid 20th century. The main one was drilling for oil, which was open to newcomers because it was not something big companies could dominate through economies of scale. How did individuals accumulate large fortunes in an era of such high taxes? Giant tax loopholes defended by two of the most powerful men in Congress, Sam Rayburn and Lyndon Johnson. But becoming a Texas oilman was not in 1950 something one could aspire to the way starting a startup or going to work on Wall Street were in 2000, because (a) there was a strong local component and (b) success depended so much on luck. [23] The Baumol Effect induced by startups is very visible in Silicon Valley. Google will pay people millions of dollars a year to keep them from leaving to start or join startups. [24] I'm not claiming variation in productivity is the only cause of economic inequality in the US. But it's a significant cause, and it will become as big a cause as it needs to, in the sense that if you ban other ways to get rich, people who want to get rich will use this route instead. Thanks to Sam Altman, Trevor Blackwell, Paul Buchheit, Patrick Collison, Ron Conway, Chris Dixon, Benedict Evans, Richard Florida, Ben Horowitz, Jessica Livingston, Robert Morris, Tim O'Reilly, Geoff Ralston, Max Roser, Alexia Tsotsis, and Qasar Younis for reading drafts of this. Max also told me about several valuable sources. Bibliography Allen, Frederick Lewis. _The Big Change_. Harper, 1952. Averitt, Robert. _The Dual Economy_. Norton, 1968. Badger, Anthony. _The New Deal_. Hill and Wang, 1989. Bainbridge, John. _The Super-Americans_. Doubleday, 1961. Beatty, Jack. _Collossus_. Broadway, 2001. Brinkley, Douglas. _Wheels for the World_. Viking, 2003. Brownleee, W.
我担心,若不承认这点,我们将陷入困境。若认为20世纪凝聚力只因少数政策调整而消失,就会妄想通过反向调整将其找回(同时莫名其妙地去除弊端)。届时我们将浪费时间对抗碎片化,而非思考如何缓解其后果。
注释 [1] 莱斯特·瑟罗在1975年指出,二战末期形成的工资差异已如此根深蒂固,以至于"即便在二战平等主义压力消失后仍被视为'公正'"。但戈尔丁和马戈认为战后市场力量也维持了工资压缩——特别是对非技术工人需求增加,受教育者供给过剩。 (奇怪的是,美国由雇主支付医保的惯例,正源于企业为规避国家战时劳工局工资管制吸引工人的策略。)
[22] 20世纪中叶有少数致富途径,主要是石油勘探——因大公司无法通过规模经济垄断而对新人开放。在高税率时代如何积累财富?依赖国会两大实权人物萨姆·雷伯恩和林登·约翰逊维护的巨大税法漏洞。 但1950年成为德州石油大亨不似2000年创办初创企业或进入华尔街那般可期,因为(a)地域限制强(b)成功极大依赖运气。
Elliot. _Federal Taxation in America_. Cambridge, 1996. Chandler, Alfred. _The Visible Hand_. Harvard, 1977. Chernow, Ron. _The House of Morgan_. Simon & Schuster, 1990. Chernow, Ron. _Titan: The Life of John D. Rockefeller_. Random House, 1998. Galbraith, John. _The New Industrial State_. Houghton Mifflin, 1967. Goldin, Claudia and Robert A. Margo. "The Great Compression: The Wage Structure in the United States at Mid-Century." NBER Working Paper 3817, 1991. Gordon, John. _An Empire of Wealth_. HarperCollins, 2004. Klein, Maury. _The Genesis of Industrial America, 1870-1920_. Cambridge, 2007. Lind, Michael. _Land of Promise_. HarperCollins, 2012. Mickelthwaite, John, and Adrian Wooldridge. _The Company_. Modern Library, 2003. Nasaw, David. _Andrew Carnegie_. Penguin, 2006. Sobel, Robert. _The Age of Giant Corporations_. Praeger, 1993. Thurow, Lester. _Generating Inequality: Mechanisms of Distribution_. Basic Books, 1975. Witte, John. _The Politics and Development of the Federal Income Tax_. Wisconsin, 1985. Related:
Too Many Elite American Men Are Obsessed With Work and Wealth.
[23] 初创企业引发的鲍莫尔效应在硅谷极为明显。谷歌愿支付数百万年薪防止员工离职创业或加入初创企业。
[24] 我并非主张生产力差异是美国经济不平等的唯一成因。但它是重要成因,且会按需成为足够大的成因——即若禁止其他致富途径,有意致富者将转向此路。
致谢 (略) 参考文献 (略) 相关阅读 (略)
January 2016 Life is short, as everyone knows. When I was a kid I used to wonder about this. Is life actually short, or are we really complaining about its finiteness? Would we be just as likely to feel life was short if we lived 10 times as long? Since there didn't seem any way to answer this question, I stopped wondering about it. Then I had kids. That gave me a way to answer the question, and the answer is that life actually is short. Having kids showed me how to convert a continuous quantity, time, into discrete quantities. You only get 52 weekends with your 2 year old. If Christmas-as-magic lasts from say ages 3 to 10, you only get to watch your child experience it 8 times. And while it's impossible to say what is a lot or a little of a continuous quantity like time, 8 is not a lot of something. If you had a handful of 8 peanuts, or a shelf of 8 books to choose from, the quantity would definitely seem limited, no matter what your lifespan was. Ok, so life actually is short. Does it make any difference to know that? It has for me. It means arguments of the form "Life is too short for x" have great force. It's not just a figure of speech to say that life is too short for something. It's not just a synonym for annoying. If you find yourself thinking that life is too short for something, you should try to eliminate it if you can. When I ask myself what I've found life is too short for, the word that pops into my head is "bullshit." I realize that answer is somewhat tautological. It's almost the definition of bullshit that it's the stuff that life is too short for. And yet bullshit does have a distinctive character. There's something fake about it. It's the junk food of experience. [1] If you ask yourself what you spend your time on that's bullshit, you probably already know the answer.
Unnecessary meetings, pointless disputes, bureaucracy, posturing, dealing with other people's mistakes, traffic jams, addictive but unrewarding pastimes. There are two ways this kind of thing gets into your life: it's either forced on you, or it tricks you. To some extent you have to put up with the bullshit forced on you by circumstances. You need to make money, and making money consists mostly of errands. Indeed, the law of supply and demand ensures that: the more rewarding some kind of work is, the cheaper people will do it. It may be that less bullshit is forced on you than you think, though. There has always been a stream of people who opt out of the default grind and go live somewhere where opportunities are fewer in the conventional sense, but life feels more authentic. This could become more common. You can do it on a smaller scale without moving. The amount of time you have to spend on bullshit varies between employers. Most large organizations (and many small ones) are steeped in it. But if you consciously prioritize bullshit avoidance over other factors like money and prestige, you can probably find employers that will waste less of your time. If you're a freelancer or a small company, you can do this at the level of individual customers. If you fire or avoid toxic customers, you can decrease the amount of bullshit in your life by more than you decrease your income. But while some amount of bullshit is inevitably forced on you, the bullshit that sneaks into your life by tricking you is no one's fault but your own. And yet the bullshit you choose may be harder to eliminate than the bullshit that's forced on you. Things that lure you into wasting your time have to be really good at tricking you. An example that will be familiar to a lot of people is arguing online. When someone contradicts you, they're in a sense attacking you. Sometimes pretty overtly. Your instinct when attacked is to defend yourself.
But like a lot of instincts, this one wasn't designed for the world we now live in. Counterintuitive as it feels, it's better most of the time not to defend yourself. Otherwise these people are literally taking your life. [2] Arguing online is only incidentally addictive. There are more dangerous things than that. As I've written before, one byproduct of technical progress is that things we like tend to become _more addictive_. Which means we will increasingly have to make a conscious effort to avoid addictions � to stand outside ourselves and ask "is this how I want to be spending my time?" As well as avoiding bullshit, one should actively seek out things that matter. But different things matter to different people, and most have to learn what matters to them. A few are lucky and realize early on that they love math or taking care of animals or writing, and then figure out a way to spend a lot of time doing it. But most people start out with a life that's a mix of things that matter and things that don't, and only gradually learn to distinguish between them. For the young especially, much of this confusion is induced by the artificial situations they find themselves in. In middle school and high school, what the other kids think of you seems the most important thing in the world. But when you ask adults what they got wrong at that age, nearly all say they cared too much what other kids thought of them. One heuristic for distinguishing stuff that matters is to ask yourself whether you'll care about it in the future. Fake stuff that matters usually has a sharp peak of seeming to matter. That's how it tricks you. The area under the curve is small, but its shape jabs into your consciousness like a pin. The things that matter aren't necessarily the ones people would call "important." Having coffee with a friend matters. You won't feel later like that was a waste of time.
One great thing about having small children is that they make you spend time on things that matter: them. They grab your sleeve as you're staring at your phone and say "will you play with me?" And odds are that is in fact the bullshit-minimizing option. If life is short, we should expect its shortness to take us by surprise. And that is just what tends to happen. You take things for granted, and then they're gone. You think you can always write that book, or climb that mountain, or whatever, and then you realize the window has closed. The saddest windows close when other people die. Their lives are short too. After my mother died, I wished I'd spent more time with her. I lived as if she'd always be there. And in her typical quiet way she encouraged that illusion. But an illusion it was. I think a lot of people make the same mistake I did. The usual way to avoid being taken by surprise by something is to be consciously aware of it. Back when life was more precarious, people used to be aware of death to a degree that would now seem a bit morbid. I'm not sure why, but it doesn't seem the right answer to be constantly reminding oneself of the grim reaper hovering at everyone's shoulder. Perhaps a better solution is to look at the problem from the other end. Cultivate a habit of impatience about the things you most want to do. Don't wait before climbing that mountain or writing that book or visiting your mother. You don't need to be constantly reminding yourself why you shouldn't wait. Just don't wait. I can think of two more things one does when one doesn't have much of something: try to get more of it, and savor what one has. Both make sense here. How you live affects how long you live. Most people could do better. Me among them. But you can probably get even more effect by paying closer attention to the time you have. It's easy to let the days rush by.
The "flow" that imaginative people love so much has a darker cousin that prevents you from pausing to savor life amid the daily slurry of errands and alarms. One of the most striking things I've read was not in a book, but the title of one: James Salter's _Burning the Days_. It is possible to slow time somewhat. I've gotten better at it. Kids help. When you have small children, there are a lot of moments so perfect that you can't help noticing. It does help too to feel that you've squeezed everything out of some experience. The reason I'm sad about my mother is not just that I miss her but that I think of all the things we could have done that we didn't. My oldest son will be 7 soon. And while I miss the 3 year old version of him, I at least don't have any regrets over what might have been. We had the best time a daddy and a 3 year old ever had. Relentlessly prune bullshit, don't wait to do things that matter, and savor the time you have. That's what you do when life is short. Notes [1] At first I didn't like it that the word that came to mind was one that had other meanings. But then I realized the other meanings are fairly closely related. Bullshit in the sense of things you waste your time on is a lot like intellectual bullshit. [2] I chose this example deliberately as a note to self. I get attacked a lot online. People tell the craziest lies about me. And I have so far done a pretty mediocre job of suppressing the natural human inclination to say "Hey, that's not true!" Thanks to Jessica Livingston and Geoff Ralston for reading drafts of this.
Korean Translation | Japanese Translation Chinese Translation.
2016年1月 人生苦短,这是众所周知的。小时候我常思考这个问题:人生是真的短暂,还是我们只是在抱怨生命的有限性?如果我们的寿命延长十倍,是否仍会感到人生短促? 由于似乎无法找到答案,我停止了这种思考。直到我有了孩子。这给了我解答这个问题的方法,而答案是:人生确实短暂。 养育孩子让我学会了如何将连续的时间量转化为离散的单元。你与两岁孩子共度的周末只有52次。如果"充满魔力的圣诞节"存在于3岁到10岁之间,你只能目睹孩子经历8次。虽然我们无法衡量连续的时间是多是少,但8次显然不算多。无论是手心里的8颗花生,还是书架上仅有的8本书可供选择,这个数量无疑都是有限的——无论你的寿命有多长。 好吧,人生确实短暂。认识到这一点有何意义? 对我而言意义重大。这意味着"生命太短,不值得为X浪费时间"这类论点具有强大的说服力。这不仅仅是修辞手法,也不仅仅是"令人烦恼"的同义词。当你发现自己在思考某件事不值得花费生命时,就应该尽力消除它。 当我自问哪些事情不值得耗费生命时,脑海中蹦出的词是"狗屁事"。我意识到这个答案有些同义反复。"狗屁事"的定义几乎就是"不值得浪费生命的事物"。但它确实具有鲜明特征——虚假性,堪称体验界的垃圾食品。[1] 如果你认真审视自己把时间浪费在哪些"狗屁事"上,答案可能早已心知肚明:不必要的会议、无意义的争论、官僚主义、装腔作势、处理他人错误、交通堵塞、令人上瘾却毫无收获的消遣。 这些事物通过两种方式侵入生活:被迫接受或受骗上当。某种程度上,你必须忍受环境强加的"狗屁事"。赚钱谋生本就充斥着各种杂务——供需定律决定了:越是令人愉悦的工作,报酬就越低。不过,你被迫承受的"狗屁事"可能比想象中少。总有人选择跳出既定轨道,前往传统机会更少但生活更真实的地方。这种选择或许会越来越普遍。 即使不搬家,也能在小范围内实现。不同雇主对"狗屁事"的时间要求差异显著。大多数大型组织(及许多小型机构)都深陷其中。但若你有意识地将"避免狗屁事"置于金钱和声望之上,很可能找到更珍惜你时间的雇主。 自由职业者或小公司可以在客户层面进行筛选。通过解约或规避问题客户,你能以小于收入降幅的比例大幅减少生活中的"狗屁事"。 虽然部分"狗屁事"难以避免,但那些通过欺骗潜入生活的"狗屁事"只能归咎于自己。更棘手的是,自选的"狗屁事"往往比被迫接受的更难消除——能诱使你浪费时间的事物必然深谙欺骗之道。网络论战就是典型例子:当有人反驳你时,本质上是在发起攻击。而人类的本能是自卫反击。但这个本能并不适应当今世界。反直觉的是,多数情况下不辩护才是更好的选择,否则这些人确实是在窃取你的生命。[2] 网络论战只是具有偶然成瘾性,更危险的事物比比皆是。正如我之前所写,技术进步带来的副产品就是我们喜爱的事物正变得_更容易上瘾_。这意味着我们必须越来越有意识地抵御诱惑——跳出自我询问:"这真是我想花费时间的方式吗?" 除了规避"狗屁事",还应主动追寻重要事物。但"重要"因人而异,多数人需要逐步摸索。少数幸运儿早早发现自己热爱数学、动物护理或写作,并找到全心投入的途径。但多数人最初的生活都是重要与不重要事物的混合体,只能慢慢学会区分。 对年轻人而言,这种困惑很大程度上源于所处的人为环境。在中学阶段,同龄人的看法似乎就是全世界最重要的事。但当你询问成年人当年的错误时,几乎所有人都表示过分在意他人看法。 区分重要事物的启发式方法是自问:"未来我还会在乎这个吗?"虚假重要的事物通常具有尖锐的重要性峰值——这正是其欺骗性的根源。曲线下面积很小,但其形状像尖刺般扎入意识。 重要事物未必是世人所谓的"重大事项"。与朋友喝咖啡就很重要——你永远不会觉得这是浪费时间。 养育幼儿的一大好处就是迫使你专注于重要事物:他们。当你盯着手机时,他们会拽着袖子说:"陪我玩好吗?"而这往往正是最小化"狗屁事"的选择。 既然生命短暂,我们就该预料到会被其短暂性突袭——事实正是如此。你把一切视为理所当然,直到它们消失。你以为总有时间写那本书、爬那座山,然后突然发现机会之窗已关闭。最悲伤的窗口是他人生命的终结。我母亲去世后,我多希望曾花更多时间陪伴她。我活得仿佛她永远会在那里——而她以特有的安静方式纵容着这种错觉。许多人犯着与我同样的错误。 避免突袭的常规方法是保持清醒认知。在生命更脆弱的年代,人们对死亡的觉察程度在现代人看来近乎病态。我不确定这是否正确解法——不断提醒自己死神在每个人肩头徘徊。或许更好的解决方案是从另一端看待问题:培养对最想做事物的迫切感。不要等待——无论是登山、写书还是探望母亲。无需不断说服自己为何不该等待,直接行动即可。 对于稀缺之物,我们通常采取两种策略:争取更多,或珍惜现有。两者在此都适用。 生活方式影响寿命长度——包括我在内的大多数人都能做得更好。 但更有效地利用现有时间可能收获更大。想象型人格钟爱的"心流"状态有个黑暗表亲——它让你在日常琐事与闹铃中无暇驻足品味生活。我读过最震撼的文字不是某本书的内容,而是书名:詹姆斯·索特的《燃烧岁月》。 某种程度上可以延缓时间感知——我在这方面有所进步。孩子帮助很大:养育幼儿时,总有许多完美瞬间让你不由自主地驻足凝视。 充分榨取体验价值也有效果。我对母亲的哀伤不仅源于思念,更源于那些未竟之事。长子即将七岁——虽然我怀念他三岁的模样,但至少毫无遗憾。我们度过了父子间最美好的三年时光。 毫不留情地剔除"狗屁事",及时做重要之事,珍惜拥有.
January 2016 Since the 1970s, economic inequality in the US has increased dramatically. And in particular, the rich have gotten a lot richer. Nearly everyone who writes about the topic says that economic inequality should be decreased. I'm interested in this question because I was one of the founders of a company called Y Combinator that helps people start startups. Almost by definition, if a startup succeeds, its founders become rich. Which means by helping startup founders I've been helping to increase economic inequality. If economic inequality should be decreased, I shouldn't be helping founders. No one should be. But that doesn't sound right. What's going on here? What's going on is that while economic inequality is a single measure (or more precisely, two: variation in income, and variation in wealth), it has multiple causes. Many of these causes are bad, like tax loopholes and drug addiction. But some are good, like Larry Page and Sergey Brin starting the company you use to find things online. If you want to understand economic inequality — and more importantly, if you actually want to fix the bad aspects of it — you have to tease apart the components. And yet the trend in nearly everything written about the subject is to do the opposite: to squash together all the aspects of economic inequality as if it were a single phenomenon. Sometimes this is done for ideological reasons. Sometimes it's because the writer only has very high-level data and so draws conclusions from that, like the proverbial drunk who looks for his keys under the lamppost, instead of where he dropped them, because the light is better there. Sometimes it's because the writer doesn't understand critical aspects of inequality, like the role of technology in wealth creation.
2016年1月 自20世纪70年代以来,美国的经济不平等现象急剧加剧。尤其是富人的财富增长尤为显著。几乎所有探讨该话题的论述都认为应当缩小经济差距。 我对这个问题产生兴趣,是因为作为创业孵化器Y Combinator的创始人之一,我们致力于帮助创业者创立公司。从定义上说,初创企业若获得成功,其创始人必将跻身富裕阶层。这意味着我的工作实质上助推了经济不平等的扩大。如果真该缩小贫富差距,那我就不该扶持创业者——任何人都不该这样做。 但这显然有悖常理。问题出在哪里?关键在于:虽然经济不平等是单一指标(更准确说是两个指标:收入差异与财富差异),但其成因错综复杂。其中不乏负面因素,如税收漏洞与毒品成瘾;但也存在积极因素,例如拉里·佩奇和谢尔盖·布林创立了人们日常使用的搜索引擎。 若要真正理解经济不平等——更重要的是想要消除其弊端——就必须进行成因解构。然而当前绝大多数相关论述却反其道而行,将所有层面的不平等现象粗暴地混为一谈。 这种倾向有时源于意识形态,有时因为作者仅掌握宏观数据便妄下结论,就像醉汉只在路灯下找钥匙,只因那里光线更好;有时则源于作者对关键因素(如科技在财富创造中的作用)的认知缺失。多数情况下——或许绝大多数情况下——关于经济不平等的论述都同时兼具这三重缺陷。 ___ 人们对经济不平等最普遍的谬误,就是将其视为单一现象。其中最天真的版本莫过于"分饼谬论"——认为富人致富必然建立在掠夺穷人的基础上。 这种观点通常是先入为主的预设,而非基于证据的结论。有时这种谬论会被直白地表述为: > ......顶层群体正在攫取国民收入中越来越大的份额——他们侵占的份额如此之大,以至于其他人的所得相应减少......[1]
有时这种观念更为无意识。但无意识的形式极为普遍。我认为这是因为我们成长在一个"财富固定论"确实成立的世界里。对孩子而言,财富就是被分割的固定馅饼,如果有人多得,必然有人受损。需要有意识地提醒自己:现实世界并非如此运作。
Much of the time, perhaps most of the time, writing about economic inequality combines all three. ___ The most common mistake people make about economic inequality is to treat it as a single phenomenon. The most naive version of which is the one based on the pie fallacy: that the rich get rich by taking money from the poor. Usually this is an assumption people start from rather than a conclusion they arrive at by examining the evidence. Sometimes the pie fallacy is stated explicitly: > ...those at the top are grabbing an increasing fraction of the nation's income — so much of a larger share that what's left over for the rest is diminished.... [1].
在现实世界中,你既能创造财富,也能夺取他人财富。木匠创造财富——他制作椅子,你心甘情愿付钱购买;高频交易员则不然——他每赚一美元,交易另一端就有人亏损一美元。
若社会中的富人通过掠夺穷人致富,那就是经济不平等的极端案例,此时贫困与富有的根源相同。但并非所有不平等案例都属此类。如果一个木匠做了五把椅子而另一个寸木未动,后者收入较少并非因为有人夺走了他的财富。
Other times it's more unconscious. But the unconscious form is very widespread. I think because we grow up in a world where the pie fallacy is actually true. To kids, wealth _is_ a fixed pie that's shared out, and if one person gets more, it's at the expense of another. It takes a conscious effort to remind oneself that the real world doesn't work that way. In the real world you can create wealth as well as taking it from others. A woodworker creates wealth. He makes a chair, and you willingly give him money in return for it. A high-frequency trader does not. He makes a dollar only when someone on the other end of a trade loses a dollar. If the rich people in a society got that way by taking wealth from the poor, then you have the degenerate case of economic inequality, where the cause of poverty is the same as the cause of wealth. But instances of inequality don't have to be instances of the degenerate case. If one woodworker makes 5 chairs and another makes none, the second woodworker will have less money, but not because anyone took anything from him. Even people sophisticated enough to know about the pie fallacy are led toward it by the custom of describing economic inequality as a ratio of one quantile's income or wealth to another's. It's so easy to slip from talking about income shifting from one quantile to another, as a figure of speech, into believing that is literally what's happening. Except in the degenerate case, economic inequality can't be described by a ratio or even a curve. In the general case it consists of multiple ways people become poor, and multiple ways people become rich. Which means to understand economic inequality in a country, you have to go find individual people who are poor or rich and figure out why. [2] If you want to understand _change_ in economic inequality, you should ask what those people would have done when it was different.
即便深谙"财富固定论"谬误之人,也容易因习惯用分位数间的收入或财富比率来描述经济不平等而误入歧途。人们很容易从修辞层面的"收入转移"讨论,滑向字面意义的理解。
除极端案例外,经济不平等无法用比率甚至曲线描述。通常它包含多种致贫之道与致富之路。这意味着要理解一国的经济不平等,必须实地考察贫富个体的具体成因。
This is one way I know the rich aren't all getting richer simply from some new system for transferring wealth to them from everyone else. When you use the would-have method with startup founders, you find what most would have done _back in 1960_, when economic inequality was lower, was to join big companies or become professors. Before Mark Zuckerberg started Facebook, his default expectation was that he'd end up working at Microsoft. The reason he and most other startup founders are richer than they would have been in the mid 20th century is not because of some right turn the country took during the Reagan administration, but because progress in technology has made it much easier to start a new company that _grows fast_. Traditional economists seem strangely averse to studying individual humans. It seems to be a rule with them that everything has to start with statistics. So they give you very precise numbers about variation in wealth and income, then follow it with the most naive speculation about the underlying causes. But while there are a lot of people who get rich through rent-seeking of various forms, and a lot who get rich by playing zero-sum games, there are also a significant number who get rich by creating wealth. And creating wealth, as a source of economic inequality, is different from taking it — not just morally, but also practically, in the sense that it is harder to eradicate. One reason is that variation in productivity is accelerating. The rate at which individuals can create wealth depends on the technology available to them, and that grows exponentially. The other reason creating wealth is such a tenacious source of inequality is that it can expand to accommodate a lot of people. ___ I'm all for shutting down the crooked ways to get rich.
若要理解经济不平等的变迁,就该探究这些人在不同时期的选择。据此我确信,富人财富增长并非全因新式财富转移机制。用"假设回溯法"分析初创企业创始人会发现,在1960年代经济更平等时期,他们大多会选择入职大公司或成为教授。扎克伯格创立Facebook前,默认预期是在微软工作。他与众多创业者比20世纪中叶更富有的原因,并非里根政府的政策转向,而是技术进步极大降低了创建高速成长企业的门槛。
传统经济学家似乎莫名抗拒个案研究,执意从统计数据出发。他们提供精确的财富收入差异数据,却对根本原因给出极其幼稚的推测。
But that won't eliminate great variations in wealth, because as long as you leave open the option of getting rich by creating wealth, people who want to get rich will do that instead. Most people who get rich tend to be fairly driven. Whatever their other flaws, laziness is usually not one of them. Suppose new policies make it hard to make a fortune in finance. Does it seem plausible that the people who currently go into finance to make their fortunes will continue to do so, but be content to work for ordinary salaries? The reason they go into finance is not because they love finance but because they want to get rich. If the only way left to get rich is to start startups, they'll start startups. They'll do well at it too, because determination is the main factor in the success of a startup. [3] And while it would probably be a good thing for the world if people who wanted to get rich switched from playing zero-sum games to creating wealth, that would not only not eliminate great variations in wealth, but might even exacerbate them. In a zero-sum game there is at least a limit to the upside. Plus a lot of the new startups would create new technology that further accelerated variation in productivity. Variation in productivity is far from the only source of economic inequality, but it is the irreducible core of it, in the sense that you'll have that left when you eliminate all other sources. And if you do, that core will be big, because it will have expanded to include the efforts of all the refugees. Plus it will have a large Baumol penumbra around it: anyone who could get rich by creating wealth on their own account will have to be paid enough to prevent them from doing it. You can't prevent great variations in wealth without preventing people from getting rich, and you can't do that without preventing them from starting startups. So let's be clear about that. Eliminating great variations in wealth would mean eliminating startups.
尽管不少人通过寻租或零和博弈致富,仍有相当数量通过创造财富实现。作为不平等根源,创造财富与掠夺财富存在本质差异——不仅是道德层面,更体现在其难以根除的特性。一方面,生产力差异正在加速扩大:个人创造财富的能力取决于可用技术,而技术呈指数增长;另一方面,财富创造能容纳大量参与者,使其成为顽固的不平等源头。
我完全支持封堵邪门歪道的致富途径。但这无法消除巨大财富差异,因为只要保留通过创造财富致富的选项,逐利者自会转向此道。
And that doesn't seem a wise move. Especially since it would only mean you eliminated startups in your own country. Ambitious people already move halfway around the world to further their careers, and startups can operate from anywhere nowadays. So if you made it impossible to get rich by creating wealth in your country, people who wanted to do that would just leave and do it somewhere else. Which would certainly get you a lower Gini coefficient, along with a lesson in being careful what you ask for. [4] I think rising economic inequality is the inevitable fate of countries that don't choose something worse. We had a 40 year stretch in the middle of the 20th century that convinced some people otherwise. But as I explained in _The Refragmentation_, that was an anomaly — a unique combination of circumstances that compressed American society not just economically but culturally too. [5] And while some of the growth in economic inequality we've seen since then has been due to bad behavior of various kinds, there has simultaneously been a huge increase in individuals' ability to create wealth. Startups are almost entirely a product of this period. And even within the startup world, there has been a qualitative change in the last 10 years. Technology has decreased the cost of starting a startup so much that founders now have the upper hand over investors. Founders get less diluted, and it is now common for them to retain _board control_ as well. Both further increase economic inequality, the former because founders own more stock, and the latter because, as investors have learned, founders tend to be better at running their companies than investors. While the surface manifestations change, the underlying forces are very, very old. The acceleration of productivity we see in Silicon Valley has been happening for thousands of years. If you look at the history of stone tools, technology was already accelerating in the Mesolithic.
多数致富者往往动力十足。懒惰通常不在其缺点之列。假设新政策使金融业难获暴利,现有从业者会甘于普通薪资吗?他们进入金融业本为求富,若创业成为唯一途径,自会转向创业。决心是创业成功的关键要素,他们很可能表现出色。尽管这对世界或是好事——将人才从零和博弈导向财富创造,但这不仅不会缩小财富差距,反而可能扩大。零和游戏至少存在收益上限,而众多新创企业将催生加速生产力差异的新技术。
生产力差异远非经济不平等的唯一根源,却是不可削减的核心——消除其他因素后它依然存在。届时这个核心将异常庞大,因为它已吸纳所有"转型者"的努力,周围还会形成庞大的"鲍莫尔阴影":任何能独立创造财富者,都需获得足够报酬以阻止其行动。
The acceleration would have been too slow to perceive in one lifetime. Such is the nature of the leftmost part of an exponential curve. But it was the same curve. You do not want to design your society in a way that's incompatible with this curve. The evolution of technology is one of the most powerful forces in history. Louis Brandeis said "We may have democracy, or we may have wealth concentrated in the hands of a few, but we can't have both." That sounds plausible. But if I have to choose between ignoring him and ignoring an exponential curve that has been operating for thousands of years, I'll bet on the curve. Ignoring any trend that has been operating for thousands of years is dangerous. But exponential growth, especially, tends to bite you. ___ If accelerating variation in productivity is always going to produce some baseline growth in economic inequality, it would be a good idea to spend some time thinking about that future. Can you have a healthy society with great variation in wealth? What would it look like? Notice how novel it feels to think about that. The public conversation so far has been exclusively about the need to decrease economic inequality. We've barely given a thought to how to live with it. I'm hopeful we'll be able to. Brandeis was a product of the Gilded Age, and things have changed since then. It's harder to hide wrongdoing now. And to get rich now you don't have to buy politicians the way railroad or oil magnates did. [6] The great concentrations of wealth I see around me in Silicon Valley don't seem to be destroying democracy. There are lots of things wrong with the US that have economic inequality as a symptom. We should fix those things. In the process we may decrease economic inequality. But we can't start from the symptom and hope to fix the underlying causes. [7] The most obvious is poverty.
要阻止巨大财富差异,必须阻止人们致富;要阻止致富,必须扼杀创业。因此必须明确:消除财富差异即意味着消灭初创企业。这绝非明智之举,尤其考虑到它只会导致本国创业活动外流。雄心勃勃者早已为事业远渡重洋,现代初创企业可立足任何地域。若在本国阻断创造财富的致富途径,逐梦者自会另觅他处。这确实能降低基尼系数,同时也将带来"求仁得仁"的深刻教训。
我认为经济不平等加剧是未选择更糟道路国家的必然命运。20世纪中叶的40年曾让人产生错觉,但正如《再分化》所言,那是社会在特殊条件下经济文化双重压缩的异常期。
I'm sure most of those who want to decrease economic inequality want to do it mainly to help the poor, not to hurt the rich. [8] Indeed, a good number are merely being sloppy by speaking of decreasing economic inequality when what they mean is decreasing poverty. But this is a situation where it would be good to be precise about what we want. Poverty and economic inequality are not identical. When the city is turning off your _water_ because you can't pay the bill, it doesn't make any difference what Larry Page's net worth is compared to yours. He might only be a few times richer than you, and it would still be just as much of a problem that your water was getting turned off. Closely related to poverty is lack of social mobility. I've seen this myself: you don't have to grow up rich or even upper middle class to get rich as a startup founder, but few successful founders grew up desperately poor. But again, the problem here is not simply economic inequality. There is an enormous difference in wealth between the household Larry Page grew up in and that of a successful startup founder, but that didn't prevent him from joining their ranks. It's not economic inequality per se that's blocking social mobility, but some specific combination of things that go wrong when kids grow up sufficiently poor. One of the most important principles in Silicon Valley is that "you make what you measure." It means that if you pick some number to focus on, it will tend to improve, but that you have to choose the right number, because only the one you choose will improve; another that seems conceptually adjacent might not. For example, if you're a university president and you decide to focus on graduation rates, then you'll improve graduation rates. But only graduation rates, not how much students learn.
虽然此后部分不平等增长源于各类不良行为,但个人创造财富的能力也实现了巨大飞跃。初创企业几乎全是这一时期的产物。即便在创业领域,过去十年也发生了质变:技术极大降低创业成本,创始人如今已掌握对投资人的优势——股权稀释更少,董事会控制权保留更普遍。二者都加剧经济不平等:前者因创始人持股更多,后者因实践证明创始人更擅运营企业。
尽管表象更迭,底层力量却亘古未变。硅谷展现的生产力加速已持续数千年。纵观石器工具史,中石器时代技术已在加速。这种加速在个体生命周期中难以察觉——这正是指数曲线左端的特性,但本质仍是同一条曲线。
Students could learn less, if to improve graduation rates you made classes easier. Economic inequality is sufficiently far from identical with the various problems that have it as a symptom that we'll probably only hit whichever of the two we aim at. If we aim at economic inequality, we won't fix these problems. So I say let's aim at the problems. For example, let's attack poverty, and if necessary damage wealth in the process. That's much more likely to work than attacking wealth in the hope that you will thereby fix poverty. [9] And if there are people getting rich by tricking consumers or lobbying the government for anti-competitive regulations or tax loopholes, then let's stop them. Not because it's causing economic inequality, but because it's stealing. [10] If all you have is statistics, it seems like that's what you need to fix. But behind a broad statistical measure like economic inequality there are some things that are good and some that are bad, some that are historical trends with immense momentum and others that are random accidents. If we want to fix the world behind the statistics, we have to understand it, and focus our efforts where they'll do the most good. Notes [1] Stiglitz, Joseph. _The Price of Inequality_. Norton, 2012. p. 32. [2] Particularly since economic inequality is a matter of outliers, and outliers are disproportionately likely to have gotten where they are by ways that have little do with the sort of things economists usually think about, like wages and productivity, but rather by, say, ending up on the wrong side of the "War on Drugs." [3] Determination is the most important factor in deciding between success and failure, which in startups tend to be sharply differentiated. But it takes more than determination to create one of the hugely successful startups.
设计社会制度时不可违背这条曲线。技术演进是历史上最强大的力量之一。布兰代斯曾言:"我们要么选择民主,要么选择财富集中于少数人之手,但不可兼得。"此言听似有理。但若要在无视先贤与无视千年指数曲线间抉择,我押注后者。忽视任何千年趋势都危险,尤其指数增长更会反噬。
若生产力差异加速必然导致经济不平等基线上升,我们就该认真思考未来图景:财富差异巨大的社会能否健康运转?其形态如何?
Though most founders start out excited about the idea of getting rich, purely mercenary founders will usually take one of the big acquisition offers most successful startups get on the way up. The founders who go on to the next stage tend to be driven by a sense of mission. They have the same attachment to their companies that an artist or writer has to their work. But it is very hard to predict at the outset which founders will do that. It's not simply a function of their initial attitude. Starting a company changes people. [4] After reading a draft of this essay, Richard Florida told me how he had once talked to a group of Europeans "who said they wanted to make Europe more entrepreneurial and more like Silicon Valley. I said by definition this will give you more inequality. They thought I was insane — they could not process it." [5] Economic inequality has been decreasing globally. But this is mainly due to the erosion of the kleptocracies that formerly dominated all the poorer countries. Once the playing field is leveler politically, we'll see economic inequality start to rise again. The US is the bellwether. The situation we face here, the rest of the world will sooner or later. [6] Some people still get rich by buying politicians. My point is that it's no longer a precondition. [7] As well as problems that have economic inequality as a symptom, there are those that have it as a cause. But in most if not all, economic inequality is not the primary cause. There is usually some injustice that is allowing economic inequality to turn into other forms of inequality, and that injustice is what we need to fix. For example, the police in the US treat the poor worse than the rich. But the solution is not to make people richer. It's to make the police treat people more equitably.
值得注意的是这种思考的新颖性。迄今公共讨论始终聚焦如何减少不平等,却鲜少探讨如何与之共存。
我持乐观态度。布兰代斯是镀金时代产物,如今时过境迁:恶行更难隐匿,致富不再依赖铁路大亨式的政客收买。硅谷的巨大财富集聚似乎并未摧毁民主。
Otherwise they'll continue to maltreat people who are weak in other ways. [8] Some who read this essay will say that I'm clueless or even being deliberately misleading by focusing so much on the richer end of economic inequality — that economic inequality is really about poverty. But that is exactly the point I'm making, though sloppier language than I'd use to make it. The real problem is poverty, not economic inequality. And if you conflate them you're aiming at the wrong target. Others will say I'm clueless or being misleading by focusing on people who get rich by creating wealth — that startups aren't the problem, but corrupt practices in finance, healthcare, and so on. Once again, that is exactly my point. The problem is not economic inequality, but those specific abuses. It's a strange task to write an essay about why something isn't the problem, but that's the situation you find yourself in when so many people mistakenly think it is. [9] Particularly since many causes of poverty are only partially driven by people trying to make money from them. For example, America's abnormally high incarceration rate is a major cause of poverty. But although _for-profit prison companies_ and _prison guard unions_ both spend a lot lobbying for harsh sentencing laws, they are not the original source of them. [10] Incidentally, tax loopholes are definitely not a product of some power shift due to recent increases in economic inequality. The golden age of economic equality in the mid 20th century was also the golden age of tax avoidance. Indeed, it was so widespread and so effective that I'm skeptical whether economic inequality was really so low then as we think.
美国诸多问题以经济不平等为表象,我们应根治这些问题。过程中或能缓解不平等,但若从表象入手则难触及根源。最显著的是贫困问题——多数主张减少不平等者实为济贫而非劫富。确实不少人将"减少贫困"误称为"减少不平等",但此时精确表述尤为重要。贫困与不平等本质不同:当城市因欠费切断你家供水时,拉里·佩奇的净资产与你何干?即便他只比你富裕数倍,断水问题依然同样严峻。
与社会流动性缺失密切相关。我亲见:创业致富无需出身富贵,但成功创始人极少来自赤贫家庭。但这仍非单纯不平等问题。佩奇的成长环境与成功创业者存在巨大财富差距,却未阻碍他跻身其列。阻碍流动性的不是不平等本身,而是极端贫困导致的特定问题组合。
In a period when people are trying to hide wealth from the government, it will tend to be hidden from statistics too. One sign of the potential magnitude of the problem is the discrepancy between government receipts as a percentage of GDP, which have remained more or less constant during the entire period from the end of World War II to the present, and tax rates, which have varied dramatically. Thanks to Sam Altman, Tiffani Ashley Bell, Patrick Collison, Ron Conway, Richard Florida, Ben Horowitz, Jessica Livingston, Robert Morris, Tim O'Reilly, Max Roser, and Alexia Tsotsis for reading drafts of this. Note: This is a new version from which I removed a pair of metaphors that made a lot of people mad, essentially by macroexpanding them. If anyone wants to see the old version, I put it _here_. Related:
The Short Version | A Reply to Ezra Klein A Reply to Russell Okung | French Translation.
硅谷重要准则"衡量什么就得到什么"揭示:聚焦特定指标会促其改善,但必须选对指标——唯有被选中的指标才会提升,概念相邻者未必。例如大学校长若聚焦毕业率,毕业率必升,但学生所学知识未必增加——降低课程难度虽提升毕业率,却可能减少学习成效。
经济不平等与诸多以其为表象的问题相去甚远,我们很可能仅能击中瞄准的目标。若瞄准不平等,这些问题将无法解决。因此我主张直击问题本身:例如主攻贫困问题,必要时不惜在此过程中损伤财富。这比指望通过打击财富来解决贫困更可能奏效。对于通过欺诈消费者、游说政府制定反竞争法规或钻税法漏洞致富者,我们要阻止——非因加剧不平等,而是因其本质即盗窃。
若仅掌握统计数据,似乎只能修正数据。但经济不平等这类宏观统计指标背后,善恶并存:既有历史洪流,也有随机偶然。要改变统计数字背后的世界,必须理解其本质,将力量用于最有效之处。
November 2015 A few months ago an article about Y Combinator said that early on it had been a "one-man show." It's sadly common to read that sort of thing. But the problem with that description is not just that it's unfair. It's also misleading. Much of what's most novel about YC is due to Jessica Livingston. If you don't understand her, you don't understand YC. So let me tell you a little about Jessica. YC had 4 founders. Jessica and I decided one night to start it, and the next day we recruited my friends Robert Morris and Trevor Blackwell. Jessica and I ran YC day to day, and Robert and Trevor read applications and did interviews with us. Jessica and I were already dating when we started YC. At first we tried to act "professional" about this, meaning we tried to conceal it. In retrospect that seems ridiculous, and we soon dropped the pretense. And the fact that Jessica and I were a couple is a big part of what made YC what it was. YC felt like a family. The founders early on were mostly young. We all had dinner together once a week, cooked for the first couple years by me. Our first building had been a private home. The overall atmosphere was shockingly different from a VC's office on Sand Hill Road, in a way that was entirely for the better. There was an authenticity that everyone who walked in could sense. And that didn't just mean that people trusted us. It was the perfect quality to instill in startups. Authenticity is one of the most important things YC looks for in founders, not just because fakers and opportunists are annoying, but because authenticity is one of the main things that separates the most successful startups from the rest. Early YC was a family, and Jessica was its mom. And the culture she defined was one of YC's most important innovations. Culture is important in any organization, but at YC culture wasn't just how we behaved when we built the product. At YC, the culture was the product.
几个月前,一篇关于Y Combinator的文章称早期它曾是"一人秀"。这种说法屡见不鲜令人遗憾。但问题不仅在于这种描述有失公允——更在于它具有误导性。YC最具创新性的特质大多源自杰西卡·利文斯顿。若不了解她,就无法真正理解YC。请允许我向你们介绍这位非凡的女性。
YC由四位创始人共同创立。那个决定命运的夜晚,我与杰西卡萌生创业念头,次日便邀请好友罗伯特·莫里斯和特雷弗·布莱克韦尔加入。日常运营由我和杰西卡负责,罗伯特与特雷弗则参与申请审核和项目面试。
创办YC时我们已是恋人。起初我们试图维持"专业形象"——即隐瞒关系,如今回想实在荒谬,这种伪装很快被摒弃。正是我们的伴侣关系塑造了YC独特气质:这里像个大家庭。早期创始人多年轻有为,每周共享家庭晚餐(头两年由我掌勺),办公场所由民宅改造,与沙丘路上那些风投机构的冰冷氛围形成鲜明对比。每位访客都能感受到这份真诚,这不仅赢得信任,更为初创企业注入珍贵特质。真实性是YC筛选创始人的核心标准,不仅因厌恶投机者,更因这是区分顶级创业者的关键要素。
早期的YC是个大家庭,杰西卡则是这个家的母亲。她塑造的文化是YC最重要的创新之一。对任何组织而言文化都至关重要,但对YC而言,文化本身就是产品。
Jessica was also the mom in another sense: she had the last word. Everything we did as an organization went through her first — who to fund, what to say to the public, how to deal with other companies, who to hire, everything. Before we had kids, YC was more or less our life. There was no real distinction between working hours and not. We talked about YC all the time. And while there might be some businesses that it would be tedious to let infect your private life, we liked it. We'd started YC because it was something we were interested in. And some of the problems we were trying to solve were endlessly difficult. How do you recognize good founders? You could talk about that for years, and we did; we still do. I'm better at some things than Jessica, and she's better at some things than me. One of the things she's best at is judging people. She's one of those rare individuals with x-ray vision for character. She can see through any kind of faker almost immediately. Her nickname within YC was the Social Radar, and this special power of hers was critical in making YC what it is. The earlier you pick startups, the more you're picking the founders. Later stage investors get to try products and look at growth numbers. At the stage where YC invests, there is often neither a product nor any numbers. Others thought YC had some special insight about the future of technology. Mostly we had the same sort of insight Socrates claimed: we at least knew we knew nothing. What made YC successful was being able to pick good founders. We thought Airbnb was a bad idea. We funded it because we liked the founders. During interviews, Robert and Trevor and I would pepper the applicants with technical questions. Jessica would mostly watch. A lot of the applicants probably read her as some kind of secretary, especially early on, because she was the one who'd go out and get each new group and she didn't ask many questions. She was ok with that.
杰西卡的"母亲"角色还有另一层含义:她握有最终决定权。所有重大决策——投资对象、公开声明、商业合作、人员聘用——都必须经由她首肯。
在孩子出生前,YC就是我们生活的全部。工作与生活没有明确界限,我们时刻讨论YC事务。虽然有些事业会侵蚀私人生活,但我们乐在其中。创办YC源于共同兴趣,而我们试图解决的某些问题具有永恒挑战性:如何识别优秀创始人?这个议题我们探讨了多年,至今仍在继续。
我们各有所长。杰西卡最出众的能力是识人——她拥有透视人格的X光眼,能瞬间识破伪装。在YC内部,她的绰号是"社交雷达",这项天赋对YC的成功至关重要。投资阶段越早,对创始人的判断就越关键。后期投资者可以评估产品和增长数据,而YC投资阶段往往两者皆无。
外界以为YC拥有预判科技未来的能力,实则我们像苏格拉底那样自知无知。YC的成功源于挑选优秀创始人的能力。我们曾认为Airbnb是个糟糕点子,但因其创始人素质而决定投资。
It was easier for her to watch people if they didn't notice her. But after the interview, the three of us would turn to Jessica and ask "What does the Social Radar say?" [1] Having the Social Radar at interviews wasn't just how we picked founders who'd be successful. It was also how we picked founders who were good people. At first we did this because we couldn't help it. Imagine what it would feel like to have x-ray vision for character. Being around bad people would be intolerable. So we'd refuse to fund founders whose characters we had doubts about even if we thought they'd be successful. Though we initially did this out of self-indulgence, it turned out to be very valuable to YC. We didn't realize it in the beginning, but the people we were picking would become the YC alumni network. And once we picked them, unless they did something really egregious, they were going to be part of it for life. Some now think YC's alumni network is its most valuable feature. I personally think YC's advice is pretty good too, but the alumni network is certainly among the most valuable features. The level of trust and helpfulness is remarkable for a group of such size. And Jessica is the main reason why. (As we later learned, it probably cost us little to reject people whose characters we had doubts about, because how good founders are and how well they do are _not orthogonal_. If bad founders succeed at all, they tend to sell early. The most successful founders are almost all good.) If Jessica was so important to YC, why don't more people realize it? Partly because I'm a writer, and writers always get disproportionate attention. YC's brand was initially my brand, and our applicants were people who'd read my essays. But there is another reason: Jessica hates attention. Talking to reporters makes her nervous. The thought of giving a talk paralyzes her.
面试时,罗伯特、特雷弗和我会连珠炮般提出技术问题,杰西卡则静观其变。许多申请人误以为她是秘书(尤其早期),因为她负责引导面试者且很少提问。她乐见这种误解——不被注意更利于观察。但面试结束后,我们三人总会转向她:"社交雷达显示什么?"[1]
"社交雷达"不仅帮我们挑选成功者,更筛选品行端正者。最初这么做是出于本能——想象拥有透视人格能力的人如何忍受与心术不正者共事?因此我们拒绝投资任何品行存疑的创始人,哪怕他们可能成功。
这个看似任性的决定后来成为YC最宝贵的财富。我们起初并未意识到,这些被选中者将构成YC校友网络的核心。如今许多人认为校友网络是YC最有价值的资产(我个人认为YC的咨询同样出色)。这个庞大群体间的高度信任与互助精神,主要归功于杰西卡。
(后来我们认识到,拒绝品行不端者几乎不会造成损失,因为创始人品质与成就呈正相关。恶劣的创始人若侥幸成功往往会提前套现,而顶级创业者几乎都是品行高尚者。)
She was even uncomfortable at our wedding, because the bride is always the center of attention. [2] It's not just because she's shy that she hates attention, but because it throws off the Social Radar. She can't be herself. You can't watch people when everyone is watching you. Another reason attention worries her is that she hates bragging. In anything she does that's publicly visible, her biggest fear (after the obvious fear that it will be bad) is that it will seem ostentatious. She says being too modest is a common problem for women. But in her case it goes beyond that. She has a horror of ostentation so visceral it's almost a phobia. She also hates fighting. She can't do it; she just shuts down. And unfortunately there is a good deal of fighting in being the public face of an organization. So although Jessica more than anyone made YC unique, the very qualities that enabled her to do it mean she tends to get written out of YC's history. Everyone buys this story that PG started YC and his wife just kind of helped. Even YC's haters buy it. A couple years ago when people were attacking us for not funding more female founders (than exist), they all treated YC as identical with PG. It would have spoiled the narrative to acknowledge Jessica's central role at YC. Jessica was boiling mad that people were accusing _her_ company of sexism. I've never seen her angrier about anything. But she did not contradict them. Not publicly. In private there was a great deal of profanity. And she wrote three separate essays about the question of female founders. But she could never bring herself to publish any of them. She'd seen the level of vitriol in this debate, and she shrank from engaging. [3] It wasn't just because she disliked fighting. She's so sensitive to character that it repels her even to fight with dishonest people. The idea of mixing it up with linkbait journalists or Twitter trolls would seem to her not merely frightening, but disgusting.
既然杰西卡如此重要,为何外界知之甚少?部分原因在于我是作家身份吸引了过多关注,YC早期品牌与我的个人声望紧密相连。但更关键的是:杰西卡厌恶被关注。面对记者令她紧张,公开演讲让她恐惧,就连婚礼都令她不适——只因新娘注定成为焦点。[2]
这种排斥不仅源于害羞,更因关注会干扰"社交雷达"运转。当所有人注视你时,你便无法观察他人。
她厌恶关注的另一原因是痛恨自夸。在任何公开活动中,她最恐惧的(仅次于表现糟糕)就是显得浮夸。她认为过度谦逊是女性常见问题,但她的情况更为极端——对炫耀的厌恶已近乎病态。
她也极度回避冲突。作为组织代言人难免卷入争端,但她只会沉默以对。
But Jessica knew her example as a successful female founder would encourage more women to start companies, so last year she did something YC had never done before and hired a PR firm to get her some interviews. At one of the first she did, the reporter brushed aside her insights about startups and turned it into a sensationalistic story about how some guy had tried to chat her up as she was waiting outside the bar where they had arranged to meet. Jessica was mortified, partly because the guy had done nothing wrong, but more because the story treated her as a victim significant only for being a woman, rather than one of the most knowledgeable investors in the Valley. After that she told the PR firm to stop. You're not going to be hearing in the press about what Jessica has achieved. So let me tell you what Jessica has achieved. Y Combinator is fundamentally a nexus of people, like a university. It doesn't make a product. What defines it is the people. Jessica more than anyone curated and nurtured that collection of people. In that sense she literally made YC. Jessica knows more about the qualities of startup founders than anyone else ever has. Her immense data set and x-ray vision are the perfect storm in that respect. The qualities of the founders are the best predictor of how a startup will do. And startups are in turn the most important source of growth in mature economies. The person who knows the most about the most important factor in the growth of mature economies — that is who Jessica Livingston is.
因此,尽管杰西卡对YC的独特性贡献最大,正是这些特质使她常被历史叙述忽略。人们总相信"PG创立YC,妻子从旁协助"的叙事,连YC的批评者也不例外。当外界指责我们未资助更多女性创始人时,所有人都将YC等同于PG。承认杰西卡的核心地位会破坏他们的批判逻辑。
杰西卡对"她的公司被控性别歧视"暴怒不已——这是我见过她最愤怒的时刻。但她没有公开反驳,只在私下激烈抗议。她曾就女性创始人问题撰写三篇文章,最终都未发表——这场争论中的恶毒言辞令她望而却步。[3]
不仅因厌恶冲突,更因她对人格极度敏感,与不诚实者争辩令她作呕。想到要与标题党记者或网络喷子纠缠,她感到的不仅是恐惧更是恶心。
但杰西卡深知自己作为成功女性创始人的榜样力量,去年她突破自我聘请公关公司安排采访。首场访谈中,记者无视她对创业的深刻见解,反而大肆渲染她在酒吧外遭遇搭讪的八卦。这令她羞愧难当——不仅因对方并无过错,更因报道将她简化为"女性受害者",而非硅谷最具洞察力的投资人。
Doesn't that sound like someone who should be better known? Notes [1] Harj Taggar reminded me that while Jessica didn't ask many questions, they tended to be important ones: "She was always good at sniffing out any red flags about the team or their determination and disarmingly asking the right question, which usually revealed more than the founders realized." [2] Or more precisely, while she likes getting attention in the sense of getting credit for what she has done, she doesn't like getting attention in the sense of being watched in real time. Unfortunately, not just for her but for a lot of people, how much you get of the former depends a lot on how much you get of the latter. Incidentally, if you saw Jessica at a public event, you would never guess she hates attention, because (a) she is very polite and (b) when she's nervous, she expresses it by smiling more. [3] The existence of people like Jessica is not just something the mainstream media needs to learn to acknowledge, but something feminists need to learn to acknowledge as well. There are successful women who don't like to fight. Which means if the public conversation about women consists of fighting, their voices will be silenced. There's a sort of Gresham's Law of conversations. If a conversation reaches a certain level of incivility, the more thoughtful people start to leave. No one understands female founders better than Jessica. But it's unlikely anyone will ever hear her speak candidly about the topic. She ventured a toe in that water a while ago, and the reaction was so violent that she decided "never again." Thanks to Sam Altman, Paul Buchheit, Patrick Collison, Daniel Gackle, Carolynn Levy, Jon Levy, Kirsty Nathoo, Robert Morris, Geoff Ralston, and Harj Taggar for reading drafts of this. And yes, Jessica Livingston, who made me cut surprisingly little..
此后她立即终止了公关合作。
媒体不会告诉你杰西卡的真正成就:YC本质上是人际网络(如同大学),不生产具体产品。杰西卡比任何人都更精心培育了这个人才生态系统——从这个意义上说,她真正创造了YC。
杰西卡对初创创始人的理解前无古人。海量数据与透视人格的能力形成完美风暴。创始人素质是预测创业成败的最佳指标,而初创企业又是成熟经济体最重要的增长引擎。
这位掌握成熟经济体增长核心密码的智者——就是杰西卡·利文斯顿。难道她不配享有更高知名度吗?
注释 [1] 哈吉·塔加尔提醒我,杰西卡提问虽少但切中要害:"她总能嗅出团队隐患或决心不足,并以看似随意的问题揭示创始人未察觉的真相。" [2] 准确说,她渴望因成就获得认可,但厌恶被实时关注。不幸的是,前者往往依赖后者。 [3] 主流媒体与女权主义者都需认识:存在杰西卡这样厌恶斗争的成功女性。当公共讨论充满对抗,她们的声音就会消失。 谈话存在"格雷欣法则":当讨论变得粗鄙,深思者便会退出。没人比杰西卡更懂女性创始人,但世人恐难听到她对此的坦诚见解——试探性发言遭遇激烈反应后,她决定永远沉默。
October 2015 This will come as a surprise to a lot of people, but in some cases it's possible to detect bias in a selection process without knowing anything about the applicant pool. Which is exciting because among other things it means third parties can use this technique to detect bias whether those doing the selecting want them to or not. You can use this technique whenever (a) you have at least a random sample of the applicants that were selected, (b) their subsequent performance is measured, and (c) the groups of applicants you're comparing have roughly equal distribution of ability. How does it work? Think about what it means to be biased. What it means for a selection process to be biased against applicants of type x is that it's harder for them to make it through. Which means applicants of type x have to be better to get selected than applicants not of type x. [1] Which means applicants of type x who do make it through the selection process will outperform other successful applicants. And if the performance of all the successful applicants is measured, you'll know if they do. Of course, the test you use to measure performance must be a valid one. And in particular it must not be invalidated by the bias you're trying to measure. But there are some domains where performance can be measured, and in those detecting bias is straightforward. Want to know if the selection process was biased against some type of applicant? Check whether they outperform the others. This is not just a heuristic for detecting bias. It's what bias means. For example, many suspect that venture capital firms are biased against female founders. This would be easy to detect: among their portfolio companies, do startups with female founders outperform those without? A couple months ago, one VC firm (almost certainly unintentionally) published a study showing bias of this type.
许多人会对此感到惊讶,但在某些情况下,我们可以在不了解申请者群体任何信息的情况下,检测选拔过程中存在的偏见。这令人振奋,因为这意味着第三方可以使用这种方法来发现偏见,无论选拔者是否愿意接受监督。
这种方法的适用条件是:(a) 你至少拥有被选中者的随机样本,(b) 他们的后续表现可被量化,(c) 所比较的申请者群体在能力上大致呈同等分布。
其原理是什么?想想偏见意味着什么。选拔过程对x类申请者存在偏见,意味着他们更难通过筛选。也就是说,x类申请者必须比非x类申请者更优秀才能被选中[1]。因此,最终通过筛选的x类申请者将比其他成功申请者表现更出色。如果对所有成功申请者的表现进行测量,你就能验证这一点。
当然,所使用的表现测量方法必须有效,尤其不能因试图测量的偏见而失效。但在某些领域,表现是可量化的,此时偏见的检测就变得直接。想知道选拔过程是否对某类申请者存在偏见?只需检查他们是否表现更优。这不仅是检测偏见的启发式方法,更是偏见的本质定义。
例如,许多人怀疑风投公司对女性创始人存在偏见。这很容易验证:在其投资组合中,由女性创始的初创公司是否比男性创始的表现更好?几个月前,一家风投公司(几乎可以确定是无意间)发布的研究正揭示了这类偏见。First Round Capital发现,其投资组合中女性创始的初创公司比非女性创始的表现高出63%[2]。
First Round Capital found that among its portfolio companies, startups with female founders _outperformed_ those without by 63%. [2] The reason I began by saying that this technique would come as a surprise to many people is that we so rarely see analyses of this type. I'm sure it will come as a surprise to First Round that they performed one. I doubt anyone there realized that by limiting their sample to their own portfolio, they were producing a study not of startup trends but of their own biases when selecting companies. I predict we'll see this technique used more in the future. The information needed to conduct such studies is increasingly available. Data about who applies for things is usually closely guarded by the organizations selecting them, but nowadays data about who gets selected is often publicly available to anyone who takes the trouble to aggregate it. Notes [1] This technique wouldn't work if the selection process looked for different things from different types of applicants—for example, if an employer hired men based on their ability but women based on their appearance. [2] As Paul Buchheit points out, First Round excluded their most successful investment, Uber, from the study. And while it makes sense to exclude outliers from some types of studies, studies of returns from startup investing, which is all about hitting outliers, are not one of them. Thanks to Sam Altman, Jessica Livingston, and Geoff Ralston for reading drafts of this.
我最初说这种方法会让许多人惊讶,是因为我们很少见到此类分析。First Round公司恐怕也没意识到,当他们将样本限定为自己的投资组合时,所做的并非初创企业趋势研究,而是揭示了自身筛选公司时的偏见。
我预测未来会看到更多此类方法的应用。开展这类研究所需的信息正日益公开。虽然申请者数据通常被选拔机构严密保护,但如今被选中者的信息往往公开可查,只要有人愿意花功夫整合。
[1] 如果选拔过程对不同类型申请者采用不同标准(例如雇主根据能力选拔男性,却根据外貌选拔女性),此方法将失效。
[2] 正如Paul Buchheit所指出的,First Round在研究中最成功的投资案例Uber。虽然某些研究需要排除异常值,但初创企业投资回报研究本就以捕捉异常值为核心,显然不在此列。
致谢 Sam Altman、Jessica Livingston和Geoff Ralston对本文草稿的审阅。
October 2015 When I talk to a startup that's been operating for more than 8 or 9 months, the first thing I want to know is almost always the same. Assuming their expenses remain constant and their revenue growth is what it has been over the last several months, do they make it to profitability on the money they have left? Or to put it more dramatically, by default do they live or die? The startling thing is how often the founders themselves don't know. Half the founders I talk to don't know whether they're default alive or default dead. If you're among that number, Trevor Blackwell has made a handy _calculator_ you can use to find out. The reason I want to know first whether a startup is default alive or default dead is that the rest of the conversation depends on the answer. If the company is default alive, we can talk about ambitious new things they could do. If it's default dead, we probably need to talk about how to save it. We know the current trajectory ends badly. How can they get off that trajectory? Why do so few founders know whether they're default alive or default dead? Mainly, I think, because they're not used to asking that. It's not a question that makes sense to ask early on, any more than it makes sense to ask a 3 year old how he plans to support himself. But as the company grows older, the question switches from meaningless to critical. That kind of switch often takes people by surprise. I propose the following solution: instead of starting to ask too late whether you're default alive or default dead, start asking too early. It's hard to say precisely when the question switches polarity. But it's probably not that dangerous to start worrying too early that you're default dead, whereas it's very dangerous to start worrying too late. The reason is a phenomenon I wrote about earlier: the fatal pinch. The fatal pinch is default dead + slow growth + not enough time to fix it.
And the way founders end up in it is by not realizing that's where they're headed. There is another reason founders don't ask themselves whether they're default alive or default dead: they assume it will be easy to raise more money. But that assumption is often false, and worse still, the more you depend on it, the falser it becomes. Maybe it will help to separate facts from hopes. Instead of thinking of the future with vague optimism, explicitly separate the components. Say "We're default dead, but we're counting on investors to save us." Maybe as you say that, it will set off the same alarms in your head that it does in mine. And if you set off the alarms sufficiently early, you may be able to avoid the fatal pinch. It would be safe to be default dead if you could count on investors saving you. As a rule their interest is a function of growth. If you have steep revenue growth, say over 5x a year, you can start to count on investors being interested even if you're not profitable. [1] But investors are so fickle that you can never do more than start to count on them. Sometimes something about your business will spook investors even if your growth is great. So no matter how good your growth is, you can never safely treat fundraising as more than a plan A. You should always have a plan B as well: you should know (as in write down) precisely what you'll need to do to survive if you can't raise more money, and precisely when you'll have to switch to plan B if plan A isn't working. In any case, growing fast versus operating cheaply is far from the sharp dichotomy many founders assume it to be. In practice there is surprisingly little connection between how much a startup spends and how fast it grows. When a startup grows fast, it's usually because the product hits a nerve, in the sense of hitting some big need straight on.
When a startup spends a lot, it's usually because the product is expensive to develop or sell, or simply because they're wasteful. If you're paying attention, you'll be asking at this point not just how to avoid the fatal pinch, but how to avoid being default dead. That one is easy: don't hire too fast. Hiring too fast is by far the biggest killer of startups that raise money. [2] Founders tell themselves they need to hire in order to grow. But most err on the side of overestimating this need rather than underestimating it. Why? Partly because there's so much work to do. Naive founders think that if they can just hire enough people, it will all get done. Partly because successful startups have lots of employees, so it seems like that's what one does in order to be successful. In fact the large staffs of successful startups are probably more the effect of growth than the cause. And partly because when founders have slow growth they don't want to face what is usually the real reason: the product is not appealing enough. Plus founders who've just raised money are often encouraged to overhire by the VCs who funded them. Kill-or-cure strategies are optimal for VCs because they're protected by the portfolio effect. VCs want to blow you up, in one sense of the phrase or the other. But as a founder your incentives are different. You want above all to survive. [3] Here's a common way startups die. They make something moderately appealing and have decent initial growth. They raise their first round fairly easily, because the founders seem smart and the idea sounds plausible. But because the product is only moderately appealing, growth is ok but not great. The founders convince themselves that hiring a bunch of people is the way to boost growth. Their investors agree. But (because the product is only moderately appealing) the growth never comes. Now they're rapidly running out of runway. They hope further investment will save them.
But because they have high expenses and slow growth, they're now unappealing to investors. They're unable to raise more, and the company dies. What the company should have done is address the fundamental problem: that the product is only moderately appealing. Hiring people is rarely the way to fix that. More often than not it makes it harder. At this early stage, the product needs to evolve more than to be "built out," and that's usually easier with fewer people. [4] Asking whether you're default alive or default dead may save you from this. Maybe the alarm bells it sets off will counteract the forces that push you to overhire. Instead you'll be compelled to seek growth in other ways. For example, by _doing things that don't scale_, or by redesigning the product in the way only founders can. And for many if not most startups, these paths to growth will be the ones that actually work. Airbnb waited 4 months after raising money at the end of Y Combinator before they hired their first employee. In the meantime the founders were terribly overworked. But they were overworked evolving Airbnb into the astonishingly successful organism it is now. Notes [1] Steep usage growth will also interest investors. Revenue will ultimately be a constant multiple of usage, so x% usage growth predicts x% revenue growth. But in practice investors discount merely predicted revenue, so if you're measuring usage you need a higher growth rate to impress investors. [2] Startups that don't raise money are saved from hiring too fast because they can't afford to. But that doesn't mean you should avoid raising money in order to avoid this problem, any more than that total abstinence is the only way to avoid becoming an alcoholic. [3] I would not be surprised if VCs' tendency to push founders to overhire is not even in their own interest.
They don't know how many of the companies that get killed by overspending might have done well if they'd survived. My guess is a significant number. [4] After reading a draft, Sam Altman wrote: "I think you should make the hiring point more strongly. I think it's roughly correct to say that YC's most successful companies have never been the fastest to hire, and one of the marks of a great founder is being able to resist this urge." Paul Buchheit adds: "A related problem that I see a lot is premature scaling—founders take a small business that isn't really working (bad unit economics, typically) and then scale it up because they want impressive growth numbers. This is similar to over-hiring in that it makes the business much harder to fix once it's big, plus they are bleeding cash really fast." Thanks to Sam Altman, Paul Buchheit, Joe Gebbia, Jessica Livingston, and Geoff Ralston for reading drafts of this..
2015年10月 当我与运营超过8、9个月的初创公司交谈时,第一个问题几乎总是相同的。假设他们的开支保持不变,收入增长保持过去几个月的趋势,他们能否用剩余资金实现盈利?或者更戏剧化地说——按现状发展,这家公司会存活还是死亡? 令人惊讶的是,创始人自己往往对此一无所知。我接触的创始人中,有一半不清楚公司属于"默认存活"还是"默认死亡"。 如果你也处于这种状态,特雷弗·布莱克威尔制作了一个便捷的计算器来帮你判断。 我首先询问这个问题的原因在于,后续对话完全取决于答案。如果公司属于默认存活,我们可以讨论他们能尝试哪些雄心勃勃的新方向;如果是默认死亡,我们可能需要探讨如何挽救它。既然当前发展轨迹注定失败,该如何扭转局面? 为什么如此多的创始人对此毫无概念?我认为主要原因在于他们不习惯思考这个问题。早期提出这个问题毫无意义,就像询问三岁孩童如何谋生一样荒谬。但随着公司成长,这个问题会从无关紧要变成生死攸关——这种转变往往让人猝不及防。 我建议采用以下解决方案:与其过晚才开始思考这个问题,不如过早开始担忧。虽然很难精确判定何时该关注这个问题,但过早担心默认死亡的风险不大,而过晚察觉则极其危险。 这涉及我早先论述过的现象:死亡挤压。当企业陷入"默认死亡+增长缓慢+无足够时间扭转"的困境时,创始人往往因未能预见危机而深陷其中。 创始人忽视这个问题的另一个原因是:他们假定融资总是轻而易举。但这个假设往往错误,更糟的是,依赖程度越高,假设就越不成立。 或许应该将事实与期望明确区分。与其盲目乐观,不如清晰地拆分要素:"我们属于默认死亡,但指望投资者挽救我们。"说出这句话时,你脑中或许会和我一样警铃大作。若能及早触发警报,就可能避免死亡挤压。 如果能确保投资者施救,默认死亡本不足惧。通常投资者的兴趣与增长率成正比——若年收入增长率超过5倍,即便未盈利也能吸引投资。[1] 但投资者反复无常,永远不要过度依赖他们。有时即便增长强劲,某些业务问题仍会吓退投资者。因此无论增长多快,融资最多只能作为A计划,必须准备B计划:明确记录(书面)若融资失败时的生存方案,以及切换至B计划的具体时间节点。 事实上,"高速增长"与"低成本运营"远非创始人想象的非此即彼。实践中,初创公司的支出与增速关联度低得惊人。快速增长通常源于产品精准击中需求痛点;而高支出往往因产品开发/销售成本高昂,或纯粹源于浪费。 此时敏锐的读者不仅会思考如何避免死亡挤压,更会追问如何规避默认死亡状态。答案很简单:控制招聘节奏。过度招聘是融资型初创公司的头号杀手。[2] 创始人常认为扩张团队是增长的必要条件,但多数人高估而非低估这种需求。原因有三:一是海量工作使人产生"只要招人就能完成"的错觉;二是成功企业往往员工众多,使人误以为这是成功前提(实则团队规模更可能是增长的结果而非原因);三是当增长乏力时,创始人不愿直面真正原因——产品吸引力不足。 此外,刚获融资的创始人常被投资方鼓励过度招聘。对风投而言,"不成功便成仁"的策略最优——投资组合效应能对冲风险。风投希望你"爆发式增长"(无论哪种含义),但创始人的核心诉求是生存。[3] 以下是初创公司的典型死法:推出中等吸引力产品,获得尚可的初期增长→因创始人靠谱+想法可行轻松获得首轮融资→因产品平庸导致增长乏力→误以为扩招能刺激增长(投资方附和)→增长始终未达预期→资金快速耗尽→寄望新融资续命→高支出+低增长使投资者失去兴趣→融资失败→公司死亡。 真正该做的是解决根本问题:提升产品吸引力。扩招很少能解决这个问题,反而常使情况恶化。早期阶段产品需要进化而非扩张,小团队往往更高效。[4] 思考"默认存活或死亡"或许能避免这种结局。它触发的警报可能抑制过度招聘的冲动,迫使你寻求其他增长途径:例如采用不可扩展的手段,或像创始人那样重构产品。对多数初创公司而言,这些才是真正有效的增长之道。 Airbnb在YC毕业融资后等了4个月才招聘首位员工。期间创始人超负荷工作,但正是这种状态将Airbnb锻造成如今的商业奇迹。 注释 [1] 用户量激增同样吸引投资。虽然收入终将与使用量成正比,x%的使用增长预示x%的收入增长,但投资者对预期收入会打折评估,因此若以使用量为指标,需更高增长率才能打动他们。 [2] 未融资的初创公司因资金限制避免了过度招聘,但这不意味着应该为避免该问题而拒绝融资,正如戒酒并非预防酗酒的唯一途径。 [3] 风投推动过度招聘的行为可能甚至不符合其自身利益——无人知晓那些因挥霍而死的公司若存活会取得何等成就,我猜测这个数字相当可观。 [4] 山姆·奥尔特曼阅后批注:"应更强调招聘问题。YC最成功的公司从不是招聘最快的,能克制这种冲动是优秀创始人的特质。"保罗·布赫海特补充:"常见问题是过早扩张——创始人将未验证的小生意(通常单位经济效益差)盲目放大以求漂亮增长数据。这与过度招聘类似:既加大整改难度,又加速资金流失。" 致谢 山姆·奥尔特曼、保罗·布赫海特、乔·杰比亚、杰西卡·利文斯顿和杰夫·罗尔斯顿对本文初稿提出建议。.
October 2015 Here's a simple trick for getting more people to read what you write: write in spoken language. Something comes over most people when they start writing. They write in a different language than they'd use if they were talking to a friend. The sentence structure and even the words are different. No one uses "pen" as a verb in spoken English. You'd feel like an idiot using "pen" instead of "write" in a conversation with a friend. The last straw for me was a sentence I read a couple days ago: > The mercurial Spaniard himself declared: "After Altamira, all is decadence."
这里有一个让更多人阅读你文章的简单诀窍:用口语化的方式写作。
大多数人一开始写作就会变得奇怪。他们使用的语言与和朋友交谈时截然不同——句子结构甚至用词都变了。没人会在日常对话中用"pen"作动词。要是和朋友聊天时用"pen"代替"write",你自己都会觉得像个傻瓜。
压垮我的最后一根稻草是前几天看到的这句话:
> 这位善变的西班牙人亲自宣称:"阿尔塔米拉之后,一切尽是颓废。"
这段文字出自尼尔·奥利弗的《古不列颠史》。用这本书举例让我有些过意不去,因为它并不比其他许多书更糟。但试想一下,当你和朋友聊天时称毕加索为"那位善变的西班牙人"。哪怕只说这么一句,在对话中都会显得怪异。然而人们却用这种文风写出整本整本的书。
It's from Neil Oliver's _A History of Ancient Britain_. I feel bad making an example of this book, because it's no worse than lots of others. But just imagine calling Picasso "the mercurial Spaniard" when talking to a friend. Even one sentence of this would raise eyebrows in conversation. And yet people write whole books of it. Ok, so written and spoken language are different. Does that make written language worse? If you want people to read and understand what you write, yes. Written language is more complex, which makes it more work to read. It's also more formal and distant, which gives the reader's attention permission to drift. But perhaps worst of all, the complex sentences and fancy words give you, the writer, the false impression that you're saying more than you actually are. You don't need complex sentences to express complex ideas. When specialists in some abstruse topic talk to one another about ideas in their field, they don't use sentences any more complex than they do when talking about what to have for lunch. They use different words, certainly. But even those they use no more than necessary. And in my experience, the harder the subject, the more informally experts speak. Partly, I think, because they have less to prove, and partly because the harder the ideas you're talking about, the less you can afford to let language get in the way. Informal language is the athletic clothing of ideas. I'm not saying spoken language always works best. Poetry is as much music as text, so you can say things you wouldn't say in conversation. And there are a handful of writers who can get away with using fancy language in prose. And then of course there are cases where writers don't want to make it easy to understand what they're saying—in corporate announcements of bad news, for example, or at the more _bogus_ end of the humanities.
好吧,书面语和口语确实不同。但这是否意味着书面语更差劲呢?
如果你想让人读懂并理解你的文字,答案是肯定的。书面语更为复杂,读起来更费劲;它也更正式疏离,容易让读者走神。但最糟糕的或许是,那些复杂的句式与花哨的词汇会给写作者造成错觉,以为自己表达的内容比实际更丰富。
表达复杂思想并不需要复杂句式。当某个深奥领域的专家讨论专业问题时,他们使用的句子并不比讨论午餐吃什么更复杂。专业术语固然不同,但即便这些术语也绝不滥用。根据我的观察,话题越艰深,专家们的表达反而越随意。部分原因在于他们无需证明什么,更因为讨论的思想越深奥,就越不能让语言成为理解的障碍。
非正式语言是思想者的运动服。
我并非主张口语永远最佳。诗歌是文字更是音乐,自然可以突破日常对话的界限。也有少数作家能在散文中驾驭华丽辞藻。当然还存在故意让人难以理解的情况——比如企业发布坏消息时,或是人文领域那些[故作高深]的论述。但对绝大多数人而言,口语化表达更好。
多数人似乎很难用口语写作。或许最佳解决方案是:先按常规方式完成初稿,然后逐句自问"和朋友聊天时会这么说吗?"如果不会,就改用你会说的方式表达。久而久之,这种过滤机制会在写作时自动生效。当写下不符合口语的表达时,你甚至会听到文字落在纸上发出的刺耳声响。
But for nearly everyone else, spoken language is better. It seems to be hard for most people to write in spoken language. So perhaps the best solution is to write your first draft the way you usually would, then afterward look at each sentence and ask "Is this the way I'd say this if I were talking to a friend?" If it isn't, imagine what you would say, and use that instead. After a while this filter will start to operate as you write. When you write something you wouldn't say, you'll hear the clank as it hits the page. Before I publish a new essay, I read it out loud and fix everything that doesn't sound like conversation. I even fix bits that are phonetically awkward; I don't know if that's necessary, but it doesn't cost much. This trick may not always be enough. I've seen writing so far removed from spoken language that it couldn't be fixed sentence by sentence. For cases like that there's a more drastic solution. After writing the first draft, try explaining to a friend what you just wrote. Then replace the draft with what you said to your friend. People often tell me how much my essays sound like me talking. The fact that this seems worthy of comment shows how rarely people manage to write in spoken language. Otherwise everyone's writing would sound like them talking. If you simply manage to write in spoken language, you'll be ahead of 95% of writers. And it's so easy to do: just don't let a sentence through unless it's the way you'd say it to a friend. Thanks to Patrick Collison and Jessica Livingston for reading drafts of this.
August 2015 If you have a US startup called X and you don't have x.com, you should probably change your name. The reason is not just that people can't find you. For companies with mobile apps, especially, having the right domain name is not as critical as it used to be for getting users. The problem with not having the .com of your name is that it signals weakness. Unless you're so big that your reputation precedes you, a marginal domain suggests you're a marginal company. Whereas (as Stripe shows) having x.com signals strength even if it has no relation to what you do. Even good founders can be in denial about this. Their denial derives from two very powerful forces: identity, and lack of imagination. X is what we _are_ , founders think. There's no other name as good. Both of which are false. You can fix the first by stepping back from the problem. Imagine you'd called your company something else. If you had, surely you'd be just as attached to that name as you are to your current one. The idea of switching to your current name would seem repellent. [1] There's nothing intrinsically great about your current name. Nearly all your attachment to it comes from it being attached to you. [2] The way to neutralize the second source of denial, your inability to think of other potential names, is to acknowledge that you're bad at naming. Naming is a completely separate skill from those you need to be a good founder. You can be a great startup founder but hopeless at thinking of names for your company. Once you acknowledge that, you stop believing there is nothing else you could be called. There are lots of other potential names that are as good or better; you just can't think of them. How do you find them? One answer is the default way to solve problems you're bad at: find someone else who can think of names. But with company names there is another possible approach.
这是保罗·格雷厄姆(Paul Graham)《改名吧》文章的第1部分,共2部分。
It turns out almost any word or word pair that is not an obviously bad name is a sufficiently good one, and the number of such domains is so large that you can find plenty that are cheap or even untaken. So make a list and try to buy some. That's what Stripe did. (Their search also turned up parse.com, which their friends at Parse took.) The reason I know that naming companies is a distinct skill orthogonal to the others you need in a startup is that I happen to have it. Back when I was running YC and did more office hours with startups, I would often help them find new names. 80% of the time we could find at least one good name in a 20 minute office hour slot. Now when I do office hours I have to focus on more important questions, like what the company is doing. I tell them when they need to change their name. But I know the power of the forces that have them in their grip, so I know most won't listen. [3] There are of course examples of startups that have succeeded without having the .com of their name. There are startups that have succeeded despite any number of different mistakes. But this mistake is less excusable than most. It's something that can be fixed in a couple days if you have sufficient discipline to acknowledge the problem. 100% of the top 20 YC companies by valuation have the .com of their name. 94% of the top 50 do. But only 66% of companies in the current batch have the .com of their name.
Which suggests there are lessons ahead for most of the rest, one way or another. Notes [1] Incidentally, this thought experiment works for nationality and religion too. [2] The liking you have for a name that has become part of your identity manifests itself not directly, which would be easy to discount, but as a collection of specious beliefs about its intrinsic qualities. (This too is true of nationality and religion as well.) [3] Sometimes founders know it's a problem that they don't have the .com of their name, but delusion strikes a step later in the belief that they'll be able to buy it despite having no evidence it's for sale. Don't believe a domain is for sale unless the owner has already told you an asking price. Thanks to Sam Altman, Jessica Livingston, and Geoff Ralston for reading drafts of this..
原文:
2015年8月 如果你的美国初创公司名叫X却没有x.com域名,或许该考虑改名了。 问题不仅在于用户难以找到你。尤其对移动应用公司而言,拥有匹配域名已不像过去那样直接影响获客。真正关键的是:缺失.com域名会传递弱势信号。除非你已是声名显赫的大公司,否则寒酸的域名会让人联想到寒酸的企业。反观Stripe的案例——即便x.com与业务毫无关联,这个域名本身就在传递实力。 即便优秀的创始人也常对此视而不见,这种抗拒源于两种强大力量:身份认同与想象力匮乏。 创始人总认为"X就是我们本身""再没有更合适的名字了",两者皆谬。 破解前者需要跳出思维定式:假设当初用了其他名字,你现在同样会对其产生依恋,反而会觉得现有名字难以接受[1]。现有名字本无特殊意义,你的依恋纯粹源于长期使用形成的绑定[2]。 克服后者(想不出替代名)的关键,是承认自己不擅长命名。命名能力与创业能力截然不同,出色的创始人可能完全缺乏公司命名天赋。一旦认清这点,你就会明白:存在无数同等或更优的命名选择,只是你暂时没想到。 如何寻找好名字?常规解法是求助命名高手,但公司命名还有更简单的方式:几乎所有非明显糟糕的单词/词组组合都是可用之选,这类域名存量极大,完全能找到廉价甚至未注册的选项。Stripe就是这样操作的(他们甚至帮朋友发现了parse.com)。 我深知命名是独立技能,因为恰巧具备这种天赋。早年执掌YC时,我常在20分钟 office hours 里帮80%的初创公司找到合适新名。 如今 office hours 需聚焦更重要议题(如业务方向),我仍会指出改名需求。但深谙人性枷锁的力量,我知道多数人不会听从[3]。 当然存在未持有.com却成功的案例,就像存在各种错误却突围的企业。但域名问题本可在几天内解决——只要你足够清醒。 YC估值前20的企业100%持有.com,前50名中占94%。而当前批次仅有66%,意味着大多数公司终将以某种方式补上这一课。 注释 [1] 该思维实验同样适用于民族与宗教认同。 [2] 对已成为身份标识的名字的偏爱,会以对其"内在特质"的种种伪论证呈现(民族与宗教同理)。 [3] 有时创始人明知域名是短板,却幻想能随时收购——即便毫无出售迹象。切记:除非卖家明确报价,否则别指望购买可能性。 致谢 萨姆·奥尔特曼、杰西卡·利文斯顿和杰夫·拉尔斯顿审阅本文草稿。
August 2015 I recently got an email from a founder that helped me understand something important: why it's safe for startup founders to be nice people. I grew up with a cartoon idea of a very successful businessman (in the cartoon it was always a man): a rapacious, cigar-smoking, table-thumping guy in his fifties who wins by exercising power, and isn't too fussy about how. As I've written before, one of the things that has surprised me most about startups is how few of the most successful founders are like that. Maybe successful people in other industries are; I don't know; but not startup founders. [1] I knew this empirically, but I never saw the math of why till I got this founder's email. In it he said he worried that he was fundamentally soft-hearted and tended to give away too much for free. He thought perhaps he needed "a little dose of sociopath-ness." I told him not to worry about it, because so long as he built something good enough to spread by word of mouth, he'd have a superlinear growth curve. If he was bad at extracting money from people, at worst this curve would be some constant multiple less than 1 of what it might have been. But a constant multiple of any curve is exactly the same shape. The numbers on the Y axis are smaller, but the curve is just as steep, and when anything grows at the rate of a successful startup, the Y axis will take care of itself. Some examples will make this clear. Suppose your company is making $1000 a month now, and you've made something so great that it's growing at 5% a week. Two years from now, you'll be making about $160k a month. Now suppose you're so un-rapacious that you only extract half as much from your users as you could. That means two years later you'll be making $80k a month instead of $160k. How far behind are you? How long will it take to catch up with where you'd have been if you were extracting every penny? A mere 15 weeks.
最近收到一位创始人的邮件,让我想明白一个重要问题:为什么创业公司的创始人做个好人其实很安全。
我从小对超级成功商人的印象都来自卡通片(卡通里总是男性形象):一个五十多岁、贪婪成性、叼着雪茄、拍桌怒吼的家伙,靠滥用权势取胜,且不择手段。正如我之前写过的,创业领域最让我惊讶的事情之一,就是极少有顶级创始人是这类形象。也许其他行业的成功人士如此;我不确定;但创业创始人绝非如此。[1]
我凭经验知道这点,但直到收到这封邮件才真正理解其数学原理。这位创始人说他担心自己本性过于心软,总是免费给出太多东西。他觉得自己可能需要"一点点反社会人格特质"。
我告诉他不必担心,因为只要他做出足够优秀、能靠口碑传播的产品,就会获得超线性增长曲线。即使他不擅长从用户身上榨取金钱,最坏情况不过是这条曲线比理想值低一个固定倍数。但任何曲线的固定倍数依然保持原形状。纵轴数值虽小,曲线斜率不变,当增长速度达到成功创业公司的级别时,纵轴问题自会解决。
After two years, the un-rapacious founder is only 3.5 months behind the rapacious one. [2] If you're going to optimize a number, the one to choose is your growth rate. Suppose as before that you only extract half as much from users as you could, but that you're able to grow 6% a week instead of 5%. Now how are you doing compared to the rapacious founder after two years? You're already ahead—$214k a month versus $160k—and pulling away fast. In another year you'll be making $4.4 million a month to the rapacious founder's $2 million. Obviously one case where it would help to be rapacious is when growth depends on that. What makes startups different is that usually it doesn't. Startups usually win by making something so great that people recommend it to their friends. And being rapacious not only doesn't help you do that, but probably hurts. [3] The reason startup founders can safely be nice is that making great things is compounded, and rapacity isn't. So if you're a founder, here's a deal you can make with yourself that will both make you happy and make your company successful. Tell yourself you can be as nice as you want, so long as you work hard on your growth rate to compensate. Most successful startups make that tradeoff unconsciously. Maybe if you do it consciously you'll do it even better. Notes [1] Many think successful startup founders are driven by money. In fact the secret weapon of the most successful founders is that they aren't. If they were, they'd have taken one of the acquisition offers that every fast-growing startup gets on the way up.
举例说明会更清晰。假设你公司现在月入1000美元,产品足够出色以致每周增长5%。两年后你月收入将达16万美元。
若你因不够贪婪只能从用户身上获取半数收益,两年后月收入将是8万而非16万。你落后多少?需要多久能追上极致榨取的状态?仅需15周。两年后,不贪婪的创始人只比贪婪者落后3.5个月。[2]
若要优化某个数值,应该选择增长率。假设如前所述你只获取半数收益,但增长率提升至每周6%。两年后与贪婪者相比如何?你已实现反超——月入21.4万对16万——且差距正急速扩大。再过一年你将月入440万,而贪婪者仅200万。
显然,唯有一种情况贪婪能带来优势:当增长依赖于此。创业公司的特殊性在于,通常并不需要。创业公司往往通过打造令人惊叹的产品致胜,靠用户自发推荐。贪婪不仅无助于此,反而可能有害。[3]
创始人可以安心做好人的原因在于:创造伟大事物能产生复合效应,而贪婪不能。
What drives the most successful founders is the same thing that drives most people who make things: the company is their project. [2] In fact since 2 ≈ 1.05 ^ 15, the un-rapacious founder is always 15 weeks behind the rapacious one. [3] The other reason it might help to be good at squeezing money out of customers is that startups usually lose money at first, and making more per customer makes it easier to get to profitability before your initial funding runs out. But while it is very common for startups to die from running through their initial funding and then being unable to raise more, the underlying cause is usually slow growth or excessive spending rather than insufficient effort to extract money from existing customers. Thanks to Sam Altman, Harj Taggar, Jessica Livingston, and Geoff Ralston for reading drafts of this, and to Randall Bennett for being such a nice guy..
所以创业者们,这里有个两全其美的心理契约:你可以尽情善良,只要用更高的增长率来平衡。多数成功创业公司都在无意识中做了这个权衡。若有意识地执行,或许效果更佳。
[1] 许多人认为创业创始人受金钱驱动。实则最成功者的秘密武器恰是不为金钱所动。若真为利,他们早该接受那些高速成长公司必经之路上频繁出现的收购要约。顶尖创业者的驱动力与多数创造者相同:公司是他们倾注心血的杰作。
[2] 由于2≈1.05^15,不贪婪者始终落后贪婪者15周。
[3] 擅长榨取用户金钱的另一可能优势是:创业公司初期通常亏损,单客收益越高越容易在初始资金耗尽前盈利。但虽然初创企业常因资金枯竭又融资失败而死亡,根本原因通常是增长缓慢或过度开支,而非对现有用户榨取不足。
致谢 Sam Altman、Harj Taggar、Jessica Livingston和Geoff Ralston审阅了本文草稿,Randall Bennett则以身示范何为好人。
February 2015 One of the most valuable exercises you can try if you want to understand startups is to look at the most successful companies and explain why they were not as lame as they seemed when they first launched. Because they practically all seemed lame at first. Not just small, lame. Not just the first step up a big mountain. More like the first step into a swamp. A Basic interpreter for the Altair? How could that ever grow into a giant company? People sleeping on airbeds in strangers' apartments? A web site for college students to stalk one another? A wimpy little single-board computer for hobbyists that used a TV as a monitor? A new search engine, when there were already about 10, and they were all trying to de-emphasize search? These ideas didn't just seem small. They seemed wrong. They were the kind of ideas you could not merely ignore, but ridicule. Often the founders themselves didn't know why their ideas were promising. They were attracted to these ideas by instinct, because they were living in the future and they sensed that something was missing. But they could not have put into words exactly how their ugly ducklings were going to grow into big, beautiful swans. Most people's first impulse when they hear about a lame-sounding new startup idea is to make fun of it. Even a lot of people who should know better. When I encounter a startup with a lame-sounding idea, I ask "What Microsoft is this the Altair Basic of?" Now it's a puzzle, and the burden is on me to solve it. Sometimes I can't think of an answer, especially when the idea is a made-up one. But it's remarkable how often there does turn out to be an answer. Often it's one the founders themselves hadn't seen yet. Intriguingly, there are sometimes multiple answers. I talked to a startup a few days ago that could grow into 3 distinct Microsofts. They'd probably vary in size by orders of magnitude.
But you can never predict how big a Microsoft is going to be, so in cases like that I encourage founders to follow whichever path is most immediately exciting to them. Their instincts got them this far. Why stop now?.
2015年2月 若想理解初创企业,最具价值的练习之一就是观察那些最成功的公司,并解释为何它们在最初亮相时并不像表面看起来那般平庸。因为它们几乎在起步时都显得平庸。不仅是规模小,而是平庸。不仅是攀登大山的第一步,更像是踏入沼泽的第一步。 为Altair电脑开发BASIC解释器?这怎么可能成长为巨头公司?在陌生人公寓里睡充气床垫的大学生?供大学生互相窥探的网站?爱好者用电视机当显示器的简陋单板计算机?当市面上已有十多个搜索引擎且都在弱化搜索功能时,再做一个新搜索引擎?这些点子不仅显得渺小,更显得荒谬。它们正是那种你不仅会忽视,更会嘲笑的构想。 通常连创始人自己也不清楚这些点子的潜力所在。他们凭着本能被这些想法吸引,因为他们生活在未来,能感知到某些缺失的东西。但他们无法确切描述自己这些"丑小鸭"将如何蜕变为美丽的天鹅。 当大多数人听到一个听起来平庸的初创点子时,第一反应往往是嘲笑。甚至许多本该更懂行的人也不例外。 每当我遇到一个听起来平庸的初创项目,就会问:"这个项目的Altair Basic对应着怎样的微软?"这便成了一个谜题,而破解的责任在我。有时我找不到答案,特别是当这个点子纯属虚构时。但令人惊讶的是,多数情况下确实存在答案,而且往往是连创始人自己都尚未察觉的。 有趣的是,有时答案不止一个。几天前我接触的一个初创项目就可能发展成三个不同的"微软",规模可能相差数个量级。但你永远无法预测一个"微软"能长到多大,因此在这种情况下,我会建议创始人选择当下最令他们兴奋的路径。既然本能已指引他们至此,何必现在停下?
January 2015 Corporate Development, aka corp dev, is the group within companies that buys other companies. If you're talking to someone from corp dev, that's why, whether you realize it yet or not. It's usually a mistake to talk to corp dev unless (a) you want to sell your company right now and (b) you're sufficiently likely to get an offer at an acceptable price. In practice that means startups should only talk to corp dev when they're either doing really well or really badly. If you're doing really badly, meaning the company is about to die, you may as well talk to them, because you have nothing to lose. And if you're doing really well, you can safely talk to them, because you both know the price will have to be high, and if they show the slightest sign of wasting your time, you'll be confident enough to tell them to get lost. The danger is to companies in the middle. Particularly to young companies that are growing fast, but haven't been doing it for long enough to have grown big yet. It's usually a mistake for a promising company less than a year old even to talk to corp dev. But it's a mistake founders constantly make. When someone from corp dev wants to meet, the founders tell themselves they should at least find out what they want. Besides, they don't want to offend Big Company by refusing to meet. Well, I'll tell you what they want. They want to talk about buying you. That's what the title "corp dev" means. So before agreeing to meet with someone from corp dev, ask yourselves, "Do we want to sell the company right now?" And if the answer is no, tell them "Sorry, but we're focusing on growing the company." They won't be offended. And certainly the founders of Big Company won't be offended. If anything they'll think more highly of you. You'll remind them of themselves. They didn't sell either; that's why they're in a position now to buy other companies. [1] Most founders who get contacted by corp dev already know what it means.
2015年1月 企业开发部门(Corporate Development,简称corp dev)是公司内部负责收购其他公司的团队。当你与企业开发部门的人交谈时,无论你是否意识到,这就是原因所在。 除非(a)你希望立即出售公司,并且(b)你有足够把握以可接受的价格获得报价,否则与企业开发部门交谈通常是一个错误。实际上,这意味着初创公司只有在表现非常好或非常糟糕时才应该与他们接触。如果你的情况非常糟糕,即公司濒临倒闭,你不妨与他们谈谈,因为你没有什么可失去的。而如果你表现非常出色,你可以放心地与他们交谈,因为你们双方都知道价格必须很高,如果他们表现出丝毫浪费你时间的迹象,你会有足够的信心告诉他们滚开。 危险在于那些处于中间状态的公司,尤其是那些增长迅速但尚未发展壮大的年轻公司。对于一个成立不到一年的有前途的公司来说,与企业开发部门交谈通常是一个错误。 但这是创始人常犯的错误。当企业开发部门的人要求会面时,创始人会告诉自己至少应该了解一下对方的意图。此外,他们不想因为拒绝会面而得罪大公司。 好吧,我来告诉你他们的意图。他们想讨论收购你。这就是“企业开发”这个头衔的含义。因此,在同意与企业开发部门的人会面之前,先问问自己:“我们现在想出售公司吗?”如果答案是否定的,就告诉他们:“抱歉,我们正专注于公司的发展。”他们不会因此感到被冒犯。大公司的创始人当然也不会觉得被冒犯。相反,他们会更加看重你。你会让他们想起自己。他们也没有出售公司;这就是为什么他们现在有能力收购其他公司。[1] 大多数被企业开发部门联系的创始人已经知道这意味着什么。然而,即使他们知道企业开发部门的职责,也知道自己不想出售公司,他们仍然会接受会面。为什么?这与创始人犯下大多数错误时的心理如出一辙:否认和一厢情愿。与想要收购你的人交谈是一种恭维。谁知道呢,也许他们的报价会高得惊人。你至少应该看看报价是多少,对吧? 不。如果他们打算立即通过电子邮件发送报价,当然,你不妨打开看看。但与企业开发部门的对话并非如此。如果你最终收到报价,那将是在一个漫长且令人难以置信的分心过程之后。如果报价令人惊讶,那只会是低得惊人。 分心是初创公司最无法承受的事情。而与企业开发部门的对话是最糟糕的分心方式,因为它们不仅消耗你的注意力,还会削弱你的士气。在艰难过程中生存下来的一个诀窍就是不要停下来思考自己有多累。相反,你要进入一种心流状态。[2]想象一下,在马拉松的第20英里时,有人跑到你旁边说:“你一定很累了吧?要不要停下来休息一下?”与企业开发部门的对话就是这样,但更糟糕,因为停止的提议与你想象中的高价报价在你脑海中交织在一起。 然后你就真的陷入麻烦了。如果可能的话,企业开发部门的人喜欢扭转局面。他们希望让你处于试图说服他们收购的位置,而不是他们试图说服你出售。令人惊讶的是,他们经常成功。 这是一个非常危险的滑坡,滑道上涂抹着对创始人心智最具影响力的力量,而推动你滑下去的是一位经验丰富的专业人士,他的全职工作就是把你推下去。 他们推动你滑下坡的策略通常相当残酷。企业开发部门的人的全部工作就是收购公司,他们甚至无法选择目标。衡量他们表现的唯一标准是他们能以多低的价格收购你,而更有野心的人会不择手段地实现这一目标。例如,他们几乎总是以一个低报价开始,只是为了看看你是否会接受。即使你不接受,最初的低价也会打击你的士气,使你更容易被操纵。 而这只是他们策略中最无害的部分。等到你同意了一个价格并认为交易已经完成时,他们会回来说他们的老板否决了交易,只愿意支付约定价格的一半。这种事情屡见不鲜。如果你认为投资者的行为可能很糟糕,那么与企业开发部门的人相比简直是小巫见大巫。即使是那些在其他方面表现良好的公司的企业开发部门也是如此。 我记得有一次向一位在谷歌工作的朋友抱怨他们的企业开发部门对一家YC初创公司耍的花招。 我问:“‘不作恶’怎么了?” 他回答:“我觉得企业开发部门没收到这份备忘录。” 在并购对话中遇到的策略可能与你在硅谷这个相对正直的世界中经历的任何事情都不同。[3]这就像传统强盗大亨商业世界的一部分基因物质被融入了初创世界。 保护自己的最简单方法是使用约翰·D·洛克菲勒(他的祖父是个酒鬼)用来避免成为酒鬼的诀窍。他曾经在主日学校课堂上说: > 孩子们,你们知道我为什么从未成为酒鬼吗?因为我从未喝下第一口酒。
And yet even when they know what corp dev does and know they don't want to sell, they take the meeting. Why do they do it? The same mix of denial and wishful thinking that underlies most mistakes founders make. It's flattering to talk to someone who wants to buy you. And who knows, maybe their offer will be surprisingly high. You should at least see what it is, right? No. If they were going to send you an offer immediately by email, sure, you might as well open it. But that is not how conversations with corp dev work. If you get an offer at all, it will be at the end of a long and unbelievably distracting process. And if the offer is surprising, it will be surprisingly low. Distractions are the thing you can least afford in a startup. And conversations with corp dev are the worst sort of distraction, because as well as consuming your attention they undermine your morale. One of the tricks to surviving a grueling process is not to stop and think how tired you are. Instead you get into a sort of flow. [2] Imagine what it would do to you if at mile 20 of a marathon, someone ran up beside you and said "You must feel really tired. Would you like to stop and take a rest?" Conversations with corp dev are like that but worse, because the suggestion of stopping gets combined in your mind with the imaginary high price you think they'll offer. And then you're really in trouble. If they can, corp dev people like to turn the tables on you. They like to get you to the point where you're trying to convince them to buy instead of them trying to convince you to sell. And surprisingly often they succeed. This is a very slippery slope, greased with some of the most powerful forces that can work on founders' minds, and attended by an experienced professional whose full time job is to push you down it. Their tactics in pushing you down that slope are usually fairly brutal.
你现在就想卖掉公司吗?不是将来某天,而是现在立刻。如果答案是否定的,那就别去参加第一次会面。他们不会因此感到冒犯。而你则可以确保自己免于经历创业公司可能遭遇的最糟糕体验之一。
如果你确实有意出售,这里有一套专门的技巧可供参考。但创始人在与企业发展部门打交道时最常犯的错误,并非是在准备就绪时谈判失利,而是在尚未准备好时就过早接触。所以只要记住本文的标题,你就已经掌握了创业第一年关于并购最需要了解的核心要义。
Corp dev people's whole job is to buy companies, and they don't even get to choose which. The only way their performance is measured is by how cheaply they can buy you, and the more ambitious ones will stop at nothing to achieve that. For example, they'll almost always start with a lowball offer, just to see if you'll take it. Even if you don't, a low initial offer will demoralize you and make you easier to manipulate. And that is the most innocent of their tactics. Just wait till you've agreed on a price and think you have a done deal, and then they come back and say their boss has vetoed the deal and won't do it for more than half the agreed upon price. Happens all the time. If you think investors can behave badly, it's nothing compared to what corp dev people can do. Even corp dev people at companies that are otherwise benevolent. I remember once complaining to a friend at Google about some nasty trick their corp dev people had pulled on a YC startup. "What happened to Don't be Evil?" I asked. "I don't think corp dev got the memo," he replied. The tactics you encounter in M&A conversations can be like nothing you've experienced in the otherwise comparatively upstanding world of Silicon Valley. It's as if a chunk of genetic material from the old-fashioned robber baron business world got incorporated into the startup world. [3] The simplest way to protect yourself is to use the trick that John D. Rockefeller, whose grandfather was an alcoholic, used to protect himself from becoming one. He once told a Sunday school class > Boys, do you know why I never became a drunkard? Because I never took the first drink..
[1] 我并非主张永远不要出售公司。而是强调你必须明确自己是否真的想要出售,不要被操控手段或一厢情愿的想法诱导,做出比原计划更早出售的决定。
[2] 在创业过程中,就像大多数竞技体育一样,手头的任务几乎会自动帮你屏蔽疲惫感——你忙得根本无暇感受疲倦。但当这种保护机制消失时(比如终场哨响的瞬间),疲惫感会如浪潮般将你吞没。与企业发展部门接洽就如同在比赛中途主动卸下这种防护。
Do you want to sell your company right now? Not eventually, right now. If not, just don't take the first meeting. They won't be offended. And you in turn will be guaranteed to be spared one of the worst experiences that can happen to a startup. If you do want to sell, there's another set of techniques for doing that. But the biggest mistake founders make in dealing with corp dev is not doing a bad job of talking to them when they're ready to, but talking to them before they are. So if you remember only the title of this essay, you already know most of what you need to know about M&A in the first year. Notes [1] I'm not saying you should never sell. I'm saying you should be clear in your own mind about whether you want to sell or not, and not be led by manipulation or wishful thinking into trying to sell earlier than you otherwise would have. [2] In a startup, as in most competitive sports, the task at hand almost does this for you; you're too busy to feel tired. But when you lose that protection, e.g. at the final whistle, the fatigue hits you like a wave. To talk to corp dev is to let yourself feel it mid-game. [3] To be fair, the apparent misdeeds of corp dev people are magnified by the fact that they function as the face of a large organization that often doesn't know its own mind. Acquirers can be surprisingly indecisive about acquisitions, and their flakiness is indistinguishable from dishonesty by the time it filters down to you. Thanks to Marc Andreessen, Jessica Livingston, Geoff Ralston, and Qasar Younis for reading drafts of this.
[3] 平心而论,企业发展部门人员看似不当的行为,某种程度上是被他们作为大型机构代言人的身份放大了——这些机构往往自身都立场模糊。收购方在并购决策上的优柔寡断可能令人吃惊,而当这种反复无常传递到你这里时,其表现与欺诈几乎无法区分。
致谢 感谢马克·安德森、杰西卡·利文斯顿、杰夫·拉尔斯顿和卡萨尔·尤尼斯审阅本文草稿。
January 2015 My father is a mathematician. For most of my childhood he worked for Westinghouse, modelling nuclear reactors. He was one of those lucky people who know early on what they want to do. When you talk to him about his childhood, there's a clear watershed at about age 12, when he "got interested in maths." He grew up in the small Welsh seacoast town of Pwllheli. As we retraced his walk to school on Google Street View, he said that it had been nice growing up in the country. "Didn't it get boring when you got to be about 15?" I asked. "No," he said, "by then I was interested in maths." In another conversation he told me that what he really liked was solving problems. To me the exercises at the end of each chapter in a math textbook represent work, or at best a way to reinforce what you learned in that chapter. To him the problems were the reward. The text of each chapter was just some advice about solving them. He said that as soon as he got a new textbook he'd immediately work out all the problems — to the slight annoyance of his teacher, since the class was supposed to work through the book gradually. Few people know so early or so certainly what they want to work on. But talking to my father reminded me of a heuristic the rest of us can use. If something that seems like work to other people doesn't seem like work to you, that's something you're well suited for. For example, a lot of programmers I know, including me, actually like debugging. It's not something people tend to volunteer; one likes it the way one likes popping zits. But you may have to like debugging to like programming, considering the degree to which programming consists of it. The stranger your tastes seem to other people, the stronger evidence they probably are of what you should do. When I was in college I used to write papers for my friends. It was quite interesting to write a paper for a class I wasn't taking.
我的父亲是数学家。在我童年的大部分时间里,他都在西屋公司工作,负责核反应堆的建模。
他是那种很早就知道自己想做什么的幸运儿。当你和他聊起童年时,12岁左右是一个明显的分水岭,那时他“对数学产生了兴趣”。
他在威尔士海滨小镇普尔赫利长大。当我们在谷歌街景上重走他上学的路时,他说在乡村长大很美好。
“到了15岁左右,会不会觉得无聊?”我问道。
“不会,”他说,“那时我已经对数学着迷了。”
在另一次谈话中,他告诉我,他真正喜欢的是解决问题。对我来说,数学课本每章末尾的习题是任务,或者充其量是巩固所学知识的手段。但对他来说,那些问题本身就是奖励。每章的正文只是解决问题的建议。他说,一拿到新课本,他就会立刻做完所有习题——这让他的老师有点恼火,因为课程本应循序渐进。
Plus they were always so relieved. It seemed curious that the same task could be painful to one person and pleasant to another, but I didn't realize at the time what this imbalance implied, because I wasn't looking for it. I didn't realize how hard it can be to decide what you should work on, and that you sometimes have to figure it out from subtle clues, like a detective solving a case in a mystery novel. So I bet it would help a lot of people to ask themselves about this explicitly. What seems like work to other people that doesn't seem like work to you? Thanks to Sam Altman, Trevor Blackwell, Jessica Livingston, Robert Morris, and my father for reading drafts of this.
很少有人能这么早或这么明确地知道自己想做什么。但和父亲的谈话让我想起了一个我们其他人也能用的启发式方法:如果某件事对别人来说是工作,对你来说却不像工作,那你就很适合做这件事。例如,我认识的许多程序员,包括我自己,其实很喜欢调试。这不是人们会主动提起的事;喜欢调试就像喜欢挤痘痘一样。但考虑到编程中调试所占的比重,你可能得喜欢调试才能真正喜欢编程。
你的爱好在别人看来越奇怪,它们可能就越能证明你应该做什么。大学时,我常帮朋友写论文。为一门我没选修的课写论文很有意思,而且他们总是如释重负。
同一个任务对一个人来说是痛苦的,对另一个人却是愉快的,这似乎很奇怪,但当时我并没有意识到这种不平衡意味着什么,因为我没有去寻找答案。我没有意识到决定自己该做什么有多难,有时你必须像侦探破解悬疑小说中的案件一样,从微妙的线索中找出答案。所以我敢肯定,明确地问自己这个问题会对很多人有帮助:哪些对别人来说是工作的事,对你来说却不像工作?
感谢萨姆·奥尔特曼、特雷弗·布莱克威尔、杰西卡·利文斯顿、罗伯特·莫里斯,以及我的父亲阅读本文的草稿。
January 2015 No one, VC or angel, has invested in more of the top startups than Ron Conway. He knows what happened in every deal in the Valley, half the time because he arranged it. And yet he's a super nice guy. In fact, nice is not the word. Ronco is good. I know of zero instances in which he has behaved badly. It's hard even to imagine. When I first came to Silicon Valley I thought "How lucky that someone so powerful is so benevolent." But gradually I realized it wasn't luck. It was by being benevolent that Ronco became so powerful. All the deals he gets to invest in come to him through referrals. Google did. Facebook did. Twitter was a referral from Evan Williams himself. And the reason so many people refer deals to him is that he's proven himself to be a good guy. Good does not mean being a pushover. I would not want to face an angry Ronco. But if Ron's angry at you, it's because you did something wrong. Ron is so old school he's Old Testament. He will smite you in his just wrath, but there's no malice in it. In almost every domain there are advantages to seeming good. It makes people trust you. But actually being good is an expensive way to seem good. To an amoral person it might seem to be overkill. In some fields it might be, but apparently not in the startup world. Though plenty of investors are jerks, there is a clear trend among them: the most successful investors are also the most upstanding. [1] It was not always this way. I would not feel confident saying that about investors twenty years ago. What changed? The startup world became more transparent and more unpredictable. Both make it harder to seem good without actually being good. It's obvious why transparency has that effect. When an investor maltreats a founder now, it gets out. Maybe not all the way to the press, but other founders hear about it, and that investor starts to lose deals. [2] The effect of unpredictability is more subtle.
2015年1月 在顶级初创企业的投资名单上,无论是风投还是天使投资人,没有人能超越罗恩·康威。他知晓硅谷每一笔交易的来龙去脉,其中半数都经由他亲手促成。
然而他却是位超级好人。事实上,"好"这个字都不足以形容。罗恩是真正良善之人。据我所知,他从未有过任何不当行为,甚至难以想象这种情况。
初到硅谷时,我曾想:"如此位高权重之人竟如此仁厚,真是幸运。"但渐渐我意识到这不是运气。正是这份仁厚让罗恩获得了今日的权势。他参与的所有投资都来自引荐——谷歌如此,脸书如此,推特更是埃文·威廉姆斯亲自牵线。而众人争相为他引荐的原因,在于他用行动证明了自己值得信赖。
良善不意味着软弱可欺。我绝不愿面对盛怒的罗恩。但若他向你发怒,那必然是你行差踏错。罗恩的作风如此传统,简直像《旧约》中的先知——他会以正义之怒惩戒你,但绝无半点恶意。
几乎在所有领域,展现良善都能带来优势,它能赢得他人信任。但真正践行良善却是种昂贵的形象经营方式,在不讲道德者眼中或许显得矫枉过正。
在某些领域或许如此,但在初创企业界显然例外。尽管不乏品行低劣的投资人,但其中存在清晰趋势:最成功的投资者往往也最正直。[1]
二十年前我不敢如此断言投资者群体,但今时不同往日。
It increases the work of being inconsistent. If you're going to be two-faced, you have to know who you should be nice to and who you can get away with being nasty to. In the startup world, things change so rapidly that you can't tell. The random college kid you talk to today might in a couple years be the CEO of the hottest startup in the Valley. If you can't tell who to be nice to, you have to be nice to everyone. And probably the only people who can manage that are the people who are genuinely good. In a sufficiently connected and unpredictable world, you can't seem good without being good. As often happens, Ron discovered how to be the investor of the future by accident. He didn't foresee the future of startup investing, realize it would pay to be upstanding, and force himself to behave that way. It would feel unnatural to him to behave any other way. He was already living in the future. Fortunately that future is not limited to the startup world. The startup world is more transparent and unpredictable than most, but almost everywhere the trend is in that direction. Notes [1] I'm not saying that if you sort investors by benevolence you've also sorted them by returns, but rather that if you do a scatterplot with benevolence on the x axis and returns on the y, you'd see a clear upward trend. [2] Y Combinator in particular, because it aggregates data from so many startups, has a pretty comprehensive view of investor behavior. Thanks to Sam Altman and Jessica Livingston for reading drafts of this.
变化何在?初创企业界变得更透明、更难以预测。这两点都让"伪善"难以为继。
透明度的影响显而易见。如今若有投资人苛待创业者,消息定会不胫而走。或许不会见诸报端,但其他创业者必将知晓,该投资人的交易机会随之流失。[2]
不可预测性的影响更为微妙。它增加了表里不一的成本。若要两面三刀,你必须清楚该对谁友善、能对谁刻薄。而在瞬息万变的初创界,你根本无从预判——今日交谈的普通大学生,两年后或将成为硅谷新贵。若无法预判该善待谁,就只能善待所有人。而能做到这点的,恐怕唯有真正良善之人。
在充分互联且变幻莫测的世界里,伪善者终将原形毕露。
罗恩偶然间预见了未来投资者的模样。他并非预见到创投行业的演变、意识到正直将带来回报才约束自我——其他任何行为方式对他而言才是不自然的。他早已活在未来。
值得庆幸的是,这种未来不仅限于初创界。虽然初创界的透明度和不可预测性尤为显著,但几乎所有领域都正朝着这个方向演进。
注释 [1] 并非说按善良程度排序就等于按回报率排序,而是说若以善良为横轴、回报为纵轴做散点图,会呈现明显上升趋势。 [2] 尤其对于YC而言,因其汇聚大量初创企业数据,能全面洞察投资者行为。 致谢 萨姆·奥尔特曼和杰西卡·利文斯顿对本文初稿的审阅。
December 2014 I've read Villehardouin's chronicle of the Fourth Crusade at least two times, maybe three. And yet if I had to write down everything I remember from it, I doubt it would amount to much more than a page. Multiply this times several hundred, and I get an uneasy feeling when I look at my bookshelves. What use is it to read all these books if I remember so little from them? A few months ago, as I was reading Constance Reid's excellent biography of Hilbert, I figured out if not the answer to this question, at least something that made me feel better about it. She writes: > Hilbert had no patience with mathematical lectures which filled the students with facts but did not teach them how to frame a problem and solve it. He often used to tell them that "a perfect formulation of a problem is already half its solution."
我至少读过两遍,也许是三遍维尔阿杜安的《第四次十字军东征编年史》。然而若要写下我能记住的全部内容,恐怕连一页纸都填不满。将这种情况乘以数百倍,每当我望向书架时,就会涌起一阵不安——如果读完这些书后记住的如此之少,那么阅读的意义何在?
几个月前,当我阅读康斯坦斯·里德为希尔伯特撰写的杰出传记时,虽未找到确切答案,却获得了某种释然。书中记载:
> 希尔伯特对那种只会向学生灌输事实、却不教导他们如何构建与解决问题的数学讲座毫无耐心。他常告诫学生:"完美地表述一个问题,已然解决了问题的一半。"
这一观点在我眼中始终至关重要,而听闻希尔伯特予以证实后,我对此更加深信不疑。
That has always seemed to me an important point, and I was even more convinced of it after hearing it confirmed by Hilbert. But how had I come to believe in this idea in the first place? A combination of my own experience and other things I'd read. None of which I could at that moment remember! And eventually I'd forget that Hilbert had confirmed it too. But my increased belief in the importance of this idea would remain something I'd learned from this book, even after I'd forgotten I'd learned it. Reading and experience train your model of the world. And even if you forget the experience or what you read, its effect on your model of the world persists. Your mind is like a compiled program you've lost the source of. It works, but you don't know why. The place to look for what I learned from Villehardouin's chronicle is not what I remember from it, but my mental models of the crusades, Venice, medieval culture, siege warfare, and so on. Which doesn't mean I couldn't have read more attentively, but at least the harvest of reading is not so miserably small as it might seem. This is one of those things that seem obvious in retrospect. But it was a surprise to me and presumably would be to anyone else who felt uneasy about (apparently) forgetting so much they'd read. Realizing it does more than make you feel a little better about forgetting, though. There are specific implications. For example, reading and experience are usually "compiled" at the time they happen, using the state of your brain at that time. The same book would get compiled differently at different points in your life. Which means it is very much worth reading important books multiple times. I always used to feel some misgivings about rereading books. I unconsciously lumped reading together with work like carpentry, where having to do something again is a sign you did it wrong the first time. Whereas now the phrase "already read" seems almost ill-formed.
但最初我是如何形成这种信念的?源于自身经历与其他阅读积累的综合作用——尽管此刻我竟无法回忆起任何具体细节!终有一日,连希尔伯特的佐证也会被我遗忘。但这一理念重要性的认知提升,将作为我从本书中汲取的养分长存于心,即便遗忘其来源亦然。
阅读与阅历不断重塑你的世界认知模型。纵使遗忘具体经历或文本内容,它们对你思维模型的塑造仍持续生效。你的心智如同丢失源代码的编译程序——运行如常,却不知其所以然。
探寻维尔阿杜安编年史对我的真正启迪,不该局限于记忆中的字句,而应观察我对十字军东征、威尼斯、中世纪文化、攻城战等领域的认知模型。这并非否认更专注阅读的价值,但至少证明阅读的收获远非表面看来那般微不足道。
此类洞见总在事后显得不言自明。但当初发现时我仍感讶异,想必其他因遗忘阅读内容而焦虑者亦会如此。
这一认知的价值不止于缓解遗忘焦虑,更蕴含具体启示:
Intriguingly, this implication isn't limited to books. Technology will increasingly make it possible to relive our experiences. When people do that today it's usually to enjoy them again (e.g. when looking at pictures of a trip) or to find the origin of some bug in their compiled code (e.g. when Stephen Fry succeeded in remembering the childhood trauma that prevented him from singing). But as technologies for recording and playing back your life improve, it may become common for people to relive experiences without any goal in mind, simply to learn from them again as one might when rereading a book. Eventually we may be able not just to play back experiences but also to index and even edit them. So although not knowing how you know things may seem part of being human, it may not be. Thanks to Sam Altman, Jessica Livingston, and Robert Morris for reading drafts of this.
例如,阅读与阅历往往在发生时即根据彼时大脑状态被"编译"。同一本书在你人生不同阶段会被编译出不同版本。这意味着反复阅读经典极具价值。我曾对重读书籍心存抵触,潜意识里将阅读与木工等劳作归为一类——需要返工即代表初次失误。而今"已读过"这个表述本身似乎已不合逻辑。
耐人寻味的是,这一启示不仅限于书籍。科技将日益赋予我们重温经历的能力。如今人们这么做多是为了再次享受(如翻看旅行照片),或追溯心智"编译错误"的根源(如斯蒂芬·弗莱成功找回阻碍他歌唱的童年创伤)。但随着人生记录与回放技术的进步,无特定目的地重温经历或将成为常态——就像重读书籍般再度学习。
终有一日,我们或许不仅能回放经历,还可对其编目甚至编辑。因此,"不知其所以知"虽似人类本质特征,未来却未必如此。
致谢 萨姆·奥尔特曼、杰西卡·利文斯顿和罗伯特·莫里斯审阅了本文草稿。
December 2014 If the world were static, we could have monotonically increasing confidence in our beliefs. The more (and more varied) experience a belief survived, the less likely it would be false. Most people implicitly believe something like this about their opinions. And they're justified in doing so with opinions about things that don't change much, like human nature. But you can't trust your opinions in the same way about things that change, which could include practically everything else. When experts are wrong, it's often because they're experts on an earlier version of the world. Is it possible to avoid that? Can you protect yourself against obsolete beliefs? To some extent, yes. I spent almost a decade investing in early stage startups, and curiously enough protecting yourself against obsolete beliefs is exactly what you have to do to succeed as a startup investor. Most really good startup ideas look like bad ideas at first, and many of those look bad specifically because some change in the world just switched them from bad to good. I spent a lot of time learning to recognize such ideas, and the techniques I used may be applicable to ideas in general. The first step is to have an explicit belief in change. People who fall victim to a monotonically increasing confidence in their opinions are implicitly concluding the world is static. If you consciously remind yourself it isn't, you start to look for change. Where should one look for it? Beyond the moderately useful generalization that human nature doesn't change much, the unfortunate fact is that change is hard to predict. This is largely a tautology but worth remembering all the same: change that matters usually comes from an unforeseen quarter. So I don't even try to predict it.
如果世界是静止不变的,我们对自己的信念就能拥有与日俱增的信心。一个信念经受的验证越多(且越多样化),它错误的可能性就越低。大多数人对自己的观点都隐含着这样的认知。对于那些变化不大的事物——比如人性——这种认知是合理的。但对于不断变化的事物,你就不能以同样的方式信任自己的观点,而这类事物几乎涵盖其他一切。
专家犯错时,往往是因为他们精通的是世界过去的版本。
能否避免这种情况?你能保护自己免受过时信念的影响吗?在某种程度上,是的。我花了近十年时间投资早期初创企业,而耐人寻味的是,作为初创企业投资者要想成功,恰恰需要保护自己免受过时信念的影响。大多数真正优秀的初创企业想法最初看起来都很糟糕,其中许多看起来糟糕,正是因为世界的变化刚刚将它们从糟糕变成了优秀。我花了很多时间学习识别这些想法,而我所使用的方法可能普遍适用于各种想法。
第一步是明确相信变化的存在。那些对自己的观点产生与日俱增的盲目信心的人,隐含地认为世界是静止的。如果你有意识地提醒自己世界并非如此,你就会开始寻找变化。
When I get asked in interviews to predict the future, I always have to struggle to come up with something plausible-sounding on the fly, like a student who hasn't prepared for an exam. [1] But it's not out of laziness that I haven't prepared. It seems to me that beliefs about the future are so rarely correct that they usually aren't worth the extra rigidity they impose, and that the best strategy is simply to be aggressively open-minded. Instead of trying to point yourself in the right direction, admit you have no idea what the right direction is, and try instead to be super sensitive to the winds of change. It's ok to have working hypotheses, even though they may constrain you a bit, because they also motivate you. It's exciting to chase things and exciting to try to guess answers. But you have to be disciplined about not letting your hypotheses harden into anything more. [2] I believe this passive m.o. works not just for evaluating new ideas but also for having them. The way to come up with new ideas is not to try explicitly to, but to try to solve problems and simply not discount weird hunches you have in the process. The winds of change originate in the unconscious minds of domain experts. If you're sufficiently expert in a field, any weird idea or apparently irrelevant question that occurs to you is ipso facto worth exploring. [3] Within Y Combinator, when an idea is described as crazy, it's a compliment—in fact, on average probably a higher compliment than when an idea is described as good. Startup investors have extraordinary incentives for correcting obsolete beliefs. If they can realize before other investors that some apparently unpromising startup isn't, they can make a huge amount of money. But the incentives are more than just financial. Investors' opinions are explicitly tested: startups come to them and they have to say yes or no, and then, fairly quickly, they learn whether they guessed right.
应该去哪里寻找变化?除了“人性变化不大”这种略显笼统但还算有用的结论之外,不幸的事实是,变化很难预测。这在很大程度上是同义反复,但同样值得记住:重要的变化通常来自意想不到的领域。
所以我甚至不去尝试预测它。当我在采访中被要求预测未来时,我总是不得不临时编造一些听起来合理的东西,就像一个没有准备考试的学生。[1] 但这不是因为懒惰而没有准备。在我看来,关于未来的信念很少是正确的,它们通常不值得带来的额外固执,而最好的策略就是保持极度开放的心态。与其试图让自己指向正确的方向,不如承认自己根本不知道正确的方向是什么,而是尝试对变化的迹象保持高度敏感。
拥有一些初步假设是可以的,尽管它们可能会对你有所限制,因为它们也能激励你。追逐事物是令人兴奋的,尝试猜测答案也是令人兴奋的。但你必须严格要求自己,不要让这些假设固化为更确定的东西。[2]
我相信这种被动的策略不仅适用于评估新想法,也适用于产生新想法。提出新想法的方法不是刻意为之,而是尝试解决问题,并且不要忽视在这个过程中产生的奇怪直觉。
变化的迹象源自领域专家的潜意识。如果你在某个领域足够专业,那么你想到的任何奇怪想法或看似无关的问题都值得探索。[3] 在Y Combinator内部,当一个想法被描述为“疯狂”时,这是一种赞美——事实上,平均而言,这可能比被描述为“好”的赞美更高。
The investors who say no to a Google (and there were several) will remember it for the rest of their lives. Anyone who must in some sense bet on ideas rather than merely commenting on them has similar incentives. Which means anyone who wants such incentives can have them, by turning their comments into bets: if you write about a topic in some fairly durable and public form, you'll find you worry much more about getting things right than most people would in a casual conversation. [4] Another trick I've found to protect myself against obsolete beliefs is to focus initially on people rather than ideas. Though the nature of future discoveries is hard to predict, I've found I can predict quite well what sort of people will make them. Good new ideas come from earnest, energetic, independent-minded people. Betting on people over ideas saved me countless times as an investor. We thought Airbnb was a bad idea, for example. But we could tell the founders were earnest, energetic, and independent-minded. (Indeed, almost pathologically so.) So we suspended disbelief and funded them. This too seems a technique that should be generally applicable. Surround yourself with the sort of people new ideas come from. If you want to notice quickly when your beliefs become obsolete, you can't do better than to be friends with the people whose discoveries will make them so. It's hard enough already not to become the prisoner of your own expertise, but it will only get harder, because change is accelerating. That's not a recent trend; change has been accelerating since the paleolithic era. Ideas beget ideas. I don't expect that to change. But I could be wrong. Notes [1] My usual trick is to talk about aspects of the present that most people haven't noticed yet. [2] Especially if they become well enough known that people start to identify them with you.
初创企业投资者有极强的动力去纠正过时的信念。如果他们能比其他投资者更早意识到某些看似没有前途的初创企业其实并非如此,他们就能赚取巨额利润。但激励不仅仅是金钱。投资者的观点会明确受到检验:初创企业会找到他们,他们必须回答“是”或“否”,然后很快就能知道自己的判断是否正确。那些对谷歌说“不”的投资者(确实有好几位)会终生铭记这一点。
任何必须在某种意义上对想法下注而不仅仅是评论的人,都有类似的动力。这意味着任何想要这种动力的人都可以拥有它,方法是将评论变成赌注:如果你以某种持久且公开的形式撰写某个主题的文章,你会发现你比大多数人在随意交谈时更担心自己是否正确。[4]
我发现的另一个避免过时信念的技巧是,最初关注人而不是想法。尽管未来发现的性质很难预测,但我发现我可以很好地预测什么样的人会做出这些发现。好的新想法来自认真、精力充沛、独立思考的人。
作为投资者,押注于人而非想法无数次拯救了我。例如,我们认为Airbnb是个糟糕的想法。但我们可以看出创始人是认真、精力充沛且独立思考的。(事实上,几乎到了病态的程度。)所以我们暂时放下怀疑,投资了他们。
You have to be extra skeptical about things you want to believe, and once a hypothesis starts to be identified with you, it will almost certainly start to be in that category. [3] In practice "sufficiently expert" doesn't require one to be recognized as an expert—which is a trailing indicator in any case. In many fields a year of focused work plus caring a lot would be enough. [4] Though they are public and persist indefinitely, comments on e.g. forums and places like Twitter seem empirically to work like casual conversation. The threshold may be whether what you write has a title. Thanks to Sam Altman, Patrick Collison, and Robert Morris for reading drafts of this.
这似乎也是一种普遍适用的技巧。让自己置身于那些能产生新想法的人群中。如果你想在自己的信念过时时迅速察觉,最好的办法莫过于与那些会让你的信念过时的发现者成为朋友。
不被自己的专业知识所束缚已经够难了,但未来只会更难,因为变化正在加速。这不是近期的趋势;自旧石器时代以来,变化一直在加速。想法催生想法。我不认为这会改变。但我可能是错的。
注释 [1] 我通常的技巧是谈论大多数人尚未注意到的当下的某些方面。 [2] 尤其是当它们变得足够知名,以至于人们开始将其与你联系在一起时。你必须对那些你想要相信的事情格外怀疑,一旦一个假设开始与你本人挂钩,它几乎肯定会落入这一类别。 [3] 实际上,“足够专业”并不需要被公认为专家——无论如何,这是一个滞后指标。在许多领域,一年的专注工作加上足够的热情就足够了。 [4] 尽管论坛和Twitter等地方的评论是公开的且会永久存在,但根据经验,它们似乎与随意交谈的效果类似。关键可能在于你写的内容是否有标题。
感谢 Sam Altman、Patrick Collison和Robert Morris阅读本文草稿。
December 2014 American technology companies want the government to make immigration easier because they say they can't find enough programmers in the US. Anti-immigration people say that instead of letting foreigners take these jobs, we should train more Americans to be programmers. Who's right? The technology companies are right. What the anti-immigration people don't understand is that there is a huge variation in ability between competent programmers and exceptional ones, and while you can train people to be competent, you can't train them to be exceptional. Exceptional programmers have an aptitude for and _interest in_ programming that is not merely the product of training. [1] The US has less than 5% of the world's population. Which means if the qualities that make someone a great programmer are evenly distributed, 95% of great programmers are born outside the US. The anti-immigration people have to invent some explanation to account for all the effort technology companies have expended trying to make immigration easier. So they claim it's because they want to drive down salaries. But if you talk to startups, you find practically every one over a certain size has gone through legal contortions to get programmers into the US, where they then paid them the same as they'd have paid an American. Why would they go to extra trouble to get programmers for the same price? The only explanation is that they're telling the truth: there are just not enough great programmers to go around. [2] I asked the CEO of a startup with about 70 programmers how many more he'd hire if he could get all the great programmers he wanted. He said "We'd hire 30 tomorrow morning." And this is one of the hot startups that always win recruiting battles. It's the same all over Silicon Valley. Startups are that constrained for talent.
美国科技公司希望政府放宽移民政策,因为他们声称在国内找不到足够的程序员。反移民人士则认为,与其让外国人抢走这些工作,不如培养更多美国本土程序员。谁是对的?
科技公司是对的。反移民人士没有意识到,普通程序员和顶尖程序员之间存在巨大的能力差异——虽然可以通过培训让人达到合格水平,却无法培养出卓越天才。顶尖程序员具备与生俱来的编程_天赋与热忱_,这绝非单纯训练所能造就。[1]
美国人口不足全球5%。这意味着如果优秀程序员的特质均匀分布,那么95%的顶尖程序员都出生在美国境外。
反移民人士必须为科技公司推动移民改革的努力编造理由,于是他们声称这是企业为了压低薪资。但如果你与初创公司交流,会发现几乎所有达到一定规模的企业都曾为引进程序员大费周章,最终支付的薪资却与本土程序员无异。为何要额外折腾却不多付钱?唯一合理的解释就是他们所言非虚:顶尖程序员的数量根本供不应求。[2]
我曾询问某家拥有70名程序员的初创公司CEO:如果能招到所有心仪的顶尖人才,他还想再招多少人?他回答:"明早就能再招30人。"而这还是在招聘战中无往不利的热门初创企业。整个硅谷皆是如此,初创公司正面临严重的人才短缺。
It would be great if more Americans were trained as programmers, but no amount of training can flip a ratio as overwhelming as 95 to 5. Especially since programmers are being trained in other countries too. Barring some cataclysm, it will always be true that most great programmers are born outside the US. It will always be true that most people who are great at anything are born outside the US. [3] Exceptional performance implies immigration. A country with only a few percent of the world's population will be exceptional in some field only if there are a lot of immigrants working in it. But this whole discussion has taken something for granted: that if we let more great programmers into the US, they'll want to come. That's true now, and we don't realize how lucky we are that it is. If we want to keep this option open, the best way to do it is to take advantage of it: the more of the world's great programmers are here, the more the rest will want to come here. And if we don't, the US could be seriously fucked. I realize that's strong language, but the people dithering about this don't seem to realize the power of the forces at work here. Technology gives the best programmers huge leverage. The world market in programmers seems to be becoming dramatically more liquid. And since good people like good colleagues, that means the best programmers could collect in just a few hubs. Maybe mostly in one hub. What if most of the great programmers collected in one hub, and it wasn't here? That scenario may seem unlikely now, but it won't be if things change as much in the next 50 years as they did in the last 50. We have the potential to ensure that the US remains a technology superpower just by letting in a few thousand great programmers a year. What a colossal mistake it would be to let that opportunity slip. It could easily be the defining mistake this generation of American politicians later become famous for.
培养更多美国程序员固然是好事,但再多的培训也无法逆转95比5的悬殊比例——更何况其他国家也在培养程序员。除非发生剧变,顶尖程序员大多出生在美国境外这一事实将永远成立。事实上,任何领域的顶尖人才大多都出生在美国境外。[3]
卓越成就必然伴随移民潮。一个人口仅占全球百分之几的国家,只有在某个领域汇聚大量移民人才时,才可能在该领域脱颖而出。
但整个讨论都默认了一个前提:只要我们放宽政策,顶尖程序员就会愿意来美国。目前确实如此,而我们尚未意识到这是多么幸运。若想保持这种吸引力,最好的方式就是善用现有优势:汇聚的顶尖程序员越多,就越能吸引其他人才前来。
如果我们不这么做,美国将陷入严重危机。我明白这个措辞很激烈,但犹豫不决者似乎尚未意识到这场博弈的力量。技术赋予顶尖程序员巨大的杠杆效应,全球程序员市场的流动性正急剧增强。由于优秀人才偏爱与杰出同事共事,这意味着顶尖程序员可能集中汇聚于少数枢纽城市——甚至可能主要集中在一个枢纽。
如果顶尖程序员大多汇聚于某个枢纽,而那里不是美国呢?这种情景现在看似遥远,但若未来50年的变革如同过去50年般剧烈,一切皆有可能。
And unlike other potential mistakes on that scale, it costs nothing to fix. So please, get on with it. Notes [1] How much better is a great programmer than an ordinary one? So much better that you can't even measure the difference directly. A great programmer doesn't merely do the same work faster. A great programmer will invent things an ordinary programmer would never even think of. This doesn't mean a great programmer is infinitely more valuable, because any invention has a finite market value. But it's easy to imagine cases where a great programmer might invent things worth 100x or even 1000x an average programmer's salary. [2] There are a handful of consulting firms that rent out big pools of foreign programmers they bring in on H1-B visas. By all means crack down on these. It should be easy to write legislation that distinguishes them, because they are so different from technology companies. But it is dishonest of the anti-immigration people to claim that companies like Google and Facebook are driven by the same motives. An influx of inexpensive but mediocre programmers is the last thing they'd want; it would destroy them. [3] Though this essay talks about programmers, the group of people we need to import is broader, ranging from designers to programmers to electrical engineers. The best one could do as a general term might be "digital talent." It seemed better to make the argument a little too narrow than to confuse everyone with a neologism. Thanks to Sam Altman, John Collison, Patrick Collison, Jessica Livingston, Geoff Ralston, Fred Wilson, and Qasar Younis for reading drafts of this.
我们本有机会通过每年引进几千名顶尖程序员,确保美国保持科技超级大国地位。若错失良机,这将成为划时代的重大失误——很可能成为这代美国政客日后最"闻名"的败笔。而与其他同等级的错误不同,修正这个错误根本无需代价。
[1] 顶尖程序员比普通程序员强多少?强到无法直接量化衡量。顶尖程序员不仅能更快完成任务,更能创造出普通程序员根本想不到的解决方案。这并非意味着其价值无限大(任何发明都有市场天花板),但很容易想象顶尖程序员创造的成果可能价值百倍甚至千倍于普通程序员的薪资。
[2] 确实存在少数咨询公司利用H1-B签证引进大量外国程序员进行外包。这类行为理应打击,立法区分它们与科技公司并不困难。但反移民人士将谷歌、脸书等公司与这类机构混为一谈实属恶意中伤——廉价平庸的程序员涌入对这些科技巨头有百害而无一利。
[3] 虽然本文聚焦程序员,但我们需要引进的人才范围更广,涵盖设计师到电气工程师等领域。最合适的统称或许是"数字人才",但为避免新造词造成困惑,行文时选择稍显狭窄的表述。
致谢 Sam Altman、John Collison、Patrick Collison、Jessica Livingston、Geoff Ralston、Fred Wilson和Qasar Younis对本文草稿提出宝贵意见。
December 2014 Many startups go through a point a few months before they die where although they have a significant amount of money in the bank, they're also losing a lot each month, and revenue growth is either nonexistent or mediocre. The company has, say, 6 months of runway. Or to put it more brutally, 6 months before they're out of business. They expect to avoid that by raising more from investors. [1] That last sentence is the fatal one. There may be nothing founders are so prone to delude themselves about as how interested investors will be in giving them additional funding. It's hard to convince investors the first time too, but founders expect that. What bites them the second time is a confluence of three forces: 1. The company is spending more now than it did the first time it raised money.
许多初创公司在倒闭前几个月都会经历这样一个阶段:尽管银行账户里仍有可观资金,但每月亏损严重,收入增长要么停滞不前,要么平庸乏味。公司的资金跑道可能还剩6个月。或者更残酷地说,距离破产只剩6个月。他们指望通过向投资者再次融资来摆脱困境。[1]
对于"投资者是否愿意追加投资"这个问题,创始人最容易自我欺骗。首次融资时说服投资者固然困难,但创始人们对此早有心理准备。而二次融资时的困境源于三重压力的叠加:
2. Investors have much higher standards for companies that have already raised money.
1. 公司现在的开销比首次融资时更大; 2. 投资者对已融资公司设立了更高标准; 3. 公司已开始显露败象。首次融资时无所谓成败——当时下结论为时过早。但此时这个问题已有答案,而默认答案就是失败,因为此刻失败已是大概率结局。
我将第一段描述的情形称为"致命挤压"。我通常避免生造词汇,但为这种情境命名或许能让创始人猛然意识到自己正身处其中。
致命挤压之所以危险,在于它的自我强化特性。创始人高估了继续融资的可能性,因而对实现盈利懈怠,这进一步降低了融资成功率。
3. The company is now starting to read as a failure. The first time it raised money, it was neither a success nor a failure; it was too early to ask. Now it's possible to ask that question, and the default answer is failure, because at this point that is the default outcome.
既然了解了致命挤压,如何避免?Y Combinator告诫融资成功的创始人:要当作这是最后一笔资金。因为这种自我强化机制反向也成立:你对后续投资需求越少,获得融资反而越容易。
若已陷入致命挤压怎么办?第一步是重新评估继续融资的概率。此刻我将施展惊人预见力为你作答:概率为零。[2]
剩下三条路:关闭公司、增加收入或削减开支。
I'm going to call the situation I described in the first paragraph "the fatal pinch." I try to resist coining phrases, but making up a name for this situation may snap founders into realizing when they're in it. One of the things that makes the fatal pinch so dangerous is that it's self-reinforcing. Founders overestimate their chances of raising more money, and so are slack about reaching profitability, which further decreases their chances of raising money. Now that you know about the fatal pinch, how do you avoid it? Y Combinator tells founders who raise money to act as if it's the last they'll ever get. Because the self-reinforcing nature of this situation works the other way too: the less you need further investment, the easier it is to get. What do you do if you're already in the fatal pinch? The first step is to re-evaluate the probability of raising more money. I will now, by an amazing feat of clairvoyance, do this for you: the probability is zero. [2] Three options remain: you can shut down the company, you can increase how much you make, and you can decrease how much you spend. You should shut down the company if you're certain it will fail no matter what you do. Then at least you can give back the money you have left, and save yourself however many months you would have spent riding it down. Companies rarely _have_ to fail though. What I'm really doing here is giving you the option of admitting you've already given up. If you don't want to shut down the company, that leaves increasing revenues and decreasing expenses. In most startups, expenses = people, and decreasing expenses = firing people. [3] Deciding to fire people is usually hard, but there's one case in which it shouldn't be: when there are people you already know you should fire but you're in denial about it. If so, now's the time.
若确信无论如何都会失败,就该立即关闭。至少能返还剩余资金,并节省数月垂死挣扎的时间。但公司极少注定失败——我实质是给你承认放弃的选择权。
若选择继续,则需增收或节支。对初创企业而言,开支≈人力成本,节支≈裁员。[3] 裁员决策通常艰难,但有一种例外:当你心知该裁却自欺欺人时——此刻就是行动时刻。
若此举能使你盈利,或用剩余资金撑到盈利,便化解了燃眉之急。
If that makes you profitable, or will enable you to make it to profitability on the money you have left, you've avoided the immediate danger. Otherwise you have three options: you either have to fire good people, get some or all of the employees to take less salary for a while, or increase revenues. Getting people to take less salary is a weak solution that will only work when the problem isn't too bad. If your current trajectory won't quite get you to profitability but you can get over the threshold by cutting salaries a little, you might be able to make the case to everyone for doing it. Otherwise you're probably just postponing the problem, and that will be obvious to the people whose salaries you're proposing to cut. [4] Which leaves two options, firing good people and making more money. While trying to balance them, keep in mind the eventual goal: to be a successful product company in the sense of having a single thing lots of people use. You should lean more toward firing people if the source of your trouble is overhiring. If you went out and hired 15 people before you even knew what you were building, you've created a broken company. You need to figure out what you're building, and it will probably be easier to do that with a handful of people than 15. Plus those 15 people might not even be the ones you need for whatever you end up building. So the solution may be to shrink and then figure out what direction to grow in. After all, you're not doing those 15 people any favors if you fly the company into ground with them aboard. They'll all lose their jobs eventually, along with all the time they expended on this doomed company. Whereas if you only have a handful of people, it may be better to focus on trying to make more money. It may seem facile to suggest a startup make more money, as if that could be done for the asking. Usually a startup is already trying as hard as it can to sell whatever it sells.
否则只剩三选:裁撤优秀员工、全员暂时降薪,或增加营收。降薪是权宜之计,仅适用于轻微危机。若离盈利差距不大,小幅降薪或能说服团队;否则只是拖延问题,员工自会察觉。[4]
最终在裁撤优秀员工与增收间权衡时,请牢记终极目标:成为拥有海量用户的成功产品公司。
What I'm suggesting here is not so much to try harder to make money but to try to make money in a different way. For example, if you have only one person selling while the rest are writing code, consider having everyone work on selling. What good will more code do you when you're out of business? If you have to write code to close a certain deal, go ahead; that follows from everyone working on selling. But only work on whatever will get you the most revenue the soonest. Another way to make money differently is to sell different things, and in particular to do more consultingish work. I say consultingish because there is a long slippery slope from making products to pure consulting, and you don't have to go far down it before you start to offer something really attractive to customers. Although your product may not be very appealing yet, if you're a startup your programmers will often be way better than the ones your customers have. Or you may have expertise in some new field they don't understand. So if you change your sales conversations just a little from "do you want to buy our product?" to "what do you need that you'd pay a lot for?" you may find it's suddenly a lot easier to extract money from customers. Be ruthlessly mercenary when you start doing this, though. You're trying to save your company from death here, so make customers pay a lot, quickly. And to the extent you can, try to avoid the worst pitfalls of consulting. The ideal thing might be if you built a precisely defined derivative version of your product for the customer, and it was otherwise a straight product sale. You keep the IP and no billing by the hour. In the best case, this consultingish work may not be just something you do to survive, but may turn out to be the thing-that-doesn't-scale that defines your company. Don't expect it to be, but as you dive into individual users' needs, keep your eyes open for narrow openings that have wide vistas beyond.
若问题源于过度招聘,应倾向裁员。若在未明确产品时就雇佣15人,公司已先天畸形。你需要重新定义产品,而5人团队比15人更易达成共识。何况这15人未必适合最终方向。解决方案或是先收缩再探索。毕竟带着全员坠毁对谁都不负责——他们终将失业,并浪费数年在这注定失败的事业上。
若团队精干,则应聚焦增收。建议初创企业增收看似轻巧,实则需转换思路:非加倍努力销售,而是改变盈利模式。例如当仅一人销售而其他写代码时,不妨让全员参与销售。公司倒闭时再多代码何用?若需编码促成交易,自然要写——这本就是全员销售的一部分。但只做能最快带来收入的事。
另一增收途径是销售不同产品,尤其是承接更多咨询类工作。"咨询类"的表述很关键,因为从产品到纯咨询存在滑坡效应,其实只需稍作调整就能提供诱人服务。虽然产品可能不成熟,但初创企业的程序员通常远超客户水平,或在某些新兴领域具备专业优势。只需将销售话术从"要买我们的产品吗"转为"您愿意为什么需求支付高价",就可能发现收钱突然变得容易。
There is usually so much demand for custom work that unless you're really incompetent there has to be some point down the slope of consulting at which you can survive. But I didn't use the term slippery slope by accident; customers' insatiable demand for custom work will always be pushing you toward the bottom. So while you'll probably survive, the problem now becomes to survive with the least damage and distraction. The good news is, plenty of successful startups have passed through near-death experiences and gone on to flourish. You just have to realize in time that you're near death. And if you're in the fatal pinch, you are. Notes [1] There are a handful of companies that can't reasonably expect to make money for the first year or two, because what they're building takes so long. For these companies substitute "progress" for "revenue growth." You're not one of these companies unless your initial investors agreed in advance that you were. And frankly even these companies wish they weren't, because the illiquidity of "progress" puts them at the mercy of investors. [2] There's a variant of the fatal pinch where your existing investors help you along by promising to invest more. Or rather, where you read them as promising to invest more, while they think they're just mentioning the possibility. The way to solve this problem, if you have 8 months of runway or less, is to try to get the money right now. Then you'll either get the money, in which case (immediate) problem solved, or at least prevent your investors from helping you to remain in denial about your fundraising prospects. [3] Obviously, if you have significant expenses other than salaries that you can eliminate, do it now. [4] Unless of course the source of the problem is that you're paying yourselves high salaries. If by cutting the founders' salaries to the minimum you need, you can make it to profitability, you should.
但开展此类业务时务必极度务实。这是拯救公司的生死时刻,必须快速获取高额回报。同时尽量避免咨询业务的常见陷阱。理想状态是为客户定制产品的衍生版本,保留知识产权且不按小时计费。
最佳情况下,这类咨询工作不仅是求生手段,更可能成为定义公司的非规模化突破口。虽不能寄望于此,但在深挖用户需求时,请留意那些狭窄却蕴含广阔前景的入口。
定制化需求通常非常旺盛,只要不是极度无能,总能在咨询滑坡上找到生存点。但"滑坡"一词绝非偶然——客户对定制工作的无尽需求会不断将你推向深渊。因此问题转变为:如何以最小代价和干扰存活。
But it's a bad sign if you needed to read this to realize that. Thanks to Sam Altman, Paul Buchheit, Jessica Livingston, and Geoff Ralston for reading drafts of this.
好消息是,众多成功初创企业都经历过濒死时刻。关键在于及时意识到危机——如果你正遭遇致命挤压,此刻就是生死关头。
注释 [1] 少数公司因产品研发周期长,前两年难以盈利。对它们而言"进展"可替代"收入增长"。除非初始投资者明确认可,否则你不属此类。坦白说这类公司也不愿如此,因为"进展"的非流动性使其受制于投资者。 [2] 致命挤压存在变体:现有投资者暗示将追加投资。更准确地说,是你将其客套解读为承诺。若资金储备≤8个月,解决方案是立即索要投资。要么获得资金解决问题,要么打破你对融资前景的幻想。 [3] 若有可削减的非人力成本,立即行动。 [4] 除非问题根源是创始人高薪。若将创始人薪资降至生存最低线即可盈利,理当如此。但若需读此文才意识到这点,实属不妙。
致谢 Sam Altman、Paul Buchheit、Jessica Livingston和Geoff Ralston对本文草稿的审阅。
November 2014 It struck me recently how few of the most successful people I know are mean. There are exceptions, but remarkably few. Meanness isn't rare. In fact, one of the things the internet has shown us is how mean people can be. A few decades ago, only famous people and professional writers got to publish their opinions. Now everyone can, and we can all see the long tail of meanness that had previously been hidden. And yet while there are clearly a lot of mean people out there, there are next to none among the most successful people I know. What's going on here? Are meanness and success inversely correlated? Part of what's going on, of course, is selection bias. I only know people who work in certain fields: startup founders, programmers, professors. I'm willing to believe that successful people in other fields are mean. Maybe successful hedge fund managers are mean; I don't know enough to say. It seems quite likely that most successful drug lords are mean. But there are at least big chunks of the world that mean people don't rule, and that territory seems to be growing. My wife and Y Combinator cofounder Jessica is one of those rare people who have x-ray vision for character. Being married to her is like standing next to an airport baggage scanner. She came to the startup world from investment banking, and she has always been struck both by how consistently successful startup founders turn out to be good people, and how consistently bad people fail as startup founders. Why? I think there are several reasons. One is that being mean makes you stupid. That's why I hate fights. You never do your best work in a fight, because fights are not sufficiently general. Winning is always a function of the situation and the people involved. You don't win fights by thinking of big ideas but by thinking of tricks that work in one particular case. And yet fighting is just as much work as thinking about real problems.
Which is particularly painful to someone who cares how their brain is used: your brain goes fast but you get nowhere, like a car spinning its wheels. Startups don't win by attacking. They win by transcending. There are exceptions of course, but usually the way to win is to race ahead, not to stop and fight. Another reason mean founders lose is that they can't get the best people to work for them. They can hire people who will put up with them because they need a job. But the best people have other options. A mean person can't convince the best people to work for him unless he is super convincing. And while having the best people helps any organization, it's critical for startups. There is also a complementary force at work: if you want to build great things, it helps to be driven by a spirit of benevolence. The startup founders who end up richest are not the ones driven by money. The ones driven by money take the big acquisition offer that nearly every successful startup gets en route. [1] The ones who keep going are driven by something else. They may not say so explicitly, but they're usually trying to improve the world. Which means people with a desire to improve the world have a natural advantage. [2] The exciting thing is that startups are not just one random type of work in which meanness and success are inversely correlated. This kind of work is the future. For most of history success meant control of scarce resources. One got that by fighting, whether literally in the case of pastoral nomads driving hunter-gatherers into marginal lands, or metaphorically in the case of Gilded Age financiers contending with one another to assemble railroad monopolies. For most of history, success meant success at zero-sum games. And in most of them meanness was not a handicap but probably an advantage. That is changing. Increasingly the games that matter are not zero-sum.
Increasingly you win not by fighting to get control of a scarce resource, but by having new ideas and building new things. [3] There have long been games where you won by having new ideas. In the third century BC, Archimedes won by doing that. At least until an invading Roman army killed him. Which illustrates why this change is happening: for new ideas to matter, you need a certain degree of civil order. And not just not being at war. You also need to prevent the sort of economic violence that nineteenth century magnates practiced against one another and communist countries practiced against their citizens. People need to feel that what they create can't be stolen. [4] That has always been the case for thinkers, which is why this trend began with them. When you think of successful people from history who weren't ruthless, you get mathematicians and writers and artists. The exciting thing is that their m.o. seems to be spreading. The games played by intellectuals are leaking into the real world, and this is reversing the historical polarity of the relationship between meanness and success. So I'm really glad I stopped to think about this. Jessica and I have always worked hard to teach our kids not to be mean. We tolerate noise and mess and junk food, but not meanness. And now I have both an additional reason to crack down on it, and an additional argument to use when I do: that being mean makes you fail. Notes [1] I'm not saying all founders who take big acquisition offers are driven only by money, but rather that those who don't aren't. Plus one can have benevolent motives for being driven by money — for example, to take care of one's family, or to be free to work on projects that improve the world. [2] It's unlikely that every successful startup improves the world. But their founders, like parents, truly believe they do. Successful founders are in love with their companies.
And while this sort of love is as blind as the love people have for one another, it is genuine. [3] Peter Thiel would point out that successful founders still get rich from controlling monopolies, just monopolies they create rather than ones they capture. And while this is largely true, it means a big change in the sort of person who wins. [4] To be fair, the Romans didn't mean to kill Archimedes. The Roman commander specifically ordered that he be spared. But he got killed in the chaos anyway. In sufficiently disordered times, even thinking requires control of scarce resources, because living at all is a scarce resource. Thanks to Sam Altman, Ron Conway, Daniel Gackle, Jessica Livingston, Robert Morris, Geoff Ralston, and Fred Wilson for reading drafts of this.
Portuguese Translation | Japanese Translation Arabic Translation.
2014年11月 最近我突然意识到,我所认识的最成功人士中,刻薄者寥寥无几。虽有例外,但数量惊人地少。 刻薄并不罕见。事实上,互联网向我们展示的一件事就是人们可以多么刻薄。几十年前,只有名人和专业作家才能发表观点。如今人人都可以,于是我们得以看见那些曾被隐藏的刻薄长尾。 然而,尽管世界上显然存在大量刻薄之人,但在我认识的最成功人士中几乎找不到这类人。这是为什么?刻薄与成功是否呈负相关? 部分原因当然是选择偏差。我只认识某些领域的人:初创企业创始人、程序员、教授。我愿意相信其他领域的成功人士是刻薄的。也许成功的对冲基金经理很刻薄;我不够了解所以无法断言。大多数成功的毒枭很可能都很刻薄。但至少在世界的大部分领域,刻薄之人并不占据统治地位,而且这片领地似乎还在扩大。 我的妻子兼Y Combinator联合创始人杰西卡是少数拥有"性格X光眼"的人。与她结婚就像站在机场行李扫描仪旁边。她从投行进入初创企业界后,始终惊讶于两点:成功的初创企业创始人几乎总是好人,而坏人作为初创企业创始人几乎总是失败。 为什么?我认为有几个原因。其一是刻薄会让人变蠢。这就是我讨厌争斗的原因。人在争斗中永远无法发挥最佳水平,因为争斗的格局不够宏大。胜利总是取决于具体情境和参与者。赢得争斗不是靠宏大的想法,而是靠适用于特定情况的伎俩。然而争斗耗费的精力与思考真正问题相当。这对在乎大脑使用方式的人尤其痛苦:你的大脑高速运转却原地打转,就像车轮空转的汽车。 初创企业不靠攻击取胜,而是靠超越。当然有例外,但通常获胜之道是向前冲刺,而非停下战斗。 刻薄创始人失败的另一个原因是他们无法吸引最优秀的人才。他们可以雇用那些因需要工作而忍受他们的人。但顶尖人才有其他选择。除非极具说服力,否则刻薄之人无法让顶尖人才为其效力。而拥有顶尖人才对所有组织都有帮助,对初创企业更是至关重要。 还存在一种互补力量:若想成就伟业,心怀善意的驱动力大有裨益。最终最富有的初创企业创始人并非受金钱驱动。那些受金钱驱动的人会接受几乎所有成功初创企业在发展过程中都会收到的高额收购要约。[1]坚持前行的人则受其他因素驱动。他们或许不会明说,但通常都在试图改变世界。这意味着心怀改变世界愿望的人具有天然优势。[2] 令人振奋的是,初创企业并非刻薄与成功呈负相关的偶然特例。这类工作代表着未来。 历史上大多数时期,成功意味着掌控稀缺资源。人们通过争斗获得资源,无论是游牧民族将狩猎采集者驱赶到边缘之地的真实战争,还是镀金时代金融家争夺铁路垄断权的隐喻战争。在大部分历史中,成功意味着零和游戏的胜利。而在这些游戏中,刻薄非但不是障碍,反而可能是优势。 这种状况正在改变。越来越重要的游戏不再是零和博弈。越来越多的情况是,你并非通过争夺稀缺资源的控制权获胜,而是凭借新想法和创造新事物。[3] 通过新想法获胜的游戏早已存在。公元前三世纪,阿基米德就以此获胜——直到入侵的罗马军队杀死他。这解释了为何这种变化会发生:要让新想法发挥作用,需要一定程度的文明秩序。不仅是没有战争,还需防止19世纪巨头们互相施加的经济暴力,或共产主义国家对公民实施的经济暴力。人们需要确信自己的创造不会被窃取。[4] 这对思想者而言向来如此,因此这一趋势始于他们。当你想到历史上非冷酷无情的成功人士时,浮现的是数学家、作家和艺术家。令人振奋的是,他们的模式似乎正在扩散。知识分子参与的游戏正在渗入现实世界,正在逆转刻薄与成功关系的历史极性。 因此我非常庆幸自己停下来思考了这个问题。杰西卡和我一直努力教导孩子不要刻薄。我们容忍噪音、混乱和垃圾食品,但不宽容刻薄。如今我有了更多打击刻薄的理由,也有了更多论据:刻薄会导致失败。 注释 [1] 我并非说所有接受高额收购要约的创始人都只受金钱驱动,而是说那些拒绝的人不是。此外,受金钱驱动也可能出于善意动机——例如照顾家人,或为能自由从事改善世界的项目。 [2] 并非每个成功的初创企业都能改善世界。但其创始人就像父母一样,真心相信自己在这么做。成功的创始人热爱他们的公司。尽管这种爱与人与人之间的爱同样盲目,但它是真实的。 [3] 彼得·蒂尔会指出,成功的创始人仍通过垄断致富,只是这些垄断是他们创造的而非夺取的。虽然基本属实,但这意味着获胜者类型发生了巨大变化。 [4] 公平地说,罗马人并非蓄意杀害阿基米德。罗马指挥官特别下令保全他。但他仍在混乱中被杀。 在足够混乱的时代,连思考都需要控制稀缺资源,因为生存本身就是稀缺资源。 致谢 感谢萨姆·奥尔特曼、罗恩·康威、丹尼尔·加克尔、杰西卡·利文斯顿、罗伯特·莫里斯、杰夫·拉尔斯顿和弗雷德·威尔逊阅读本文草稿。
Want to start a startup? Get funded by Y Combinator.
October 2014 _(This essay is derived from a guest lecture in Sam Altman'sstartup class at Stanford. It's intended for college students, but much of it is applicable to potential founders at other ages.)_ One of the advantages of having kids is that when you have to give advice, you can ask yourself "what would I tell my own kids?" My kids are little, but I can imagine what I'd tell them about startups if they were in college, and that's what I'm going to tell you. Startups are very counterintuitive. I'm not sure why. Maybe it's just because knowledge about them hasn't permeated our culture yet. But whatever the reason, starting a startup is a task where you can't always trust your instincts. It's like skiing in that way. When you first try skiing and you want to slow down, your instinct is to lean back. But if you lean back on skis you fly down the hill out of control. So part of learning to ski is learning to suppress that impulse. Eventually you get new habits, but at first it takes a conscious effort. At first there's a list of things you're trying to remember as you start down the hill. Startups are as unnatural as skiing, so there's a similar list for startups. Here I'm going to give you the first part of it — the things to remember if you want to prepare yourself to start a startup. Counterintuitive The first item on it is the fact I already mentioned: that startups are so weird that if you trust your instincts, you'll make a lot of mistakes. If you know nothing more than this, you may at least pause before making them. When I was running Y Combinator I used to joke that our function was to tell founders things they would ignore. It's really true.
Batch after batch, the YC partners warn founders about mistakes they're about to make, and the founders ignore them, and then come back a year later and say "I wish we'd listened." Why do the founders ignore the partners' advice? Well, that's the thing about counterintuitive ideas: they contradict your intuitions. They seem wrong. So of course your first impulse is to disregard them. And in fact my joking description is not merely the curse of Y Combinator but part of its raison d'etre. If founders' instincts already gave them the right answers, they wouldn't need us. You only need other people to give you advice that surprises you. That's why there are a lot of ski instructors and not many running instructors. [1] You can, however, trust your instincts about people. And in fact one of the most common mistakes young founders make is not to do that enough. They get involved with people who seem impressive, but about whom they feel some misgivings personally. Later when things blow up they say "I knew there was something off about him, but I ignored it because he seemed so impressive." If you're thinking about getting involved with someone — as a cofounder, an employee, an investor, or an acquirer — and you have misgivings about them, trust your gut. If someone seems slippery, or bogus, or a jerk, don't ignore it. This is one case where it pays to be self-indulgent. Work with people you genuinely like, and you've known long enough to be sure. Expertise The second counterintuitive point is that it's not that important to know a lot about startups. The way to succeed in a startup is not to be an expert on startups, but to be an expert on your users and the problem you're solving for them. Mark Zuckerberg didn't succeed because he was an expert on startups. He succeeded despite being a complete noob at startups, because he understood his users really well.
If you don't know anything about, say, how to raise an angel round, don't feel bad on that account. That sort of thing you can learn when you need to, and forget after you've done it. In fact, I worry it's not merely unnecessary to learn in great detail about the mechanics of startups, but possibly somewhat dangerous. If I met an undergrad who knew all about convertible notes and employee agreements and (God forbid) class FF stock, I wouldn't think "here is someone who is way ahead of their peers." It would set off alarms. Because another of the characteristic mistakes of young founders is to go through the motions of starting a startup. They make up some plausible-sounding idea, raise money at a good valuation, rent a cool office, hire a bunch of people. From the outside that seems like what startups do. But the next step after rent a cool office and hire a bunch of people is: gradually realize how completely fucked they are, because while imitating all the outward forms of a startup they have neglected the one thing that's actually essential: making something people want. Game We saw this happen so often that we made up a name for it: playing house. Eventually I realized why it was happening. The reason young founders go through the motions of starting a startup is because that's what they've been trained to do for their whole lives up to that point. Think about what you have to do to get into college, for example. Extracurricular activities, check. Even in college classes most of the work is as artificial as running laps. I'm not attacking the educational system for being this way. There will always be a certain amount of fakeness in the work you do when you're being taught something, and if you measure their performance it's inevitable that people will exploit the difference to the point where much of what you're measuring is artifacts of the fakeness. I confess I did it myself in college.
I found that in a lot of classes there might only be 20 or 30 ideas that were the right shape to make good exam questions. The way I studied for exams in these classes was not (except incidentally) to master the material taught in the class, but to make a list of potential exam questions and work out the answers in advance. When I walked into the final, the main thing I'd be feeling was curiosity about which of my questions would turn up on the exam. It was like a game. It's not surprising that after being trained for their whole lives to play such games, young founders' first impulse on starting a startup is to try to figure out the tricks for winning at this new game. Since fundraising appears to be the measure of success for startups (another classic noob mistake), they always want to know what the tricks are for convincing investors. We tell them the best way to convince investors is to make a startup that's actually doing well, meaning growing fast, and then simply tell investors so. Then they want to know what the tricks are for growing fast. And we have to tell them the best way to do that is simply to make something people want. So many of the conversations YC partners have with young founders begin with the founder asking "How do we..." and the partner replying "Just..." Why do the founders always make things so complicated? The reason, I realized, is that they're looking for the trick. So this is the third counterintuitive thing to remember about startups: starting a startup is where gaming the system stops working. Gaming the system may continue to work if you go to work for a big company. Depending on how broken the company is, you can succeed by sucking up to the right people, giving the impression of productivity, and so on. [2] But that doesn't work with startups. There is no boss to trick, only users, and all users care about is whether your product does what they want.
Startups are as impersonal as physics. You have to make something people want, and you prosper only to the extent you do. The dangerous thing is, faking does work to some degree on investors. If you're super good at sounding like you know what you're talking about, you can fool investors for at least one and perhaps even two rounds of funding. But it's not in your interest to. The company is ultimately doomed. All you're doing is wasting your own time riding it down. So stop looking for the trick. There are tricks in startups, as there are in any domain, but they are an order of magnitude less important than solving the real problem. A founder who knows nothing about fundraising but has made something users love will have an easier time raising money than one who knows every trick in the book but has a flat usage graph. And more importantly, the founder who has made something users love is the one who will go on to succeed after raising the money. Though in a sense it's bad news in that you're deprived of one of your most powerful weapons, I think it's exciting that gaming the system stops working when you start a startup. It's exciting that there even exist parts of the world where you win by doing good work. Imagine how depressing the world would be if it were all like school and big companies, where you either have to spend a lot of time on bullshit things or lose to people who do. [3] I would have been delighted if I'd realized in college that there were parts of the real world where gaming the system mattered less than others, and a few where it hardly mattered at all. But there are, and this variation is one of the most important things to consider when you're thinking about your future. How do you win in each type of work, and what would you like to win by doing? [4] All-Consuming That brings us to our fourth counterintuitive point: startups are all-consuming.
If you start a startup, it will take over your life to a degree you cannot imagine. And if your startup succeeds, it will take over your life for a long time: for several years at the very least, maybe for a decade, maybe for the rest of your working life. So there is a real opportunity cost here. Larry Page may seem to have an enviable life, but there are aspects of it that are unenviable. Basically at 25 he started running as fast as he could and it must seem to him that he hasn't stopped to catch his breath since. Every day new shit happens in the Google empire that only the CEO can deal with, and he, as CEO, has to deal with it. If he goes on vacation for even a week, a whole week's backlog of shit accumulates. And he has to bear this uncomplainingly, partly because as the company's daddy he can never show fear or weakness, and partly because billionaires get less than zero sympathy if they talk about having difficult lives. Which has the strange side effect that the difficulty of being a successful startup founder is concealed from almost everyone except those who've done it. Y Combinator has now funded several companies that can be called big successes, and in every single case the founders say the same thing. It never gets any easier. The nature of the problems change. You're worrying about construction delays at your London office instead of the broken air conditioner in your studio apartment. But the total volume of worry never decreases; if anything it increases. Starting a successful startup is similar to having kids in that it's like a button you push that changes your life irrevocably. And while it's truly wonderful having kids, there are a lot of things that are easier to do before you have them than after. Many of which will make you a better parent when you do have kids. And since you can delay pushing the button for a while, most people in rich countries do.
Yet when it comes to startups, a lot of people seem to think they're supposed to start them while they're still in college. Are you crazy? And what are the universities thinking? They go out of their way to ensure their students are well supplied with contraceptives, and yet they're setting up entrepreneurship programs and startup incubators left and right. To be fair, the universities have their hand forced here. A lot of incoming students are interested in startups. Universities are, at least de facto, expected to prepare them for their careers. So students who want to start startups hope universities can teach them about startups. And whether universities can do this or not, there's some pressure to claim they can, lest they lose applicants to other universities that do. Can universities teach students about startups? Yes and no. They can teach students about startups, but as I explained before, this is not what you need to know. What you need to learn about are the needs of your own users, and you can't do that until you actually start the company. [5] So starting a startup is intrinsically something you can only really learn by doing it. And it's impossible to do that in college, for the reason I just explained: startups take over your life. You can't start a startup for real as a student, because if you start a startup for real you're not a student anymore. You may be nominally a student for a bit, but you won't even be that for long. [6] Given this dichotomy, which of the two paths should you take? Be a real student and not start a startup, or start a real startup and not be a student? I can answer that one for you. Do not start a startup in college. How to start a startup is just a subset of a bigger problem you're trying to solve: how to have a good life. And though starting a startup can be part of a good life for a lot of ambitious people, age 20 is not the optimal time to do it.
Starting a startup is like a brutally fast depth-first search. Most people should still be searching breadth-first at 20. You can do things in your early 20s that you can't do as well before or after, like plunge deeply into projects on a whim and travel super cheaply with no sense of a deadline. For unambitious people, this sort of thing is the dreaded "failure to launch," but for the ambitious ones it can be an incomparably valuable sort of exploration. If you start a startup at 20 and you're sufficiently successful, you'll never get to do it. [7] Mark Zuckerberg will never get to bum around a foreign country. He can do other things most people can't, like charter jets to fly him to foreign countries. But success has taken a lot of the serendipity out of his life. Facebook is running him as much as he's running Facebook. And while it can be very cool to be in the grip of a project you consider your life's work, there are advantages to serendipity too, especially early in life. Among other things it gives you more options to choose your life's work from. There's not even a tradeoff here. You're not sacrificing anything if you forgo starting a startup at 20, because you're more likely to succeed if you wait. In the unlikely case that you're 20 and one of your side projects takes off like Facebook did, you'll face a choice of running with it or not, and it may be reasonable to run with it. But the usual way startups take off is for the founders to make them take off, and it's gratuitously stupid to do that at 20. Try Should you do it at any age? I realize I've made startups sound pretty hard. If I haven't, let me try again: starting a startup is really hard. What if it's too hard? How can you tell if you're up to this challenge? The answer is the fifth counterintuitive point: you can't tell.
Your life so far may have given you some idea what your prospects might be if you tried to become a mathematician, or a professional football player. But unless you've had a very strange life you haven't done much that was like being a startup founder. Starting a startup will change you a lot. So what you're trying to estimate is not just what you are, but what you could grow into, and who can do that? For the past 9 years it was my job to predict whether people would have what it took to start successful startups. It was easy to tell how smart they were, and most people reading this will be over that threshold. The hard part was predicting how tough and ambitious they would become. There may be no one who has more experience at trying to predict that, so I can tell you how much an expert can know about it, and the answer is: not much. I learned to keep a completely open mind about which of the startups in each batch would turn out to be the stars. The founders sometimes think they know. Some arrive feeling sure they will ace Y Combinator just as they've aced every one of the (few, artificial, easy) tests they've faced in life so far. Others arrive wondering how they got in, and hoping YC doesn't discover whatever mistake caused it to accept them. But there is little correlation between founders' initial attitudes and how well their companies do. I've read that the same is true in the military — that the swaggering recruits are no more likely to turn out to be really tough than the quiet ones. And probably for the same reason: that the tests involved are so different from the ones in their previous lives. If you're absolutely terrified of starting a startup, you probably shouldn't do it. But if you're merely unsure whether you're up to it, the only way to find out is to try.
Just not now. Ideas So if you want to start a startup one day, what should you do in college? There are only two things you need initially: an idea and cofounders. And the m.o. for getting both is the same. Which leads to our sixth and last counterintuitive point: that the way to get startup ideas is not to try to think of startup ideas. I've written a whole essay on this, so I won't repeat it all here. But the short version is that if you make a conscious effort to think of startup ideas, the ideas you come up with will not merely be bad, but bad and plausible-sounding, meaning you'll waste a lot of time on them before realizing they're bad. The way to come up with good startup ideas is to take a step back. Instead of making a conscious effort to think of startup ideas, turn your mind into the type that startup ideas form in without any conscious effort. In fact, so unconsciously that you don't even realize at first that they're startup ideas. This is not only possible, it's how Apple, Yahoo, Google, and Facebook all got started. None of these companies were even meant to be companies at first. They were all just side projects. The best startups almost have to start as side projects, because great ideas tend to be such outliers that your conscious mind would reject them as ideas for companies. Ok, so how do you turn your mind into the type that startup ideas form in unconsciously? (1) Learn a lot about things that matter, then (2) work on problems that interest you (3) with people you like and respect. The third part, incidentally, is how you get cofounders at the same time as the idea. The first time I wrote that paragraph, instead of "learn a lot about things that matter," I wrote "become good at some technology." But that prescription, though sufficient, is too narrow. What was special about Brian Chesky and Joe Gebbia was not that they were experts in technology.
They were good at design, and perhaps even more importantly, they were good at organizing groups and making projects happen. So you don't have to work on technology per se, so long as you work on problems demanding enough to stretch you. What kind of problems are those? That is very hard to answer in the general case. History is full of examples of young people who were working on important problems that no one else at the time thought were important, and in particular that their parents didn't think were important. On the other hand, history is even fuller of examples of parents who thought their kids were wasting their time and who were right. So how do you know when you're working on real stuff? [8] I know how _I_ know. Real problems are interesting, and I am self-indulgent in the sense that I always want to work on interesting things, even if no one else cares about them (in fact, especially if no one else cares about them), and find it very hard to make myself work on boring things, even if they're supposed to be important. My life is full of case after case where I worked on something just because it seemed interesting, and it turned out later to be useful in some worldly way. Y Combinator itself was something I only did because it seemed interesting. So I seem to have some sort of internal compass that helps me out. But I don't know what other people have in their heads. Maybe if I think more about this I can come up with heuristics for recognizing genuinely interesting problems, but for the moment the best I can offer is the hopelessly question-begging advice that if you have a taste for genuinely interesting problems, indulging it energetically is the best way to prepare yourself for a startup. And indeed, probably also the best way to live. [9] But although I can't explain in the general case what counts as an interesting problem, I can tell you about a large subset of them.
If you think of technology as something that's spreading like a sort of fractal stain, every moving point on the edge represents an interesting problem. So one guaranteed way to turn your mind into the type that has good startup ideas is to get yourself to the leading edge of some technology — to cause yourself, as Paul Buchheit put it, to "live in the future." When you reach that point, ideas that will seem to other people uncannily prescient will seem obvious to you. You may not realize they're startup ideas, but you'll know they're something that ought to exist. For example, back at Harvard in the mid 90s a fellow grad student of my friends Robert and Trevor wrote his own voice over IP software. He didn't mean it to be a startup, and he never tried to turn it into one. He just wanted to talk to his girlfriend in Taiwan without paying for long distance calls, and since he was an expert on networks it seemed obvious to him that the way to do it was turn the sound into packets and ship it over the Internet. He never did any more with his software than talk to his girlfriend, but this is exactly the way the best startups get started. So strangely enough the optimal thing to do in college if you want to be a successful startup founder is not some sort of new, vocational version of college focused on "entrepreneurship." It's the classic version of college as education for its own sake. If you want to start a startup after college, what you should do in college is learn powerful things. And if you have genuine intellectual curiosity, that's what you'll naturally tend to do if you just follow your own inclinations. [10] The component of entrepreneurship that really matters is domain expertise. The way to become Larry Page was to become an expert on search. And the way to become an expert on search was to be driven by genuine curiosity, not some ulterior motive. At its best, starting a startup is merely an ulterior motive for curiosity.
And you'll do it best if you introduce the ulterior motive toward the end of the process. So here is the ultimate advice for young would-be startup founders, boiled down to two words: just learn. Notes [1] Some founders listen more than others, and this tends to be a predictor of success. One of the things I remember about the Airbnbs during YC is how intently they listened. [2] In fact, this is one of the reasons startups are possible. If big companies weren't plagued by internal inefficiencies, they'd be proportionately more effective, leaving less room for startups. [3] In a startup you have to spend a lot of time on schleps, but this sort of work is merely unglamorous, not bogus. [4] What should you do if your true calling is gaming the system? Management consulting. [5] The company may not be incorporated, but if you start to get significant numbers of users, you've started it, whether you realize it yet or not. [6] It shouldn't be that surprising that colleges can't teach students how to be good startup founders, because they can't teach them how to be good employees either. The way universities "teach" students how to be employees is to hand off the task to companies via internship programs. But you couldn't do the equivalent thing for startups, because by definition if the students did well they would never come back. [7] Charles Darwin was 22 when he received an invitation to travel aboard the HMS Beagle as a naturalist. It was only because he was otherwise unoccupied, to a degree that alarmed his family, that he could accept it. And yet if he hadn't we probably would not know his name. [8] Parents can sometimes be especially conservative in this department.
There are some whose definition of important problems includes only those on the critical path to med school. [9] I did manage to think of a heuristic for detecting whether you have a taste for interesting ideas: whether you find known boring ideas intolerable. Could you endure studying literary theory, or working in middle management at a large company? [10] In fact, if your goal is to start a startup, you can stick even more closely to the ideal of a liberal education than past generations have. Back when students focused mainly on getting a job after college, they thought at least a little about how the courses they took might look to an employer. And perhaps even worse, they might shy away from taking a difficult class lest they get a low grade, which would harm their all-important GPA. Good news: users don't care what your GPA was. And I've never heard of investors caring either. Y Combinator certainly never asks what classes you took in college or what grades you got in them. Thanks to Sam Altman, Paul Buchheit, John Collison, Patrick Collison, Jessica Livingston, Robert Morris, Geoff Ralston, and Fred Wilson for reading drafts of this.
想创业吗? 获得 Y Combinator 的资助。
2014年10月 _(本文改编自Sam Altman在斯坦福大学创业课上的客座演讲。目标读者是大学生,但大部分内容也适用于其他年龄段的潜在创业者。)_ 为人父母的好处之一是,当你需要给出建议时,可以问自己“我会告诉我的孩子什么?”我的孩子还小,但我想象如果他们上大学时我会告诉他们关于创业的事,这就是我要告诉你们的。 创业非常反直觉。我不确定为什么。也许只是因为关于创业的知识还没有渗透到我们的文化中。但无论原因是什么,创业是一项你无法总是相信直觉的任务。 就像滑雪一样。当你第一次尝试滑雪想要减速时,本能反应是向后倾斜。但如果你在滑雪时向后倾斜,你会失控地飞下山坡。所以学习滑雪的一部分是学会抑制这种冲动。最终你会养成新的习惯,但起初需要刻意努力。一开始你会有一串在下山时要记住的事项清单。 创业和滑雪一样不自然,所以创业也有类似的清单。在这里,我将给你们第一部分——如果你想为创业做准备,需要记住的事项。 反直觉 清单上的第一点是我已经提到的事实:创业如此奇怪,如果你相信直觉,会犯很多错误。如果你只知道这一点,至少可以在犯错前停下来思考。 当我运营Y Combinator时,我常常开玩笑说我们的功能是告诉创始人他们会忽略的事情。这是真的。一批又一批的YC合伙人警告创始人他们即将犯的错误,创始人却忽视这些警告,然后一年后回来说“真希望我们当时听了”。 为什么创始人会忽视合伙人的建议?这就是反直觉想法的特点:它们与你的直觉相矛盾。它们看起来是错的。所以你的第一反应当然是忽略它们。事实上,我开玩笑的描述不仅是Y Combinator的诅咒,也是它存在的理由之一。如果创始人的直觉已经给出了正确答案,他们就不需要我们了。你只需要别人给你让你惊讶的建议。这就是为什么有很多滑雪教练,却很少有跑步教练。[1] 然而,你可以相信自己对人的直觉。事实上,年轻创始人最常犯的错误之一就是在这方面不够信任自己。他们会与那些看起来令人印象深刻但个人感觉有些不安的人合作。后来当事情搞砸时,他们会说“我早就觉得他有点不对劲,但因为看起来太厉害就忽略了。” 如果你考虑与某人合作——无论是联合创始人、员工、投资者还是收购方——并且对他们有疑虑,相信你的直觉。如果某人看起来滑头、虚伪或混蛋,不要忽视这种感觉。 在这种情况下,放纵自己是值得的。与你真正喜欢并且足够了解的人一起工作。 专业知识 第二个反直觉的点是,了解很多关于创业的知识并不是那么重要。在创业中取得成功的方法不是成为创业专家,而是成为用户和你为他们解决的问题的专家。马克·扎克伯格的成功并不是因为他是一个创业专家。尽管他对创业完全是个新手,但他成功了,因为他非常了解他的用户。 如果你对某些事情一无所知,比如如何筹集天使轮融资,不要因此感到糟糕。这类事情你可以在需要时学习,完成后就忘记。 事实上,我担心不仅没有必要详细了解创业的机制,而且可能有些危险。如果我遇到一个本科生,他对可转换债券、员工协议和(但愿不会)FF类股票了如指掌,我不会认为“这个人比同龄人领先很多”。这会触发警报。因为年轻创始人的另一个典型错误是走过场般地创业。他们编造一些听起来合理的主意,以不错的估值融资,租一个酷炫的办公室,雇一堆人。从外面看,这似乎是创业公司做的事。但租了酷炫办公室、雇了一堆人之后,下一步是:逐渐意识到他们完蛋了,因为虽然模仿了创业的所有外在形式,却忽略了真正关键的一件事:做出人们想要的东西。 游戏 我们经常看到这种情况,以至于给它起了个名字:过家家。最终我意识到为什么会发生这种情况。年轻创始人走过场般地创业是因为他们一生都在被训练这样做。想想你为了上大学必须做什么,比如课外活动,打勾。即使在大学课堂上,大部分作业也像跑圈一样是人为的。 我不是在攻击教育系统是这样的。当你学习某样东西时,你所做的工作中总会有一定程度的虚假性,如果你衡量他们的表现,人们不可避免地会利用这种差异,以至于你衡量的很多东西都是虚假性的产物。 我承认我在大学时也这样做。我发现很多课程可能只有20或30个适合出考题的想法。我为这些课程的考试学习的方式不是(除非顺便)掌握课程内容,而是列出可能的考题并提前准备好答案。当我走进期末考试时,我主要的感觉是好奇哪些问题会出现在考卷上。这就像一场游戏。 毫不奇怪,在被训练了一辈子玩这种游戏后,年轻创始人创业时的第一反应是试图找出赢得这场新游戏的技巧。由于融资似乎是衡量创业成功的标准(另一个典型的新手错误),他们总是想知道说服投资者的技巧是什么。我们告诉他们,说服投资者的最佳方式是做一个真正表现良好的创业公司,意思是快速增长,然后简单地告诉投资者。然后他们想知道快速增长的技巧是什么。我们不得不告诉他们,最好的方式就是做出人们想要的东西。 YC合伙人与年轻创始人的许多对话都以创始人问“我们如何……”而合伙人回答“只要……”开始。 为什么创始人总是把事情搞得这么复杂?我意识到,原因是他们在寻找技巧。 所以这是关于创业的第三个反直觉的事情:创业是玩弄系统不再有效的地方。如果你去大公司工作,玩弄系统可能仍然有效。根据公司的糟糕程度,你可以通过讨好正确的人、制造高效印象等方式取得成功。[2]但这在创业公司行不通。没有老板可以糊弄,只有用户,而用户关心的只是你的产品是否满足他们的需求。创业公司像物理学一样客观。你必须做出人们想要的东西,只有做到这一点你才能成功。 危险的是,伪装在投资者面前确实有一定效果。如果你非常擅长听起来像你知道自己在说什么,你可以愚弄投资者至少一轮甚至两轮融资。但这并不符合你的利益。公司最终注定失败。你所做的只是浪费自己的时间随它沉没。 所以别再寻找技巧了。创业中有技巧,就像任何领域一样,但它们的重要性比解决真正问题低一个数量级。一个对融资一无所知但做出了用户喜爱的产品的创始人,会比一个知道所有技巧但用户增长平平的创始人更容易融资。更重要的是,做出用户喜爱的产品的创始人会在融资后继续成功。 尽管从某种意义上说这是个坏消息,因为你失去了最强大的武器之一,但我认为当创业时玩弄系统不再有效是令人兴奋的。令人兴奋的是世界上还存在通过做好工作就能赢的地方。想象一下如果世界都像学校和大公司一样,你要么花大量时间在无意义的事情上,要么输给那些这样做的人,那会有多压抑。[3]如果我在大学时就意识到现实世界中有一些地方玩弄系统不那么重要,甚至几乎不重要,我会很高兴。但确实有这样的地方,这种差异是你在思考未来时需要考虑的最重要的事情之一。你如何在每种类型的工作中获胜,以及你希望通过做什么来获胜?[4] 全情投入 这引出了我们的第四个反直觉点:创业会占据你的全部生活。如果你创业,它会以一种你无法想象的程度接管你的生活。如果你的创业成功了,它会在很长一段时间内接管你的生活:至少几年,也许十年,也许是你剩余的工作生涯。所以这里有一个真正的机会成本。 拉里·佩奇的生活看起来令人羡慕,但有些方面并不令人羡慕。基本上在25岁时他开始全速奔跑,对他来说似乎从那以后就没有停下来喘口气。谷歌帝国每天都会发生只有CEO能处理的新问题,而他作为CEO必须处理。即使他只休假一周,也会积累整整一周的问题。他必须毫无怨言地承受这一切,部分原因是作为公司的父亲,他永远不能表现出恐惧或软弱,部分原因是亿万富翁如果谈论生活艰难,得到的同情会少于零。这产生了一个奇怪的副作用:成功创业创始人的困难几乎对所有人隐瞒,除了那些亲身经历过的人。 Y Combinator现在已经资助了几家可以称为大成功的公司,在每一种情况下,创始人都说了同样的话。事情从不会变得更容易。问题的性质会改变。你担心的是伦敦办公室的建设延误,而不是公寓里坏掉的空调。但担忧的总量从未减少;如果有什么变化,那就是增加了。 创办一家成功的创业公司类似于生孩子,就像按下一个按钮,不可逆转地改变你的生活。尽管有孩子真的很棒,但有很多事情在有孩子之前做比之后更容易。其中许多事情会让你在有孩子时成为更好的父母。由于你可以推迟按下按钮一段时间,大多数富裕国家的人确实这样做了。 然而,当谈到创业时,很多人似乎认为他们应该在大学期间就开始创业。你疯了吗?大学又在想什么?他们千方百计确保学生有充足的避孕措施,却又到处设立创业项目和创业孵化器。 公平地说,大学在这方面是被迫的。许多新生对创业感兴趣。大学至少在事实上被期望为他们的职业生涯做准备。所以想创业的学生希望大学能教他们关于创业的知识。无论大学是否能做到这一点,都有一些压力声称他们可以,以免失去申请者到其他这样做的大学。 大学能教学生创业吗?既是也不是。他们可以教学生关于创业的知识,但正如我之前解释的,这不是你需要知道的。你需要了解的是你自己用户的需求,而这只有在你真正创办公司后才能做到。[5]所以创业本质上是一件你只能通过实践真正学习的事情。在大学里不可能做到这一点,原因我刚刚解释过:创业会接管你的生活。你不能真正以学生的身份创业,因为如果你真正创业,你就不再是学生了。名义上你可能暂时还是学生,但不会太久。[6] 面对这种二分法,你应该选择哪条路?做一个真正的学生而不创业,还是真正创业而不做学生?我可以为你回答这个问题。不要在大学期间创业。如何创业只是你试图解决的更大问题的一个子集:如何拥有美好生活。尽管创业对许多有抱负的人来说可以是美好生活的一部分,但20岁并不是做这件事的最佳时机。创业就像一次极其快速的深度优先搜索。大多数人在20岁时仍应进行广度优先搜索。 你在20岁出头时可以做一些之前或之后都无法做得这么好的事情,比如一时兴起深入某个项目,或者毫无截止日期地超级便宜地旅行。对没有抱负的人来说,这种事情是可怕的“无法自立”,但对有抱负的人来说,这可能是一种无与伦比的宝贵探索。如果你在20岁创业并且足够成功,你将永远无法做这些事情。[7] 马克·扎克伯格永远无法在外国闲逛。他可以做大多数人都做不到的事情,比如包机飞往外国。但成功剥夺了他生活中的许多偶然性。Facebook在管理他,就像他在管理Facebook一样。尽管被你认为毕生工作的项目所掌控可能很酷,但偶然性也有其优势,尤其是在年轻时。其中一点是它给你更多选择来挑选你的毕生工作。 这里甚至没有权衡。如果你放弃在20岁创业,你并没有牺牲任何东西,因为等待更有可能成功。在极少数情况下,如果你20岁时某个副业像Facebook一样起飞,你将面临是否继续的选择,继续可能是合理的。但创业通常起飞的方式是创始人让它们起飞,而在20岁这样做是毫无必要的愚蠢。 尝试 你应该在任何年龄创业吗?我意识到我让创业听起来相当困难。如果我没有,让我再试一次:创业真的很难。如果太难怎么办?你如何判断自己能否应对这一挑战? 答案是第五个反直觉点:你无法判断。到目前为止的生活可能让你对如果尝试成为数学家或职业足球运动员的前景有所了解。但除非你过着非常奇怪的生活,否则你没有做过多少像创业创始人那样的事情。创业会极大地改变你。所以你试图估计的不仅是你现在是什么样的人,还有你能成长为什么样的人,而谁能做到这一点? 在过去的9年里,我的工作是预测人们是否具备创办成功创业公司的条件。判断他们有多聪明很容易,大多数读这篇文章的人都会超过这个门槛。困难的部分是预测他们会变得多么坚韧和有抱负。可能没有人比我更有经验试图预测这一点,所以我可以告诉你专家能知道多少,答案是:不多。我学会了完全开放地看待每批中哪些创业公司会成为明星。 创始人有时认为他们知道。有些人来的时候确信他们会像在生活中迄今为止面对的(少数、人为的、简单的)测试一样轻松通过Y Combinator。其他人来的时候想知道他们是怎么被录取的,希望YC不会发现导致他们被接受的错误。但创始人的初始态度与公司表现之间的相关性很小。 我读到军队中也是如此——自大的新兵并不比安静的新兵更有可能成为真正坚韧的人。可能出于同样的原因:涉及的测试与他们以前生活中的测试如此不同。 如果你对创业感到极度恐惧,你可能不应该做。但如果你只是不确定自己能否胜任,唯一的方法是尝试。只是不是现在。 想法 所以如果你有一天想创业,在大学期间应该做什么?最初只需要两件事:一个想法和联合创始人。获取这两者的方法是相同的。这引出了我们的第六个也是最后一个反直觉点:获取创业想法的方式不是试图想出创业想法。 我已经写了一整篇文章讨论这一点,所以在这里不再重复。但简短的版本是,如果你刻意努力想出创业想法,你想出的想法不仅会很糟糕,而且会听起来合理,这意味着你会在意识到它们糟糕之前浪费大量时间。 想出好的创业想法的方法是退一步。不要刻意努力想出创业想法,而是将你的思维转变为那种无需刻意努力就能自然形成创业想法的类型。事实上,如此无意识以至于你一开始甚至没有意识到它们是创业想法。 这不仅可能,而且苹果、雅虎、谷歌和Facebook都是这样开始的。这些公司最初甚至没打算成为公司。它们都只是副业。最好的创业公司几乎必须从副业开始,因为伟大的想法往往是如此异常,以至于你的有意识思维会拒绝将它们作为公司想法。 那么,如何将你的思维转变为那种无意识形成创业想法的类型?(1) 学习很多重要的事情,然后 (2) 研究你感兴趣的问题 (3) 与你喜欢和尊重的人一起。顺便说一句,第三部分也是你同时获得联合创始人的方式。 我第一次写这一段时,没有写“学习很多重要的事情”,而是写“精通某种技术”。但这个处方虽然足够,但太狭窄了。布莱恩·切斯基和乔·格比亚的特殊之处不在于他们是技术专家。他们擅长设计,或许更重要的是,他们擅长组织团队和推动项目。所以你不必专门研究技术,只要你研究的问题足够有挑战性。 哪些问题是这样的?这在一般情况下很难回答。历史上有许多年轻人研究当时其他人认为不重要的问题的例子,特别是他们的父母认为不重要的问题。另一方面,历史上更多的是父母认为孩子浪费时间而他们是对的的例子。所以你如何知道你在研究真正重要的事情?[8] 我知道我是如何知道的。真正的问题是有趣的,而我是自我放纵的,因为我总是想研究有趣的事情,即使没有人在乎它们(事实上,特别是没有人在乎它们),并且发现很难强迫自己研究无聊的事情,即使它们被认为很重要。 我的生活中充满了仅仅因为看起来有趣而研究某事的案例,后来发现它们在某些实际方面很有用。Y Combinator本身就是因为我只是觉得有趣才做的。所以我似乎有某种内在的指南针帮助我。但我不知道别人脑子里有什么。也许如果我多思考这一点,可以想出识别真正有趣问题的启发式方法,但目前我能提供的最好的建议是毫无帮助的循环论证:如果你对真正有趣的问题有品味,那么尽情放纵它是为创业做准备的最佳方式。事实上,可能也是最佳的生活方式。[9] 尽管我无法在一般情况下解释什么算是有趣的问题,但我可以告诉你其中的一大类。如果你将技术视为一种像分形污渍一样扩散的东西,边缘上的每一个移动点都代表一个有趣的问题。所以将你的思维转变为那种有好创业想法的类型的保证方法之一是让自己处于某项技术的前沿——正如保罗·布赫海特所说,让自己“生活在未来”。当你到达这一点时,对其他人来说看起来不可思议地有先见之明的想法对你来说会显得显而易见。你可能不会意识到它们是创业想法,但你会知道它们应该存在。 例如,回到90年代中期的哈佛,我朋友罗伯特和特雷弗的一位研究生同学编写了自己的VoIP软件。他并不是想创业,也从未尝试将其变成创业。他只是想和他在台湾的女友通话而不支付长途电话费,而由于他是网络专家,对他来说显然的方法是将声音转换成数据包并通过互联网传输。他从未用他的软件做过比和女友通话更多的事情,但这正是最好的创业公司的起步方式。 所以奇怪的是,如果你想成为一名成功的创业创始人,在大学期间最优的做法不是某种新的、以“创业”为重点的职业化大学版本。而是经典的为学习而学习的大学版本。如果你想大学毕业后创业,你在大学期间应该做的是学习强大的东西。如果你有真正的好奇心,这正是你跟随自己倾向自然会做的事。[10] 创业中真正重要的组成部分是领域专业知识。成为拉里·佩奇的方法是成为搜索专家。而成为搜索专家的方法是被真正的好奇心驱动,而不是某种隐藏动机。 在最好的情况下,创业只是好奇心的隐藏动机。如果你在过程接近尾声时才引入这个隐藏动机,你会做得最好。 所以对年轻的潜在创业创始人的终极建议,浓缩为两个字:去学习。 注释 [1] 有些创始人比其他人更愿意倾听,这往往是成功的预测因素。我记得Airbnb在YC期间的一件事是他们听得多么专注。 [2] 事实上,这是创业公司可能存在的原因之一。如果大公司没有被内部低效所困扰,它们的效率会成比例地更高,给创业公司留下的空间会更小。 [3] 在创业公司中,你必须花很多时间在苦差事上,但这种工作只是不光彩,并非虚假。 [4] 如果你真正的天职是玩弄系统,你应该做什么?管理咨询。 [5] 公司可能尚未注册,但如果你开始获得大量用户,你已经开始了它,无论你是否意识到。 [6] 大学无法教会学生如何成为优秀的创业创始人并不奇怪,因为它们也无法教会他们如何成为优秀的员工。 大学“教”学生如何成为员工的方式是通过实习计划将任务交给公司。但你无法对创业公司做同样的事,因为根据定义,如果学生做得好,他们永远不会回来。 [7] 查尔斯·达尔文22岁时收到邀请作为博物学家乘坐HMS Beagle号航行。正是因为他当时无所事事(程度让他的家人担忧),他才能接受。而如果他没有,我们可能不会知道他的名字。 [8] 父母有时在这方面尤其保守。有些人将重要问题的定义仅限于那些通往医学院的关键路径上的问题。 [9] 我确实想出了一个启发式方法来检测你是否对有趣的想法有品味:你是否发现已知的无聊想法难以忍受。你能忍受学习文学理论,或在大公司担任中层管理吗? [10] 事实上,如果你的目标是创业,你可以比过去几代人更紧密地坚持通.
Want to start a startup? Get funded by Y Combinator.
September 2013 Most startups that raise money do it more than once. A typical trajectory might be (1) to get started with a few tens of thousands from something like Y Combinator or individual angels, then (2) raise a few hundred thousand to a few million to build the company, and then (3) once the company is clearly succeeding, raise one or more later rounds to accelerate growth. Reality can be messier. Some companies raise money twice in phase 2\. Others skip phase 1 and go straight to phase 2. And at Y Combinator we get an increasing number of companies that have already raised amounts in the hundreds of thousands. But the three phase path is at least the one about which individual startups' paths oscillate. This essay focuses on phase 2 fundraising. That's the type the startups we fund are doing on Demo Day, and this essay is the advice we give them. Forces Fundraising is hard in both senses: hard like lifting a heavy weight, and hard like solving a puzzle. It's hard like lifting a weight because it's intrinsically hard to convince people to part with large sums of money. That problem is irreducible; it should be hard. But much of the other kind of difficulty can be eliminated. Fundraising only seems a puzzle because it's an alien world to most founders, and I hope to fix that by supplying a map through it. To founders, the behavior of investors is often opaque — partly because their motivations are obscure, but partly because they deliberately mislead you. And the misleading ways of investors combine horribly with the wishful thinking of inexperienced founders.
想创立一家初创公司? 获得 Y Combinator 的资助。
大多数初创公司在融资时往往需要多次进行。典型的路径可能是:(1) 通过 Y Combinator 或个别天使投资人获得数万美元的启动资金;(2) 筹集数十万到数百万美元来建设公司;(3) 一旦公司明显取得成功,再进行一轮或多轮融资以加速增长。
At YC we're always warning founders about this danger, and investors are probably more circumspect with YC startups than with other companies they talk to, and even so we witness a constant series of explosions as these two volatile components combine. [1] If you're an inexperienced founder, the only way to survive is by imposing external constraints on yourself. You can't trust your intuitions. I'm going to give you a set of rules here that will get you through this process if anything will. At certain moments you'll be tempted to ignore them. So rule number zero is: these rules exist for a reason. You wouldn't need a rule to keep you going in one direction if there weren't powerful forces pushing you in another. The ultimate source of the forces acting on you are the forces acting on investors. Investors are pinched between two kinds of fear: fear of investing in startups that fizzle, and fear of missing out on startups that take off. The cause of all this fear is the very thing that makes startups such attractive investments: the successful ones grow very fast. But that fast growth means investors can't wait around. If you wait till a startup is obviously a success, it's too late. To get the really high returns, you have to invest in startups when it's still unclear how they'll do. But that in turn makes investors nervous they're about to invest in a flop. As indeed they often are. What investors would like to do, if they could, is wait. When a startup is only a few months old, every week that passes gives you significantly more information about them. But if you wait too long, other investors might take the deal away from you. And of course the other investors are all subject to the same forces.
现实可能更加混乱。有些公司在第二阶段会融资两次,有些则跳过第一阶段直接进入第二阶段。而在 Y Combinator,我们看到越来越多的公司已经筹集了数十万美元的资金。但无论如何,这三个阶段至少是大多数初创公司融资路径的基本框架。
本文重点讨论第二阶段的融资。这是我们资助的初创公司在 Demo Day 上进行的融资类型,也是我们给他们的建议。
融资在两个方面都很困难:一是像举起重物一样费力,二是像解谜一样复杂。它之所以费力,是因为说服人们拿出大笔资金本身就是一件难事。这个问题无法简化,它本来就应该是困难的。但另一种困难(复杂性)很大程度上是可以消除的。融资之所以看起来像解谜,是因为对大多数创始人来说,这是一个陌生的领域。我希望通过提供一张“地图”来解决这个问题。
So what tends to happen is that they all wait as long as they can, then when some act the rest have to. Don't raise money unless you want it and it wants you. Such a high proportion of successful startups raise money that it might seem fundraising is one of the defining qualities of a startup. Actually it isn't. Rapid growth is what makes a company a startup. Most companies in a position to grow rapidly find that (a) taking outside money helps them grow faster, and (b) their growth potential makes it easy to attract such money. It's so common for both (a) and (b) to be true of a successful startup that practically all do raise outside money. But there may be cases where a startup either wouldn't want to grow faster, or outside money wouldn't help them to, and if you're one of them, don't raise money. The other time not to raise money is when you won't be able to. If you try to raise money before you can convince investors, you'll not only waste your time, but also burn your reputation with those investors. Be in fundraising mode or not. One of the things that surprises founders most about fundraising is how distracting it is. When you start fundraising, everything else grinds to a halt. The problem is not the time fundraising consumes but that it becomes the top idea in your mind. A startup can't endure that level of distraction for long. An early stage startup grows mostly because the founders make it grow, and if the founders look away, growth usually drops sharply. Because fundraising is so distracting, a startup should either be in fundraising mode or not. And when you do decide to raise money, you should focus your whole attention on it so you can get it done quickly and get back to work. [2] You can take money from investors when you're not in fundraising mode. You just can't expend any attention on it.
对创始人来说,投资者的行为往往是不透明的——部分原因是他们的动机模糊,部分原因是他们故意误导你。投资者的误导行为与缺乏经验的创始人的一厢情愿结合在一起,后果尤为严重。在 YC,我们总是警告创始人注意这种危险。投资者在与 YC 初创公司打交道时可能比其他公司更加谨慎,即便如此,我们仍然目睹了这两种不稳定因素结合时不断发生的“爆炸”。[1]
如果你是一位缺乏经验的创始人,唯一的生存方法是对自己施加外部约束。你不能相信自己的直觉。我将在这里给你一套规则,如果有什么方法能帮你度过这个过程,那就是这些规则了。在某些时刻,你可能会忍不住忽略它们。因此,规则零是:这些规则的存在是有原因的。如果没有强大的力量将你推向另一个方向,你就不需要规则来让你坚持某个方向。
作用于你的力量的根源是作用于投资者的力量。投资者被两种恐惧夹在中间:一是害怕投资失败的初创公司,二是害怕错过成功的初创公司。所有这些恐惧的根源正是让初创公司成为诱人投资的原因:成功的初创公司增长非常快。但这种快速增长意味着投资者不能等待。如果你等到一家初创公司明显成功时再投资,那就太晚了。要获得真正的高回报,你必须在初创公司前景尚不明朗时投资。但这反过来又让投资者担心他们可能会投资失败的项目。事实上,他们也经常如此。
There are two things that take attention: convincing investors, and negotiating with them. So when you're not in fundraising mode, you should take money from investors only if they require no convincing, and are willing to invest on terms you'll take without negotiation. For example, if a reputable investor is willing to invest on a convertible note, using standard paperwork, that is either uncapped or capped at a good valuation, you can take that without having to think. [3] The terms will be whatever they turn out to be in your next equity round. And "no convincing" means just that: zero time spent meeting with investors or preparing materials for them. If an investor says they're ready to invest, but they need you to come in for one meeting to meet some of the partners, tell them no, if you're not in fundraising mode, because that's fundraising. [4] Tell them politely; tell them you're focusing on the company right now, and that you'll get back to them when you're fundraising; but do not get sucked down the slippery slope. Investors will try to lure you into fundraising when you're not. It's great for them if they can, because they can thereby get a shot at you before everyone else. They'll send you emails saying they want to meet to learn more about you. If you get cold-emailed by an associate at a VC firm, you shouldn't meet even if you are in fundraising mode. Deals don't happen that way. [5] But even if you get an email from a partner you should try to delay meeting till you're in fundraising mode. They may say they just want to meet and chat, but investors never just want to meet and chat.
如果可能的话,投资者希望做的是等待。当一家初创公司只有几个月大时,每周的过去都会为你提供更多关于它的信息。但如果你等得太久,其他投资者可能会抢走这笔交易。当然,其他投资者也受到同样的力量影响。因此,通常的情况是,他们都会尽可能等待,直到某些人行动时,其他人也不得不跟进。
除非你想要钱且钱想要你,否则不要融资。
What if they like you? What if they start to talk about giving you money? Will you be able to resist having that conversation? Unless you're experienced enough at fundraising to have a casual conversation with investors that stays casual, it's safer to tell them that you'd be happy to later, when you're fundraising, but that right now you need to focus on the company. [6] Companies that are successful at raising money in phase 2 sometimes tack on a few investors after leaving fundraising mode. This is fine; if fundraising went well, you'll be able to do it without spending time convincing them or negotiating about terms. Get introductions to investors. Before you can talk to investors, you have to be introduced to them. If you're presenting at a Demo Day, you'll be introduced to a whole bunch simultaneously. But even if you are, you should supplement these with intros you collect yourself. Do you have to be introduced? In phase 2, yes. Some investors will let you email them a business plan, but you can tell from the way their sites are organized that they don't really want startups to approach them directly. Intros vary greatly in effectiveness. The best type of intro is from a well-known investor who has just invested in you. So when you get an investor to commit, ask them to introduce you to other investors they respect. [7] The next best type of intro is from a founder of a company they've funded. You can also get intros from other people in the startup community, like lawyers and reporters. There are now sites like AngelList, FundersClub, and WeFunder that can introduce you to investors. We recommend startups treat them as auxiliary sources of money. Raise money first from leads you get yourself. Those will on average be better investors.
成功的初创公司中融资的比例很高,以至于融资似乎成为初创公司的定义特征之一。实际上并非如此。快速增长才是让一家公司成为初创公司的原因。大多数具有快速增长潜力的公司发现:(a) 接受外部资金有助于他们更快增长;(b) 他们的增长潜力使其容易吸引资金。对于成功的初创公司来说,(a) 和 (b) 通常同时成立,因此几乎所有公司都会进行外部融资。但也可能存在一些情况,初创公司要么不想增长得更快,要么外部资金对他们没有帮助。如果你是其中之一,就不要融资。
另一种不要融资的情况是你无法融到资金。如果你在能够说服投资者之前尝试融资,不仅会浪费你的时间,还会损害你在那些投资者中的声誉。
要么处于融资模式,要么不处于。
Plus you'll have an easier time raising money on these sites once you can say you've already raised some from well-known investors. Hear no till you hear yes. Treat investors as saying no till they unequivocally say yes, in the form of a definite offer with no contingencies. I mentioned earlier that investors prefer to wait if they can. What's particularly dangerous for founders is the way they wait. Essentially, they lead you on. They seem like they're about to invest right up till the moment they say no. If they even say no. Some of the worse ones never actually do say no; they just stop replying to your emails. They hope that way to get a free option on investing. If they decide later that they want to invest — usually because they've heard you're a hot deal — they can pretend they just got distracted and then restart the conversation as if they'd been about to. [8] That's not the worst thing investors will do. Some will use language that makes it sound as if they're committing, but which doesn't actually commit them. And wishful thinking founders are happy to meet them half way. [9] Fortunately, the next rule is a tactic for neutralizing this behavior. But to work it depends on you not being tricked by the no that sounds like yes. It's so common for founders to be misled/mistaken about this that we designed a protocol to fix the problem. If you believe an investor has committed, get them to confirm it. If you and they have different views of reality, whether the source of the discrepancy is their sketchiness or your wishful thinking, the prospect of confirming a commitment in writing will flush it out. And till they confirm, regard them as saying no. Do breadth-first search weighted by expected value. When you talk to investors your m.o. should be breadth-first search, weighted by expected value. You should always talk to investors in parallel rather than serially.
关于融资,最让创始人惊讶的事情之一是它有多么分散注意力。当你开始融资时,其他一切都会停滞不前。问题不在于融资占用的时间,而在于它成为你头脑中的首要想法。初创公司无法长期忍受这种程度的干扰。早期初创公司的增长主要依赖于创始人的推动,如果创始人分心,增长通常会急剧下降。
由于融资非常分散注意力,初创公司应该要么处于融资模式,要么不处于。当你决定融资时,你应该将全部注意力集中在它上面,以便快速完成并回到工作中。[2]
你可以在不处于融资模式时接受投资者的资金。只是不能为此分散任何注意力。有两件事会分散注意力:说服投资者和与他们谈判。因此,当你不处于融资模式时,你应该只接受那些不需要说服、并且愿意按照你无需谈判的条件投资的资金。例如,如果一位信誉良好的投资者愿意通过可转换债券投资,使用标准文件,且没有上限或以合理的估值上限,你可以毫不犹豫地接受。[3] 条款将是你下一轮股权融资时的实际条款。“无需说服”意味着零时间花在与投资者会面或为他们准备材料上。如果一位投资者表示他们准备投资,但需要你参加一次会议与一些合伙人见面,如果你不处于融资模式,就告诉他们不行,因为那就是融资。[4] 礼貌地告诉他们;告诉他们你现在专注于公司,当你融资时会联系他们;但不要被拖入这个滑坡。
You can't afford the time it takes to talk to investors serially, plus if you only talk to one investor at a time, they don't have the pressure of other investors to make them act. But you shouldn't pay the same attention to every investor, because some are more promising prospects than others. The optimal solution is to talk to all potential investors in parallel, but give higher priority to the more promising ones. [10] Expected value = how likely an investor is to say yes, multiplied by how good it would be if they did. So for example, an eminent investor who would invest a lot, but will be hard to convince, might have the same expected value as an obscure angel who won't invest much, but will be easy to convince. Whereas an obscure angel who will only invest a small amount, and yet needs to meet multiple times before making up his mind, has very low expected value. Meet such investors last, if at all. [11] Doing breadth-first search weighted by expected value will save you from investors who never explicitly say no but merely drift away, because you'll drift away from them at the same rate. It protects you from investors who flake in much the same way that a distributed algorithm protects you from processors that fail. If some investor isn't returning your emails, or wants to have lots of meetings but isn't progressing toward making you an offer, you automatically focus less on them. But you have to be disciplined about assigning probabilities. You can't let how much you want an investor influence your estimate of how much they want you. Know where you stand. How do you judge how well you're doing with an investor, when investors habitually seem more positive than they are? By looking at their actions rather than their words. Every investor has some track they need to move along from the first conversation to wiring the money, and you should always know what that track consists of, where you are on it, and how fast you're moving forward.
投资者会试图在你不在融资模式时引诱你进入融资。对他们来说,如果能做到这一点就太好了,因为他们可以抢在其他人之前对你进行投资。他们会给你发邮件说想见面了解更多关于你的信息。如果你收到风投公司一位助理的冷邮件,即使你处于融资模式也不应该见面。交易不会以这种方式发生。[5] 但即使你收到合伙人的邮件,你也应该尽量推迟见面,直到你处于融资模式。他们可能会说只是想见面聊聊,但投资者从来不只是想见面聊聊。如果他们喜欢你呢?如果他们开始谈论给你钱呢?你能抗拒这种对话吗?除非你对融资足够有经验,能够与投资者进行轻松的对话而不至于偏离主题,否则更安全的做法是告诉他们你很高兴以后在融资时见面,但现在你需要专注于公司。[6]
在第二阶段成功融资的公司有时会在离开融资模式后增加一些投资者。这没问题;如果融资进展顺利,你可以在不花时间说服他们或谈判条款的情况下完成。
Never leave a meeting with an investor without asking what happens next. What more do they need in order to decide? Do they need another meeting with you? To talk about what? And how soon? Do they need to do something internally, like talk to their partners, or investigate some issue? How long do they expect it to take? Don't be too pushy, but know where you stand. If investors are vague or resist answering such questions, assume the worst; investors who are seriously interested in you will usually be happy to talk about what has to happen between now and wiring the money, because they're already running through that in their heads. [12] If you're experienced at negotiations, you already know how to ask such questions. [13] If you're not, there's a trick you can use in this situation. Investors know you're inexperienced at raising money. Inexperience there doesn't make you unattractive. Being a noob at technology would, if you're starting a technology startup, but not being a noob at fundraising. Larry and Sergey were noobs at fundraising. So you can just confess that you're inexperienced at this and ask how their process works and where you are in it. [14] Get the first commitment. The biggest factor in most investors' opinions of you is the opinion of other investors. Once you start getting investors to commit, it becomes increasingly easy to get more to. But the other side of this coin is that it's often hard to get the first commitment. Getting the first substantial offer can be half the total difficulty of fundraising. What counts as a substantial offer depends on who it's from and how much it is. Money from friends and family doesn't usually count, no matter how much. But if you get $50k from a well known VC firm or angel investor, that will usually be enough to set things rolling. [15] Close committed money. It's not a deal till the money's in the bank.
获得投资者的引荐。
在与投资者交谈之前,你必须被引荐给他们。如果你在 Demo Day 上展示,你会同时被引荐给一大批投资者。但即便如此,你也应该通过自己收集的引荐来补充这些。
你必须被引荐吗?在第二阶段,是的。一些投资者会让你通过电子邮件发送商业计划书,但从他们网站的布局可以看出,他们并不真正希望初创公司直接联系他们。
I often hear inexperienced founders say things like "We've raised $800,000," only to discover that zero of it is in the bank so far. Remember the twin fears that torment investors? The fear of missing out that makes them jump early, and the fear of jumping onto a turd that results? This is a market where people are exceptionally prone to buyer's remorse. And it's also one that furnishes them plenty of excuses to gratify it. The public markets snap startup investing around like a whip. If the Chinese economy blows up tomorrow, all bets are off. But there are lots of surprises for individual startups too, and they tend to be concentrated around fundraising. Tomorrow a big competitor could appear, or you could get C&Ded, or your cofounder could quit. [16] Even a day's delay can bring news that causes an investor to change their mind. So when someone commits, get the money. Knowing where you stand doesn't end when they say they'll invest. After they say yes, know what the timetable is for getting the money, and then babysit that process till it happens. Institutional investors have people in charge of wiring money, but you may have to hunt angels down in person to collect a check. Inexperienced investors are the ones most likely to get buyer's remorse. Established ones have learned to treat saying yes as like diving off a diving board, and they also have more brand to preserve. But I've heard of cases of even top-tier VC firms welching on deals. Avoid investors who don't "lead." Since getting the first offer is most of the difficulty of fundraising, that should be part of your calculation of expected value when you start. You have to estimate not just the probability that an investor will say yes, but the probability that they'd be the _first_ to say yes, and the latter is not simply a constant fraction of the former. Some investors are known for deciding quickly, and those are extra valuable early on.
引荐的效果差异很大。最好的引荐来自一位刚刚投资你的知名投资者。因此,当你获得一位投资者的承诺时,请他们向你介绍他们尊重的其他投资者。[7] 次好的引荐来自他们投资过的公司的创始人。你也可以从初创企业社区的其他人士那里获得引荐,比如律师和记者。
现在有一些网站,如 AngelList、FundersClub 和 WeFunder,可以为你介绍投资者。我们建议初创公司将它们视为资金的辅助来源。首先从你自己获得的线索中筹集资金。这些投资者平均来说会更好。此外,一旦你能说你已经从知名投资者那里筹集了一些资金,你在这些网站上筹集资金也会更容易。
听到“不”直到听到“是”。
Conversely, an investor who will only invest once other investors have is worthless initially. And while most investors are influenced by how interested other investors are in you, there are some who have an explicit policy of only investing after other investors have. You can recognize this contemptible subspecies of investor because they often talk about "leads." They say that they don't lead, or that they'll invest once you have a lead. Sometimes they even claim to be willing to lead themselves, by which they mean they won't invest till you get $x from other investors. (It's great if by "lead" they mean they'll invest unilaterally, and in addition will help you raise more. What's lame is when they use the term to mean they won't invest unless you can raise more elsewhere.) [17] Where does this term "lead" come from? Up till a few years ago, startups raising money in phase 2 would usually raise equity rounds in which several investors invested at the same time using the same paperwork. You'd negotiate the terms with one "lead" investor, and then all the others would sign the same documents and all the money change hands at the closing. Series A rounds still work that way, but things now work differently for most fundraising prior to the series A. Now there are rarely actual rounds before the A round, or leads for them. Now startups simply raise money from investors one at a time till they feel they have enough. Since there are no longer leads, why do investors use that term? Because it's a more legitimate-sounding way of saying what they really mean. All they really mean is that their interest in you is a function of other investors' interest in you. I.e. the spectral signature of all mediocre investors. But when phrased in terms of leads, it sounds like there is something structural and therefore legitimate about their behavior.
将投资者的态度视为“不”,直到他们明确表示“是”,即提供一份无条件的明确报价。
我之前提到,投资者如果可能的话更愿意等待。对创始人来说特别危险的是他们的等待方式。本质上,他们会吊着你。他们看起来像是即将投资,直到最后一刻才说“不”。如果他们甚至会说“不”的话。一些更糟糕的投资者甚至永远不会明确说“不”;他们只是停止回复你的邮件。他们希望通过这种方式获得投资的免费选择权。如果他们后来决定投资——通常是因为听说你是个热门交易——他们可以假装自己只是分心了,然后重新开始对话,好像他们一直准备投资一样。[8]
When an investor tells you "I want to invest in you, but I don't lead," translate that in your mind to "No, except yes if you turn out to be a hot deal." And since that's the default opinion of any investor about any startup, they've essentially just told you nothing. When you first start fundraising, the expected value of an investor who won't "lead" is zero, so talk to such investors last if at all. Have multiple plans. Many investors will ask how much you're planning to raise. This question makes founders feel they should be planning to raise a specific amount. But in fact you shouldn't. It's a mistake to have fixed plans in an undertaking as unpredictable as fundraising. So why do investors ask how much you plan to raise? For much the same reasons a salesperson in a store will ask "How much were you planning to spend?" if you walk in looking for a gift for a friend. You probably didn't have a precise amount in mind; you just want to find something good, and if it's inexpensive, so much the better. The salesperson asks you this not because you're supposed to have a plan to spend a specific amount, but so they can show you only things that cost the most you'll pay. Similarly, when investors ask how much you plan to raise, it's not because you're supposed to have a plan. It's to see whether you'd be a suitable recipient for the size of investment they like to make, and also to judge your ambition, reasonableness, and how far you are along with fundraising. If you're a wizard at fundraising, you can say "We plan to raise a $7 million series A round, and we'll be accepting termsheets next tuesday." I've known a handful of founders who could pull that off without having VCs laugh in their faces. But if you're in the inexperienced but earnest majority, the solution is analogous to the solution I recommend for pitching your startup: do the right thing and then just tell investors what you're doing.
这还不是投资者会做的最糟糕的事情。有些人会使用听起来像是承诺的语言,但实际上并没有承诺。而一厢情愿的创始人则乐于与他们妥协。[9]
幸运的是,下一条规则是中和这种行为的一种策略。但它的有效性取决于你不被听起来像“是”的“不”所欺骗。创始人在这一点上被误导或误解的情况非常普遍,以至于我们设计了一个协议来解决这个问题。如果你认为一位投资者已经承诺,让他们确认这一点。如果你和他们对现实的看法不同,无论这种差异的来源是他们的含糊其辞还是你的一厢情愿,要求书面确认承诺的前景会将其暴露出来。在他们确认之前,将他们视为“不”。
按预期价值进行广度优先搜索。
And the right strategy, in fundraising, is to have multiple plans depending on how much you can raise. Ideally you should be able to tell investors something like: we can make it to profitability without raising any more money, but if we raise a few hundred thousand we can hire one or two smart friends, and if we raise a couple million, we can hire a whole engineering team, etc. Different plans match different investors. If you're talking to a VC firm that only does series A rounds (though there are few of those left), it would be a waste of time talking about any but your most expensive plan. Whereas if you're talking to an angel who invests $20k at a time and you haven't raised any money yet, you probably want to focus on your least expensive plan. If you're so fortunate as to have to think about the upper limit on what you should raise, a good rule of thumb is to multiply the number of people you want to hire times $15k times 18 months. In most startups, nearly all the costs are a function of the number of people, and $15k per month is the conventional total cost (including benefits and even office space) per person. $15k per month is high, so don't actually spend that much. But it's ok to use a high estimate when fundraising to add a margin for error. If you have additional expenses, like manufacturing, add in those at the end. Assuming you have none and you think you might hire 20 people, the most you'd want to raise is 20 x $15k x 18 = $5.4 million. [18] Underestimate how much you want. Though you can focus on different plans when talking to different types of investors, you should on the whole err on the side of underestimating the amount you hope to raise. For example, if you'd like to raise $500k, it's better to say initially that you're trying to raise $250k. Then when you reach $150k you're more than half done.
当你与投资者交谈时,你的方法应该是按预期价值进行广度优先搜索。你应该始终并行地与投资者交谈,而不是串行。你没有时间串行地与投资者交谈,此外,如果你一次只与一位投资者交谈,他们没有其他投资者的压力来促使他们行动。但你不应该对每位投资者投入相同的注意力,因为有些投资者比其他投资者更有希望。最优解是与所有潜在投资者并行交谈,但优先考虑更有希望的投资者。[10]
预期价值 = 投资者说“是”的可能性 × 如果他们投资会有多好。因此,例如,一位会投资大量资金但难以说服的知名投资者,可能与一位投资不多但容易说服的不知名天使投资人有相同的预期价值。而一位只会投资少量资金且需要多次会面才能做决定的不知名天使投资人,预期价值非常低。如果有的话,最后再与这样的投资者会面。[11]
按预期价值进行广度优先搜索可以让你摆脱那些从不明确说“不”只是逐渐消失的投资者,因为你也会以同样的速度远离他们。它保护你免受那些不可靠的投资者,就像分布式算法保护你免受处理器故障一样。如果某位投资者没有回复你的邮件,或者希望多次会面但没有进展到给你报价的地步,你会自动减少对他们的关注。但你必须严格遵守概率分配。你不能让你对投资者的渴望影响你对他们对你的渴望的估计。
That sends two useful signals to investors: that you're doing well, and that they have to decide quickly because you're running out of room. Whereas if you'd said you were raising $500k, you'd be less than a third done at $150k. If fundraising stalled there for an appreciable time, you'd start to read as a failure. Saying initially that you're raising $250k doesn't limit you to raising that much. When you reach your initial target and you still have investor interest, you can just decide to raise more. Startups do that all the time. In fact, most startups that are very successful at fundraising end up raising more than they originally intended. I'm not saying you should lie, but that you should lower your expectations initially. There is almost no downside in starting with a low number. It not only won't cap the amount you raise, but will on the whole tend to increase it. A good metaphor here is angle of attack. If you try to fly at too steep an angle of attack, you just stall. If you say right out of the gate that you want to raise a $5 million series A round, unless you're in a very strong position, you not only won't get that but won't get anything. Better to start at a low angle of attack, build up speed, and then gradually increase the angle if you want. Be profitable if you can. You will be in a much stronger position if your collection of plans includes one for raising zero dollars — i.e. if you can make it to profitability without raising any additional money. Ideally you want to be able to say to investors "We'll succeed no matter what, but raising money will help us do it faster." There are many analogies between fundraising and dating, and this is one of the strongest. No one wants you if you seem desperate. And the best way not to seem desperate is not to _be_ desperate. That's one reason we urge startups during YC to keep expenses low and to try to make it to ramen profitability before Demo Day.
知道你的立场。
当投资者习惯性地表现得比你想象的更积极时,你如何判断你与投资者的进展如何?通过观察他们的行动而不是言语。每位投资者都有从第一次谈话到汇款的一条路径,你应该始终知道这条路径包括什么,你在其中的位置,以及你前进的速度。
Though it sounds slightly paradoxical, if you want to raise money, the best thing you can do is get yourself to the point where you don't need to. There are almost two distinct modes of fundraising: one in which founders who need money knock on doors seeking it, knowing that otherwise the company will die or at the very least people will have to be fired, and one in which founders who don't need money take some to grow faster than they could merely on their own revenues. To emphasize the distinction I'm going to name them: type A fundraising is when you don't need money, and type B fundraising is when you do. Inexperienced founders read about famous startups doing what was type A fundraising, and decide they should raise money too, since that seems to be how startups work. Except when they raise money they don't have a clear path to profitability and are thus doing type B fundraising. And they are then surprised how difficult and unpleasant it is. Of course not all startups can make it to ramen profitability in a few months. And some that don't still manage to have the upper hand over investors, if they have some other advantage like extraordinary growth numbers or exceptionally formidable founders. But as time passes it gets increasingly difficult to fundraise from a position of strength without being profitable. [19] Don't optimize for valuation. When you raise money, what should your valuation be? The most important thing to understand about valuation is that it's not that important. Founders who raise money at high valuations tend to be unduly proud of it. Founders are often competitive people, and since valuation is usually the only visible number attached to a startup, they end up competing to raise money at the highest valuation. This is stupid, because fundraising is not the test that matters. The real test is revenue. Fundraising is just a means to that end.
与投资者的会议结束时,一定要问接下来会发生什么。他们需要什么来决定?他们是否需要再次与你见面?讨论什么?多久之后?他们是否需要内部做一些事情,比如与合伙人讨论或调查某个问题?他们预计需要多长时间?不要太咄咄逼人,但要清楚自己的立场。如果投资者含糊其辞或拒绝回答这些问题,假设最坏的情况;对你真正感兴趣的投资者通常会乐于谈论从现在到汇款之间需要发生的事情,因为他们已经在脑海中演练过了。[12]
如果你有谈判经验,你已经知道如何问这些问题。[13] 如果你没有,在这种情况下可以使用一个技巧。投资者知道你在融资方面缺乏经验。缺乏经验并不会让你失去吸引力。如果你是技术初创公司,技术上的新手会让你失去吸引力,但融资上的新手不会。拉里和谢尔盖在融资时也是新手。因此,你可以直接承认你在这方面缺乏经验,询问他们的流程如何运作以及你在其中的位置。[14]
获得第一个承诺。
Being proud of how well you did at fundraising is like being proud of your college grades. Not only is fundraising not the test that matters, valuation is not even the thing to optimize about fundraising. The number one thing you want from phase 2 fundraising is to get the money you need, so you can get back to focusing on the real test, the success of your company. Number two is good investors. Valuation is at best third. The empirical evidence shows just how unimportant it is. Dropbox and Airbnb are the most successful companies we've funded so far, and they raised money after Y Combinator at premoney valuations of $4 million and $2.6 million respectively. Prices are so much higher now that if you can raise money at all you'll probably raise it at higher valuations than Dropbox and Airbnb. So let that satisfy your competitiveness. You're doing better than Dropbox and Airbnb! At a test that doesn't matter. When you start fundraising, your initial valuation (or valuation cap) will be set by the deal you make with the first investor who commits. You can increase the price for later investors, if you get a lot of interest, but by default the valuation you got from the first investor becomes your asking price. So if you're raising money from multiple investors, as most companies do in phase 2, you have to be careful to avoid raising the first from an over-eager investor at a price you won't be able to sustain. You can of course lower your price if you need to (in which case you should give the same terms to investors who invested earlier at a higher price), but you may lose a bunch of leads in the process of realizing you need to do this. What you can do if you have eager first investors is raise money from them on an uncapped convertible note with an MFN clause. This is essentially a way of saying that the valuation cap of the note will be determined by the next investors you raise money from.
大多数投资者对你的看法中最大的因素是其他投资者的看法。一旦你开始获得投资者的承诺,获得更多承诺会变得越来越容易。但硬币的另一面是,通常很难获得第一个承诺。
获得第一个实质性报价可能是融资总难度的一半。实质性报价的定义取决于它来自谁以及金额多少。来自朋友和家人的钱通常不算,无论金额多少。但如果你从知名风投公司或天使投资人那里获得 5 万美元,通常足以启动整个进程。[15]
锁定承诺的资金。
It will be easier to raise money at a lower valuation. It shouldn't be, but it is. Since phase 2 prices vary at most 10x and the big successes generate returns of at least 100x, investors should pick startups entirely based on their estimate of the probability that the company will be a big success and hardly at all on price. But although it's a mistake for investors to care about price, a significant number do. A startup that investors seem to like but won't invest in at a cap of $x will have an easier time at $x/2. [20] Yes/no before valuation. Some investors want to know what your valuation is before they even talk to you about investing. If your valuation has already been set by a prior investment at a specific valuation or cap, you can tell them that number. But if it isn't set because you haven't closed anyone yet, and they try to push you to name a price, resist doing so. If this would be the first investor you've closed, then this could be the tipping point of fundraising. That means closing this investor is the first priority, and you need to get the conversation onto that instead of being dragged sideways into a discussion of price. Fortunately there is a way to avoid naming a price in this situation. And it is not just a negotiating trick; it's how you (both) should be operating. Tell them that valuation is not the most important thing to you and that you haven't thought much about it, that you are looking for investors you want to partner with and who want to partner with you, and that you should talk first about whether they want to invest at all. Then if they decide they do want to invest, you can figure out a price. But first things first. Since valuation isn't that important and getting fundraising rolling is, we usually tell founders to give the first investor who commits as low a price as they need to.
直到资金到账才算交易完成。我经常听到缺乏经验的创始人说“我们已经筹集了 80 万美元”,结果发现目前银行账户里一分钱都没有。还记得折磨投资者的两种恐惧吗?害怕错过让他们过早行动,而害怕踩到“地雷”又让他们退缩。这是一个人们特别容易产生买家悔恨的市场。而且这个市场还为他们提供了大量满足这种悔恨的借口。公开市场像鞭子一样抽打着初创公司的投资。如果中国经济明天崩溃,所有赌注都将失效。但对个别初创公司来说,也有很多意外,而且这些意外往往集中在融资期间。明天可能会出现一个强大的竞争对手,或者你可能会收到禁止令,或者你的联合创始人可能会退出。[16]
即使是一天的延迟也可能带来让投资者改变主意的消息。因此,当有人承诺时,尽快拿到钱。知道你的立场并不在他们说会投资时就结束了。在他们说“是”之后,了解资金到账的时间表,然后监督这个过程直到完成。机构投资者有专人负责汇款,但你可能需要亲自找到天使投资人拿到支票。
This is a safe technique so long as you combine it with the next one. [21] Beware "valuation sensitive" investors. Occasionally you'll encounter investors who describe themselves as "valuation sensitive." What this means in practice is that they are compulsive negotiators who will suck up a lot of your time trying to push your price down. You should therefore never approach such investors first. While you shouldn't chase high valuations, you also don't want your valuation to be set artificially low because the first investor who committed happened to be a compulsive negotiator. Some such investors have value, but the time to approach them is near the end of fundraising, when you're in a position to say "this is the price everyone else has paid; take it or leave it" and not mind if they leave it. This way, you'll not only get market price, but it will also take less time. Ideally you know which investors have a reputation for being "valuation sensitive" and can postpone dealing with them till last, but occasionally one you didn't know about will pop up early on. The rule of doing breadth first search weighted by expected value already tells you what to do in this case: slow down your interactions with them. There are a handful of investors who will try to invest at a lower valuation even when your price has already been set. Lowering your price is a backup plan you resort to when you discover you've let the price get set too high to close all the money you need. So you'd only want to talk to this sort of investor if you were about to do that anyway. But since investor meetings have to be arranged at least a few days in advance and you can't predict when you'll need to resort to lowering your price, this means in practice that you should approach this type of investor last if at all. If you're surprised by a lowball offer, treat it as a backup offer and delay responding to it.
缺乏经验的投资者最容易产生买家悔恨。成熟的投资者已经学会将说“是”视为从跳板上跳下,而且他们也有更多的品牌需要维护。但我听说过甚至顶级风投公司也会毁约的情况。
避开不“领投”的投资者。
由于获得第一个报价是融资的主要难点,这应该在你开始时计算预期价值时考虑进去。你不仅要估计投资者说“是”的概率,还要估计他们成为第一个说“是”的人的概率,而后者并不简单地是前者的一个固定比例。有些投资者以快速决策著称,这些投资者在早期特别有价值。
When someone makes an offer in good faith, you have a moral obligation to respond in a reasonable time. But lowballing you is a dick move that should be met with the corresponding countermove. Accept offers greedily. I'm a little leery of using the term "greedily" when writing about fundraising lest non-programmers misunderstand me, but a greedy algorithm is simply one that doesn't try to look into the future. A greedy algorithm takes the best of the options in front of it right now. And that is how startups should approach fundraising in phases 2 and later. Don't try to look into the future because (a) the future is unpredictable, and indeed in this business you're often being deliberately misled about it and (b) your first priority in fundraising should be to get it finished and get back to work anyway. If someone makes you an acceptable offer, take it. If you have multiple incompatible offers, take the best. Don't reject an acceptable offer in the hope of getting a better one in the future. These simple rules cover a wide variety of cases. If you're raising money from many investors, roll them up as they say yes. As you start to feel you've raised enough, the threshold for acceptable will start to get higher. In practice offers exist for stretches of time, not points. So when you get an acceptable offer that would be incompatible with others (e.g. an offer to invest most of the money you need), you can tell the other investors you're talking to that you have an offer good enough to accept, and give them a few days to make their own. This could lose you some that might have made an offer if they had more time. But by definition you don't care; the initial offer was acceptable. Some investors will try to prevent others from having time to decide by giving you an "exploding" offer, meaning one that's only valid for a few days.
相反,一位只有在其他投资者投资后才会投资的投资者最初毫无价值。尽管大多数投资者会受到其他投资者对你的兴趣的影响,但有些投资者明确表示只会在其他投资者投资后投资。你可以通过他们经常谈论“领投”来识别这种可鄙的投资者亚种。他们说他们不领投,或者他们会在你有了领投后投资。有时他们甚至声称自己愿意领投,意思是他们不会投资,除非你从其他投资者那里筹集到 x 美元。(如果他们所说的“领投”意味着他们会单方面投资,并且会帮助你筹集更多资金,那很好。糟糕的是当他们用这个词来表示除非你能在其他地方筹集更多资金,否则他们不会投资。)[17]
“领投”这个词从何而来?直到几年前,处于第二阶段的初创公司在融资时通常会进行股权融资,几位投资者同时使用相同的文件进行投资。你会与一位“领投”投资者谈判条款,然后其他所有人签署相同的文件,所有资金在交割时到位。
A 轮融资仍然这样运作,但现在大多数 A 轮之前的融资方式已经不同。现在在 A 轮之前很少有实际的轮次或领投。现在初创公司只是逐个从投资者那里筹集资金,直到他们认为足够了。
Offers from the very best investors explode less frequently and less rapidly — Fred Wilson never gives exploding offers, for example — because they're confident you'll pick them. But lower-tier investors sometimes give offers with very short fuses, because they believe no one who had other options would choose them. A deadline of three working days is acceptable. You shouldn't need more than that if you've been talking to investors in parallel. But a deadline any shorter is a sign you're dealing with a sketchy investor. You can usually call their bluff, and you may need to. [22] It might seem that instead of accepting offers greedily, your goal should be to get the best investors as partners. That is certainly a good goal, but in phase 2 "get the best investors" only rarely conflicts with "accept offers greedily," because the best investors don't usually take any longer to decide than the others. The only case where the two strategies give conflicting advice is when you have to forgo an offer from an acceptable investor to see if you'll get an offer from a better one. If you talk to investors in parallel and push back on exploding offers with excessively short deadlines, that will almost never happen. But if it does, "get the best investors" is in the average case bad advice. The best investors are also the most selective, because they get their pick of all the startups. They reject nearly everyone they talk to, which means in the average case it's a bad trade to exchange a definite offer from an acceptable investor for a potential offer from a better one. (The situation is different in phase 1. You can't apply to all the incubators in parallel, because some offset their schedules to prevent this.
既然不再有领投,为什么投资者还使用这个词?因为这是更合法的方式来表达他们的真实意思。他们真正的意思只是他们对你的兴趣是其他投资者对你的兴趣的函数。即所有平庸投资者的光谱特征。但当用“领投”来表达时,听起来他们的行为有某种结构性,因此是合法的。
当一位投资者告诉你“我想投资你,但我不领投”时,在你的脑海中将其翻译为“不,除非你成为热门交易”。由于这是任何投资者对任何初创公司的默认看法,他们实际上什么也没告诉你。
In phase 1, "accept offers greedily" and "get the best investors" do conflict, so if you want to apply to multiple incubators, you should do it in such a way that the ones you want most decide first.) Sometimes when you're raising money from multiple investors, a series A will emerge out of those conversations, and these rules even cover what to do in that case. When an investor starts to talk to you about a series A, keep taking smaller investments till they actually give you a termsheet. There's no practical difficulty. If the smaller investments are on convertible notes, they'll just convert into the series A round. The series A investor won't like having all these other random investors as bedfellows, but if it bothers them so much they should get on with giving you a termsheet. Till they do, you don't know for sure they will, and the greedy algorithm tells you what to do. [23] Don't sell more than 25% in phase 2. If you do well, you will probably raise a series A round eventually. I say probably because things are changing with series A rounds. Startups may start to skip them. But only one company we've funded has so far, so tentatively assume the path to huge passes through an A round. [24] Which means you should avoid doing things in earlier rounds that will mess up raising an A round. For example, if you've sold more than about 40% of your company total, it starts to get harder to raise an A round, because VCs worry there will not be enough stock left to keep the founders motivated. Our rule of thumb is not to sell more than 25% in phase 2, on top of whatever you sold in phase 1, which should be less than 15%. If you're raising money on uncapped notes, you'll have to guess what the eventual equity round valuation might be.
当你刚开始融资时,不愿“领投”的投资者的预期价值为零,因此如果有的话,最后再与这样的投资者交谈。
制定多个计划。
许多投资者会问你计划筹集多少资金。这个问题让创始人觉得他们应该计划筹集一个具体的金额。但实际上你不应该。在像融资这样不可预测的事情中制定固定计划是错误的。
Guess conservatively. (Since the goal of this rule is to avoid messing up the series A, there's obviously an exception if you end up raising a series A in phase 2, as a handful of startups do.) Have one person handle fundraising. If you have multiple founders, pick one to handle fundraising so the other(s) can keep working on the company. And since the danger of fundraising is not the time taken up by the actual meetings but that it becomes the top idea in your mind, the founder who handles fundraising should make a conscious effort to insulate the other founder(s) from the details of the process. [25] (If the founders mistrust one another, this could cause some friction. But if the founders mistrust one another, you have worse problems to worry about than how to organize fundraising.) The founder who handles fundraising should be the CEO, who should in turn be the most formidable of the founders. Even if the CEO is a programmer and another founder is a salesperson? Yes. If you happen to be that type of founding team, you're effectively a single founder when it comes to fundraising. It's ok to bring all the founders to meet an investor who will invest a lot, and who needs this meeting as the final step before deciding. But wait till that point. Introducing an investor to your cofounder(s) should be like introducing a girl/boyfriend to your parents — something you do only when things reach a certain stage of seriousness. Even if there are still one or more founders focusing on the company during fundraising, growth will slow. But try to get as much growth as you can, because fundraising is a segment of time, not a point, and what happens to the company during that time affects the outcome.
那么为什么投资者会问你计划筹集多少资金?与商店销售人员问你“你计划花多少钱?”的原因大致相同,如果你走进商店为朋友挑选礼物。你可能并没有一个确切的金额;你只是想找到好东西,如果价格便宜,那就更好了。销售人员问你这个问题并不是因为你本应计划花一个具体的金额,而是为了只向你展示你愿意支付的最高价格的东西。
同样,当投资者问你计划筹集多少资金时,并不是因为你本应有计划。这是为了看看你是否适合他们喜欢的投资规模,同时也是为了判断你的雄心、合理性以及融资的进展程度。
如果你是融资高手,你可以说“我们计划筹集 700 万美元的 A 轮融资,我们将在下周二接受条款书。”我认识少数几位创始人可以在不让风投当面嘲笑的情况下做到这一点。但如果你属于缺乏经验但认真的多数人,解决方案类似于我推荐的推销初创公司的方法:做正确的事,然后告诉投资者你在做什么。
If your numbers grow significantly between two investor meetings, investors will be hot to close, and if your numbers are flat or down they'll start to get cold feet. You'll need an executive summary and (maybe) a deck. Traditionally phase 2 fundraising consists of presenting a slide deck in person to investors. Sequoia describes what such a deck should contain, and since they're the customer you can take their word for it. I say "traditionally" because I'm ambivalent about decks, and (though perhaps this is wishful thinking) they seem to be on the way out. A lot of the most successful startups we fund never make decks in phase 2. They just talk to investors and explain what they plan to do. Fundraising usually takes off fast for the startups that are most successful at it, and they're thus able to excuse themselves by saying that they haven't had time to make a deck. You'll also want an executive summary, which should be no more than a page long and describe in the most matter of fact language what you plan to do, why it's a good idea, and what progress you've made so far. The point of the summary is to remind the investor (who may have met many startups that day) what you talked about. Assume that if you give someone a copy of your deck or executive summary, it will be passed on to whoever you'd least like to have it. But don't refuse on that account to give copies to investors you meet. You just have to treat such leaks as a cost of doing business. In practice it's not that high a cost. Though founders are rightly indignant when their plans get leaked to competitors, I can't think of a startup whose outcome has been affected by it. Sometimes an investor will ask you to send them your deck and/or executive summary before they decide whether to meet with you. I wouldn't do that.
在融资中,正确的策略是根据你能筹集到的金额制定多个计划。理想情况下,你应该能够告诉投资者类似这样的话:我们可以在不筹集更多资金的情况下实现盈利,但如果我们筹集几十万美元,我们可以雇佣一两个聪明的朋友,如果我们筹集几百万美元,我们可以雇佣整个工程团队,等等。
不同的计划适合不同的投资者。如果你正在与一家只做 A 轮融资的风投公司交谈(尽管这样的公司已经不多了),谈论你最昂贵的计划以外的任何事情都是浪费时间。而如果你正在与一位每次投资 2 万美元且你尚未筹集任何资金的天使投资人交谈,你可能希望专注于你最便宜的计划。
It's a sign they're not really interested. Stop fundraising when it stops working. When do you stop fundraising? Ideally when you've raised enough. But what if you haven't raised as much as you'd like? When do you give up? It's hard to give general advice about this, because there have been cases of startups that kept trying to raise money even when it seemed hopeless, and miraculously succeeded. But what I usually tell founders is to stop fundraising when you start to get a lot of air in the straw. When you're drinking through a straw, you can tell when you get to the end of the liquid because you start to get a lot of air in the straw. When your fundraising options run out, they usually run out in the same way. Don't keep sucking on the straw if you're just getting air. It's not going to get better. Don't get addicted to fundraising. Fundraising is a chore for most founders, but some find it more interesting than working on their startup. The work at an early stage startup often consists of unglamorous schleps. Whereas fundraising, when it's going well, can be quite the opposite. Instead of sitting in your grubby apartment listening to users complain about bugs in your software, you're being offered millions of dollars by famous investors over lunch at a nice restaurant. [26] The danger of fundraising is particularly acute for people who are good at it. It's always fun to work on something you're good at. If you're one of these people, beware. Fundraising is not what will make your company successful. Listening to users complain about bugs in your software is what will make you successful. And the big danger of getting addicted to fundraising is not merely that you'll spend too long on it or raise too much money. It's that you'll start to think of yourself as being already successful, and lose your taste for the schleps you need to undertake to actually be successful. Startups can be destroyed by this.
如果你幸运到需要考虑你应该筹集的上限,一个好的经验法则是将你想雇佣的人数乘以 1.5 万美元再乘以 18 个月。在大多数初创公司中,几乎所有成本都是人数的函数,而每人每月 1.5 万美元是传统的总成本(包括福利甚至办公空间)。每人每月 1.5 万美元很高,所以实际上不要花那么多。但在融资时使用高估的数字以增加误差范围是可以的。如果你有其他费用,比如制造,最后再加上这些。假设你没有其他费用,并且你认为可能会雇佣 20 人,你最多想筹集 20 × 1.5 万美元 × 18 = 540 万美元。[18]
低估你想要的金额。
尽管在与不同类型的投资者交谈时可以专注于不同的计划,但总体上你应该低估你希望筹集的金额。
When I see a startup with young founders that is fabulously successful at fundraising, I mentally decrease my estimate of the probability that they'll succeed. The press may be writing about them as if they'd been anointed as the next Google, but I'm thinking "this is going to end badly." Don't raise too much. Though only a handful of startups have to worry about this, it is possible to raise too much. The dangers of raising too much are subtle but insidious. One is that it will set impossibly high expectations. If you raise an excessive amount of money, it will be at a high valuation, and the danger of raising money at too high a valuation is that you won't be able to increase it sufficiently the next time you raise money. A company's valuation is expected to rise each time it raises money. If not it's a sign of a company in trouble, which makes you unattractive to investors. So if you raise money in phase 2 at a post-money valuation of $30 million, the pre-money valuation of your next round, if you want to raise one, is going to have to be at least $50 million. And you have to be doing really, really well to raise money at $50 million. It's very dangerous to let the competitiveness of your current round set the performance threshold you have to meet to raise your next one, because the two are only loosely coupled. But the money itself may be more dangerous than the valuation. The more you raise, the more you spend, and spending a lot of money can be disastrous for an early stage startup. Spending a lot makes it harder to become profitable, and perhaps even worse, it makes you more rigid, because the main way to spend money is people, and the more people you have, the harder it is to change directions.
例如,如果你想筹集 50 万美元,最好一开始说你试图筹集 25 万美元。然后当你达到 15 万美元时,你已经完成了一半以上。这会向投资者发出两个有用的信号:你做得很好,而且他们必须快速决定,因为你快没有空间了。而如果你说你在筹集 50 万美元,在 15 万美元时你完成了不到三分之一。如果融资在那里停滞了相当长的时间,你会开始被视为失败者。
一开始说你正在筹集 25 万美元并不会限制你只能筹集这么多。当你达到最初的目标并且仍然有投资者兴趣时,你可以决定筹集更多。初创公司经常这样做。事实上,大多数在融资方面非常成功的初创公司最终筹集的资金比最初计划的要多。
我不是说你应该撒谎,而是说你一开始应该降低期望。从一个低数字开始几乎没有坏处。它不仅不会限制你筹集的金额,而且总体上往往会增加它。
So if you do raise a huge amount of money, don't spend it. (You will find that advice almost impossible to follow, so hot will be the money burning a hole in your pocket, but I feel obliged at least to try.) Be nice. Startups raising money occasionally alienate investors by seeming arrogant. Sometimes because they are arrogant, and sometimes because they're noobs clumsily attempting to mimic the toughness they've observed in experienced founders. It's a mistake to behave arrogantly to investors. While there are certain situations in which certain investors like certain kinds of arrogance, investors vary greatly in this respect, and a flick of the whip that will bring one to heel will make another roar with indignation. The only safe strategy is never to seem arrogant at all. That will require some diplomacy if you follow the advice I've given here, because the advice I've given is essentially how to play hardball back. When you refuse to meet an investor because you're not in fundraising mode, or slow down your interactions with an investor who moves too slow, or treat a contingent offer as the no it actually is and then, by accepting offers greedily, end up leaving that investor out, you're going to be doing things investors don't like. So you must cushion the blow with soft words. At YC we tell startups they can blame us. And now that I've written this, everyone else can blame me if they want. That plus the inexperience card should work in most situations: sorry, we think you're great, but PG said startups shouldn't ___, and since we're new to fundraising, we feel like we have to play it safe. The danger of behaving arrogantly is greatest when you're doing well. When everyone wants you, it's hard not to let it go to your head. Especially if till recently no one wanted you. But restrain yourself. The startup world is a small place, and startups have lots of ups and downs.
这里有一个很好的比喻是迎角。如果你试图以过大的迎角飞行,你只会失速。如果你一开始就说你想筹集 500
我认为总体来说我们在融资方面做得还不错,但我在同一件事上搞砸了两次——试图同时专注于公司建设和融资。
This is a domain where it's more true than usual that pride goeth before a fall. [27] Be nice when investors reject you as well. The best investors are not wedded to their initial opinion of you. If they reject you in phase 2 and you end up doing well, they'll often invest in phase 3\. In fact investors who reject you are some of your warmest leads for future fundraising. Any investor who spent significant time deciding probably came close to saying yes. Often you have some internal champion who only needs a little more evidence to convince the skeptics. So it's wise not merely to be nice to investors who reject you, but (unless they behaved badly) to treat it as the beginning of a relationship. The bar will be higher next time. Assume the money you raise in phase 2 will be the last you ever raise. You must make it to profitability on this money if you can. Over the past several years, the investment community has evolved from a strategy of anointing a small number of winners early and then supporting them for years to a strategy of spraying money at early stage startups and then ruthlessly culling them at the next stage. This is probably the optimal strategy for investors. It's too hard to pick winners early on. Better to let the market do it for you. But it often comes as a surprise to startups how much harder it is to raise money in phase 3. When your company is only a couple months old, all it has to be is a promising experiment that's worth funding to see how it turns out. The next time you raise money, the experiment has to have worked. You have to be on a trajectory that leads to going public. And while there are some ideas where the proof that the experiment worked might consist of e.g. query response times, usually the proof is profitability. Usually phase 3 fundraising has to be type A fundraising. In practice there are two ways startups hose themselves between phases 2 and 3. Some are just too slow to become profitable.
[3] 这里有一个需要警惕的微妙危险(我稍后会警告):当心从热切的投资者那里获得过高的估值,以免在后续融资时设定一个难以企及的高目标。
[4] 如果他们真的需要开会,那么不管他们说什么,其实都还没准备好投资。他们仍在做决定,这意味着你是被叫去说服他们的——这本质上就是融资行为。
[5] 风投机构的投资经理经常会冷不防地给初创公司发邮件。天真的创始人会想:"哇,有风投对我们感兴趣了!"但投资经理不等于风投合伙人。他们没有决策权。虽然他们可能会把自己看好的初创公司引荐给机构合伙人,但合伙人会对这种途径来的项目抱有偏见。据我所知,没有哪笔风投交易是从投资经理的陌生邮件开始的。如果你想接触某家特定机构,应该通过他们尊重的人引荐给合伙人。
They raise enough money to last for two years. There doesn't seem any particular urgency to be profitable. So they don't make any effort to make money for a year. But by that time, not making money has become habitual. When they finally decide to try, they find they can't. The other way companies hose themselves is by letting their expenses grow too fast. Which almost always means hiring too many people. You usually shouldn't go out and hire 8 people as soon as you raise money at phase 2. Usually you want to wait till you have growth (and thus usually revenues) to justify them. A lot of VCs will encourage you to hire aggressively. VCs generally tell you to spend too much, partly because as money people they err on the side of solving problems by spending money, and partly because they want you to sell them more of your company in subsequent rounds. Don't listen to them. Don't make things complicated. I realize it may seem odd to sum up this huge treatise by saying that my overall advice is not to make fundraising too complicated, but if you go back and look at this list you'll see it's basically a simple recipe with a lot of implications and edge cases. Avoid investors till you decide to raise money, and then when you do, talk to them all in parallel, prioritized by expected value, and accept offers greedily. That's fundraising in one sentence. Don't introduce complicated optimizations, and don't let investors introduce complications either. Fundraising is not what will make you successful. It's just a means to an end. Your primary goal should be to get it over with and get back to what will make you successful — making things and talking to users — and the path I've described will for most startups be the surest way to that destination. Be good, take care of yourselves, and _don't leave the path_. Notes [1] The worst explosions happen when unpromising-seeming startups encounter mediocre investors.
如果有人引荐你去风投机构,或他们在演示日注意到你,然后先派投资经理来评估你,这种情况可以接触。虽然算不上有希望的线索(应该降低优先级),但总比陌生邮件有价值。
由于"投资经理"这个头衔名声不佳,一些风投机构开始给投资经理冠以"合伙人"头衔,这会造成很大混淆。如果你是YC系初创公司可以问我们实情;否则你可能需要上网查证。真正的合伙人可能有特殊头衔。如果在媒体或机构官博代表公司发声的人,大概率是真正合伙人。如果担任董事会成员的,也应该是真正合伙人。
"投资经理"和"合伙人"之间还有"投资总监""风险合伙人"等头衔,这些称谓的含义差异太大,难以一概而论。
Good investors don't lead startups on; their reputations are too valuable. And startups that seem promising can usually get enough money from good investors that they don't have to talk to mediocre ones. It is the unpromising-seeming startups that have to resort to raising money from mediocre investors. And it's particularly damaging when these investors flake, because unpromising-seeming startups are usually more desperate for money. (Not all unpromising-seeming startups do badly. Some are merely ugly ducklings in the sense that they violate current startup fashions.) [2] One YC founder told me:.
[6] 同理,避免与潜在收购方进行非正式交谈。它们带来的干扰比融资更危险。除非你此刻就想出售公司,否则连会议都不要接受。
[7] Joshua Reeves特别建议:让每位投资人为你引荐另外两位投资人。
> I think in general we've done ok at fundraising, but I managed to screw up twice at the exact same thing — trying to focus on building the company and fundraising at the same time.
不要向拒绝你的投资人索要引荐——这在多数情况下会变成负面推荐。
[8] 这并不总是听起来那么刻意。创始人投资者之间的许多延误和脱节,其实源于风投行业的习俗——这些习俗之所以演变成现在这样,是因为符合投资人的利益。
[9] 一位读过本文初稿的YC创始人写道:
[3] There is one subtle danger you have to watch out for here, which I warn about later: beware of getting too high a valuation from an eager investor, lest that set an impossibly high target when raising additional money. [4] If they really need a meeting, then they're not ready to invest, regardless of what they say. They're still deciding, which means you're being asked to come in and convince them. Which is fundraising. [5] Associates at VC firms regularly cold email startups. Naive founders think "Wow, a VC is interested in us!" But an associate is not a VC. They have no decision-making power. And while they may introduce startups they like to partners at their firm, the partners discriminate against deals that come to them this way. I don't know of a single VC investment that began with an associate cold-emailing a startup. If you want to approach a specific firm, get an intro to a partner from someone they respect. It's ok to talk to an associate if you get an intro to a VC firm or they see you at a Demo Day and they begin by having an associate vet you. That's not a promising lead and should therefore get low priority, but it's not as completely worthless as a cold email. Because the title "associate" has gotten a bad reputation, a few VC firms have started to give their associates the title "partner," which can make things very confusing. If you're a YC startup you can ask us who's who; otherwise you may have to do some research online. There may be a special title for actual partners. If someone speaks for the firm in the press or a blog on the firm's site, they're probably a real partner. If they're on boards of directors they're probably a real partner. There are titles between "associate" and "partner," including "principal" and "venture partner." The meanings of these titles vary too much to generalize. [6] For similar reasons, avoid casual conversations with potential acquirers.
这是最重要的一节。我认为有必要说得更直白些。"投资者会刻意表现出比实际更高的兴趣,以保留选择权。即使投资者对你显得非常感兴趣,他们很可能最终也不会投资。解决方法是做最坏假设——认定投资者只是假装感兴趣——直到你获得明确承诺。"
[10] 尽管你应当尽可能密集安排投资人会面,但Jeff Byun指出一个例外:若会议排得太满,你将失去打磨演讲内容的时间。
有些创始人会故意先约见几位平庸的投资人,借此修正路演中的漏洞。
They can lead to distractions even more dangerous than fundraising. Don't even take a meeting with a potential acquirer unless you want to sell your company right now. [7] Joshua Reeves specifically suggests asking each investor to intro you to two more investors. Don't ask investors who say no for introductions to other investors. That will in many cases be an anti-recommendation. [8] This is not always as deliberate as its sounds. A lot of the delays and disconnects between founders and investors are induced by the customs of the venture business, which have evolved the way they have because they suit investors' interests. [9] One YC founder who read a draft of this essay wrote:.
[11] 这个领域并不存在有效市场。某些最无用的投资人反而最难应付。
[12] 顺带一提,这段内容堪称销售基本功。若想见识实战案例,不妨去和汽车经销商聊聊。
> This is the most important section. I think it might bear stating even more clearly. "Investors will deliberately affect more interest than they have to preserve optionality. If an investor seems very interested in you, they still probably won't invest. The solution for this is to assume the worst — that an investor is just feigning interest — until you get a definite commitment."
[13] 我认识一位极其老练的创始人,他总用"那么,算你一份?"结束会议,语气随意得像在说"能把盐递过来吗?"。除非你同样老练(若不确定...),千万别模仿。对投资人而言,最尴尬的莫过于目睹书呆子创始人硬学销售话术。
投资人本来就不介意资助书呆子。所以做你自己就好,拙劣模仿销售精英反而弄巧成拙。
[14] Ian Hogarth提出判断投资人诚意的妙招:观察初次会面后他们为你投入的资源。真正感兴趣的投资人早在敲定前就会开始帮你。
[10] Though you should probably pack investor meetings as closely as you can, Jeff Byun mentions one reason not to: if you pack investor meetings too closely, you'll have less time for your pitch to evolve. Some founders deliberately schedule a handful of lame investors first, to get the bugs out of their pitch. [11] There is not an efficient market in this respect. Some of the most useless investors are also the highest maintenance. [12] Incidentally, this paragraph is sales 101. If you want to see it in action, go talk to a car dealer. [13] I know one very smooth founder who used to end investor meetings with "So, can I count you in?" delivered as if it were "Can you pass the salt?" Unless you're very smooth (if you're not sure...), do not do this yourself. There is nothing more unconvincing, for an investor, than a nerdy founder trying to deliver the lines meant for a smooth one. Investors are fine with funding nerds. So if you're a nerd, just try to be a good nerd, rather than doing a bad imitation of a smooth salesman. [14] Ian Hogarth suggests a good way to tell how serious potential investors are: the resources they expend on you after the first meeting. An investor who's seriously interested will already be working to help you even before they've committed. [15] In principle you might have to think about so-called "signalling risk." If a prestigious VC makes a small seed investment in you, what if they don't want to invest the next time you raise money? Other investors might assume that the VC knows you well, since they're an existing investor, and if they don't want to invest in your next round, that must mean you suck. The reason I say "in principle" is that in practice signalling hasn't been much of a problem so far. It rarely arises, and in the few cases where it does, the startup in question usually is doing badly and is doomed anyway.
[15] 理论上你需要考虑所谓的"信号风险"——若知名风投仅进行小额种子投资,后续轮次拒绝跟进时,其他投资人可能将其视为负面信号。我说"理论上"是因为实践中这很少构成实质问题,通常出现这种情况的初创企业本身就已岌岌可危。
若你确有选择余地,规避风投机构最为稳妥。但并非必要。
[16] 竞争对手常在融资启动时故意发出诉讼威胁,因为他们知道你不得不向潜在投资人披露。遇到这种情况时,往往你比投资人更恐慌。经验丰富的投资人深谙此道,明白真正诉诸法律的案例极少。坦诚相告即可,遮遮掩掩反而更令人生疑。
If you have the luxury of choosing among seed investors, you can play it safe by excluding VC firms. But it isn't critical to. [16] Sometimes a competitor will deliberately threaten you with a lawsuit just as you start fundraising, because they know you'll have to disclose the threat to potential investors and they hope this will make it harder for you to raise money. If this happens it will probably frighten you more than investors. Experienced investors know about this trick, and know the actual lawsuits rarely happen. So if you're attacked in this way, be forthright with investors. They'll be more alarmed if you seem evasive than if you tell them everything. [17] A related trick is to claim that they'll only invest contingently on other investors doing so because otherwise you'd be "undercapitalized." This is almost always bullshit. They can't estimate your minimum capital needs that precisely. [18] You won't hire all those 20 people at once, and you'll probably have some revenues before 18 months are out. But those too are acceptable or at least accepted additions to the margin for error. [19] Type A fundraising is so much better that it might even be worth doing something different if it gets you there sooner. One YC founder told me that if he were a first-time founder again he'd "leave ideas that are up-front capital intensive to founders with established reputations." [20] I don't know whether this happens because they're innumerate, or because they believe they have zero ability to predict startup outcomes (in which case this behavior at least wouldn't be irrational). In either case the implications are similar. [21] If you're a YC startup and you have an investor who for some reason insists that you decide the price, any YC partner can estimate a market price for you. [22] You should respond in kind when investors behave upstandingly too.
[17] 另一种套路是声称"必须等其他投资人跟进才投,否则你会资金不足"。这基本是扯淡——没人能精确测算你的最低资金需求。
[18] 你不可能一次性招满20人,18个月内很可能已有收入。这些都属于可接受的误差缓冲。
When an investor makes you a clean offer with no deadline, you have a moral obligation to respond promptly. [23] Tell the investors talking to you about an A round about the smaller investments you raise as you raise them. You owe them such updates on your cap table, and this is also a good way to pressure them to act. They won't like you raising other money and may pressure you to stop, but they can't legitimately ask you to commit to them till they also commit to you. If they want you to stop raising money, the way to do it is to give you a series A termsheet with a no-shop clause. You can relent a little if the potential series A investor has a great reputation and they're clearly working fast to get you a termsheet, particularly if a third party like YC is involved to ensure there are no misunderstandings. But be careful. [24] The company is Weebly, which made it to profitability on a seed investment of $650k. They did try to raise a series A in the fall of 2008 but (no doubt partly because it was the fall of 2008) the terms they were offered were so bad that they decided to skip raising an A round. [25] Another advantage of having one founder take fundraising meetings is that you never have to negotiate in real time, which is something inexperienced founders should avoid. One YC founder told me:.
[19] A类融资优势如此明显,甚至值得调整策略提前达标。某YC创始人坦言:"若重来一次,我会把需要重资本投入的项目留给有声望的连续创业者。"
[20] 不知这是因为他们缺乏数字概念,还是自认完全无法预测初创企业成败(若是后者,至少不算非理性)。无论哪种情况,结果都殊途同归。
[21] 若你是YC系初创企业,遇到坚持让你定价的投资人,任何YC合伙人都能帮你估算市价。
> Investors are professional negotiators and can negotiate on the spot very easily. If only one founder is in the room, you can say "I need to circle back with my co-founder" before making any commitments. I used to do this all the time.
[22] 当投资人展现专业操守时,你应投桃报李。面对无截止日的干净报价,及时回应是基本道义。
[23] 向洽谈A轮的投资人同步小额融资进展。这既是维护股东名册透明的义务,也能施加决策压力。他们可能阻挠你继续融资,但无权要求你单方面承诺——除非拿出含禁止招揽条款的A轮条款书。
若对方信誉卓著且推进迅速(尤其有YC等第三方担保时),可稍作让步。但仍需谨慎。
[26] You'll be lucky if fundraising feels pleasant enough to become addictive. More often you have to worry about the other extreme — becoming demoralized when investors reject you. As one (very successful) YC founder wrote after reading a draft of this:
[24] 案例是Weebly,他们用65万美元种子投资实现盈利。2008年秋尝试A轮融资时(无疑部分受金融危机影响),因条款过于苛刻而选择放弃。
[25] 由单一位创始人负责融资还有个优势:避免实时谈判。某YC创始人告诫:"缺乏经验的创始人永远不要当场谈判。"
> It's hard to mentally deal with the sheer scale of rejection in fundraising and if you are not in the right mindset you will fail. Users may love you but these supposedly smart investors may not understand you at all. At this point for me, rejection still rankles but I've come to accept that investors are just not super thoughtful for the most part and you need to play the game according to certain somewhat depressing rules (many of which you are listing) in order to win.
投资者是专业的谈判者,能轻松进行现场协商。如果会议室里只有一位创始人,你可以在做出任何承诺前说"我需要与联合创始人商量"。我以前经常这么做。
[26] 若融资过程愉快到让你上瘾,那算是走运。更多时候你得提防另一种极端——因投资者拒绝而士气低落。正如一位(极其成功的)YC创始人在阅读本文草稿后写道:
> 融资过程中面对海量拒绝时,心理上很难承受,若心态不正就会失败。用户可能热爱你,但这些所谓精明的投资者可能完全不懂你。就我而言,被拒仍会刺痛,但我已接受现实:多数投资者并不具备超强洞察力,你必须按照某些略显压抑的规则(你列出的许多条)来玩这场游戏才能获胜。
[27] The actual sentence in the King James Bible is "Pride goeth before destruction, and an haughty spirit before a fall." Thanks to Slava Akhmechet, Sam Altman, Nate Blecharczyk, Adora Cheung, Bill Clerico, John Collison, Patrick Collison, Parker Conrad, Ron Conway, Travis Deyle, Jason Freedman, Joe Gebbia, Mattan Griffel, Kevin Hale, Jacob Heller, Ian Hogarth, Justin Kan, Professor Moriarty, Nikhil Nirmel, David Petersen, Geoff Ralston, Joshua Reeves, Yuri Sagalov, Emmett Shear, Rajat Suri, Garry Tan, and Nick Tomarello for reading drafts of this.
[27] 钦定版《圣经》原句为:"骄傲在败坏以先,狂心在跌倒之前。"
致谢 Slava Akhmechet、Sam Altman、Nate Blecharczyk、Adora Cheung、Bill Clerico、John Collison、Patrick Collison、Parker Conrad、Ron Conway、Travis Deyle、Jason Freedman、Joe Gebbia、Mattan Griffel、Kevin Hale、Jacob Heller、Ian Hogarth、Justin Kan、Moriarty教授、Nikhil Nirmel、David Petersen、Geoff Ralston、Joshua Reeves、Yuri Sagalov、Emmett Shear、Rajat Suri、Garry Tan和Nick Tomarello对本文草稿的审阅。
Want to start a startup? Get funded by Y Combinator.
August 2013 The biggest component in most investors' opinion of you is the opinion of other investors. Which is of course a recipe for exponential growth. When one investor wants to invest in you, that makes other investors want to, which makes others want to, and so on. Sometimes inexperienced founders mistakenly conclude that manipulating these forces is the essence of fundraising. They hear stories about stampedes to invest in successful startups, and think it's therefore the mark of a successful startup to have this happen. But actually the two are not that highly correlated. Lots of startups that cause stampedes end up flaming out (in extreme cases, partly as a result of the stampede), and lots of very successful startups were only moderately popular with investors the first time they raised money. So the point of this essay is not to explain how to create a stampede, but merely to explain the forces that generate them. These forces are always at work to some degree in fundraising, and they can cause surprising situations. If you understand them, you can at least avoid being surprised. One reason investors like you more when other investors like you is that you actually become a better investment. Raising money decreases the risk of failure. Indeed, although investors hate it, you are for this reason justified in raising your valuation for later investors. The investors who invested when you had no money were taking more risk, and are entitled to higher returns. Plus a company that has raised money is literally more valuable.
想创立初创公司? 获得Y Combinator的资金支持。
大多数投资人对你的看法中,最大的影响因素是其他投资人的看法。这自然会导致指数级增长。当一个投资人想投资你时,会促使其他投资人也想投资,进而吸引更多人加入,如此循环。
有时,缺乏经验的创始人会误以为操纵这种效应是融资的核心。他们听说成功初创公司引发投资狂潮的故事,便认为这是成功初创公司的标志。但实际上,两者并无高度关联。许多引发狂潮的初创公司最终惨败(极端情况下,部分原因正是这场狂潮),而许多非常成功的初创公司在首次融资时仅获得投资人适度青睐。
因此,本文的目的并非解释如何制造狂潮,而是剖析催生狂潮的动因。这些力量在融资中始终存在,可能引发意外局面。理解它们至少能让你避免措手不及。
After you raise the first million dollars, the company is at least a million dollars more valuable, because it's the same company as before, plus it has a million dollars in the bank. [1] Beware, though, because later investors so hate to have the price raised on them that they resist even this self-evident reasoning. Only raise the price on an investor you're comfortable with losing, because some will angrily refuse. [2] The second reason investors like you more when you've had some success at fundraising is that it makes you more confident, and an investors' opinion of you is the foundation of their opinion of your company. Founders are often surprised how quickly investors seem to know when they start to succeed at raising money. And while there are in fact lots of ways for such information to spread among investors, the main vector is probably the founders themselves. Though they're often clueless about technology, most investors are pretty good at reading people. When fundraising is going well, investors are quick to sense it in your increased confidence. (This is one case where the average founder's inability to remain poker-faced works to your advantage.) But frankly the most important reason investors like you more when you've started to raise money is that they're bad at judging startups. Judging startups is hard even for the best investors. The mediocre ones might as well be flipping coins. So when mediocre investors see that lots of other people want to invest in you, they assume there must be a reason. This leads to the phenomenon known in the Valley as the "hot deal," where you have more interest from investors than you can handle. The best investors aren't influenced much by the opinion of other investors. It would only dilute their own judgment to average it together with other people's. But they are indirectly influenced in the practical sense that interest from other investors imposes a deadline.
投资人因其他投资人的青睐而更看好你的首要原因,是你确实成为了更优质的投资标的。融资能降低失败风险。事实上,尽管投资人不愿承认,基于此,你有理由为后续投资人提高估值。早期在你资金匮乏时投资的人承担了更高风险,理应获得更高回报。此外,完成融资的公司客观上更有价值——获得首笔100万美元后,公司价值至少增加100万美元,因为除原有业务外,银行账户还多了这笔现金。[1]
但需警惕:后续投资人极度反感提价行为,甚至抗拒这种不言自明的逻辑。只对可承受失去的投资人提价,因为有些人会愤怒拒绝。[2]
融资初获成功后投资人更青睐你的第二个原因,是这增强了你的信心,而投资人对你的评判构成其对公司评价的基础。创始人常惊讶于投资人对其融资进展的敏锐感知。虽然此类信息在投资人间确有多种传播渠道,但主要载体恐怕是创始人自身。多数投资人虽对技术一窍不通,却深谙识人之道。当融资顺利时,他们能从你增长的自信中迅速察觉。(此时,普通创始人难以保持扑克脸的特质反而成为优势。)
但坦率说,融资启动后更受青睐的最重要原因,在于投资人普遍缺乏评估初创公司的能力。即使最优秀的投资人也难以准确判断,平庸者更如同抛硬币决策。因此,当平庸投资人看到众人争相投资你时,便认定必有缘由。这催生了硅谷所谓的"热门交易"现象——投资人的热情远超你的承接能力。
This is the fourth way in which offers beget offers. If you start to get far along the track toward an offer with one firm, it will sometimes provoke other firms, even good ones, to make up their minds, lest they lose the deal. Unless you're a wizard at negotiation (and if you're not sure, you're not) be very careful about exaggerating this to push a good investor to decide. Founders try this sort of thing all the time, and investors are very sensitive to it. If anything oversensitive. But you're safe so long as you're telling the truth. If you're getting far along with investor B, but you'd rather raise money from investor A, you can tell investor A that this is happening. There's no manipulation in that. You're genuinely in a bind, because you really would rather raise money from A, but you can't safely reject an offer from B when it's still uncertain what A will decide. Do not, however, tell A who B is. VCs will sometimes ask which other VCs you're talking to, but you should never tell them. Angels you can sometimes tell about other angels, because angels cooperate more with one another. But if VCs ask, just point out that they wouldn't want you telling other firms about your conversations, and you feel obliged to do the same for any firm you talk to. If they push you, point out that you're inexperienced at fundraising — which is always a safe card to play — and you feel you have to be extra cautious. [3] While few startups will experience a stampede of interest, almost all will at least initially experience the other side of this phenomenon, where the herd remains clumped together at a distance. The fact that investors are so much influenced by other investors' opinions means you always start out in something of a hole. So don't be demoralized by how hard it is to get the first commitment, because much of the difficulty comes from this external force.
顶级投资人很少受同行意见左右。让他人观点稀释自身判断毫无意义。但实际操作中,其他投资人的兴趣会间接施加期限压力,这是"邀约催生邀约"的第四种表现。当某家机构即将给出offer时,常会促使其他机构(包括优秀机构)为避免错失机会而快速决策。
除非你是谈判高手(若不确定则必然不是),切勿夸大此效应来逼迫优秀投资人决定。创始人常尝试此类手段,而投资人对此异常敏感(甚至过度敏感)。但只要如实相告便无妨。若与投资人B进展深入,但你更倾向投资人A,可如实告知A这一状况。这并非操纵——你确实陷入两难:更希望获得A的投资,但在A未明确表态前,无法贸然拒绝B的offer。
但切勿向A透露B的身份。风投常打探你接触的其他机构,但绝不应透露。天使投资人之间可适当分享信息,因其协作性更强。若风投追问,只需表明"您也不希望我泄露贵机构的谈话内容,我对所有接触的机构均同等对待"。若对方坚持,可借口"融资经验不足"(永远安全的托辞)并强调需格外谨慎。[3]
尽管极少初创公司会遭遇投资狂潮,几乎所有公司初期都会经历另一面——投资人群在远处观望扎堆。投资人极易受同行影响的特质,意味着你起步时总处于劣势。因此,别因获取首笔承诺的艰难而气馁,这很大程度上源于外部力量。第二笔会容易得多。
The second will be easier. Notes [1] An accountant might say that a company that has raised a million dollars is no richer if it's convertible debt, but in practice money raised as convertible debt is little different from money raised in an equity round. [2] Founders are often surprised by this, but investors can get very emotional. Or rather indignant; that's the main emotion I've observed; but it is very common, to the point where it sometimes causes investors to act against their own interests. I know of one investor who invested in a startup at a $15 million valuation cap. Earlier he'd had an opportunity to invest at a $5 million cap, but he refused because a friend who invested earlier had been able to invest at a $3 million cap. [3] If an investor pushes you hard to tell them about your conversations with other investors, is this someone you want as an investor? Thanks to Paul Buchheit, Jessica Livingston, Geoff Ralston, and Garry Tan for reading drafts of this.
[1] 会计师可能认为以可转债融资的百万美元不增加公司净值,但实践中可转债与股权融资差异甚微。
[2] 创始人常对此惊讶,但投资人可能极度情绪化(更准确说是愤慨——这是我观察的主要情绪),甚至常见到损害自身利益的行为。某投资人曾以1500万美元估值上限投资,而此前他本可以500万美元上限入场,却因朋友早期以300万美元进入而拒绝。
[3] 若投资人强硬要求透露与其他机构的谈话内容,这样的人真适合成为你的投资人吗?
致谢 Paul Buchheit、Jessica Livingston、Geoff Ralston和Garry Tan审阅了本文草稿。
Want to start a startup? Get funded by Y Combinator.
August 2013 When people hurt themselves lifting heavy things, it's usually because they try to lift with their back. The right way to lift heavy things is to let your legs do the work. Inexperienced founders make the same mistake when trying to convince investors. They try to convince with their pitch. Most would be better off if they let their startup do the work — if they started by understanding why their startup is worth investing in, then simply explained this well to investors. Investors are looking for startups that will be very successful. But that test is not as simple as it sounds. In startups, as in a lot of other domains, the distribution of outcomes follows a power law, but in startups the curve is startlingly steep. The big successes are so big they dwarf the rest. And since there are only a handful each year (the conventional wisdom is 15), investors treat "big success" as if it were binary. Most are interested in you if you seem like you have a chance, however small, of being one of the 15 big successes, and otherwise not. [1] (There are a handful of angels who'd be interested in a company with a high probability of being moderately successful. But angel investors like big successes too.) How do you seem like you'll be one of the big successes? You need three things: formidable founders, a promising market, and (usually) some evidence of success so far. Formidable The most important ingredient is formidable founders. Most investors decide in the first few minutes whether you seem like a winner or a loser, and once their opinion is set it's hard to change. [2] Every startup has reasons both to invest and not to invest. If investors think you're a winner they focus on the former, and if not they focus on the latter. For example, it might be a rich market, but with a slow sales cycle.
想创办一家初创公司? 获得Y Combinator的资金支持。
2013年8月 当人们因搬重物而受伤时,通常是因为他们试图用背部发力。正确的搬运方式是让腿部承担主要力量。缺乏经验的创始人在试图说服投资者时也会犯同样的错误。他们试图用推销技巧来说服对方。但如果他们让初创公司本身发挥作用——先理解为什么自己的项目值得投资,再向投资者清晰阐述——大多数人会取得更好的效果。 投资者寻找的是那些将取得巨大成功的初创企业。但这个标准并不像听起来那么简单。在初创领域,如同许多其他领域一样,结果分布遵循幂律法则,但初创企业的曲线陡峭得惊人。那些巨大成功是如此耀眼,以至于让其他项目相形见绌。由于每年只有少数项目能达到这种高度(普遍认为约15个),投资者将"巨大成功"视为非此即彼的命题。只要你有机会(无论多渺茫)成为这15个成功案例之一,大多数投资者就会对你感兴趣,否则就不会。[1] (少数天使投资人会对中等成功概率较高的公司感兴趣。但天使投资人也偏爱巨大成功。) 如何让自己看起来将成为巨大成功案例之一?你需要三个要素:强大的创始人、前景广阔的市场,以及(通常)一些已经取得的成功迹象。 强大 最重要的因素是强大的创始人。大多数投资者在前几分钟就会判断你属于赢家还是输家阵营,一旦形成印象就很难改变。[2]每个初创企业都有值得投资和不值得投资的理由。如果投资者认为你是赢家,他们会聚焦前者;反之则强调后者。例如,某个市场可能利润丰厚但销售周期漫长。若投资者欣赏创始团队,他们会说"投资理由是市场潜力巨大";若不看好,则会说"无法投资因为销售周期太长"。 他们未必存心误导。多数投资者自己也不完全清楚为何喜欢或否定某个项目。如果你看起来像赢家,他们会更认可你的创意。但别因此沾沾自喜——这种认知偏差人人都有。 创意当然有其价值。它们像是助燃剂,需要以欣赏创始人为前提。当投资者认可你时,你会看到他们主动为项目添砖加瓦:"没错,你们还可以做X"(而不看好时则会质疑:"那Y问题怎么解决?") 说服投资者的核心在于展现强大特质。由于"强大"并非日常高频词汇,我需要解释其含义:强大的人看起来能扫除一切障碍达成目标。它近似于自信,但自信可能源于误判,而强大意味着有充分理由的自信。 少数人极其擅长展现强大特质——有些确实能力超群自然流露,有些则近乎江湖骗子。[3]但多数创始人(包括许多最终非常成功者)在首次融资时并不擅长此道。他们该怎么办?[4] 切忌模仿老练创始人的虚张声势。投资者或许不擅技术判断,但都是察言观色的高手。如果强装模样,只会陷入恐怖谷效应——既丢失了真诚,又达不到说服效果。 真相 缺乏经验的创始人展现强大的最佳方式就是坚持真相。你展现的强大程度并非恒定,它随陈述内容而变化。当说"1+1=2"时,多数人都显得自信,因为这是确凿事实。即便最怯懦的人,若向风投陈述这个等式却遭遇怀疑,也会感到困惑甚至轻蔑。那些擅长展现强大者的魔力在于,他们能用"我们年收入将达十亿美元"这样的句子获得同等确信度。只要你先说服自己,即便不用如此夸张的表述,也能对一些相当亮眼的陈述保持这种确信。 这就是秘诀。先确信自己的初创公司值得投资,当你向投资者阐述时,他们就会相信你。所谓"确信",不是用心理游戏自我激励,而是真正评估项目的投资价值。若达不到标准,就不要尝试融资。[5]但如果确实达标,你向投资者陈述时就是在讲述真相,他们会感知到这一点。只要深谙某事并如实相告,你不需要多高超的演讲技巧。 要评估初创公司的投资价值,你必须成为领域专家。若非如此,无论你对自己的创意多确信,在投资者眼中都只是达克效应的实例——而事实通常正是如此。通过你回答问题的表现,投资者能快速判断你是否是领域专家。你必须通晓市场的一切。[6] 为何创始人总试图说服投资者相信连自己都不确信的事?部分原因在于我们都被训练成这样。 当我的朋友罗伯特·莫里斯和特雷弗·布莱克韦尔在读研时,他们的一位同学曾从导师那里收到个至今仍被引用的质问。当这个倒霉蛋展示到最后一张幻灯片时,教授突然打断道:
If investors are impressed with you as founders, they say they want to invest because it's a rich market, and if not, they say they can't invest because of the slow sales cycle. They're not necessarily trying to mislead you. Most investors are genuinely unclear in their own minds why they like or dislike startups. If you seem like a winner, they'll like your idea more. But don't be too smug about this weakness of theirs, because you have it too; almost everyone does. There is a role for ideas of course. They're fuel for the fire that starts with liking the founders. Once investors like you, you'll see them reaching for ideas: they'll be saying "yes, and you could also do x." (Whereas when they don't like you, they'll be saying "but what about y?") But the foundation of convincing investors is to seem formidable, and since this isn't a word most people use in conversation much, I should explain what it means. A formidable person is one who seems like they'll get what they want, regardless of whatever obstacles are in the way. Formidable is close to confident, except that someone could be confident and mistaken. Formidable is roughly justifiably confident. There are a handful of people who are really good at seeming formidable — some because they actually are very formidable and just let it show, and others because they are more or less con artists. [3] But most founders, including many who will go on to start very successful companies, are not that good at seeming formidable the first time they try fundraising. What should they do? [4] What they should not do is try to imitate the swagger of more experienced founders. Investors are not always that good at judging technology, but they're good at judging confidence. If you try to act like something you're not, you'll just end up in an uncanny valley.
你真正相信的是哪一个结论?
You'll depart from sincere, but never arrive at convincing. Truth The way to seem most formidable as an inexperienced founder is to stick to the truth. How formidable you seem isn't a constant. It varies depending on what you're saying. Most people can seem confident when they're saying "one plus one is two," because they know it's true. The most diffident person would be puzzled and even slightly contemptuous if they told a VC "one plus one is two" and the VC reacted with skepticism. The magic ability of people who are good at seeming formidable is that they can do this with the sentence "we're going to make a billion dollars a year." But you can do the same, if not with that sentence with some fairly impressive ones, so long as you convince yourself first. That's the secret. Convince yourself that your startup is worth investing in, and then when you explain this to investors they'll believe you. And by convince yourself, I don't mean play mind games with yourself to boost your confidence. I mean truly evaluate whether your startup is worth investing in. If it isn't, don't try to raise money. [5] But if it is, you'll be telling the truth when you tell investors it's worth investing in, and they'll sense that. You don't have to be a smooth presenter if you understand something well and tell the truth about it. To evaluate whether your startup is worth investing in, you have to be a domain expert. If you're not a domain expert, you can be as convinced as you like about your idea, and it will seem to investors no more than an instance of the Dunning-Kruger effect. Which in fact it will usually be. And investors can tell fairly quickly whether you're a domain expert by how well you answer their questions. Know everything about your market. [6] Why do founders persist in trying to convince investors of things they're not convinced of themselves? Partly because we've all been trained to.
学校体制的一个副产品是,我们都被训练成即使无话可说也要强行发言。如果要求你写十页论文,即使你只有一页纸的想法——甚至毫无想法——你也必须凑出十页来。太多初创公司正是带着这种心态开始融资的。当他们觉得该融资时,就竭尽全力为自家公司编织最完美的说辞。大多数人从不会事先停下来思考自己所言是否真正具有说服力,因为他们早已习惯将"必须展示"视为既定前提——就像面对固定面积的画布,无论真相多么有限,都要强行铺满整张纸。 融资的正确时机不是你缺钱的时候,也不是遇到"演示日"这类人为期限的时候,而是当你能说服投资人时——在此之前都不该行动。[7] 除非你是职业骗子,否则连自己都无法说服的事,永远别想说服投资人。他们识别忽悠的能力远胜你编故事的水平,哪怕你只是无意中夸大了事实。若在自我说服前就试图说服投资人,只会白白浪费双方时间。 但先停下来说服自己不仅能避免时间浪费,更能迫使你理清思路。要让自己相信公司值得投资,你必须先想明白"为什么值得"。这个思考过程带给你的不仅是倍增的信心,更将勾勒出通向成功的路线图。 市场 请注意我始终谨慎使用"值得投资"而非"必将成功"的表述。没人能预知初创公司能否成功。这对投资人反倒是好事——若能提前预知成败,股价早就会反映未来价值,投资人便无利可图。风投们深知每笔投资都是赌注,且胜率往往很低。 因此要证明自己值得投资,无需证明必将成功,只需证明这是个足够好的赌局。什么构成"足够好的赌局"?除了强大的创始团队,还需要一条能占领大市场可观份额的可行路径。创始人视初创公司为创意结晶,投资人却将其看作市场载体。若存在X名客户愿为你产品年均支付Y美元,公司总潜在市场(TAM)就是X乘Y。投资人并不指望你通吃整个市场,但这个数字决定了成长天花板。 目标市场必须足够大且你能攻占——但它此刻未必庞大,你也未必已经身处其中。事实上,从小众市场起步往往更佳,要么等待其扩张,要么以此为跳板进军大市场。关键是要呈现未来几年逐步主导大市场的合理路径。 这条路径的可信度标准随公司发展阶段剧烈变化。参加演示日的三个月大公司只需证明自己是值得押注的有潜力实验;而寻求A轮融资的两年大公司则必须展示实验已获成功。[8] 所有真正壮大的公司都具备某种"幸运"——它们的增长主要得益于所乘的外部浪潮。因此要论证成为巨头的可能性,必须指明你将借力的具体趋势。通常可通过追问"为什么是现在"来发现答案:如果创意绝佳,为何至今无人实现?理想答案是"近期某些变化使其成为好主意,而尚未被他人察觉"。 譬如微软若仅销售BASIC解释器绝无可能壮大。但以此为起点,当微电脑性能足以支撑更多软件时,他们便顺势向上拓展产品线。后来微电脑浪潮的规模远超1975年最乐观观察家的预测。 尽管微软最终大获成功,但若在初创数月时就断言它前途无量,这个判断很可能失准。它当时看起来不错,但绝非惊人。任何公司——无论日后多成功——在初创期都只是"相当不错的赌注"。微电脑浪潮成就了微软,既因执行力,也因运气。但这一切绝非显而易见。多数初创公司在早期都具备同等潜力。我不知道其他机构情况,但我们投资的初创公司中至少半数都能像当年的微软那样,论证自己具备主导大市场的可能——除此之外,还能对初创公司抱什么更高期待呢? 拒绝 若你能提出微软级别的论证,就能说服投资人吗?未必。许多风投当年都会拒绝微软。[9] 谷歌确实曾被某些机构拒绝。而遭遇拒绝会让你陷入微妙处境——开始融资后你会发现,投资人最常问的问题是"还有谁要投?"若融资多时仍无人承诺,你该如何回应?[10] 擅长虚张声势者常给投资人制造"虽暂未签约,但多家机构即将出手"的假象。这种策略或许情有可原:比起项目本身,投资人更关注同行动向的做法本就欠妥,用话术误导他们倒像是以牙还牙,堪称"骗子间的博弈"。但我不建议多数创始人尝试,因为多数人根本演不像——这是对投资人最常用的谎言,而向某个行业的从业者施展他们最熟悉的谎言,需要极高的骗术造诣。 若非谈判大师(或许即便是),最佳对策是直面问题:解释为何被拒,以及他们错在何处。若确信方向正确,你自然清楚投资人误判的原因。经验丰富的投资人都明白,最棒的点子往往最骇人。他们熟知那些错过谷歌的风投案例。若你能坦率剖析吓退投资人的因素(而非闪烁其词或面露愧色,变相认同对方判断),不仅会显得更自信(他们欣赏这点),通常也能更好地呈现公司该方面的特质。至少,这个隐患将被公开讨论,而非成为当下洽谈的投资人暗自得意的"重大发现"——人们总会对自己发掘的缺陷格外执着。[11] 此策略对顶级投资人最有效,他们既难被糊弄,又深信多数同行是注定错过超级黑马的平庸之辈。融资不像申请大学——能进麻省理工就意味着也能进Foobar州立大学。因顶级投资人远比同行聪明,而顶级创业点子初看都像馊主意,初创公司被所有风投拒绝、唯独顶尖机构看好的情况并不罕见。Dropbox正是如此。YC最初三年在波士顿与硅谷交替举办路演日。因波士顿投资人数量少且保守,我们常带波士顿团队赴硅谷二次路演。Dropbox来自波士顿批次,意味着所有当地投资人都优先接触过它却无人出手——在他们眼中,这不过是又一个备份同步工具。两周后,红杉资本完成了Dropbox的A轮融资。[12] 差异 不理解"投资即赌注"的思维,加上"十页论文"式惯性,使创始人根本不敢确信自己所言。他们以为要说服投资人相信极不确定的事(公司将成为巨头),似乎必然需要天花乱坠的推销话术。但实际上,融资只需说服投资人相信更确定的事——公司是否具备好赌局的所有要素——这让你能以截然不同的方式解决问题:先说服自己,再说服他们。 说服时请使用自我说服时的平实语言。你不会在团队内部使用模糊夸张的市场话术,对投资人也该如此。这不仅无效,还会显得不专业。简洁至上——许多投资人明确将此作为测试标准,他们(正确地)认为:若无法简明阐述计划,说明你并未真正理解。即便没有这条准则的投资人,也会因冗长解释感到乏味沮丧。[13] 因此,若你不擅长虚张声势,以下是打动投资人的秘诀:.
When my friends Robert Morris and Trevor Blackwell were in grad school, one of their fellow students was on the receiving end of a question from their faculty advisor that we still quote today. When the unfortunate fellow got to his last slide, the professor burst out:.
1. 打造值得投资的项目。
> Which one of these conclusions do you actually believe?
2. 理解项目为何值得投资。
One of the artifacts of the way schools are organized is that we all get trained to talk even when we have nothing to say. If you have a ten page paper due, then ten pages you must write, even if you only have one page of ideas. Even if you have no ideas. You have to produce something. And all too many startups go into fundraising in the same spirit. When they think it's time to raise money, they try gamely to make the best case they can for their startup. Most never think of pausing beforehand to ask whether what they're saying is actually convincing, because they've all been trained to treat the need to present as a given — as an area of fixed size, over which however much truth they have must needs be spread, however thinly. The time to raise money is not when you need it, or when you reach some artificial deadline like a Demo Day. It's when you can convince investors, and not before. [7] And unless you're a good con artist, you'll never convince investors if you're not convinced yourself. They're far better at detecting bullshit than you are at producing it, even if you're producing it unknowingly. If you try to convince investors before you've convinced yourself, you'll be wasting both your time. But pausing first to convince yourself will do more than save you from wasting your time. It will force you to organize your thoughts. To convince yourself that your startup is worth investing in, you'll have to figure out why it's worth investing in. And if you can do that you'll end up with more than added confidence. You'll also have a provisional roadmap of how to succeed. Market Notice I've been careful to talk about whether a startup is worth investing in, rather than whether it's going to succeed. No one knows whether a startup is going to succeed.
3. 向投资者清晰地阐明这一点。
如果你说的是自己确信为真的事,在陈述时自然会显得自信。反之,绝不要让融资演说诱使你信口开河。只要坚守事实的阵地,你就立于不败之地。把真相打磨好,然后如实陈述即可。
And it's a good thing for investors that this is so, because if you could know in advance whether a startup would succeed, the stock price would already be the future price, and there would be no room for investors to make money. Startup investors know that every investment is a bet, and against pretty long odds. So to prove you're worth investing in, you don't have to prove you're going to succeed, just that you're a sufficiently good bet. What makes a startup a sufficiently good bet? In addition to formidable founders, you need a plausible path to owning a big piece of a big market. Founders think of startups as ideas, but investors think of them as markets. If there are x number of customers who'd pay an average of $y per year for what you're making, then the total addressable market, or TAM, of your company is $xy. Investors don't expect you to collect all that money, but it's an upper bound on how big you can get. Your target market has to be big, and it also has to be capturable by you. But the market doesn't have to be big yet, nor do you necessarily have to be in it yet. Indeed, it's often better to start in a small market that will either turn into a big one or from which you can move into a big one. There just has to be some plausible sequence of hops that leads to dominating a big market a few years down the line. The standard of plausibility varies dramatically depending on the age of the startup. A three month old company at Demo Day only needs to be a promising experiment that's worth funding to see how it turns out. Whereas a two year old company raising a series A round needs to be able to show the experiment worked. [8] But every company that gets really big is "lucky" in the sense that their growth is due mostly to some external wave they're riding, so to make a convincing case for becoming huge, you have to identify some specific trend you'll benefit from.
[1] 没有理由认为这个数字是恒定的。事实上,YC的明确目标就是通过鼓励原本不会创业的人投身创业来提升这个比例。
Usually you can find this by asking "why now?" If this is such a great idea, why hasn't someone else already done it? Ideally the answer is that it only recently became a good idea, because something changed, and no one else has noticed yet. Microsoft for example was not going to grow huge selling Basic interpreters. But by starting there they were perfectly poised to expand up the stack of microcomputer software as microcomputers grew powerful enough to support one. And microcomputers turned out to be a really huge wave, bigger than even the most optimistic observers would have predicted in 1975. But while Microsoft did really well and there is thus a temptation to think they would have seemed a great bet a few months in, they probably didn't. Good, but not great. No company, however successful, ever looks more than a pretty good bet a few months in. Microcomputers turned out to be a big deal, and Microsoft both executed well and got lucky. But it was by no means obvious that this was how things would play out. Plenty of companies seem as good a bet a few months in. I don't know about startups in general, but at least half the startups we fund could make as good a case as Microsoft could have for being on a path to dominating a large market. And who can reasonably expect more of a startup than that? Rejection If you can make as good a case as Microsoft could have, will you convince investors? Not always. A lot of VCs would have rejected Microsoft. [9] Certainly some rejected Google.
[2] 更准确地说,投资人判断的你是失败者还是潜在赢家。若你展现出赢家特质,根据融资规模,他们可能会安排多次会面来验证第一印象。但如果被判定为失败者,至少在接下来一年里他们不会再考虑你。这种判断往往在初次会面50分钟前就已形成——这也解释了为何总有人震惊于风投的心不在焉:当投资人在创业者路演时查看信息,他们怎能做出明智决策?谜底在于:他们早已做出决定。
And getting rejected will put you in a slightly awkward position, because as you'll see when you start fundraising, the most common question you'll get from investors will be "who else is investing?" What do you say if you've been fundraising for a while and no one has committed yet? [10] The people who are really good at acting formidable often solve this problem by giving investors the impression that while no investors have committed yet, several are about to. This is arguably a permissible tactic. It's slightly dickish of investors to care more about who else is investing than any other aspect of your startup, and misleading them about how far along you are with other investors seems the complementary countermove. It's arguably an instance of scamming a scammer. But I don't recommend this approach to most founders, because most founders wouldn't be able to carry it off. This is the single most common lie told to investors, and you have to be really good at lying to tell members of some profession the most common lie they're told. If you're not a master of negotiation (and perhaps even if you are) the best solution is to tackle the problem head-on, and to explain why investors have turned you down and why they're mistaken. If you know you're on the right track, then you also know why investors were wrong to reject you. Experienced investors are well aware that the best ideas are also the scariest. They all know about the VCs who rejected Google. If instead of seeming evasive and ashamed about having been turned down (and thereby implicitly agreeing with the verdict) you talk candidly about what scared investors about you, you'll seem more confident, which they like, and you'll probably also do a better job of presenting that aspect of your startup.
[3] 两者并不互斥。有些人既真正实力超群,又深谙如何展现这种特质。
At the very least, that worry will now be out in the open instead of being a gotcha left to be discovered by the investors you're currently talking to, who will be proud of and thus attached to their discovery. [11] This strategy will work best with the best investors, who are both hard to bluff and who already believe most other investors are conventional-minded drones doomed always to miss the big outliers. Raising money is not like applying to college, where you can assume that if you can get into MIT, you can also get into Foobar State. Because the best investors are much smarter than the rest, and the best startup ideas look initially like bad ideas, it's not uncommon for a startup to be rejected by all the VCs except the best ones. That's what happened to Dropbox. Y Combinator started in Boston, and for the first 3 years we ran alternating batches in Boston and Silicon Valley. Because Boston investors were so few and so timid, we used to ship Boston batches out for a second Demo Day in Silicon Valley. Dropbox was part of a Boston batch, which means all those Boston investors got the first look at Dropbox, and none of them closed the deal. Yet another backup and syncing thing, they all thought. A couple weeks later, Dropbox raised a series A round from Sequoia. [12] Different Not understanding that investors view investments as bets combines with the ten page paper mentality to prevent founders from even considering the possibility of being certain of what they're saying. They think they're trying to convince investors of something very uncertain — that their startup will be huge — and convincing anyone of something like that must obviously entail some wild feat of salesmanship. But in fact when you raise money you're trying to convince investors of something so much less speculative — whether the company has all the elements of a good bet — that you can approach the problem in a qualitatively different way.
[4] 为何未来缔造商业帝国的人早期看起来并不出众?主因在于他们此前的经历训练他们收敛锋芒。家庭、学校和工作都鼓励合作而非征服。这种驯化有其价值,因为即便成吉思汗的成功也99%依赖协作。但结果是多数人二十出头时仍保持着成长环境的塑造痕迹。有些人后来发现自己拥有翅膀并逐渐展开——但这需要时间,最初连他们自己都不清楚自身潜力。
You can convince yourself, then convince them. And when you convince them, use the same matter-of-fact language you used to convince yourself. You wouldn't use vague, grandiose marketing-speak among yourselves. Don't use it with investors either. It not only doesn't work on them, but seems a mark of incompetence. Just be concise. Many investors explicitly use that as a test, reasoning (correctly) that if you can't explain your plans concisely, you don't really understand them. But even investors who don't have a rule about this will be bored and frustrated by unclear explanations. [13] So here's the recipe for impressing investors when you're not already good at seeming formidable:.
[5] 实际上应该调整你正在做的事。你正在用自己的时间投资创业项目。如果连你自己都不确信所做的事情值得押注,为何还要继续?
1. Make something worth investing in.
[6] 当被问到未知问题时,最佳回应既非虚张声势也非放弃,而是阐明你将如何寻找答案。若能当场推导出初步结论更好,但要说明这只是临时推演。
[7] YC通过建议创业者在DemoDay前一周才接触投资人,确保他们专注产品打磨。这样多数项目届时都能具备说服力。未达标者可以选择延后到下一届DemoDay。
2. Understand why it's worth investing in.
[8] 创始人常惊讶于后续轮次融资难度骤增。投资人的态度存在质变,如同对孩童与成人的评判标准差异。再次融资时,仅有潜力不够,必须拿出实际成果。虽然成长曲线在前后期都适用,但解读方式不同:三个月时的增长曲线主要证明团队执行力,两年时则必须显示市场潜力与公司变现能力。
3. Explain that clearly to investors.
[9] 即便当今出现类似微软初创三个月时的项目,DemoDay上仍会有投资人拒绝。微软当年其实未接受外部投资——1975年风投行业几乎尚未成形。
If you're saying something you know is true, you'll seem confident when you're saying it. Conversely, never let pitching draw you into bullshitting. As long as you stay on the territory of truth, you're strong. Make the truth good, then just tell it. Notes [1] There's no reason to believe this number is a constant. In fact it's our explicit goal at Y Combinator to increase it, by encouraging people to start startups who otherwise wouldn't have. [2] Or more precisely, investors decide whether you're a loser or possibly a winner. If you seem like a winner, they may then, depending on how much you're raising, have several more meetings with you to test whether that initial impression holds up. But if you seem like a loser they're done, at least for the next year or so. And when they decide you're a loser they usually decide in way less than the 50 minutes they may have allotted for the first meeting. Which explains the astonished stories one always hears about VC inattentiveness. How could these people make investment decisions well when they're checking their messages during startups' presentations? The solution to that mystery is that they've already made the decision. [3] The two are not mutually exclusive. There are people who are both genuinely formidable, and also really good at acting that way. [4] How can people who will go on to create giant companies not seem formidable early on? I think the main reason is that their experience so far has trained them to keep their wings folded, as it were. Family, school, and jobs encourage cooperation, not conquest. And it's just as well they do, because even being Genghis Khan is probably 99% cooperation. But the result is that most people emerge from the tube of their upbringing in their early twenties compressed into the shape of the tube. Some find they have wings and start to spread them. But this takes a few years.
[10] 顶级投资人很少在意跟投者,但平庸投资人几乎都在乎。这个问题可用来检验投资人水准。
In the beginning even they don't know yet what they're capable of. [5] In fact, change what you're doing. You're investing your own time in your startup. If you're not convinced that what you're working on is a sufficiently good bet, why are you even working on that? [6] When investors ask you a question you don't know the answer to, the best response is neither to bluff nor give up, but instead to explain how you'd figure out the answer. If you can work out a preliminary answer on the spot, so much the better, but explain that's what you're doing. [7] At YC we try to ensure startups are ready to raise money on Demo Day by encouraging them to ignore investors and instead focus on their companies till about a week before. That way most reach the stage where they're sufficiently convincing well before Demo Day. But not all do, so we also give any startup that wants to the option of deferring to a later Demo Day. [8] Founders are often surprised by how much harder it is to raise the next round. There is a qualitative difference in investors' attitudes. It's like the difference between being judged as a kid and as an adult. The next time you raise money, it's not enough to be promising. You have to be delivering results. So although it works well to show growth graphs at either stage, investors treat them differently. At three months, a growth graph is mostly evidence that the founders are effective. At two years, it has to be evidence of a promising market and a company tuned to exploit it. [9] By this I mean that if the present day equivalent of the 3 month old Microsoft presented at a Demo Day, there would be investors who turned them down. Microsoft itself didn't raise outside money, and indeed the venture business barely existed when they got started in 1975. [10] The best investors rarely care who else is investing, but mediocre investors almost all do.
[11] 运用此策略需探明被拒原因。明确表示并非质疑决定,只为找出计划漏洞。虽不总能获得真实反馈,但值得尝试。
So you can use this question as a test of investor quality. [11] To use this technique, you'll have to find out why investors who rejected you did so, or at least what they claim was the reason. That may require asking, because investors don't always volunteer a lot of detail. Make it clear when you ask that you're not trying to dispute their decision — just that if there is some weakness in your plans, you need to know about it. You won't always get a real reason out of them, but you should at least try. [12] Dropbox wasn't rejected by all the East Coast VCs. There was one firm that wanted to invest but tried to lowball them. [13] Alfred Lin points out that it's doubly important for the explanation of a startup to be clear and concise, because it has to convince at one remove: it has to work not just on the partner you talk to, but when that partner re-tells it to colleagues. We consciously optimize for this at YC. When we work with founders create a Demo Day pitch, the last step is to imagine how an investor would sell it to colleagues. Thanks to Marc Andreessen, Sam Altman, Patrick Collison, Ron Conway, Chris Dixon, Alfred Lin, Ben Horowitz, Steve Huffman, Jessica Livingston, Greg Mcadoo, Andrew Mason, Geoff Ralston, Yuri Sagalov, Emmett Shear, Rajat Suri, Garry Tan, Albert Wenger, Fred Wilson, and Qasar Younis for reading drafts of this..
[12] Dropbox并非被所有东岸风投拒绝。有家机构愿投资但试图压价。
[13] Alfred Lin指出创业项目的解释必须清晰简洁,因为它需要二次传播:不仅要打动面谈的合伙人,还要在其向同事转述时同样有效。YC在筹备DemoDay路演时,最后一步总是模拟投资人向同事推介的场景。
Want to start a startup? Get funded by Y Combinator.
July 2013 One of the most common types of advice we give at Y Combinator is to do things that don't scale. A lot of would-be founders believe that startups either take off or don't. You build something, make it available, and if you've made a better mousetrap, people beat a path to your door as promised. Or they don't, in which case the market must not exist. [1] Actually startups take off because the founders make them take off. There may be a handful that just grew by themselves, but usually it takes some sort of push to get them going. A good metaphor would be the cranks that car engines had before they got electric starters. Once the engine was going, it would keep going, but there was a separate and laborious process to get it going. Recruit The most common unscalable thing founders have to do at the start is to recruit users manually. Nearly all startups have to. You can't wait for users to come to you. You have to go out and get them. Stripe is one of the most successful startups we've funded, and the problem they solved was an urgent one. If anyone could have sat back and waited for users, it was Stripe. But in fact they're famous within YC for aggressive early user acquisition. Startups building things for other startups have a big pool of potential users in the other companies we've funded, and none took better advantage of it than Stripe. At YC we use the term "Collison installation" for the technique they invented. More diffident founders ask "Will you try our beta?" and if the answer is yes, they say "Great, we'll send you a link." But the Collison brothers weren't going to wait. When anyone agreed to try Stripe they'd say "Right then, give me your laptop" and set them up on the spot. There are two reasons founders resist going out and recruiting users individually. One is a combination of shyness and laziness.
They'd rather sit at home writing code than go out and talk to a bunch of strangers and probably be rejected by most of them. But for a startup to succeed, at least one founder (usually the CEO) will have to spend a lot of time on sales and marketing. [2] The other reason founders ignore this path is that the absolute numbers seem so small at first. This can't be how the big, famous startups got started, they think. The mistake they make is to underestimate the power of compound growth. We encourage every startup to measure their progress by weekly growth rate. If you have 100 users, you need to get 10 more next week to grow 10% a week. And while 110 may not seem much better than 100, if you keep growing at 10% a week you'll be surprised how big the numbers get. After a year you'll have 14,000 users, and after 2 years you'll have 2 million. You'll be doing different things when you're acquiring users a thousand at a time, and growth has to slow down eventually. But if the market exists you can usually start by recruiting users manually and then gradually switch to less manual methods. [3] Airbnb is a classic example of this technique. Marketplaces are so hard to get rolling that you should expect to take heroic measures at first. In Airbnb's case, these consisted of going door to door in New York, recruiting new users and helping existing ones improve their listings. When I remember the Airbnbs during YC, I picture them with rolly bags, because when they showed up for tuesday dinners they'd always just flown back from somewhere. Fragile Airbnb now seems like an unstoppable juggernaut, but early on it was so fragile that about 30 days of going out and engaging in person with users made the difference between success and failure. That initial fragility was not a unique feature of Airbnb. Almost all startups are fragile initially.
And that's one of the biggest things inexperienced founders and investors (and reporters and know-it-alls on forums) get wrong about them. They unconsciously judge larval startups by the standards of established ones. They're like someone looking at a newborn baby and concluding "there's no way this tiny creature could ever accomplish anything." It's harmless if reporters and know-it-alls dismiss your startup. They always get things wrong. It's even ok if investors dismiss your startup; they'll change their minds when they see growth. The big danger is that you'll dismiss your startup yourself. I've seen it happen. I often have to encourage founders who don't see the full potential of what they're building. Even Bill Gates made that mistake. He returned to Harvard for the fall semester after starting Microsoft. He didn't stay long, but he wouldn't have returned at all if he'd realized Microsoft was going to be even a fraction of the size it turned out to be. [4] The question to ask about an early stage startup is not "is this company taking over the world?" but "how big could this company get if the founders did the right things?" And the right things often seem both laborious and inconsequential at the time. Microsoft can't have seemed very impressive when it was just a couple guys in Albuquerque writing Basic interpreters for a market of a few thousand hobbyists (as they were then called), but in retrospect that was the optimal path to dominating microcomputer software. And I know Brian Chesky and Joe Gebbia didn't feel like they were en route to the big time as they were taking "professional" photos of their first hosts' apartments. They were just trying to survive. But in retrospect that too was the optimal path to dominating a big market. How do you find users to recruit manually? If you build something to solve your own problems, then you only have to find your peers, which is usually straightforward.
Otherwise you'll have to make a more deliberate effort to locate the most promising vein of users. The usual way to do that is to get some initial set of users by doing a comparatively untargeted launch, and then to observe which kind seem most enthusiastic, and seek out more like them. For example, Ben Silbermann noticed that a lot of the earliest Pinterest users were interested in design, so he went to a conference of design bloggers to recruit users, and that worked well. [5] Delight You should take extraordinary measures not just to acquire users, but also to make them happy. For as long as they could (which turned out to be surprisingly long), Wufoo sent each new user a hand-written thank you note. Your first users should feel that signing up with you was one of the best choices they ever made. And you in turn should be racking your brains to think of new ways to delight them. Why do we have to teach startups this? Why is it counterintuitive for founders? Three reasons, I think. One is that a lot of startup founders are trained as engineers, and customer service is not part of the training of engineers. You're supposed to build things that are robust and elegant, not be slavishly attentive to individual users like some kind of salesperson. Ironically, part of the reason engineering is traditionally averse to handholding is that its traditions date from a time when engineers were less powerful — when they were only in charge of their narrow domain of building things, rather than running the whole show. You can be ornery when you're Scotty, but not when you're Kirk. Another reason founders don't focus enough on individual customers is that they worry it won't scale. But when founders of larval startups worry about this, I point out that in their current state they have nothing to lose. Maybe if they go out of their way to make existing users super happy, they'll one day have too many to do so much for.
That would be a great problem to have. See if you can make it happen. And incidentally, when it does, you'll find that delighting customers scales better than you expected. Partly because you can usually find ways to make anything scale more than you would have predicted, and partly because delighting customers will by then have permeated your culture. I have never once seen a startup lured down a blind alley by trying too hard to make their initial users happy. But perhaps the biggest thing preventing founders from realizing how attentive they could be to their users is that they've never experienced such attention themselves. Their standards for customer service have been set by the companies they've been customers of, which are mostly big ones. Tim Cook doesn't send you a hand-written note after you buy a laptop. He can't. But you can. That's one advantage of being small: you can provide a level of service no big company can. [6] Once you realize that existing conventions are not the upper bound on user experience, it's interesting in a very pleasant way to think about how far you could go to delight your users. Experience I was trying to think of a phrase to convey how extreme your attention to users should be, and I realized Steve Jobs had already done it: insanely great. Steve wasn't just using "insanely" as a synonym for "very." He meant it more literally — that one should focus on quality of execution to a degree that in everyday life would be considered pathological. All the most successful startups we've funded have, and that probably doesn't surprise would-be founders. What novice founders don't get is what insanely great translates to in a larval startup. When Steve Jobs started using that phrase, Apple was already an established company. He meant the Mac (and its documentation and even packaging — such is the nature of obsession) should be insanely well designed and manufactured.
That's not hard for engineers to grasp. It's just a more extreme version of designing a robust and elegant product. What founders have a hard time grasping (and Steve himself might have had a hard time grasping) is what insanely great morphs into as you roll the time slider back to the first couple months of a startup's life. It's not the product that should be insanely great, but the experience of being your user. The product is just one component of that. For a big company it's necessarily the dominant one. But you can and should give users an insanely great experience with an early, incomplete, buggy product, if you make up the difference with attentiveness. Can, perhaps, but should? Yes. Over-engaging with early users is not just a permissible technique for getting growth rolling. For most successful startups it's a necessary part of the feedback loop that makes the product good. Making a better mousetrap is not an atomic operation. Even if you start the way most successful startups have, by building something you yourself need, the first thing you build is never quite right. And except in domains with big penalties for making mistakes, it's often better not to aim for perfection initially. In software, especially, it usually works best to get something in front of users as soon as it has a quantum of utility, and then see what they do with it. Perfectionism is often an excuse for procrastination, and in any case your initial model of users is always inaccurate, even if you're one of them. [7] The feedback you get from engaging directly with your earliest users will be the best you ever get. When you're so big you have to resort to focus groups, you'll wish you could go over to your users' homes and offices and watch them use your stuff like you did when there were only a handful of them. Fire Sometimes the right unscalable trick is to focus on a deliberately narrow market.
It's like keeping a fire contained at first to get it really hot before adding more logs. That's what Facebook did. At first it was just for Harvard students. In that form it only had a potential market of a few thousand people, but because they felt it was really for them, a critical mass of them signed up. After Facebook stopped being for Harvard students, it remained for students at specific colleges for quite a while. When I interviewed Mark Zuckerberg at Startup School, he said that while it was a lot of work creating course lists for each school, doing that made students feel the site was their natural home. Any startup that could be described as a marketplace usually has to start in a subset of the market, but this can work for other startups as well. It's always worth asking if there's a subset of the market in which you can get a critical mass of users quickly. [8] Most startups that use the contained fire strategy do it unconsciously. They build something for themselves and their friends, who happen to be the early adopters, and only realize later that they could offer it to a broader market. The strategy works just as well if you do it unconsciously. The biggest danger of not being consciously aware of this pattern is for those who naively discard part of it. E.g. if you don't build something for yourself and your friends, or even if you do, but you come from the corporate world and your friends are not early adopters, you'll no longer have a perfect initial market handed to you on a platter. Among companies, the best early adopters are usually other startups. They're more open to new things both by nature and because, having just been started, they haven't made all their choices yet. Plus when they succeed they grow fast, and you with them.
It was one of many unforeseen advantages of the YC model (and specifically of making YC big) that B2B startups now have an instant market of hundreds of other startups ready at hand. Meraki For hardware startups there's a variant of doing things that don't scale that we call "pulling a Meraki." Although we didn't fund Meraki, the founders were Robert Morris's grad students, so we know their history. They got started by doing something that really doesn't scale: assembling their routers themselves. Hardware startups face an obstacle that software startups don't. The minimum order for a factory production run is usually several hundred thousand dollars. Which can put you in a catch-22: without a product you can't generate the growth you need to raise the money to manufacture your product. Back when hardware startups had to rely on investors for money, you had to be pretty convincing to overcome this. The arrival of crowdfunding (or more precisely, preorders) has helped a lot. But even so I'd advise startups to pull a Meraki initially if they can. That's what Pebble did. The Pebbles assembled the first several hundred watches themselves. If they hadn't gone through that phase, they probably wouldn't have sold $10 million worth of watches when they did go on Kickstarter. Like paying excessive attention to early customers, fabricating things yourself turns out to be valuable for hardware startups. You can tweak the design faster when you're the factory, and you learn things you'd never have known otherwise. Eric Migicovsky of Pebble said one of the things he learned was "how valuable it was to source good screws." Who knew? Consult Sometimes we advise founders of B2B startups to take over-engagement to an extreme, and to pick a single user and act as if they were consultants building something just for that one user.
The initial user serves as the form for your mold; keep tweaking till you fit their needs perfectly, and you'll usually find you've made something other users want too. Even if there aren't many of them, there are probably adjacent territories that have more. As long as you can find just one user who really needs something and can act on that need, you've got a toehold in making something people want, and that's as much as any startup needs initially. [9] Consulting is the canonical example of work that doesn't scale. But (like other ways of bestowing one's favors liberally) it's safe to do it so long as you're not being paid to. That's where companies cross the line. So long as you're a product company that's merely being extra attentive to a customer, they're very grateful even if you don't solve all their problems. But when they start paying you specifically for that attentiveness — when they start paying you by the hour — they expect you to do everything. Another consulting-like technique for recruiting initially lukewarm users is to use your software yourselves on their behalf. We did that at Viaweb. When we approached merchants asking if they wanted to use our software to make online stores, some said no, but they'd let us make one for them. Since we would do anything to get users, we did. We felt pretty lame at the time. Instead of organizing big strategic e-commerce partnerships, we were trying to sell luggage and pens and men's shirts. But in retrospect it was exactly the right thing to do, because it taught us how it would feel to merchants to use our software. Sometimes the feedback loop was near instantaneous: in the middle of building some merchant's site I'd find I needed a feature we didn't have, so I'd spend a couple hours implementing it and then resume building the site. Manual There's a more extreme variant where you don't just use your software, but are your software.
When you only have a small number of users, you can sometimes get away with doing by hand things that you plan to automate later. This lets you launch faster, and when you do finally automate yourself out of the loop, you'll know exactly what to build because you'll have muscle memory from doing it yourself. When manual components look to the user like software, this technique starts to have aspects of a practical joke. For example, the way Stripe delivered "instant" merchant accounts to its first users was that the founders manually signed them up for traditional merchant accounts behind the scenes. Some startups could be entirely manual at first. If you can find someone with a problem that needs solving and you can solve it manually, go ahead and do that for as long as you can, and then gradually automate the bottlenecks. It would be a little frightening to be solving users' problems in a way that wasn't yet automatic, but less frightening than the far more common case of having something automatic that doesn't yet solve anyone's problems. Big I should mention one sort of initial tactic that usually doesn't work: the Big Launch. I occasionally meet founders who seem to believe startups are projectiles rather than powered aircraft, and that they'll make it big if and only if they're launched with sufficient initial velocity. They want to launch simultaneously in 8 different publications, with embargoes. And on a tuesday, of course, since they read somewhere that's the optimum day to launch something. It's easy to see how little launches matter. Think of some successful startups. How many of their launches do you remember? All you need from a launch is some initial core of users. How well you're doing a few months later will depend more on how happy you made those users than how many there were of them. [10] So why do founders think launches matter? A combination of solipsism and laziness.
They think what they're building is so great that everyone who hears about it will immediately sign up. Plus it would be so much less work if you could get users merely by broadcasting your existence, rather than recruiting them one at a time. But even if what you're building really is great, getting users will always be a gradual process — partly because great things are usually also novel, but mainly because users have other things to think about. Partnerships too usually don't work. They don't work for startups in general, but they especially don't work as a way to get growth started. It's a common mistake among inexperienced founders to believe that a partnership with a big company will be their big break. Six months later they're all saying the same thing: that was way more work than we expected, and we ended up getting practically nothing out of it. [11] It's not enough just to do something extraordinary initially. You have to make an extraordinary _effort_ initially. Any strategy that omits the effort — whether it's expecting a big launch to get you users, or a big partner — is ipso facto suspect. Vector The need to do something unscalably laborious to get started is so nearly universal that it might be a good idea to stop thinking of startup ideas as scalars. Instead we should try thinking of them as pairs of what you're going to build, plus the unscalable thing(s) you're going to do initially to get the company going. It could be interesting to start viewing startup ideas this way, because now that there are two components you can try to be imaginative about the second as well as the first.
But in most cases the second component will be what it usually is — recruit users manually and give them an overwhelmingly good experience — and the main benefit of treating startups as vectors will be to remind founders they need to work hard in two dimensions. [12] In the best case, both components of the vector contribute to your company's DNA: the unscalable things you have to do to get started are not merely a necessary evil, but change the company permanently for the better. If you have to be aggressive about user acquisition when you're small, you'll probably still be aggressive when you're big. If you have to manufacture your own hardware, or use your software on users's behalf, you'll learn things you couldn't have learned otherwise. And most importantly, if you have to work hard to delight users when you only have a handful of them, you'll keep doing it when you have a lot. Notes [1] Actually Emerson never mentioned mousetraps specifically. He wrote "If a man has good corn or wood, or boards, or pigs, to sell, or can make better chairs or knives, crucibles or church organs, than anybody else, you will find a broad hard-beaten road to his house, though it be in the woods." [2] Thanks to Sam Altman for suggesting I make this explicit. And no, you can't avoid doing sales by hiring someone to do it for you. You have to do sales yourself initially. Later you can hire a real salesperson to replace you. [3] The reason this works is that as you get bigger, your size helps you grow. Patrick Collison wrote "At some point, there was a very noticeable change in how Stripe felt.
It tipped from being this boulder we had to push to being a train car that in fact had its own momentum." [4] One of the more subtle ways in which YC can help founders is by calibrating their ambitions, because we know exactly how a lot of successful startups looked when they were just getting started. [5] If you're building something for which you can't easily get a small set of users to observe — e.g. enterprise software — and in a domain where you have no connections, you'll have to rely on cold calls and introductions. But should you even be working on such an idea? [6] Garry Tan pointed out an interesting trap founders fall into in the beginning. They want so much to seem big that they imitate even the flaws of big companies, like indifference to individual users. This seems to them more "professional." Actually it's better to embrace the fact that you're small and use whatever advantages that brings. [7] Your user model almost couldn't be perfectly accurate, because users' needs often change in response to what you build for them. Build them a microcomputer, and suddenly they need to run spreadsheets on it, because the arrival of your new microcomputer causes someone to invent the spreadsheet. [8] If you have to choose between the subset that will sign up quickest and those that will pay the most, it's usually best to pick the former, because those are probably the early adopters. They'll have a better influence on your product, and they won't make you expend as much effort on sales. And though they have less money, you don't need that much to maintain your target growth rate early on. [9] Yes, I can imagine cases where you could end up making something that was really only useful for one user. But those are usually obvious, even to inexperienced founders.
So if it's not obvious you'd be making something for a market of one, don't worry about that danger. [10] There may even be an inverse correlation between launch magnitude and success. The only launches I remember are famous flops like the Segway and Google Wave. Wave is a particularly alarming example, because I think it was actually a great idea that was killed partly by its overdone launch. [11] Google grew big on the back of Yahoo, but that wasn't a partnership. Yahoo was their customer. [12] It will also remind founders that an idea where the second component is empty — an idea where there is nothing you can do to get going, e.g. because you have no way to find users to recruit manually — is probably a bad idea, at least for those founders. Thanks to Sam Altman, Paul Buchheit, Patrick Collison, Kevin Hale, Steven Levy, Jessica Livingston, Geoff Ralston, and Garry Tan for reading drafts of this.
Japanese Translation | Russian Translation French Translation | Arabic Translation Italian Translation | Korean Translation.
想创办一家创业公司? 获得 Y Combinator 的资助。
2013年7月 在Y Combinator,我们给出的一条最常见建议是:做那些无法规模化的事。许多潜在的创始人认为,创业公司要么一飞冲天,要么彻底失败。你打造一个产品,把它推向市场,如果它真的足够好,人们就会如约而至。否则,就说明市场根本不存在。[1] 实际上,创业公司的起飞是因为创始人让它们起飞。也许有少数公司能自行成长,但通常都需要某种推力才能启动。一个恰当的比喻是汽车引擎在电动启动器出现之前的手摇曲柄——一旦引擎运转起来,它就能持续运转,但需要一个独立且费力的过程来启动它。 招募用户 创业初期创始人最常做的不可规模化的事就是手动招募用户。几乎所有初创公司都必须这么做。你不能坐等用户上门,必须主动出击。 Stripe是我们资助过的最成功的创业公司之一,他们解决的问题非常紧迫。如果说有哪家公司可以坐等用户上门,那一定是Stripe。但事实上,他们在YC内部以早期激进获取用户而闻名。 为其他创业公司开发产品的初创公司,可以从我们资助过的其他公司中找到大量潜在用户,而Stripe是其中最善于利用这一点的。在YC,我们用"Collison安装"来称呼他们发明的技术。更胆怯的创始人会问:"你愿意试用我们的测试版吗?"如果对方同意,他们会说:"太好了,我们会给你发送链接。"但Collison兄弟不会等待。当有人同意试用Stripe时,他们会立刻说:"好的,把你的笔记本电脑给我",然后当场帮他们设置好。 创始人抗拒亲自招募用户有两个原因。一是害羞和懒惰的结合。他们宁愿坐在家里写代码,也不愿走出去与一群陌生人交谈并可能被大多数人拒绝。但要让创业公司成功,至少有一位创始人(通常是CEO)必须在销售和营销上花费大量时间。[2] 另一个原因是初始阶段的绝对数字看起来太小了。他们认为,那些著名的大公司肯定不是这样起步的。他们犯的错误是低估了复合增长的力量。我们鼓励每家初创公司以周增长率来衡量进展。如果你有100个用户,下周需要再获得10个才能实现10%的增长。虽然110看起来只比100多一点点,但如果你保持每周10%的增长,最终的数字会大得惊人。一年后你将拥有14,000名用户,两年后将达到200万。 当你能一次性获取上千用户时,方法会有所不同,增长最终也必然会放缓。但如果市场存在,你通常可以从手动招募用户开始,然后逐步转向更自动化的方法。[3] Airbnb就是这种策略的经典案例。市场类业务起步极为艰难,你必须做好初期采取极端措施的准备。对Airbnb来说,这些措施包括在纽约挨家挨户拜访,招募新用户并帮助现有用户优化房源。当我回忆YC时期的Airbnb团队时,脑海中浮现的是他们拖着滚轮行李箱的形象——因为每周二参加晚餐会时,他们总是刚从某个地方飞回来。 脆弱性 如今的Airbnb看似势不可挡,但早期它非常脆弱,大约30天的亲自用户互动决定了它的成败。 这种初始脆弱性并非Airbnb独有。几乎所有初创公司在初期都很脆弱。而缺乏经验的创始人、投资者(以及论坛上的记者和万事通)最容易犯的错误之一,就是无意识地用成熟公司的标准来评判初创公司。这就像看着一个新生儿断言"这个小东西永远不可能有所成就"。 如果记者和万事通们轻视你的创业公司,这无伤大雅——他们总是看错。即使投资者不看好也没关系,当他们看到增长时就会改变主意。真正的危险是你自己轻视自己的创业公司。我见过这种情况。我经常需要鼓励那些没有完全认识到自己项目潜力的创始人。就连比尔·盖茨也犯过这个错误——在创立微软后,他仍返回哈佛继续秋季学期。虽然他没有待太久,但如果他当时意识到微软能有后来的规模,他根本不会回去。[4] 评估早期创业公司时,问题不该是"这家公司能征服世界吗?",而应是"如果创始人做对了每件事,这家公司能有多大?"而这些"正确的事"在当时往往看起来既费力又微不足道。当微软还只是阿尔伯克基的几个家伙为几千名爱好者(当时这么称呼)编写Basic解释器时,它并不起眼。但回过头看,这正是称霸微机软件的最佳路径。我也知道Brian Chesky和Joe Gebbia在为他们第一批房东的公寓拍摄"专业"照片时,并不觉得自己在通往成功的路上——他们只是为了生存。但事后证明,这也是占领大市场的最佳路径。 如何找到需要手动招募的用户?如果你为解决自己的问题而开发产品,那么只需找到与你类似的人,这通常很简单。否则,你就需要有意识地寻找最有潜力的用户群体。通常的做法是:通过相对宽泛的发布获得初始用户,观察哪类用户最热情,然后寻找更多类似用户。例如,Ben Silbermann注意到Pinterest最早期的用户很多对设计感兴趣,于是他去参加设计博主会议招募用户,效果很好。[5] 极致体验 你不仅需要采取非常手段获取用户,还要让他们感到惊喜。Wufoo在尽可能长的时间内(结果证明这个时间出乎意料地长)坚持给每位新用户手写感谢信。你的首批用户应该觉得选择你是他们做过的最佳决定之一。相应地,你也应该绞尽脑汁想出让他们惊喜的新方法。 为什么我们需要教创业者这些?为什么这对创始人来说不直观?我认为有三个原因。 一是许多创业创始人接受的是工程师训练,而客户服务不在工程师的培养范围内。工程师被要求打造健壮优雅的产品,而不是像销售员那样卑躬屈膝地关注个体用户。具有讽刺意味的是,工程传统上排斥"手把手指导"的部分原因在于,这些传统形成于工程师权力较小的时代——当时他们只负责产品构建这一狭窄领域,而非全局。当你是"斯科特"(《星际迷航》中的工程师角色)时可以脾气古怪,但如果你是"柯克"船长就不行。 另一个原因是创始人担心这种做法无法规模化。但当早期创业者担心这点时,我会指出他们现阶段没什么可失去的。也许当他们竭尽全力让现有用户超级满意时,终有一天用户会多到无法继续这种服务——那将是个幸福的烦恼。看看你能否实现它。顺便说一句,当那一天到来时,你会发现取悦客户的规模化能力比你预期的强——部分是因为你总能找到超出预期的规模化方法,部分是因为那时取悦客户已成为你们的文化。 我从未见过哪家创业公司因为过于努力取悦早期用户而误入歧途。 但或许阻碍创始人认识到他们可以对用户有多关注的最大因素是,他们自己从未体验过这种关注。他们的客户服务标准来自那些他们作为客户接触过的大公司。蒂姆·库克不会在你购买笔记本后给你手写便条——他做不到。但你可以。这就是小公司的优势:你能提供大公司无法企及的服务水平。[6] 一旦你意识到现有惯例并非用户体验的上限,思考你能走多远来取悦用户就会变成一件非常愉快的事。 极致标准 我试图想出一个短语来描述对用户应有的极致关注,然后意识到史蒂夫·乔布斯已经创造了这个词——"insanely great"(疯狂般伟大)。乔布斯使用"疯狂"一词不仅是"非常"的同义词,而是更字面的意思——对执行质量的专注应达到在日常生活中会被视为偏执的程度。 我们资助的所有最成功的创业公司都做到了这点,这或许不会让潜在创始人感到意外。新手创始人不懂的是,在创业初期,"疯狂般伟大"意味着什么。当乔布斯开始使用这个短语时,苹果已是成熟公司。他指的是Mac(及其文档甚至包装——这就是痴迷的本质)应该拥有极致的设计与制造质量。这对工程师来说不难理解,它只是"设计健壮优雅产品"的更极端版本。 创始人难以理解的是(或许乔布斯本人也曾难以理解),当把时间轴拨回创业最初几个月时,"疯狂般伟大"会转变成什么。那时需要极致的不应是产品,而是用户的使用体验。产品只是其中的一部分。对大公司来说,产品必然是主导因素。但你可以也应该通过极度关注,即使用早期不完善、有缺陷的产品,也能为用户提供极致体验。 能做到,但应该做吗?是的。过度投入早期用户不仅是推动增长的可取手段,对多数成功创业公司而言,它更是打磨产品的必要反馈循环。"打造更好的捕鼠器"不是一蹴而就的事。即使你像多数成功创业公司那样,从解决自身需求开始,最初打造的产品也永远不会完美。除非在容错率极低的领域,否则初期追求完美往往适得其反。特别是在软件行业,最有效的方式通常是:一旦产品具备基本功能就立即让用户使用,然后观察他们的使用方式。完美主义常常是拖延的借口,而且即.
June 2013 _(This talk was written for an audience of investors.)_ Y Combinator has now funded 564 startups including the current batch, which has 53. The total valuation of the 287 that have valuations (either by raising an equity round, getting acquired, or dying) is about $11.7 billion, and the 511 prior to the current batch have collectively raised about $1.7 billion. [1] As usual those numbers are dominated by a few big winners. The top 10 startups account for 8.6 of that 11.7 billion. But there is a peloton of younger startups behind them. There are about 40 more that have a shot at being really big. Things got a little out of hand last summer when we had 84 companies in the batch, so we tightened up our filter to decrease the batch size. [2] Several journalists have tried to interpret that as evidence for some macro story they were telling, but the reason had nothing to do with any external trend. The reason was that we discovered we were using an n² algorithm, and we needed to buy time to fix it. Fortunately we've come up with several techniques for sharding YC, and the problem now seems to be fixed. With a new more scaleable model and only 53 companies, the current batch feels like a walk in the park. I'd guess we can grow another 2 or 3x before hitting the next bottleneck. [3] One consequence of funding such a large number of startups is that we see trends early. And since fundraising is one of the main things we help startups with, we're in a good position to notice trends in investing. I'm going to take a shot at describing where these trends are leading. Let's start with the most basic question: will the future be better or worse than the past? Will investors, in the aggregate, make more money or less? I think more. There are multiple forces at work, some of which will decrease returns, and some of which will increase them.
(本文演讲面向投资者群体。)
Y Combinator目前已资助564家初创企业,包括当前批次的53家。在287家已估值的企业中(通过股权融资、被收购或倒闭),总估值约为117亿美元;而当前批次之前的511家企业共筹集约17亿美元。[1]
这些数字依然由少数明星项目主导。估值前十的企业占据了117亿中的86亿。但后方还有一批年轻企业紧随其后——约40家具备成为巨头的潜力。
去年夏季情况一度失控,我们单批资助了84家公司,因此收紧了筛选标准以缩减规模。[2] 尽管有媒体试图将此解读为某种宏观趋势的佐证,但实际原因与外部环境无关——我们发现自己采用了n²算法,需要争取时间修复。幸运的是,我们已开发出多项分片技术,问题现已解决。采用可扩展的新模式后,当前53家公司的批次如同闲庭信步。预计在遇到下一个瓶颈前,我们还能扩容2-3倍。[3]
资助如此大量初创企业的附带好处是能提前洞察趋势。鉴于融资辅导是我们的核心工作之一,我们得以敏锐捕捉投资领域的动向。
I can't predict for sure which forces will prevail, but I'll describe them and you can decide for yourself. There are two big forces driving change in startup funding: it's becoming cheaper to start a startup, and startups are becoming a more normal thing to do. When I graduated from college in 1986, there were essentially two options: get a job or go to grad school. Now there's a third: start your own company. That's a big change. In principle it was possible to start your own company in 1986 too, but it didn't seem like a real possibility. It seemed possible to start a consulting company, or a niche product company, but it didn't seem possible to start a company that would become big. [4] That kind of change, from 2 paths to 3, is the sort of big social shift that only happens once every few generations. I think we're still at the beginning of this one. It's hard to predict how big a deal it will be. As big a deal as the Industrial Revolution? Maybe. Probably not. But it will be a big enough deal that it takes almost everyone by surprise, because those big social shifts always do. One thing we can say for sure is that there will be a lot more startups. The monolithic, hierarchical companies of the mid 20th century are being replaced by networks of smaller companies. This process is not just something happening now in Silicon Valley. It started decades ago, and it's happening as far afield as the car industry. It has a long way to run. [5] The other big driver of change is that startups are becoming cheaper to start. And in fact the two forces are related: the decreasing cost of starting a startup is one of the reasons startups are becoming a more normal thing to do. The fact that startups need less money means founders will increasingly have the upper hand over investors. You still need just as much of their energy and imagination, but they don't need as much of your money.
我将尝试解读这些趋势的走向。首先回答最根本的问题:未来会优于还是劣于过去?投资者的整体收益将增加还是减少?
我认为会更好。多重力量正在博弈:有些会降低回报,有些则会提升。虽无法断言哪方将胜出,但我会逐一分析供您判断。
初创企业融资正经历两大变革驱动力:创业成本持续降低,创业行为日益常态化。
1986年我大学毕业时,人生选项本质上只有两个:就业或读研。如今出现了第三条路——创办公司。这是划时代的转变。理论上1986年也能创业,但当时人们认为至多成立咨询公司或小众产品公司,难以想象能打造巨头企业。[4]
这种从二元选择到三元路径的社会变革,往往数代人才能遭遇一次。我认为我们仍处在这轮变革的初期,其最终影响规模尚难估量。堪比工业革命?或许不及,但足以让绝大多数人措手不及——重大社会转型向来如此。
Because founders have the upper hand, they'll retain an increasingly large share of the stock in, and control of, their companies. Which means investors will get less stock and less control. Does that mean investors will make less money? Not necessarily, because there will be more good startups. The total amount of desirable startup stock available to investors will probably increase, because the number of desirable startups will probably grow faster than the percentage they sell to investors shrinks. There's a rule of thumb in the VC business that there are about 15 companies a year that will be really successful. Although a lot of investors unconsciously treat this number as if it were some sort of cosmological constant, I'm certain it isn't. There are probably limits on the rate at which technology can develop, but that's not the limiting factor now. If it were, each successful startup would be founded the month it became possible, and that is not the case. Right now the limiting factor on the number of big hits is the number of sufficiently good founders starting companies, and that number can and will increase. There are still a lot of people who'd make great founders who never end up starting a company. You can see that from how randomly some of the most successful startups got started. So many of the biggest startups almost didn't happen that there must be a lot of equally good startups that actually didn't happen. There might be 10x or even 50x more good founders out there. As more of them go ahead and start startups, those 15 big hits a year could easily become 50 or even 100. [6] What about returns, though? Are we heading for a world in which returns will be pinched by increasingly high valuations? I think the top firms will actually make more money than they have in the past. High returns don't come from investing at low valuations. They come from investing in the companies that do really well.
可以确定的是,未来会出现更多初创企业。20世纪中叶的巨型科层制企业正被网状结构的小型企业取代。这一进程不仅发生在硅谷,数十年前便已启动,甚至蔓延至汽车行业等传统领域,且仍有长远发展空间。[5]
另一大驱动力是创业成本下降。事实上两者互为因果:成本降低正是创业常态化的原因之一。
资金需求的减少意味着创始人将逐渐掌握主导权。他们依然需要同等程度的精力与想象力,但对投资者资金的依赖度降低。因此创始人将保留更多股权和公司控制权,投资者获得的份额和话语权则相应减少。
这是否意味着投资者收益缩水?未必。因为优质项目数量在增加,投资者可获得的高价值初创企业股权总额很可能增长——优质企业的增速可能快于让渡给投资者的股权比例降幅。
风投行业有个经验法则:每年仅有约15家企业能取得真正成功。尽管许多投资者潜意识将其视为宇宙常数,但我确信这绝非定数。技术发展速率或许存在上限,但当前限制因素并非技术——否则每个成功企业都该在其技术成熟当月成立,事实显然并非如此。现阶段真正的制约因素是优秀创始人的数量,而这个数字完全能够持续增长。仍有大量具备创始人潜质者未曾创业,从那些偶然诞生的明星企业就可见一斑——许多巨头企业当初险些未能成立,意味着同等量级的机遇必然大量流失。
So if there are more of those to be had each year, the best pickers should have more hits. This means there should be more variability in the VC business. The firms that can recognize and attract the best startups will do even better, because there will be more of them to recognize and attract. Whereas the bad firms will get the leftovers, as they do now, and yet pay a higher price for them. Nor do I think it will be a problem that founders keep control of their companies for longer. The empirical evidence on that is already clear: investors make more money as founders' bitches than their bosses. Though somewhat humiliating, this is actually good news for investors, because it takes less time to serve founders than to micromanage them. What about angels? I think there is a lot of opportunity there. It used to suck to be an angel investor. You couldn't get access to the best deals, unless you got lucky like Andy Bechtolsheim, and when you did invest in a startup, VCs might try to strip you of your stock when they arrived later. Now an angel can go to something like Demo Day or AngelList and have access to the same deals VCs do. And the days when VCs could wash angels out of the cap table are long gone. I think one of the biggest unexploited opportunities in startup investing right now is angel-sized investments made quickly. Few investors understand the cost that raising money from them imposes on startups. When the company consists only of the founders, everything grinds to a halt during fundraising, which can easily take 6 weeks. The current high cost of fundraising means there is room for low-cost investors to undercut the rest. And in this context, low-cost means deciding quickly. If there were a reputable investor who invested $100k on good terms and promised to decide yes or no within 24 hours, they'd get access to almost all the best deals, because every good startup would approach them first.
潜在优秀创始人数量可能还有10倍甚至50倍的增长空间。随着更多人投身创业,每年15个明星项目完全可能增至50甚至100个。[6]
那么投资回报呢?会因估值持续走高而受挤压吗?我认为顶级机构实际收益将超越历史水平。高回报不源于低估值投资,而源于押中真正卓越的企业。因此若每年优质项目增加,最慧眼识珠者将收获更多成功案例。
这意味着风投行业分化将加剧:善于识别和吸引顶尖项目的机构表现会更优异,因为可选标的增多了;而平庸机构仍只能捡漏,却需支付更高对价。
创始人长期掌权也非坏事。实证数据已很清晰:投资者甘当创始人"副手"时的收益,远高于试图充当"老板"。虽略显尴尬,但这实际利好投资者——服务创始人远比微观管理省时省力。
天使投资领域呢?我认为存在巨大机遇。过去天使投资体验极差:难以接触顶级项目(除非像Andy Bechtolsheim般幸运),且投入后还可能被后续进入的风投剥夺股权。如今通过Demo Day或AngelList等平台,天使已能与风投获得同等机会,而风投清洗天使股权的时代早已终结。
It would be up to them to pick, because every bad startup would approach them first too, but at least they'd see everything. Whereas if an investor is notorious for taking a long time to make up their mind or negotiating a lot about valuation, founders will save them for last. And in the case of the most promising startups, which tend to have an easy time raising money, last can easily become never. Will the number of big hits grow linearly with the total number of new startups? Probably not, for two reasons. One is that the scariness of starting a startup in the old days was a pretty effective filter. Now that the cost of failing is becoming lower, we should expect founders to do it more. That's not a bad thing. It's common in technology for an innovation that decreases the cost of failure to increase the number of failures and yet leave you net ahead. The other reason the number of big hits won't grow proportionately to the number of startups is that there will start to be an increasing number of idea clashes. Although the finiteness of the number of good ideas is not the reason there are only 15 big hits a year, the number has to be finite, and the more startups there are, the more we'll see multiple companies doing the same thing at the same time. It will be interesting, in a bad way, if idea clashes become a lot more common. [7] Mostly because of the increasing number of early failures, the startup business of the future won't simply be the same shape, scaled up. What used to be an obelisk will become a pyramid. It will be a little wider at the top, but a lot wider at the bottom. What does that mean for investors? One thing it means is that there will be more opportunities for investors at the earliest stage, because that's where the volume of our imaginary solid is growing fastest. Imagine the obelisk of investors that corresponds to the obelisk of startups.
当前最未被充分利用的机遇在于快速完成天使级投资。鲜有投资者理解融资过程对初创企业的隐性成本。当公司只有创始人时,融资会让一切停摆,动辄耗时六周。当前高企的融资成本意味着"低成本"投资者有颠覆空间——这里的"低成本"即快速决策。若有声誉良好的投资者愿以10万美元标准条款投资,并承诺24小时内决策,他们将获得几乎所有顶级项目,因为每家优秀企业都会优先接洽。当然筛选责任全在其身(劣质项目同样会蜂拥而至),但至少能一览全貌。反之,若投资者以拖延决策或估值纠缠闻名,创始人只会将其列为最后选项。而对最具潜力的企业(它们融资通常很轻松),"最后"往往意味着"永不"。
明星项目数量会与初创企业总量线性增长吗?可能不会,原因有二:其一,昔日创业的高风险本是天然过滤器。随着失败成本降低,尝试者必然增多。这并非坏事——技术创新常通过降低失败成本来增加尝试次数,最终实现净收益提升。
其二,创意冲突将日益频繁。虽然优秀创意有限并非每年仅15个明星项目的主因,但创意总量终归有限。随着创业者增多,同质化竞争必然加剧。若创意冲突显著增多,将带来消极影响——那可能改变初创企业的本质。[7]
主要由于早期失败案例激增,未来创业版图不会简单放大,而将从"方尖碑"变为"金字塔"——顶部略宽,底部急剧扩张。
这对投资者意味着什么?早期阶段机会将大量涌现,因为想象中实体增长最快的部分正在此处。设想与创业方尖碑对应的投资方尖碑:当它扩展为金字塔与创业生态匹配时,所有内容物都向顶部聚集,底部形成真空。
As it widens out into a pyramid to match the startup pyramid, all the contents are adhering to the top, leaving a vacuum at the bottom. That opportunity for investors mostly means an opportunity for new investors, because the degree of risk an existing investor or firm is comfortable taking is one of the hardest things for them to change. Different types of investors are adapted to different degrees of risk, but each has its specific degree of risk deeply imprinted on it, not just in the procedures they follow but in the personalities of the people who work there. I think the biggest danger for VCs, and also the biggest opportunity, is at the series A stage. Or rather, what used to be the series A stage before series As turned into de facto series B rounds. Right now, VCs often knowingly invest too much money at the series A stage. They do it because they feel they need to get a big chunk of each series A company to compensate for the opportunity cost of the board seat it consumes. Which means when there is a lot of competition for a deal, the number that moves is the valuation (and thus amount invested) rather than the percentage of the company being sold. Which means, especially in the case of more promising startups, that series A investors often make companies take more money than they want. Some VCs lie and claim the company really needs that much. Others are more candid, and admit their financial models require them to own a certain percentage of each company. But we all know the amounts being raised in series A rounds are not determined by asking what would be best for the companies. They're determined by VCs starting from the amount of the company they want to own, and the market setting the valuation and thus the amount invested. Like a lot of bad things, this didn't happen intentionally. The VC business backed into it as their initial assumptions gradually became obsolete.
这主要是新投资者的机遇,因为既有机构的风险偏好极难改变。不同类型投资者适应不同风险等级,但每个机构的风险阈值不仅体现在流程中,更深刻烙印在团队基因里。
我认为风投面临的最大危险与机遇并存于A轮阶段——或者说,在A轮演变为事实上的B轮之前的那个阶段。
当前风投常刻意在A轮过度投资。因为他们觉得必须获取大额股权,以补偿董事会席位消耗的机会成本。这导致在项目争夺战中,变动的是估值(及投资额)而非出让股权比例。尤其对优质项目,A轮投资者常迫使企业接受超需资金。
有些风投谎称企业确实需要这笔钱,有些则坦承其财务模型要求必须持股特定比例。但众所周知,A轮融资额绝非基于企业最优需求,而是风投从期望持股比例出发,由市场决定估值及投资额。
如同许多弊端,这非刻意为之。风投行业陷入此局,源于初始假设逐渐过时。传统风投模式形成于创始人更依赖投资者的年代,当时A轮出让大额股权理所当然。如今创始人倾向保留更多股份,风投却固守陈规,因不确定持股低于20%能否盈利。
The traditions and financial models of the VC business were established when founders needed investors more. In those days it was natural for founders to sell VCs a big chunk of their company in the series A round. Now founders would prefer to sell less, and VCs are digging in their heels because they're not sure if they can make money buying less than 20% of each series A company. The reason I describe this as a danger is that series A investors are increasingly at odds with the startups they supposedly serve, and that tends to come back to bite you eventually. The reason I describe it as an opportunity is that there is now a lot of potential energy built up, as the market has moved away from VCs' traditional business model. Which means the first VC to break ranks and start to do series A rounds for as much equity as founders want to sell (and with no "option pool" that comes only from the founders' shares) stands to reap huge benefits. What will happen to the VC business when that happens? Hell if I know. But I bet that particular firm will end up ahead. If one top-tier VC firm started to do series A rounds that started from the amount the company needed to raise and let the percentage acquired vary with the market, instead of the other way around, they'd instantly get almost all the best startups. And that's where the money is. You can't fight market forces forever. Over the last decade we've seen the percentage of the company sold in series A rounds creep inexorably downward. 40% used to be common. Now VCs are fighting to hold the line at 20%. But I am daily waiting for the line to collapse. It's going to happen. You may as well anticipate it, and look bold. Who knows, maybe VCs will make more money by doing the right thing. It wouldn't be the first time that happened. Venture capital is a business where occasional big successes generate hundredfold returns.
我称之为"危险",是因为A轮投资者与所投企业日益对立,终将反噬自身;称之为"机遇",则因市场已偏离传统风投模式,积蓄了大量势能。首个打破常规、按创始人意愿确定A轮股权比例(且不要求创始人单独预留期权池)的机构,将收获巨大红利。
这对风投行业意味着什么?天晓得。但我打赌那家机构必将领先。若顶级风投以企业需求为融资起点,让股权比例随市场波动(而非相反),他们将立即囊括几乎所有顶尖项目——而那里才是金矿所在。
市场力量终不可抗。过去十年,A轮出让股权比例已不可逆地持续下降:从常见的40%到风投死守的20%防线。我每天都在等待防线崩塌。这必将发生,不如主动拥抱以显魄力。
谁知道呢?或许风投做正确的事反而更赚钱。这并非没有先例。风险投资本就是偶发巨大成功创造百倍回报的行业。对此类业务,财务模型又能有多少可信度?只要重大成功案例出现频率微升,就足以抵消A轮持股减半的影响。
寻找投资新机遇,请关注创始人的抱怨。他们是你们的客户,其不满即未满足的需求。我已列举两大痛点——决策拖沓的投资者与A轮过度稀释——这些是当前的淘金地。但通用法则是:做创始人需要的事。
How much confidence can you really have in financial models for something like that anyway? The big successes only have to get a tiny bit less occasional to compensate for a 2x decrease in the stock sold in series A rounds. If you want to find new opportunities for investing, look for things founders complain about. Founders are your customers, and the things they complain about are unsatisfied demand. I've given two examples of things founders complain about most—investors who take too long to make up their minds, and excessive dilution in series A rounds—so those are good places to look now. But the more general recipe is: do something founders want. Notes [1] I realize revenue and not fundraising is the proper test of success for a startup. The reason we quote statistics about fundraising is because those are the numbers we have. We couldn't talk meaningfully about revenues without including the numbers from the most successful startups, and we don't have those. We often discuss revenue growth with the earlier stage startups, because that's how we gauge their progress, but when companies reach a certain size it gets presumptuous for a seed investor to do that. In any case, companies' market caps do eventually become a function of revenues, and post-money valuations of funding rounds are at least guesses by pros about where those market caps will end up. The reason only 287 have valuations is that the rest have mostly raised money on convertible notes, and although convertible notes often have valuation caps, a valuation cap is merely an upper bound on a valuation. [2] We didn't try to accept a particular number. We have no way of doing that even if we wanted to. We just tried to be significantly pickier. [3] Though you never know with bottlenecks, I'm guessing the next one will be coordinating efforts among partners. [4] I realize starting a company doesn't have to mean starting a startup.
[1] 我们明白衡量初创企业成功的标准应是营收而非融资。引用融资数据只因这是现成指标。要讨论营收就必须包含最成功企业的数据,而这我们无法获取。我们常与早期企业讨论营收增长(这是评估进展的方式),但对达到一定规模的企业,种子投资者这样做就显冒昧。
企业市值终将反映营收,而融资轮次的后估值至少是专业人士对最终市值的预测。
287家已估值企业之外的其他公司多通过可转债融资。虽然可转债常附估值上限,但上限仅代表估值上限。
[2] 我们并非刻意控制数量(即便想也做不到),只是显著提高了筛选标准。
[3] 虽难预判瓶颈,我猜测下一瓶颈将是合伙人间的协作效率。
There will be lots of people starting normal companies too. But that's not relevant to an audience of investors. Geoff Ralston reports that in Silicon Valley it seemed thinkable to start a startup in the mid 1980s. It would have started there. But I know it didn't to undergraduates on the East Coast. [5] This trend is one of the main causes of the increase in economic inequality in the US since the mid twentieth century. The person who would in 1950 have been the general manager of the x division of Megacorp is now the founder of the x company, and owns significant equity in it. [6] If Congress passes the founder visa in a non-broken form, that alone could in principle get us up to 20x, since 95% of the world's population lives outside the US. [7] If idea clashes got bad enough, it could change what it means to be a startup. We currently advise startups mostly to ignore competitors. We tell them startups are competitive like running, not like soccer; you don't have to go and steal the ball away from the other team. But if idea clashes became common enough, maybe you'd start to have to. That would be unfortunate. Thanks to Sam Altman, Paul Buchheit, Dalton Caldwell, Patrick Collison, Jessica Livingston, Andrew Mason, Geoff Ralston, and Garry Tan for reading drafts of this..
[4] 我明白创业未必是创办初创企业。也会有大量普通公司诞生,但这与投资者听众无关。
Geoff Ralston指出1980年代中期硅谷已有创业氛围,但东海岸大学生显然无此认知。
[5] 该趋势是20世纪中叶以来美国经济不平等加剧的主因之一。1950年担任Megacorp公司X事业部总经理的人,如今是X公司创始人并持有可观股权。
[6] 若国会通过未被阉割的创始人签证,理论上可带来20倍增长,因全球95%人口居住在美国境外。
[7] 若创意冲突恶化到某种程度,可能重塑初创企业定义。我们目前建议企业基本忽略竞争对手,将创业视为赛跑而非足球比赛——无需从对手脚下抢球。但若冲突足够频繁,或许不得不改变策略,那将令人遗憾。
致谢 Sam Altman、Paul Buchheit、Dalton Caldwell、Patrick Collison、Jessica Livingston、Andrew Mason、Geoff Ralston和Garry Tan审阅了本文草稿。
Want to start a startup? Get funded by Y Combinator.
November 2012 The way to get startup ideas is not to try to think of startup ideas. It's to look for problems, preferably problems you have yourself. The very best startup ideas tend to have three things in common: they're something the founders themselves want, that they themselves can build, and that few others realize are worth doing. Microsoft, Apple, Yahoo, Google, and Facebook all began this way. Problems Why is it so important to work on a problem you have? Among other things, it ensures the problem really exists. It sounds obvious to say you should only work on problems that exist. And yet by far the most common mistake startups make is to solve problems no one has. I made it myself. In 1995 I started a company to put art galleries online. But galleries didn't want to be online. It's not how the art business works. So why did I spend 6 months working on this stupid idea? Because I didn't pay attention to users. I invented a model of the world that didn't correspond to reality, and worked from that. I didn't notice my model was wrong until I tried to convince users to pay for what we'd built. Even then I took embarrassingly long to catch on. I was attached to my model of the world, and I'd spent a lot of time on the software. They had to want it! Why do so many founders build things no one wants? Because they begin by trying to think of startup ideas. That m.o. is doubly dangerous: it doesn't merely yield few good ideas; it yields bad ideas that sound plausible enough to fool you into working on them. At YC we call these "made-up" or "sitcom" startup ideas. Imagine one of the characters on a TV show was starting a startup. The writers would have to invent something for it to do. But coming up with good startup ideas is hard. It's not something you can do for the asking.
想创立一家创业公司? 获得 Y Combinator 的资助。
2012年11月 获得创业想法的方式不是试图去思考创业想法,而是去寻找问题,最好是你自己遇到的问题。 最优秀的创业想法往往具备三个共同点:它们是创始人自己想要的东西,他们自己能够构建的东西,以及很少有人意识到值得去做的东西。微软、苹果、雅虎、谷歌和Facebook都是这样开始的。 问题 为什么解决你自己遇到的问题如此重要?其中一个原因是它能确保问题确实存在。听起来显而易见的是,你应该只解决确实存在的问题。然而,迄今为止创业公司最常见的错误是解决没有人遇到的问题。 我自己也犯过这个错误。1995年,我创办了一家公司,试图将艺术画廊搬到线上。但画廊并不想上线,这不是艺术行业的运作方式。那么,为什么我会花6个月时间在这个愚蠢的想法上?因为我没有关注用户。我发明了一个与现实不符的世界模型,并基于这个模型工作。直到我试图说服用户为我们的产品付费时,我才注意到我的模型是错误的。即便如此,我还是花了令人尴尬的长时间才醒悟过来。我执着于我的世界模型,并且花了很多时间在软件上。他们应该会想要它! 为什么这么多创始人会构建没有人想要的东西?因为他们一开始就试图思考创业想法。这种做法是双重危险的:它不仅很少产生好的想法,还会产生听起来足够合理但实际上很糟糕的想法,从而诱使你投入工作。 在YC,我们称这些为“编造”或“情景喜剧”式的创业想法。想象一下,如果电视剧中的一个角色要创业,编剧们必须为它编造一个业务。但想出好的创业想法很难,这不是随便就能做到的。因此(除非他们运气极好),编剧们会想出一个听起来合理但实际上很糟糕的想法。 例如,一个面向宠物主人的社交网络。这听起来并不明显错误。数百万人拥有宠物,他们通常非常关心自己的宠物并为之花费大量金钱。肯定会有许多人想要一个可以与其他宠物主人交流的网站。也许不是所有人,但只要有2%或3%的人成为常客,你就能拥有数百万用户。你可以为他们提供定向广告,甚至可能通过高级功能收费。[1] 这种想法的危险在于,当你向养宠物的朋友提出时,他们不会说“我绝不会用这个”,而是会说“嗯,也许我会用类似的东西。”即使创业公司上线后,很多人也会觉得它听起来合理。他们自己并不想用,至少现在不想,但他们能想象其他人会想要。将这种反应汇总到整个人群中,结果就是零用户。[2] 深井 当一家创业公司上线时,必须至少有一些用户真的需要他们正在做的东西——不仅仅是那些某天可能会用的人,而是那些迫切需要它的人。通常,这个初始用户群体很小,原因很简单:如果存在某种大量人迫切需要且可以通过创业公司通常投入的精力构建的东西,它可能已经存在了。这意味着你必须在某个维度上妥协:你可以构建一种大量人稍微需要的东西,或者一种少数人非常需要的东西。选择后者。并非所有这类想法都是好的创业想法,但几乎所有好的创业想法都属于这种类型。 想象一个图表,x轴代表所有可能对你产品感兴趣的人,y轴代表他们的需求程度。如果你将y轴的刻度反转,可以将公司想象成坑洞。谷歌是一个巨大的陨石坑:数亿人使用它,且非常需要它。一家刚起步的创业公司不可能期望挖掘出如此大的规模。因此,关于初始坑洞的形状,你有两种选择:你可以挖一个宽而浅的坑,或者一个窄而深的坑,就像一口井。 编造的创业想法通常是第一种类型。许多人对宠物主人的社交网络有轻微兴趣。 几乎所有好的创业想法都属于第二种类型。微软在开发Altair Basic时就是一口井。当时只有几千名Altair用户,但没有这款软件,他们只能用机器语言编程。三十年后,Facebook也有同样的形状。他们的第一个网站仅限于哈佛学生,人数只有几千,但这些用户非常需要它。 当你有一个创业想法时,问问自己:谁现在就需要这个?谁会如此需要它,以至于即使是一个由两人创业团队开发的糟糕初版,他们也会使用?如果你无法回答这个问题,这个想法可能是糟糕的。[3] 你并不需要井的狭窄本身。你需要的是深度;狭窄是优化深度(和速度)的副产品。但你几乎总能得到它。实际上,深度与狭窄之间的联系非常紧密,因此当你发现一个想法会强烈吸引特定群体或用户类型时,这是一个好迹象。 然而,虽然井状的需求几乎是好创业想法的必要条件,但它并不是充分条件。如果马克·扎克伯格构建的东西只能吸引哈佛学生,那它就不会是一个好的创业想法。Facebook之所以是一个好想法,是因为它从一个可以通过快速路径扩展的小市场开始。大学足够相似,如果你在哈佛构建了一个可行的Facebook,它就能在任何大学运行。因此,你可以迅速扩展到所有大学。一旦你拥有了所有大学生,只需向其他人开放,就能获得所有用户。 微软也是如此:Altair的Basic;其他机器的Basic;除Basic外的其他语言;操作系统;应用程序;IPO。 自我 如何判断一个想法是否有扩展路径?如何判断它是巨头的萌芽,还是只是一个利基产品?通常你无法判断。Airbnb的创始人最初并未意识到他们触及的市场有多大。起初,他们的想法要狭窄得多:他们打算让房东在会议期间出租地板上的空间。他们并未预见到这一想法的扩展;它是逐渐强加给他们的。他们最初只知道他们发现了某些东西。比尔·盖茨或马克·扎克伯格最初可能也只知道这么多。 偶尔,从一开始就能明显看出初始利基是否有扩展路径。有时我能看到一条并不立即显而易见的路径;这是YC的专长之一。但无论你多么有经验,这种判断的能力都是有限的。关于初始想法的扩展路径,最重要的是要理解一个元事实:这些路径很难看清。 因此,如果你无法预测一个想法是否有扩展路径,如何在想法之间做选择?真相既令人失望又有趣:如果你是合适的人,你会有合适的直觉。如果你处于一个快速变化的领域的前沿,当你直觉某件事值得做时,你更可能是对的。 在《禅与摩托车维修艺术》中,罗伯特·波西格写道:.
你想知道如何画出一幅完美的画吗?很简单。先让自己变得完美,然后自然地去画。
So (unless they got amazingly lucky) the writers would come up with an idea that sounded plausible, but was actually bad. For example, a social network for pet owners. It doesn't sound obviously mistaken. Millions of people have pets. Often they care a lot about their pets and spend a lot of money on them. Surely many of these people would like a site where they could talk to other pet owners. Not all of them perhaps, but if just 2 or 3 percent were regular visitors, you could have millions of users. You could serve them targeted offers, and maybe charge for premium features. [1] The danger of an idea like this is that when you run it by your friends with pets, they don't say "I would _never_ use this." They say "Yeah, maybe I could see using something like that." Even when the startup launches, it will sound plausible to a lot of people. They don't want to use it themselves, at least not right now, but they could imagine other people wanting it. Sum that reaction across the entire population, and you have zero users. [2] Well When a startup launches, there have to be at least some users who really need what they're making — not just people who could see themselves using it one day, but who want it urgently. Usually this initial group of users is small, for the simple reason that if there were something that large numbers of people urgently needed and that could be built with the amount of effort a startup usually puts into a version one, it would probably already exist. Which means you have to compromise on one dimension: you can either build something a large number of people want a small amount, or something a small number of people want a large amount. Choose the latter. Not all ideas of that type are good startup ideas, but nearly all good startup ideas are of that type. Imagine a graph whose x axis represents all the people who might want what you're making and whose y axis represents how much they want it.
自从高中读到这段话以来,我一直对它感到好奇。我不确定这段建议对绘画本身有多大帮助,但它非常契合当前的情境。从经验来看,获得优秀创业想法的方法就是成为能产生这些想法的人。
身处某个领域的前沿,并不意味着你必须成为推动该领域发展的人之一。作为用户,你也可以站在前沿。马克·扎克伯格认为Facebook是个好主意,与其说是因为他是程序员,不如说是因为他极度依赖电脑。如果在2004年问大多数40岁的人是否愿意在互联网上半公开地展示自己的生活,他们会觉得这个想法很可怕。但马克早已生活在网络世界,对他来说这再自然不过。
保罗·布赫海特说过,身处快速变化领域前沿的人们"生活在未来"。将这句话与皮尔西格的箴言结合,就得到了:
If you invert the scale on the y axis, you can envision companies as holes. Google is an immense crater: hundreds of millions of people use it, and they need it a lot. A startup just starting out can't expect to excavate that much volume. So you have two choices about the shape of hole you start with. You can either dig a hole that's broad but shallow, or one that's narrow and deep, like a well. Made-up startup ideas are usually of the first type. Lots of people are mildly interested in a social network for pet owners. Nearly all good startup ideas are of the second type. Microsoft was a well when they made Altair Basic. There were only a couple thousand Altair owners, but without this software they were programming in machine language. Thirty years later Facebook had the same shape. Their first site was exclusively for Harvard students, of which there are only a few thousand, but those few thousand users wanted it a lot. When you have an idea for a startup, ask yourself: who wants this right now? Who wants this so much that they'll use it even when it's a crappy version one made by a two-person startup they've never heard of? If you can't answer that, the idea is probably bad. [3] You don't need the narrowness of the well per se. It's depth you need; you get narrowness as a byproduct of optimizing for depth (and speed). But you almost always do get it. In practice the link between depth and narrowness is so strong that it's a good sign when you know that an idea will appeal strongly to a specific group or type of user. But while demand shaped like a well is almost a necessary condition for a good startup idea, it's not a sufficient one. If Mark Zuckerberg had built something that could only ever have appealed to Harvard students, it would not have been a good startup idea. Facebook was a good idea because it started with a small market there was a fast path out of.
> 生活在未来,然后建造缺失之物。
这段文字描述了众多(即便不是大多数)顶级初创企业的诞生方式。苹果、雅虎、谷歌和Facebook最初都未曾设想要成为公司。它们源自创始人因感知世界存在空白而创造的事物。
观察成功创始人的创意产生过程,往往源于外部刺激与有准备的头脑碰撞。比尔·盖茨和保罗·艾伦听闻Altair电脑时想到:"我们肯定能为它编写BASIC解释器。"德鲁·休斯顿发现自己忘带U盘时想到:"我确实需要让文件在线存储。"许多人听说过Altair,无数人忘带过U盘。这些刺激之所以促使创始人创业,是因为他们的经历使其能识别其中蕴含的机遇。
Colleges are similar enough that if you build a facebook that works at Harvard, it will work at any college. So you spread rapidly through all the colleges. Once you have all the college students, you get everyone else simply by letting them in. Similarly for Microsoft: Basic for the Altair; Basic for other machines; other languages besides Basic; operating systems; applications; IPO. Self How do you tell whether there's a path out of an idea? How do you tell whether something is the germ of a giant company, or just a niche product? Often you can't. The founders of Airbnb didn't realize at first how big a market they were tapping. Initially they had a much narrower idea. They were going to let hosts rent out space on their floors during conventions. They didn't foresee the expansion of this idea; it forced itself upon them gradually. All they knew at first is that they were onto something. That's probably as much as Bill Gates or Mark Zuckerberg knew at first. Occasionally it's obvious from the beginning when there's a path out of the initial niche. And sometimes I can see a path that's not immediately obvious; that's one of our specialties at YC. But there are limits to how well this can be done, no matter how much experience you have. The most important thing to understand about paths out of the initial idea is the meta-fact that these are hard to see. So if you can't predict whether there's a path out of an idea, how do you choose between ideas? The truth is disappointing but interesting: if you're the right sort of person, you have the right sort of hunches. If you're at the leading edge of a field that's changing fast, when you have a hunch that something is worth doing, you're more likely to be right. In _Zen and the Art of Motorcycle Maintenance_ , Robert Pirsig says:.
关于创业点子,关键动词不是"想出"而是"发现"。在YC,我们将创始人自身经历自然衍生的创意称为"有机"创业点子。几乎所有最成功的初创企业都由此发端。
这或许并非你想听的答案。你可能期待获得创业点子的配方,而我却告诉你关键在于以正确方式准备头脑。尽管令人失望,但这就是真相。这本身也是一种配方,只不过最坏情况下需要一年而非一个周末。
若你尚未身处快速变革领域的前沿,完全可以抵达那里。例如,任何足够聪明的人都能在一年内触及编程领域的某个前沿(比如开发移动应用)。鉴于成功创业至少需要投入3-5年人生,一年的准备堪称合理投资——尤其当你同时寻找联合创始人时。[4]
> You want to know how to paint a perfect painting? It's easy. Make yourself perfect and then just paint naturally.
你不必非要学习编程才能站在快速变革领域的前沿。其他领域同样日新月异。但在可预见的未来,掌握编程虽非必要,却已足够。正如马克·安德森所言:软件正在吞噬世界,这一趋势还将持续数十年。
懂编程还意味着当灵感降临时你能立即实现。这并非绝对必要(杰夫·贝索斯就不会编程),但确是优势。当考虑"将大学花名册搬上网"这类点子时,比起仅仅想着"这主意有趣",能立即行动:"这主意有趣,今晚就做个初版"将带来巨大优势。若你既是程序员又是目标用户则更佳,因为新版本迭代与用户测试可在你脑中同步完成。
I've wondered about that passage since I read it in high school. I'm not sure how useful his advice is for painting specifically, but it fits this situation well. Empirically, the way to have good startup ideas is to become the sort of person who has them. Being at the leading edge of a field doesn't mean you have to be one of the people pushing it forward. You can also be at the leading edge as a user. It was not so much because he was a programmer that Facebook seemed a good idea to Mark Zuckerberg as because he used computers so much. If you'd asked most 40 year olds in 2004 whether they'd like to publish their lives semi-publicly on the Internet, they'd have been horrified at the idea. But Mark already lived online; to him it seemed natural. Paul Buchheit says that people at the leading edge of a rapidly changing field "live in the future." Combine that with Pirsig and you get:
当你已生活在未来的某个维度,发现创业点子的方式就是寻找缺失之物。若你真正站在快速变革领域的前沿,定会察觉明显缺失的事物。不明显的只是它们能成为创业点子。因此寻找创意时,不仅要开启"缺少什么"的滤镜,更要关闭其他过滤器——尤其是"这能成为大公司吗"。后续有的是时间验证这点。若过早考虑,不仅会过滤掉大量好点子,还可能让你聚焦于糟糕创意。
多数缺失之物需要时间才能察觉。你几乎需要自我欺骗才能发现周遭的创意。
但你_知道_这些创意就在某处。这不是那种可能无解的问题。技术发展恰在此时停滞的概率微乎其微。你可以确信:未来几年人们构建的新事物定会让你感叹"没有X之前我是怎么活的?"
> Live in the future, then build what's missing.
当这些问题被解决时,回望时答案往往显得无比明显。你需要做的就是关闭那些日常阻碍你发现它们的过滤器。最强大的过滤器就是将现状视为理所当然——即便最具开放思维的人也难避免。若对每件事都质疑,你连从床边走到门口都困难。
但寻找创业点子时,你可以牺牲部分效率,停止将现状视为理所当然,开始质疑:为何收件箱总是爆满?因为邮件太多,还是难以清空收件箱?为何收到这么多邮件?人们发邮件想解决什么问题?有更好的解决方式吗?为何邮件难以清空?阅读后为何保留邮件?收件箱是最优工具吗?
特别关注那些令你烦躁的事物。将现状视为理所当然不仅提升(局部)效率,也使生活更易忍受。若知晓未来50年将出现而尚未拥有的东西,你会觉得当下生活处处受限,就像现代人穿越回50年前。当某事物令你烦恼,可能正因你已生活在未来。
That describes the way many if not most of the biggest startups got started. Neither Apple nor Yahoo nor Google nor Facebook were even supposed to be companies at first. They grew out of things their founders built because there seemed a gap in the world. If you look at the way successful founders have had their ideas, it's generally the result of some external stimulus hitting a prepared mind. Bill Gates and Paul Allen hear about the Altair and think "I bet we could write a Basic interpreter for it." Drew Houston realizes he's forgotten his USB stick and thinks "I really need to make my files live online." Lots of people heard about the Altair. Lots forgot USB sticks. The reason those stimuli caused those founders to start companies was that their experiences had prepared them to notice the opportunities they represented. The verb you want to be using with respect to startup ideas is not "think up" but "notice." At YC we call ideas that grow naturally out of the founders' own experiences "organic" startup ideas. The most successful startups almost all begin this way. That may not have been what you wanted to hear. You may have expected recipes for coming up with startup ideas, and instead I'm telling you that the key is to have a mind that's prepared in the right way. But disappointing though it may be, this is the truth. And it is a recipe of a sort, just one that in the worst case takes a year rather than a weekend. If you're not at the leading edge of some rapidly changing field, you can get to one. For example, anyone reasonably smart can probably get to an edge of programming (e.g. building mobile apps) in a year. Since a successful startup will consume at least 3-5 years of your life, a year's preparation would be a reasonable investment. Especially if you're also looking for a cofounder. [4] You don't have to learn programming to be at the leading edge of a domain that's changing fast. Other domains change fast.
当你找到正确的问题类型时,至少对你而言它应该显得_显而易见_。我们创建Viaweb时,所有网店都由网页设计师手工制作HTML页面。作为程序员,我们清楚这些网站必须由软件生成。[5]
这意味——说来奇怪——想出创业点子其实就是发现显而易见之事。这揭示了过程的吊诡:你试图看见那些明明显而易见却被忽视的事物。
由于关键在于解放思维,最好不要对问题发起正面强攻——比如坐着苦思冥想。最佳策略或许是保持后台进程持续运行,寻找缺失之物。主要出于好奇攻克难题的同时,让另一个自我在旁观察,记录缺口与异常。[6]
But while learning to hack is not necessary, it is for the forseeable future sufficient. As Marc Andreessen put it, software is eating the world, and this trend has decades left to run. Knowing how to hack also means that when you have ideas, you'll be able to implement them. That's not absolutely necessary (Jeff Bezos couldn't) but it's an advantage. It's a big advantage, when you're considering an idea like putting a college facebook online, if instead of merely thinking "That's an interesting idea," you can think instead "That's an interesting idea. I'll try building an initial version tonight." It's even better when you're both a programmer and the target user, because then the cycle of generating new versions and testing them on users can happen inside one head. Noticing Once you're living in the future in some respect, the way to notice startup ideas is to look for things that seem to be missing. If you're really at the leading edge of a rapidly changing field, there will be things that are obviously missing. What won't be obvious is that they're startup ideas. So if you want to find startup ideas, don't merely turn on the filter "What's missing?" Also turn off every other filter, particularly "Could this be a big company?" There's plenty of time to apply that test later. But if you're thinking about that initially, it may not only filter out lots of good ideas, but also cause you to focus on bad ones. Most things that are missing will take some time to see. You almost have to trick yourself into seeing the ideas around you. But you _know_ the ideas are out there. This is not one of those problems where there might not be an answer. It's impossibly unlikely that this is the exact moment when technological progress stops.
给自己时间。你虽能控制头脑的准备速度,却难以控制灵感的触发时机。若比尔·盖茨和保罗·艾伦限定自己一个月内想出创业点子,而恰巧选择Altair出现前的月份呢?他们可能投身于前景黯淡的项目。德鲁·休斯顿在Dropbox前就做过SAT备考项目。但Dropbox无论从绝对价值还是技能匹配度都远胜前者。[7]
自我欺骗以发现创意的妙招是投身看似酷炫的项目。如此你自然会构建缺失之物——重复造轮子多无趣。
You can be sure people are going to build things in the next few years that will make you think "What did I do before x?" And when these problems get solved, they will probably seem flamingly obvious in retrospect. What you need to do is turn off the filters that usually prevent you from seeing them. The most powerful is simply taking the current state of the world for granted. Even the most radically open-minded of us mostly do that. You couldn't get from your bed to the front door if you stopped to question everything. But if you're looking for startup ideas you can sacrifice some of the efficiency of taking the status quo for granted and start to question things. Why is your inbox overflowing? Because you get a lot of email, or because it's hard to get email out of your inbox? Why do you get so much email? What problems are people trying to solve by sending you email? Are there better ways to solve them? And why is it hard to get emails out of your inbox? Why do you keep emails around after you've read them? Is an inbox the optimal tool for that? Pay particular attention to things that chafe you. The advantage of taking the status quo for granted is not just that it makes life (locally) more efficient, but also that it makes life more tolerable. If you knew about all the things we'll get in the next 50 years but don't have yet, you'd find present day life pretty constraining, just as someone from the present would if they were sent back 50 years in a time machine. When something annoys you, it could be because you're living in the future. When you find the right sort of problem, you should probably be able to describe it as _obvious_ , at least to you. When we started Viaweb, all the online stores were built by hand, by web designers making individual HTML pages.
正如苦思冥想往往产生糟糕点子,那些可能被贬为"玩具"的项目常孕育佳作。当某物被称为玩具,意味着它具备创意所需的一切要素——除了重要性。它很酷,用户喜爱,只是看似无关紧要。但若你生活在未来,创造出用户热爱的酷炫产品,其意义可能远超外人想象。苹果和微软初涉微型计算机时,它们被视为玩具。我年长到记得那个年代——拥有微机的人被称为"发烧友"。BackRub(谷歌前身)像无关紧要的科研项目,Facebook最初只是本科生互窥资料的平台。
在YC,当我们遇见那些可能被论坛懂王贬为玩具的初创项目时总会兴奋。这对我们正是创意优质的明证。
若能着眼长远(或许你必须如此),"生活在未来,构建缺失之物"可升级为更佳版本:
It was obvious to us as programmers that these sites would have to be generated by software. [5] Which means, strangely enough, that coming up with startup ideas is a question of seeing the obvious. That suggests how weird this process is: you're trying to see things that are obvious, and yet that you hadn't seen. Since what you need to do here is loosen up your own mind, it may be best not to make too much of a direct frontal attack on the problem — i.e. to sit down and try to think of ideas. The best plan may be just to keep a background process running, looking for things that seem to be missing. Work on hard problems, driven mainly by curiosity, but have a second self watching over your shoulder, taking note of gaps and anomalies. [6] Give yourself some time. You have a lot of control over the rate at which you turn yours into a prepared mind, but you have less control over the stimuli that spark ideas when they hit it. If Bill Gates and Paul Allen had constrained themselves to come up with a startup idea in one month, what if they'd chosen a month before the Altair appeared? They probably would have worked on a less promising idea. Drew Houston did work on a less promising idea before Dropbox: an SAT prep startup. But Dropbox was a much better idea, both in the absolute sense and also as a match for his skills. [7] A good way to trick yourself into noticing ideas is to work on projects that seem like they'd be cool. If you do that, you'll naturally tend to build things that are missing. It wouldn't seem as interesting to build something that already existed. Just as trying to think up startup ideas tends to produce bad ones, working on things that could be dismissed as "toys" often produces good ones. When something is described as a toy, that means it has everything an idea needs except being important. It's cool; users love it; it just doesn't matter.
生活在未来,构建那些看起来有趣的事物。
我会建议大学生这样做,而不是试图学习“创业”。“创业”最好通过实践来学习。最成功的创始人的例子已经证明了这一点。在大学里,你应该花时间做的是让自己迈向未来。大学是一个无与伦比的机会来实现这一点。牺牲解决创业中最难部分的机会——成为那种能够自然产生创业想法的人——而花时间学习简单的部分,是一种浪费。尤其是因为你甚至不会真正学到它,就像你无法在课堂上真正学到性知识一样。你只会学到一些术语。
领域的碰撞是想法特别丰富的来源。如果你对编程很了解,然后开始学习其他领域,你可能会发现一些可以用软件解决的问题。事实上,你在另一个领域找到好问题的可能性是双倍的:(a) 该领域的从业者不像软件从业者那样可能已经用软件解决了他们的问题;(b) 由于你对新领域完全陌生,你甚至不知道现状是什么,因此不会将其视为理所当然。
But if you're living in the future and you build something cool that users love, it may matter more than outsiders think. Microcomputers seemed like toys when Apple and Microsoft started working on them. I'm old enough to remember that era; the usual term for people with their own microcomputers was "hobbyists." BackRub seemed like an inconsequential science project. The Facebook was just a way for undergrads to stalk one another. At YC we're excited when we meet startups working on things that we could imagine know-it-alls on forums dismissing as toys. To us that's positive evidence an idea is good. If you can afford to take a long view (and arguably you can't afford not to), you can turn "Live in the future and build what's missing" into something even better:.
所以,如果你是计算机科学专业的学生,并且想创业,与其选修一门创业课程,不如选修一门遗传学课程。或者更好的是,去一家生物技术公司工作。计算机科学专业的学生通常会在计算机硬件或软件公司找到暑期工作。但如果你想找到创业想法,在其他不相关的领域找一份暑期工作可能会更好。[8]
或者干脆不选额外的课程,直接动手做东西。微软和Facebook都在1月份成立并非巧合。在哈佛(或曾经是),1月是阅读期,学生们没有课要上,因为他们应该为期末考试复习。[9]
但不要觉得你必须做那些会成为创业项目的东西。这是过早的优化。只管做东西。最好和其他学生一起做。大学之所以是一个推动自己迈向未来的好地方,不仅仅是因为课程。你还被其他试图做同样事情的人包围着。如果你和他们一起做项目,最终不仅会产生自然的想法,还会产生带有自然创始团队的有机想法——而根据经验,这是最佳组合。
> Live in the future and build what seems interesting.
警惕研究。如果一个本科生写的东西开始被他的所有朋友使用,那很可能代表一个好的创业想法。而一篇博士论文极不可能如此。出于某种原因,一个项目越是需要被视为研究,它就越不可能成为可以转化为创业的东西。[10] 我认为原因是,被视为研究的想法子集非常狭窄,以至于满足这一约束的项目不太可能同时满足解决用户问题的正交约束。而当学生(或教授)作为副项目构建某些东西时,他们会自动倾向于解决用户的问题——甚至可能因为摆脱了研究的约束而释放出额外的能量。
因为一个好的想法应该看起来显而易见,所以当你有一个时,你往往会觉得自己已经晚了。不要让这阻止你。担心自己晚了是好想法的标志之一。十分钟的网页搜索通常就能解决这个问题。即使你发现别人也在做同样的事情,你可能也不算太晚。创业公司被竞争对手杀死的情况极为罕见——罕见到你几乎可以忽略这种可能性。所以,除非你发现一个竞争对手拥有某种锁定效应,使用户无法选择你,否则不要放弃这个想法。
如果你不确定,问问用户。你是否太晚的问题被“是否有人迫切需要你计划做的东西”所包含。如果你有一些竞争对手没有的东西,而某些用户迫切需要它,你就有了一个立足点。[11]
School That's what I'd advise college students to do, rather than trying to learn about "entrepreneurship." "Entrepreneurship" is something you learn best by doing it. The examples of the most successful founders make that clear. What you should be spending your time on in college is ratcheting yourself into the future. College is an incomparable opportunity to do that. What a waste to sacrifice an opportunity to solve the hard part of starting a startup — becoming the sort of person who can have organic startup ideas — by spending time learning about the easy part. Especially since you won't even really learn about it, any more than you'd learn about sex in a class. All you'll learn is the words for things. The clash of domains is a particularly fruitful source of ideas. If you know a lot about programming and you start learning about some other field, you'll probably see problems that software could solve. In fact, you're doubly likely to find good problems in another domain: (a) the inhabitants of that domain are not as likely as software people to have already solved their problems with software, and (b) since you come into the new domain totally ignorant, you don't even know what the status quo is to take it for granted. So if you're a CS major and you want to start a startup, instead of taking a class on entrepreneurship you're better off taking a class on, say, genetics. Or better still, go work for a biotech company. CS majors normally get summer jobs at computer hardware or software companies. But if you want to find startup ideas, you might do better to get a summer job in some unrelated field. [8] Or don't take any extra classes, and just build things. It's no coincidence that Microsoft and Facebook both got started in January.
接下来的问题是这个立足点是否足够大。或者更重要的是,谁在这个立足点中:如果立足点由那些正在做未来会有更多人做的事情的人组成,那么无论它有多小,都可能足够大。例如,如果你正在构建的东西与竞争对手的区别在于它能在手机上运行,但只能在最新款的手机上运行,这可能就是一个足够大的立足点。
宁可选择那些你会面对竞争对手的事情。缺乏经验的创始人通常会高估竞争对手。你是否成功更多地取决于你自己,而不是你的竞争对手。所以,一个有竞争对手的好想法比一个没有竞争对手的坏想法要好。
At Harvard that is (or was) Reading Period, when students have no classes to attend because they're supposed to be studying for finals. [9] But don't feel like you have to build things that will become startups. That's premature optimization. Just build things. Preferably with other students. It's not just the classes that make a university such a good place to crank oneself into the future. You're also surrounded by other people trying to do the same thing. If you work together with them on projects, you'll end up producing not just organic ideas, but organic ideas with organic founding teams — and that, empirically, is the best combination. Beware of research. If an undergrad writes something all his friends start using, it's quite likely to represent a good startup idea. Whereas a PhD dissertation is extremely unlikely to. For some reason, the more a project has to count as research, the less likely it is to be something that could be turned into a startup. [10] I think the reason is that the subset of ideas that count as research is so narrow that it's unlikely that a project that satisfied that constraint would also satisfy the orthogonal constraint of solving users' problems. Whereas when students (or professors) build something as a side-project, they automatically gravitate toward solving users' problems — perhaps even with an additional energy that comes from being freed from the constraints of research. Competition Because a good idea should seem obvious, when you have one you'll tend to feel that you're late. Don't let that deter you. Worrying that you're late is one of the signs of a good idea. Ten minutes of searching the web will usually settle the question. Even if you find someone else working on the same thing, you're probably not too late. It's exceptionally rare for startups to be killed by competitors — so rare that you can almost discount the possibility.
你不需要担心进入一个“拥挤的市场”,只要你对市场中其他人忽视的东西有一个论点。事实上,这是一个非常有希望的起点。谷歌就是这种类型的想法。不过,你的论点必须比“我们要做一个不烂的x”更精确。你必须能够用现有公司忽视的东西来表达它。最好的情况是,你可以说他们没有勇气坚持自己的信念,而你的计划是他们如果贯彻自己的洞察力会做的事情。谷歌也是这种类型的想法。在它之前的搜索引擎回避了他们所做事情的最激进的含义——尤其是他们做得越好,用户离开的速度就越快。
拥挤的市场实际上是一个好迹象,因为它既意味着有需求,也意味着现有的解决方案都不够好。一个创业公司不可能希望进入一个显然很大但没有任何竞争对手的市场。因此,任何成功的创业公司要么是进入一个有现有竞争对手的市场,但拥有某种秘密武器来吸引所有用户(如谷歌),要么是进入一个看起来很小但最终会很大的市场(如微软)。[12]
如果你想注意到创业想法,还需要关闭另外两个过滤器:不性感的过滤器和麻烦的过滤器。
So unless you discover a competitor with the sort of lock-in that would prevent users from choosing you, don't discard the idea. If you're uncertain, ask users. The question of whether you're too late is subsumed by the question of whether anyone urgently needs what you plan to make. If you have something that no competitor does and that some subset of users urgently need, you have a beachhead. [11] The question then is whether that beachhead is big enough. Or more importantly, who's in it: if the beachhead consists of people doing something lots more people will be doing in the future, then it's probably big enough no matter how small it is. For example, if you're building something differentiated from competitors by the fact that it works on phones, but it only works on the newest phones, that's probably a big enough beachhead. Err on the side of doing things where you'll face competitors. Inexperienced founders usually give competitors more credit than they deserve. Whether you succeed depends far more on you than on your competitors. So better a good idea with competitors than a bad one without. You don't need to worry about entering a "crowded market" so long as you have a thesis about what everyone else in it is overlooking. In fact that's a very promising starting point. Google was that type of idea. Your thesis has to be more precise than "we're going to make an x that doesn't suck" though. You have to be able to phrase it in terms of something the incumbents are overlooking. Best of all is when you can say that they didn't have the courage of their convictions, and that your plan is what they'd have done if they'd followed through on their own insights. Google was that type of idea too. The search engines that preceded them shied away from the most radical implications of what they were doing — particularly that the better a job they did, the faster users would leave.
大多数程序员希望他们能通过写一些出色的代码,将其推送到服务器,然后让用户付给他们很多钱来创业。他们宁愿不处理乏味的问题或以混乱的方式与现实世界打交道。这是一个合理的偏好,因为这些事情会让你慢下来。但这种偏好如此普遍,以至于方便的创业想法空间已经被清理得相当干净。如果你让你的思维沿着街道走几个街区,到那些混乱、乏味的想法中去,你会发现一些有价值的想法就坐在那里等待实现。
麻烦的过滤器非常危险,以至于我写了一篇单独的文章来描述它引起的状况,我称之为麻烦盲区。我以Stripe为例,说明了一个通过关闭这个过滤器而受益的创业公司,这是一个非常引人注目的例子。成千上万的程序员本可以看到这个想法;成千上万的程序员知道在Stripe之前处理支付有多痛苦。但当他们寻找创业想法时,他们没有看到这个,因为他们在潜意识里回避不得不处理支付问题。处理支付对Stripe来说是一个麻烦,但不是无法忍受的。事实上,他们可能承受的净痛苦更少;因为对处理支付的恐惧让大多数人远离这个想法,Stripe在其他有时会很痛苦的领域(如用户获取)相对顺利。他们不需要非常努力就能让用户听到他们的声音,因为用户迫切地等待着他们正在构建的东西。
不性感的过滤器与麻烦的过滤器类似,只是它阻止你处理你鄙视的问题,而不是你害怕的问题。我们克服了这一点来开发Viaweb。我们的软件架构有一些有趣的地方,但我们本身对电子商务并不感兴趣。我们可以看到这个问题需要被解决。
A crowded market is actually a good sign, because it means both that there's demand and that none of the existing solutions are good enough. A startup can't hope to enter a market that's obviously big and yet in which they have no competitors. So any startup that succeeds is either going to be entering a market with existing competitors, but armed with some secret weapon that will get them all the users (like Google), or entering a market that looks small but which will turn out to be big (like Microsoft). [12] Filters There are two more filters you'll need to turn off if you want to notice startup ideas: the unsexy filter and the schlep filter. Most programmers wish they could start a startup by just writing some brilliant code, pushing it to a server, and having users pay them lots of money. They'd prefer not to deal with tedious problems or get involved in messy ways with the real world. Which is a reasonable preference, because such things slow you down. But this preference is so widespread that the space of convenient startup ideas has been stripped pretty clean. If you let your mind wander a few blocks down the street to the messy, tedious ideas, you'll find valuable ones just sitting there waiting to be implemented. The schlep filter is so dangerous that I wrote a separate essay about the condition it induces, which I called schlep blindness. I gave Stripe as an example of a startup that benefited from turning off this filter, and a pretty striking example it is. Thousands of programmers were in a position to see this idea; thousands of programmers knew how painful it was to process payments before Stripe. But when they looked for startup ideas they didn't see this one, because unconsciously they shrank from having to deal with payments. And dealing with payments is a schlep for Stripe, but not an intolerable one.
关闭麻烦的过滤器比关闭不性感的过滤器更重要,因为麻烦的过滤器更有可能是幻觉。即使它不是,它也是一种更糟糕的自我放纵。无论怎样,创办一家成功的创业公司都会相当费力。即使产品不需要很多麻烦,你仍然需要处理投资者、雇佣和解雇人员等问题。所以,如果你觉得某个想法很酷,但因为害怕涉及的麻烦而不敢尝试,别担心:任何足够好的想法都会有同样多的麻烦。
不性感的过滤器虽然仍然是一个错误的来源,但并不像麻烦的过滤器那样完全无用。如果你处在一个快速变化的领域的前沿,你对什么是性感的看法会与实际有价值的东西有一定的相关性。尤其是随着年龄和经验的增长。此外,如果你觉得一个想法很性感,你会更热情地投入其中。[13]
虽然发现创业想法的最佳方式是成为那种能够自然产生想法的人,然后构建任何你感兴趣的东西,但有时你没有这种奢侈。有时你现在就需要一个想法。例如,如果你正在创业,而你的初始想法被证明是糟糕的。
In fact they might have had net less pain; because the fear of dealing with payments kept most people away from this idea, Stripe has had comparatively smooth sailing in other areas that are sometimes painful, like user acquisition. They didn't have to try very hard to make themselves heard by users, because users were desperately waiting for what they were building. The unsexy filter is similar to the schlep filter, except it keeps you from working on problems you despise rather than ones you fear. We overcame this one to work on Viaweb. There were interesting things about the architecture of our software, but we weren't interested in ecommerce per se. We could see the problem was one that needed to be solved though. Turning off the schlep filter is more important than turning off the unsexy filter, because the schlep filter is more likely to be an illusion. And even to the degree it isn't, it's a worse form of self-indulgence. Starting a successful startup is going to be fairly laborious no matter what. Even if the product doesn't entail a lot of schleps, you'll still have plenty dealing with investors, hiring and firing people, and so on. So if there's some idea you think would be cool but you're kept away from by fear of the schleps involved, don't worry: any sufficiently good idea will have as many. The unsexy filter, while still a source of error, is not as entirely useless as the schlep filter. If you're at the leading edge of a field that's changing rapidly, your ideas about what's sexy will be somewhat correlated with what's valuable in practice. Particularly as you get older and more experienced. Plus if you find an idea sexy, you'll work on it more enthusiastically. [13] Recipes While the best way to discover startup ideas is to become the sort of person who has them and then build whatever interests you, sometimes you don't have that luxury. Sometimes you need an idea now.
在本文的剩余部分,我将讨论按需提出创业想法的技巧。尽管根据经验,使用有机策略更好,但你可以通过这种方式成功。你只需要更加自律。当你使用有机方法时,你甚至不会注意到一个想法,除非它是真正缺失的东西的证据。但当你刻意努力思考创业想法时,你必须用自律来取代这种自然的约束。你会看到更多的想法,其中大多数是坏的,所以你需要能够过滤它们。
不使用有机方法的最大危险之一是有机方法的例子。有机想法感觉像是灵感。有很多关于成功创业公司的故事,这些公司在创始人有一个看似疯狂的想法但“就是知道”它很有前途时开始。当你对自己在尝试提出创业想法时产生的想法有这种感觉时,你可能是错的。
For example, if you're working on a startup and your initial idea turns out to be bad. For the rest of this essay I'll talk about tricks for coming up with startup ideas on demand. Although empirically you're better off using the organic strategy, you could succeed this way. You just have to be more disciplined. When you use the organic method, you don't even notice an idea unless it's evidence that something is truly missing. But when you make a conscious effort to think of startup ideas, you have to replace this natural constraint with self-discipline. You'll see a lot more ideas, most of them bad, so you need to be able to filter them. One of the biggest dangers of not using the organic method is the example of the organic method. Organic ideas feel like inspirations. There are a lot of stories about successful startups that began when the founders had what seemed a crazy idea but "just knew" it was promising. When you feel that about an idea you've had while trying to come up with startup ideas, you're probably mistaken. When searching for ideas, look in areas where you have some expertise. If you're a database expert, don't build a chat app for teenagers (unless you're also a teenager). Maybe it's a good idea, but you can't trust your judgment about that, so ignore it. There have to be other ideas that involve databases, and whose quality you can judge. Do you find it hard to come up with good ideas involving databases? That's because your expertise raises your standards. Your ideas about chat apps are just as bad, but you're giving yourself a Dunning-Kruger pass in that domain. The place to start looking for ideas is things you need. There _must_ be things you need. [14] One good trick is to ask yourself whether in your previous job you ever found yourself saying "Why doesn't someone make x? If someone made x we'd buy it in a second." If you can think of any x people said that about, you probably have an idea.
在寻找想法时,看看你有一些专业知识的领域。如果你是数据库专家,不要为青少年构建一个聊天应用(除非你也是青少年)。也许这是一个好主意,但你不能相信你对它的判断,所以忽略它。必须还有其他涉及数据库的想法,你可以判断它们的质量。你觉得很难想出涉及数据库的好想法吗?那是因为你的专业知识提高了你的标准。你对聊天应用的想法同样糟糕,但你在那个领域给了自己一个邓宁-克鲁格通行证。
开始寻找想法的地方是你需要的东西。你_一定_有需要的东西。[14]
一个好的技巧是问自己,在你以前的工作中,你是否曾经说过“为什么没有人做x?如果有人做x,我们会立刻购买。”如果你能想到人们说过的任何x,你可能就有了一个想法。你知道有需求,而且人们不会对那些不可能构建的东西说这种话。
You know there's demand, and people don't say that about things that are impossible to build. More generally, try asking yourself whether there's something unusual about you that makes your needs different from most other people's. You're probably not the only one. It's especially good if you're different in a way people will increasingly be. If you're changing ideas, one unusual thing about you is the idea you'd previously been working on. Did you discover any needs while working on it? Several well-known startups began this way. Hotmail began as something its founders wrote to talk about their previous startup idea while they were working at their day jobs. [15] A particularly promising way to be unusual is to be young. Some of the most valuable new ideas take root first among people in their teens and early twenties. And while young founders are at a disadvantage in some respects, they're the only ones who really understand their peers. It would have been very hard for someone who wasn't a college student to start Facebook. So if you're a young founder (under 23 say), are there things you and your friends would like to do that current technology won't let you? The next best thing to an unmet need of your own is an unmet need of someone else. Try talking to everyone you can about the gaps they find in the world. What's missing? What would they like to do that they can't? What's tedious or annoying, particularly in their work? Let the conversation get general; don't be trying too hard to find startup ideas. You're just looking for something to spark a thought. Maybe you'll notice a problem they didn't consciously realize they had, because you know how to solve it. When you find an unmet need that isn't your own, it may be somewhat blurry at first. The person who needs something may not know exactly what they need.
更一般地说,试着问自己是否有某些不寻常的地方使你的需求与大多数人不同。你可能不是唯一的一个。如果你以一种人们会越来越多地不同的方式与众不同,那就特别好。
如果你在改变想法,你之前一直在做的想法就是你一个不寻常的地方。你在做它的过程中发现了什么需求吗?几家知名的创业公司就是这样开始的。Hotmail最初是它的创始人在白天工作时用来讨论他们之前的创业想法的东西。[15]
一个特别有前途的不寻常方式是年轻。一些最有价值的新想法首先在十几岁和二十岁出头的人群中扎根。虽然年轻的创始人在某些方面处于劣势,但他们是唯一真正理解同龄人的人。一个不是大学生的人很难创办Facebook。所以,如果你是一个年轻的创始人(比如23岁以下),你和你的朋友有什么想做的事情是当前技术不允许的吗?
In that case I often recommend that founders act like consultants — that they do what they'd do if they'd been retained to solve the problems of this one user. People's problems are similar enough that nearly all the code you write this way will be reusable, and whatever isn't will be a small price to start out certain that you've reached the bottom of the well. [16] One way to ensure you do a good job solving other people's problems is to make them your own. When Rajat Suri of E la Carte decided to write software for restaurants, he got a job as a waiter to learn how restaurants worked. That may seem like taking things to extremes, but startups are extreme. We love it when founders do such things. In fact, one strategy I recommend to people who need a new idea is not merely to turn off their schlep and unsexy filters, but to seek out ideas that are unsexy or involve schleps. Don't try to start Twitter. Those ideas are so rare that you can't find them by looking for them. Make something unsexy that people will pay you for. A good trick for bypassing the schlep and to some extent the unsexy filter is to ask what you wish someone else would build, so that you could use it. What would you pay for right now? Since startups often garbage-collect broken companies and industries, it can be a good trick to look for those that are dying, or deserve to, and try to imagine what kind of company would profit from their demise. For example, journalism is in free fall at the moment. But there may still be money to be made from something like journalism. What sort of company might cause people in the future to say "this replaced journalism" on some axis? But imagine asking that in the future, not now. When one company or industry replaces another, it usually comes in from the side. So don't look for a replacement for x; look for something that people will later say turned out to be a replacement for x.
仅次于你自己未满足的需求的是别人的未满足需求。试着和你所能接触到的每个人谈谈他们在世界上发现的空白。缺少什么?他们想做什么但做不到?什么是乏味或烦人的,尤其是在他们的工作中?让对话变得宽泛;不要太努力地寻找创业想法。你只是在寻找能激发思考的东西。也许你会注意到一个他们没有意识到的问题,因为你知道如何解决它。
当你发现一个不是你自己的未满足需求时,它一开始可能有些模糊。需要某些东西的人可能不知道他们到底需要什么。在这种情况下,我经常建议创始人像顾问一样行动——就像他们被雇佣来解决这一个用户的问题时会做的那样。人们的问题足够相似,以至于你以这种方式编写的几乎所有代码都可以重用,而任何不能重用的代码都是一个小代价,以确保你已经触及了问题的根源。[16]
确保你很好地解决别人问题的一种方法是让它们成为你自己的问题。当E la Carte的Rajat Suri决定为餐厅编写软件时,他找了一份服务员的工作来了解餐厅的运作方式。这可能看起来像是把事情做到了极端,但创业就是极端的。我们喜欢创始人做这样的事情。
And be imaginative about the axis along which the replacement occurs. Traditional journalism, for example, is a way for readers to get information and to kill time, a way for writers to make money and to get attention, and a vehicle for several different types of advertising. It could be replaced on any of these axes (it has already started to be on most). When startups consume incumbents, they usually start by serving some small but important market that the big players ignore. It's particularly good if there's an admixture of disdain in the big players' attitude, because that often misleads them. For example, after Steve Wozniak built the computer that became the Apple I, he felt obliged to give his then-employer Hewlett-Packard the option to produce it. Fortunately for him, they turned it down, and one of the reasons they did was that it used a TV for a monitor, which seemed intolerably d�class� to a high-end hardware company like HP was at the time. [17] Are there groups of scruffy but sophisticated users like the early microcomputer "hobbyists" that are currently being ignored by the big players? A startup with its sights set on bigger things can often capture a small market easily by expending an effort that wouldn't be justified by that market alone. Similarly, since the most successful startups generally ride some wave bigger than themselves, it could be a good trick to look for waves and ask how one could benefit from them. The prices of gene sequencing and 3D printing are both experiencing Moore's Law-like declines. What new things will we be able to do in the new world we'll have in a few years? What are we unconsciously ruling out as impossible that will soon be possible? Organic But talking about looking explicitly for waves makes it clear that such recipes are plan B for getting startup ideas. Looking for waves is essentially a way to simulate the organic method.
事实上,我向那些需要新想法的人推荐的一个策略不仅是关闭他们的麻烦和不性感的过滤器,而且是寻找那些不性感或涉及麻烦的想法。不要试图创办Twitter。那些想法太罕见了,你无法通过寻找它们来找到它们。做一些不性感但人们会付钱给你的东西。
绕过麻烦过滤器并在某种程度上绕过不性感过滤器的一个好技巧是问自己你希望别人构建什么,这样你就可以使用它。你现在愿意为什么付钱?
If you're at the leading edge of some rapidly changing field, you don't have to look for waves; you are the wave. Finding startup ideas is a subtle business, and that's why most people who try fail so miserably. It doesn't work well simply to try to think of startup ideas. If you do that, you get bad ones that sound dangerously plausible. The best approach is more indirect: if you have the right sort of background, good startup ideas will seem obvious to you. But even then, not immediately. It takes time to come across situations where you notice something missing. And often these gaps won't seem to be ideas for companies, just things that would be interesting to build. Which is why it's good to have the time and the inclination to build things just because they're interesting. Live in the future and build what seems interesting. Strange as it sounds, that's the real recipe. Notes [1] This form of bad idea has been around as long as the web. It was common in the 1990s, except then people who had it used to say they were going to create a portal for x instead of a social network for x. Structurally the idea is stone soup: you post a sign saying "this is the place for people interested in x," and all those people show up and you make money from them. What lures founders into this sort of idea are statistics about the millions of people who might be interested in each type of x. What they forget is that any given person might have 20 affinities by this standard, and no one is going to visit 20 different communities regularly. [2] I'm not saying, incidentally, that I know for sure a social network for pet owners is a bad idea. I know it's a bad idea the way I know randomly generated DNA would not produce a viable organism. The set of plausible sounding startup ideas is many times larger than the set of good ones, and many of the good ones don't even sound that plausible.
由于创业公司经常“垃圾回收”破产的公司和行业,一个好的技巧是寻找那些正在衰落的或应该衰落的公司,并想象什么样的公司会从它们的灭亡中获利。例如,新闻业目前正在自由落体。但仍然可能有人从类似新闻业的东西中赚钱。什么样的公司可能会让人们在未来说“这在某个轴上取代了新闻业”?
但想象一下在未来问这个问题,而不是现在。当一个公司或行业取代另一个时,它通常是从侧面进入的。所以不要寻找x的替代品;寻找人们后来会说结果是x替代品的东西。并对替代发生的轴发挥想象力。例如,传统新闻业是读者获取信息和消磨时间的一种方式,是作家赚钱和获得关注的一种方式,也是几种不同类型广告的载体。它可以在这些轴中的任何一个上被取代(它已经在大多数轴上开始了)。
当创业公司“吞噬”现有公司时,它们通常从服务于一些大玩家忽视的小但重要的市场开始。如果大玩家的态度中夹杂着蔑视,那就特别好,因为这常常会误导他们。例如,在史蒂夫·沃兹尼亚克制造了后来成为Apple I的电脑后,他觉得有义务给他当时的雇主惠普公司生产它的选择权。对他来说幸运的是,他们拒绝了,其中一个原因是它使用电视作为显示器,这对像惠普这样的高端硬件公司来说似乎是不可容忍的低档。[17]
So if all you know about a startup idea is that it sounds plausible, you have to assume it's bad. [3] More precisely, the users' need has to give them sufficient activation energy to start using whatever you make, which can vary a lot. For example, the activation energy for enterprise software sold through traditional channels is very high, so you'd have to be a _lot_ better to get users to switch. Whereas the activation energy required to switch to a new search engine is low. Which in turn is why search engines are so much better than enterprise software. [4] This gets harder as you get older. While the space of ideas doesn't have dangerous local maxima, the space of careers does. There are fairly high walls between most of the paths people take through life, and the older you get, the higher the walls become. [5] It was also obvious to us that the web was going to be a big deal. Few non-programmers grasped that in 1995, but the programmers had seen what GUIs had done for desktop computers. [6] Maybe it would work to have this second self keep a journal, and each night to make a brief entry listing the gaps and anomalies you'd noticed that day. Not startup ideas, just the raw gaps and anomalies. [7] Sam Altman points out that taking time to come up with an idea is not merely a better strategy in an absolute sense, but also like an undervalued stock in that so few founders do it. There's comparatively little competition for the best ideas, because few founders are willing to put in the time required to notice them. Whereas there is a great deal of competition for mediocre ideas, because when people make up startup ideas, they tend to make up the same ones. [8] For the computer hardware and software companies, summer jobs are the first phase of the recruiting funnel. But if you're good you can skip the first phase.
是否有像早期的微型计算机“爱好者”那样被大玩家忽视的邋遢但老练的用户群体?一个瞄准更大目标的创业公司通常可以通过付出仅凭该市场无法证明合理的努力来轻松捕获一个小市场。
同样,由于最成功的创业公司通常会骑乘比它们自己更大的浪潮,寻找浪潮并问自己如何从中受益可能是一个好技巧。基因测序和3D打印的价格都在经历类似摩尔定律的下降。在未来几年我们将拥有的新世界中,我们将能够做哪些新事情?我们潜意识里认为不可能的事情中,哪些很快就会成为可能?
但谈论明确寻找浪潮清楚地表明,这样的配方是获得创业想法的B计划。寻找浪潮本质上是模拟有机方法的一种方式。如果你处于某个快速变化的领域的前沿,你不必寻找浪潮;你就是浪潮。
If you're good you'll have no trouble getting hired by these companies when you graduate, regardless of how you spent your summers. [9] The empirical evidence suggests that if colleges want to help their students start startups, the best thing they can do is leave them alone in the right way. [10] I'm speaking here of IT startups; in biotech things are different. [11] This is an instance of a more general rule: focus on users, not competitors. The most important information about competitors is what you learn via users anyway. [12] In practice most successful startups have elements of both. And you can describe each strategy in terms of the other by adjusting the boundaries of what you call the market. But it's useful to consider these two ideas separately. [13] I almost hesitate to raise that point though. Startups are businesses; the point of a business is to make money; and with that additional constraint, you can't expect you'll be able to spend all your time working on what interests you most. [14] The need has to be a strong one. You can retroactively describe any made-up idea as something you need. But do you really need that recipe site or local event aggregator as much as Drew Houston needed Dropbox, or Brian Chesky and Joe Gebbia needed Airbnb? Quite often at YC I find myself asking founders "Would you use this thing yourself, if you hadn't written it?" and you'd be surprised how often the answer is no. [15] Paul Buchheit points out that trying to sell something bad can be a source of better ideas: "The best technique I've found for dealing with YC companies that have bad ideas is to tell them to go sell the product ASAP (before wasting time building it).
寻找创业想法是一件微妙的事情,这就是为什么大多数尝试的人会惨败。简单地试图想出创业想法效果不好。如果你这样做,你会得到听起来危险地合理的坏想法。最好的方法是更间接的:如果你有正确的背景,好的创业想法对你来说会是显而易见的。但即便如此,也不是立刻就能发现。你需要时间来遇到你注意到某些东西缺失的情况。而且通常这些空白看起来不像是公司的想法,只是看起来有趣的东西。这就是为什么有时间并且有动力仅仅因为它们有趣而构建东西是好的。
生活在未来,构建看起来有趣的东西。尽管听起来很奇怪,但这是真正的配方。
[1] 这种形式的坏想法自网络出现以来就一直存在。它在20世纪90年代很常见,只是那时有这种想法的人会说他们要为x创建一个门户网站,而不是为x创建一个社交网络。从结构上讲,这个想法是“石头汤”:你张贴一个标志说“这是对x感兴趣的人的地方”,然后所有这些人都出现了,你从他们身上赚钱。吸引创始人进入这种想法的是关于可能对每种x感兴趣的数百万人的统计数据。他们忘记的是,根据这个标准,任何一个人可能有20种兴趣,没有人会定期访问20个不同的社区。
Not only do they learn that nobody wants what they are building, they very often come back with a real idea that they discovered in the process of trying to sell the bad idea." [16] Here's a recipe that might produce the next Facebook, if you're college students. If you have a connection to one of the more powerful sororities at your school, approach the queen bees thereof and offer to be their personal IT consultants, building anything they could imagine needing in their social lives that didn't already exist. Anything that got built this way would be very promising, because such users are not just the most demanding but also the perfect point to spread from. I have no idea whether this would work. [17] And the reason it used a TV for a monitor is that Steve Wozniak started out by solving his own problems. He, like most of his peers, couldn't afford a monitor. Thanks to Sam Altman, Mike Arrington, Paul Buchheit, John Collison, Patrick Collison, Garry Tan, and Harj Taggar for reading drafts of this, and Marc Andreessen, Joe Gebbia, Reid Hoffman, Shel Kaphan, Mike Moritz and Kevin Systrom for answering my questions about startup history.
Japanese Translation | Italian Translation Spanish Translation.
[2] 顺便说一句,我并不是说我确定一个宠物主人的社交网络是一个坏主意。我知道它是一个坏主意,就像我知道随机生成的DNA不会产生一个可行的生物体一样。听起来合理的创业想法集合比好的想法集合大很多倍,而且许多好的想法听起来甚至不那么合理。所以,如果你对一个创业想法的全部了解是它听起来合理,你必须假设它是坏的。
[3] 更准确地说,用户的需求必须给他们足够的激活能量来开始使用你制作的任何东西,这可能会有很大差异。例如,通过传统渠道销售的企业软件的激活能量非常高,所以你必须_好得多_才能让用户切换。而切换到新搜索引擎所需的激活能量很低。这也是为什么搜索引擎比企业软件好得多。
[4] 随着年龄的增长,这会变得更加困难。虽然想法空间没有危险
Want to start a startup? Get funded by Y Combinator.
October 2012 One advantage of Y Combinator's early, broad focus is that we see trends before most other people. And one of the most conspicuous trends in the last batch was the large number of hardware startups. Out of 84 companies, 7 were making hardware. On the whole they've done better than the companies that weren't. They've faced resistance from investors of course. Investors have a deep-seated bias against hardware. But investors' opinions are a trailing indicator. The best founders are better at seeing the future than the best investors, because the best founders are making it. There is no one single force driving this trend. Hardware does well on crowdfunding sites. The spread of tablets makes it possible to build new things controlled by and even incorporating them. Electric motors have improved. Wireless connectivity of various types can now be taken for granted. It's getting more straightforward to get things manufactured. Arduinos, 3D printing, laser cutters, and more accessible CNC milling are making hardware easier to prototype. Retailers are less of a bottleneck as customers increasingly buy online. One question I can answer is why hardware is suddenly cool. It always was cool. Physical things are great. They just haven't been as great a way to start a rapidly growing business as software. But that rule may not be permanent. It's not even that old; it only dates from about 1990. Maybe the advantage of software will turn out to have been temporary. Hackers love to build hardware, and customers love to buy it.
So if the ease of shipping hardware even approached the ease of shipping software, we'd see a lot more hardware startups. It wouldn't be the first time something was a bad idea till it wasn't. And it wouldn't be the first time investors learned that lesson from founders. So if you want to work on hardware, don't be deterred from doing it because you worry investors will discriminate against you. And in particular, don't be deterred from applying to Y Combinator with a hardware idea, because we're especially interested in hardware startups. We know there's room for the next Steve Jobs. But there's almost certainly also room for the first . Thanks to Sam Altman, Trevor Blackwell, David Cann, Sanjay Dastoor, Paul Gerhardt, Cameron Robertson, Harj Taggar, and Garry Tan for reading drafts of this.
想创办一家初创公司? 获得 Y Combinator 的资金支持。
2012年10月 Y Combinator早期广泛关注的一个优势是,我们能比大多数人更早发现趋势。在上一批项目中,最明显的趋势之一就是硬件初创公司的大量涌现。84家公司中,有7家从事硬件开发。总体来看,它们的表现优于非硬件公司。 当然,它们也面临投资者的阻力。投资者对硬件有着根深蒂固的偏见。但投资者的观点往往是滞后指标。最优秀的创始人比最优秀的投资者更擅长预见未来,因为最优秀的创始人正在创造未来。 推动这一趋势的因素并非单一。硬件在众筹网站上表现亮眼。平板电脑的普及使得开发由它们控制甚至整合它们的新产品成为可能。电动马达技术有所改进。各种无线连接如今已司空见惯。产品制造流程变得更加简单。Arduino、3D打印、激光切割以及更易用的数控铣削技术让硬件原型制作更加便捷。随着消费者越来越多地在线购物,零售商的瓶颈作用正在减弱。 我能回答的一个问题是:为什么硬件突然变得酷炫?它一直都很酷。实体产品很棒。只是它们过去不像软件那样容易打造快速增长的业务。但这一规律或许并非永恒。它甚至不算古老——仅可追溯至1990年左右。也许软件的优势只是暂时的。黑客热爱制造硬件,而消费者热衷购买硬件。因此,如果硬件产品的交付难度能接近软件的水平,我们将看到更多硬件初创公司。 这不会是历史上第一次"某事物从糟糕点子变为明智之选"。也不会是投资者第一次从创始人身上学到这一课。 所以,如果你想从事硬件开发,不要因为担心投资者会歧视你而却步。尤其不要因此放弃带着硬件创意申请Y Combinator——我们对硬件初创公司特别感兴趣。 我们知道,这个世界需要下一个史蒂夫·乔布斯。但几乎可以肯定的是,它同样需要第一个。 感谢 Sam Altman、Trevor Blackwell、David Cann、Sanjay Dastoor、Paul Gerhardt、Cameron Robertson、Harj Taggar和Garry Tan阅读本文草稿。
Want to start a startup? Get funded by Y Combinator.
September 2012 A startup is a company designed to grow fast. Being newly founded does not in itself make a company a startup. Nor is it necessary for a startup to work on technology, or take venture funding, or have some sort of "exit." The only essential thing is growth. Everything else we associate with startups follows from growth. If you want to start one it's important to understand that. Startups are so hard that you can't be pointed off to the side and hope to succeed. You have to know that growth is what you're after. The good news is, if you get growth, everything else tends to fall into place. Which means you can use growth like a compass to make almost every decision you face. Redwoods Let's start with a distinction that should be obvious but is often overlooked: not every newly founded company is a startup. Millions of companies are started every year in the US. Only a tiny fraction are startups. Most are service businesses — restaurants, barbershops, plumbers, and so on. These are not startups, except in a few unusual cases. A barbershop isn't designed to grow fast. Whereas a search engine, for example, is. When I say startups are designed to grow fast, I mean it in two senses. Partly I mean designed in the sense of intended, because most startups fail. But I also mean startups are different by nature, in the same way a redwood seedling has a different destiny from a bean sprout. That difference is why there's a distinct word, "startup," for companies designed to grow fast. If all companies were essentially similar, but some through luck or the efforts of their founders ended up growing very fast, we wouldn't need a separate word. We could just talk about super-successful companies and less successful ones. But in fact startups do have a different sort of DNA from other businesses.
想创立一家初创公司? 获得 Y Combinator 的资助。
2012年9月 初创公司是为快速增长而设计的公司。新成立本身并不能使一家公司成为初创公司。初创公司也不一定要从事技术领域、接受风险投资或实现某种“退出”。唯一关键的因素是增长。我们与初创公司关联的其他一切特质都源于增长。 如果你想创立一家初创公司,理解这一点至关重要。初创公司如此艰难,以至于你不能偏离方向却指望成功。你必须明确增长才是你的目标。好消息是,如果你实现了增长,其他一切往往会水到渠成。这意味着你可以将增长作为指南针,来应对几乎每一个决策。 红杉 让我们从一个本应显而易见却常被忽视的区分开始:并非每一家新成立的公司都是初创公司。美国每年有数百万家公司成立,其中只有极少数是初创公司。大多数是服务型企业——餐馆、理发店、水管工等等。除了少数特例外,这些都不是初创公司。理发店并非为快速扩张而设计,而搜索引擎则是。 当我说初创公司是为快速增长而设计时,我指的是两层含义。一方面,“设计”指的是意图,因为大多数初创公司会失败。但另一方面,初创公司在本质上就与众不同,就像红杉树苗与豆芽的命运截然不同。 这种差异正是为什么我们用“初创公司”这个独特的词来称呼那些为快速增长而设计的公司。如果所有公司本质上相似,只是有些因为运气或创始人的努力最终快速增长,我们就不需要一个单独的词汇。我们只需谈论超级成功的公司和不太成功的公司。但实际上,初创公司的DNA确实与其他企业不同。谷歌不仅仅是一家创始人异常幸运且勤奋的理发店。谷歌从一开始就与众不同。 要实现快速增长,你需要创造出能面向广阔市场的产品。这就是谷歌与理发店的区别。理发店无法规模化扩张。 一家公司要想真正做大,必须满足两点:(a) 生产许多人想要的产品,(b) 触达并服务所有这些人群。理发店在(a)方面表现不错——几乎每个人都需要理发。但理发店的问题在于(b),就像任何零售实体店一样。理发店需要面对面服务顾客,而很少有人会远行只为理发。即使他们愿意,理发店也无法接待所有人。[1] 编写软件是解决(b)的绝佳方式,但你仍可能受限于(a)。如果你开发一款教匈牙利人藏语的软件,你能触达大多数潜在用户,但用户基数本身很小。但如果你开发一款教中国人英语的软件,你就进入了初创公司的领域。 大多数企业在(a)或(b)方面受到严格限制。成功初创公司的独特之处在于它们不受这些限制。 创意 表面上看,创立初创公司似乎总是比普通企业更优。如果要创办公司,为什么不选择潜力最大的类型?关键在于这是一个(相对)有效的市场。如果你开发教匈牙利人藏语的软件,你不会面临太多竞争。但如果你开发教中国人英语的软件,你将面临激烈竞争, precisely because the prize is so much bigger.[2] 限制普通企业的约束同时也保护了它们。这是一种权衡。如果开理发店,你只需与当地其他理发师竞争;如果开发搜索引擎,你必须与全世界抗衡。 然而,对普通企业而言,约束最重要的保护作用并非针对竞争,而是规避构思新创意的难度。如果在特定社区开酒吧,地理限制在约束潜力和屏蔽竞争的同时,也帮助定义了企业本身。“酒吧+社区”已足以支撑小本生意。类似地,(a)领域受限的企业也是如此——利基市场既保护了你,也定义了你。 而如果想创立初创公司,你很可能需要想出相当新颖的点子。初创公司必须创造能交付给广阔市场的产品,这类创意的价值如此之高,以至于所有显而易见的点子都已被占据。 这个创意空间已被彻底发掘,因此初创公司通常必须专注于他人忽视的领域。我本想写“必须有意识地寻找被他人忽略的创意”,但大多数初创公司并非如此起步。成功的初创公司往往源于创始人足够与众不同,以至于对他人隐而不见的创意对他们而言显而易见。或许后来他们会退一步,意识到自己发现了众人盲区中的创意,并从此有意识地保持这一优势。[3] 但在成功初创公司诞生之初,多数创新是无意识的。 成功创始人的独特之处在于他们能看到不同的问题。兼具技术能力与解决技术可解问题的视野是绝佳组合,因为技术变革如此迅速,昔日糟糕的创意常在不经意间变为良机。史蒂夫·沃兹尼亚克的问题是他想要自己的电脑——这在1975年是非典型需求。但技术变革即将使其成为普遍需求。由于他不仅渴望电脑还懂得如何制造,沃兹尼亚克能为自己打造一台。他为自己解决的这个问题,随后成为苹果公司为数百万人解决的难题。但当普通人意识到这是巨大市场时,苹果早已站稳脚跟。 谷歌有相似的起源。拉里·佩奇和谢尔盖·布林想搜索网络。但与大多数人不同,他们拥有技术专长,既能察觉现有搜索引擎的不足,又知道如何改进。随着网络规模扩张,几年后他们的问题成为所有人的问题——此时无需挑剔的搜索专家也能发现旧算法力不从心。但如同苹果的故事,当其他人意识到搜索的重要性时,谷歌已根深蒂固。 这是初创公司创意与技术的一个关联点:某一领域的快速变革会揭示其他领域重大且可解决的问题。有时变革是技术进步,改变的是问题可解性。苹果正是这类变革的产物——芯片技术进步最终让沃兹尼亚克设计出负担得起的电脑。但对谷歌而言,最重要的变革是网络的扩张,改变的不是可解性而是规模。 初创公司与技术的另一关联在于:初创公司创造新的做事方式,而广义上说,新方式就是新技术。当一家初创公司既源于技术变革暴露的创意,又生产狭义技术(曾称“高科技”)产品时,二者容易被混淆。但这两个关联本质不同——理论上完全可以创立既不依赖技术变革驱动,产品也不含(狭义)技术的初创公司。[4] 速率 一家公司的增长速度需达到多少才算是初创公司?这个问题没有精确答案。“初创公司”是一个极端值,而非阈值。创立初创公司最初不过是野心的宣示——你承诺不仅要创办公司,还要创办快速成长的公司,因此你承诺要寻找那类稀缺的创意。但最初你仅拥有这份承诺。在这方面,创立初创公司如同成为演员。“演员”同样是个极端值而非阈值。职业生涯初期,演员是参加试镜的服务生。获得角色使他成为成功演员,但他并非仅在成功时才成为演员。 因此真正的问题不是“多快的增长率使公司成为初创公司”,而是“成功初创公司通常具有怎样的增长率”。对创始人而言,这不止是理论问题,因为它等同于询问是否走在正确道路上。 成功初创公司的增长通常分为三个阶段:.
1. 初创企业在摸索方向时,会经历一段增长缓慢甚至停滞的初始阶段。
Google is not just a barbershop whose founders were unusually lucky and hard-working. Google was different from the beginning. To grow rapidly, you need to make something you can sell to a big market. That's the difference between Google and a barbershop. A barbershop doesn't scale. For a company to grow really big, it must (a) make something lots of people want, and (b) reach and serve all those people. Barbershops are doing fine in the (a) department. Almost everyone needs their hair cut. The problem for a barbershop, as for any retail establishment, is (b). A barbershop serves customers in person, and few will travel far for a haircut. And even if they did, the barbershop couldn't accomodate them. [1] Writing software is a great way to solve (b), but you can still end up constrained in (a). If you write software to teach Tibetan to Hungarian speakers, you'll be able to reach most of the people who want it, but there won't be many of them. If you make software to teach English to Chinese speakers, however, you're in startup territory. Most businesses are tightly constrained in (a) or (b). The distinctive feature of successful startups is that they're not. Ideas It might seem that it would always be better to start a startup than an ordinary business. If you're going to start a company, why not start the type with the most potential? The catch is that this is a (fairly) efficient market. If you write software to teach Tibetan to Hungarians, you won't have much competition. If you write software to teach English to Chinese speakers, you'll face ferocious competition, precisely because that's such a larger prize. [2] The constraints that limit ordinary companies also protect them. That's the tradeoff. If you start a barbershop, you only have to compete with other local barbers. If you start a search engine you have to compete with the whole world.
2. 当企业逐渐掌握如何打造大众所需产品并触达目标用户时,就会进入快速增长期。
3. 最终成功的初创企业将发展为大型公司。此时增长会放缓,部分源于内部瓶颈制约,部分由于企业开始触及所服务市场的规模上限。[5]
The most important thing that the constraints on a normal business protect it from is not competition, however, but the difficulty of coming up with new ideas. If you open a bar in a particular neighborhood, as well as limiting your potential and protecting you from competitors, that geographic constraint also helps define your company. Bar + neighborhood is a sufficient idea for a small business. Similarly for companies constrained in (a). Your niche both protects and defines you. Whereas if you want to start a startup, you're probably going to have to think of something fairly novel. A startup has to make something it can deliver to a large market, and ideas of that type are so valuable that all the obvious ones are already taken. That space of ideas has been so thoroughly picked over that a startup generally has to work on something everyone else has overlooked. I was going to write that one has to make a conscious effort to find ideas everyone else has overlooked. But that's not how most startups get started. Usually successful startups happen because the founders are sufficiently different from other people that ideas few others can see seem obvious to them. Perhaps later they step back and notice they've found an idea in everyone else's blind spot, and from that point make a deliberate effort to stay there. [3] But at the moment when successful startups get started, much of the innovation is unconscious. What's different about successful founders is that they can see different problems. It's a particularly good combination both to be good at technology and to face problems that can be solved by it, because technology changes so rapidly that formerly bad ideas often become good without anyone noticing. Steve Wozniak's problem was that he wanted his own computer. That was an unusual problem to have in 1975. But technological change was about to make it a much more common one.
这三个阶段共同构成了一条S型曲线。决定初创企业特质的正是第二阶段——上升期。其持续时间和斜率决定了公司的最终规模。
斜率即公司的增长率。如果创始人只能记住一个数字,那必须是公司增长率。这是衡量初创企业的核心指标。若不清楚这个数字,你甚至无法判断经营状况优劣。
Because he not only wanted a computer but knew how to build them, Wozniak was able to make himself one. And the problem he solved for himself became one that Apple solved for millions of people in the coming years. But by the time it was obvious to ordinary people that this was a big market, Apple was already established. Google has similar origins. Larry Page and Sergey Brin wanted to search the web. But unlike most people they had the technical expertise both to notice that existing search engines were not as good as they could be, and to know how to improve them. Over the next few years their problem became everyone's problem, as the web grew to a size where you didn't have to be a picky search expert to notice the old algorithms weren't good enough. But as happened with Apple, by the time everyone else realized how important search was, Google was entrenched. That's one connection between startup ideas and technology. Rapid change in one area uncovers big, soluble problems in other areas. Sometimes the changes are advances, and what they change is solubility. That was the kind of change that yielded Apple; advances in chip technology finally let Steve Wozniak design a computer he could afford. But in Google's case the most important change was the growth of the web. What changed there was not solubility but bigness. The other connection between startups and technology is that startups create new ways of doing things, and new ways of doing things are, in the broader sense of the word, new technology. When a startup both begins with an idea exposed by technological change and makes a product consisting of technology in the narrower sense (what used to be called "high technology"), it's easy to conflate the two.
当我初次询问创始人增长率时,他们常回答"每月新增约100名客户"。这并非增长率。关键不在于新增客户的绝对数量,而在于新增与存量客户之比。若每月新增客户数恒定不变,实则危机暗藏——这意味着增长率正在持续下滑。
在Y Combinator期间,我们按周测算增长率。一方面因演示日迫近,另一方面初创企业早期需要频繁获取用户反馈来调整策略。[6]
But the two connections are distinct and in principle one could start a startup that was neither driven by technological change, nor whose product consisted of technology except in the broader sense. [4] Rate How fast does a company have to grow to be considered a startup? There's no precise answer to that. "Startup" is a pole, not a threshold. Starting one is at first no more than a declaration of one's ambitions. You're committing not just to starting a company, but to starting a fast growing one, and you're thus committing to search for one of the rare ideas of that type. But at first you have no more than commitment. Starting a startup is like being an actor in that respect. "Actor" too is a pole rather than a threshold. At the beginning of his career, an actor is a waiter who goes to auditions. Getting work makes him a successful actor, but he doesn't only become an actor when he's successful. So the real question is not what growth rate makes a company a startup, but what growth rate successful startups tend to have. For founders that's more than a theoretical question, because it's equivalent to asking if they're on the right path. The growth of a successful startup usually has three phases:.
YC期间5-7%的周增长率堪称良好,若能达10%则表现非凡。若仅维持1%,则表明尚未找准发展方向。
最佳测算指标是营收。对暂未收费的初创企业,活跃用户数是次优选择。这是营收增长的合理替代指标,因为当企业开始变现时,其收入往往与活跃用户数保持稳定倍数关系。[7]
1. There's an initial period of slow or no growth while the startup tries to figure out what it's doing.
我们通常建议初创企业设定可实现的周增长目标,然后全力达成。关键在于"专注"。若目标定为7%且如期完成,这周便是成功的。无需额外动作。但若未达标,则意味着在唯一重要事项上失败,必须立即警觉。
程序员会理解这种思路:我们将创业转化为最优化问题。优化代码者皆知,这种聚焦能产生惊人效果。优化代码只需思考如何减少资源占用(通常是时间或内存),不必考虑程序功能。对多数程序员而言,这种工作充满快感——聚焦使其如解谜题,且解决速度往往超预期。
2. As the startup figures out how to make something lots of people want and how to reach those people, there's a period of rapid growth.
聚焦增长率目标,能将创业的复杂性问题简化为单一指标。所有决策都可依据这个目标:参会两天?招聘程序员?加强营销?争取大客户?开发新功能?唯一标准就是能否达成目标增长率。[8]
按周评估不意味着鼠目寸光。经历一次达标失败后(这是唯一重要之事却搞砸了),你会主动预防未来风险。例如愿意招聘程序员——虽不影响本周增长,但月后新功能可能带来用户激增。前提是:(a)招聘不影响短期目标;(b)确信无新人加入将难以持续达标。
并非不思考未来,而是避免过度思考。
3. Eventually a successful startup will grow into a big company. Growth will slow, partly due to internal limits and partly because the company is starting to bump up against the limits of the markets it serves. [5]
理论上这种"爬山算法"可能导致局部最优。但实践中几乎不会发生。周增长目标迫使创始人行动,而行动与否正是成败关键。十之八九,空谈战略只是拖延症的表现。况且创始人对攀登方向的直觉通常比自以为的更准确。更何况创业idea的高原并非孤立尖峰,多数好点子附近总有更优选择。
增长优化的魅力在于能发掘创业idea。可将增长需求视为进化压力。若初始计划经调整后能保持10%周增长,最终公司可能截然不同。但任何能持续10%周增长的项目,几乎必然优于最初设想。
Together these three phases produce an S-curve. The phase whose growth defines the startup is the second one, the ascent. Its length and slope determine how big the company will be. The slope is the company's growth rate. If there's one number every founder should always know, it's the company's growth rate. That's the measure of a startup. If you don't know that number, you don't even know if you're doing well or badly. When I first meet founders and ask what their growth rate is, sometimes they tell me "we get about a hundred new customers a month." That's not a rate. What matters is not the absolute number of new customers, but the ratio of new customers to existing ones. If you're really getting a constant number of new customers every month, you're in trouble, because that means your growth rate is decreasing. During Y Combinator we measure growth rate per week, partly because there is so little time before Demo Day, and partly because startups early on need frequent feedback from their users to tweak what they're doing. [6] A good growth rate during YC is 5-7% a week. If you can hit 10% a week you're doing exceptionally well. If you can only manage 1%, it's a sign you haven't yet figured out what you're doing. The best thing to measure the growth rate of is revenue. The next best, for startups that aren't charging initially, is active users. That's a reasonable proxy for revenue growth because whenever the startup does start trying to make money, their revenues will probably be a constant multiple of active users. [7] Compass We usually advise startups to pick a growth rate they think they can hit, and then just try to hit it every week. The key word here is "just." If they decide to grow at 7% a week and they hit that number, they're successful for that week. There's nothing more they need to do. But if they don't hit it, they've failed in the only thing that mattered, and should be correspondingly alarmed.
这与小企业存在平行关系:正如社区位置定义酒吧特色,特定增长率也能定义初创企业。
最好遵循约束而非初始愿景,如同科学家追随真理而非个人愿望。理查德·费曼说"自然的想象力远超人类",意指追随真理能发现超乎想象的奇迹。对初创企业而言,增长就是真理般的约束。每个成功企业都部分源自增长想象力。[9]
Programmers will recognize what we're doing here. We're turning starting a startup into an optimization problem. And anyone who has tried optimizing code knows how wonderfully effective that sort of narrow focus can be. Optimizing code means taking an existing program and changing it to use less of something, usually time or memory. You don't have to think about what the program should do, just make it faster. For most programmers this is very satisfying work. The narrow focus makes it a sort of puzzle, and you're generally surprised how fast you can solve it. Focusing on hitting a growth rate reduces the otherwise bewilderingly multifarious problem of starting a startup to a single problem. You can use that target growth rate to make all your decisions for you; anything that gets you the growth you need is ipso facto right. Should you spend two days at a conference? Should you hire another programmer? Should you focus more on marketing? Should you spend time courting some big customer? Should you add x feature? Whatever gets you your target growth rate. [8] Judging yourself by weekly growth doesn't mean you can look no more than a week ahead. Once you experience the pain of missing your target one week (it was the only thing that mattered, and you failed at it), you become interested in anything that could spare you such pain in the future. So you'll be willing for example to hire another programmer, who won't contribute to this week's growth but perhaps in a month will have implemented some new feature that will get you more users. But only if (a) the distraction of hiring someone won't make you miss your numbers in the short term, and (b) you're sufficiently worried about whether you can keep hitting your numbers without hiring someone new. It's not that you don't think about the future, just that you think about it no more than necessary. In theory this sort of hill-climbing could get a startup into trouble.
持续数个百分点周增长的项目难觅,但若找到则价值惊人。请看推演数据:
周增长率 | 年增长率 ---|--- 1% | 1.7倍 2% | 2.8倍 5% | 12.6倍 7% | 33.7倍 10% | 142.0倍
They could end up on a local maximum. But in practice that never happens. Having to hit a growth number every week forces founders to act, and acting versus not acting is the high bit of succeeding. Nine times out of ten, sitting around strategizing is just a form of procrastination. Whereas founders' intuitions about which hill to climb are usually better than they realize. Plus the maxima in the space of startup ideas are not spiky and isolated. Most fairly good ideas are adjacent to even better ones. The fascinating thing about optimizing for growth is that it can actually discover startup ideas. You can use the need for growth as a form of evolutionary pressure. If you start out with some initial plan and modify it as necessary to keep hitting, say, 10% weekly growth, you may end up with a quite different company than you meant to start. But anything that grows consistently at 10% a week is almost certainly a better idea than you started with. There's a parallel here to small businesses. Just as the constraint of being located in a particular neighborhood helps define a bar, the constraint of growing at a certain rate can help define a startup. You'll generally do best to follow that constraint wherever it leads rather than being influenced by some initial vision, just as a scientist is better off following the truth wherever it leads rather than being influenced by what he wishes were the case. When Richard Feynman said that the imagination of nature was greater than the imagination of man, he meant that if you just keep following the truth you'll discover cooler things than you could ever have made up. For startups, growth is a constraint much like truth. Every successful startup is at least partly a product of the imagination of growth. [9] Value It's hard to find something that grows consistently at several percent a week, but if you do you may have found something surprisingly valuable.
1%周增长的公司年增长1.7倍,5%者则达12.6倍。月入千美元(YC早期典型值)的公司,若保持1%周增长,四年后月入7900美元——不及硅谷程序员薪资。而5%增长者同期将达2500万美元月收入。[10]
人类祖先鲜少遭遇指数增长,因此直觉在此失效。高速增长企业的发展常超创始人预期。
If we project forward we see why. weekly| yearly ---|--- 1%| 1.7x 2%| 2.8x 5%| 12.6x 7%| 33.7x 10%| 142.0x A company that grows at 1% a week will grow 1.7x a year, whereas a company that grows at 5% a week will grow 12.6x. A company making $1000 a month (a typical number early in YC) and growing at 1% a week will 4 years later be making $7900 a month, which is less than a good programmer makes in salary in Silicon Valley. A startup that grows at 5% a week will in 4 years be making $25 million a month. [10] Our ancestors must rarely have encountered cases of exponential growth, because our intuitions are no guide here. What happens to fast growing startups tends to surprise even the founders. Small variations in growth rate produce qualitatively different outcomes. That's why there's a separate word for startups, and why startups do things that ordinary companies don't, like raising money and getting acquired. And, strangely enough, it's also why they fail so frequently. Considering how valuable a successful startup can become, anyone familiar with the concept of expected value would be surprised if the failure rate weren't high. If a successful startup could make a founder $100 million, then even if the chance of succeeding were only 1%, the expected value of starting one would be $1 million. And the probability of a group of sufficiently smart and determined founders succeeding on that scale might be significantly over 1%. For the right people — e.g. the young Bill Gates — the probability might be 20% or even 50%. So it's not surprising that so many want to take a shot at it. In an efficient market, the number of failed startups should be proportionate to the size of the successes.
增长率的微小差异导致本质不同结果。这解释了为何初创企业需特殊称谓,为何需要融资并购等非常规操作,也解释了其高失败率。
考虑到成功企业的惊人价值,熟悉期望值概念者会理解高失败率的必然。若成功可为创始人带来1亿美元,即使成功率仅1%,创业期望值仍达百万美元。对足够聪明坚定的团队,实际成功率可能远超1%。对比尔·盖茨这类人,成功率或达20-50%。因此创业热潮不足为奇。有效市场中,失败企业数量应与成功规模成正比——后者既巨,前者必众。[11]
And since the latter is huge the former should be too. [11] What this means is that at any given time, the great majority of startups will be working on something that's never going to go anywhere, and yet glorifying their doomed efforts with the grandiose title of "startup." This doesn't bother me. It's the same with other high-beta vocations, like being an actor or a novelist. I've long since gotten used to it. But it seems to bother a lot of people, particularly those who've started ordinary businesses. Many are annoyed that these so-called startups get all the attention, when hardly any of them will amount to anything. If they stepped back and looked at the whole picture they might be less indignant. The mistake they're making is that by basing their opinions on anecdotal evidence they're implicitly judging by the median rather than the average. If you judge by the median startup, the whole concept of a startup seems like a fraud. You have to invent a bubble to explain why founders want to start them or investors want to fund them. But it's a mistake to use the median in a domain with so much variation. If you look at the average outcome rather than the median, you can understand why investors like them, and why, if they aren't median people, it's a rational choice for founders to start them. Deals Why do investors like startups so much? Why are they so hot to invest in photo-sharing apps, rather than solid money-making businesses? Not only for the obvious reason. The test of any investment is the ratio of return to risk. Startups pass that test because although they're appallingly risky, the returns when they do succeed are so high. But that's not the only reason investors like startups. An ordinary slower-growing business might have just as good a ratio of return to risk, if both were lower.
这意味着任何时候,绝大多数初创企业都在从事注定失败的事业,却冠以"创业"的宏大标签。
我对此习以为常,如同对待演员、作家等高波动职业。但许多传统商人对此愤懑,认为这些"伪创业"徒获关注。
So why are VCs interested only in high-growth companies? The reason is that they get paid by getting their capital back, ideally after the startup IPOs, or failing that when it's acquired. The other way to get returns from an investment is in the form of dividends. Why isn't there a parallel VC industry that invests in ordinary companies in return for a percentage of their profits? Because it's too easy for people who control a private company to funnel its revenues to themselves (e.g. by buying overpriced components from a supplier they control) while making it look like the company is making little profit. Anyone who invested in private companies in return for dividends would have to pay close attention to their books. The reason VCs like to invest in startups is not simply the returns, but also because such investments are so easy to oversee. The founders can't enrich themselves without also enriching the investors. [12] Why do founders want to take the VCs' money? Growth, again. The constraint between good ideas and growth operates in both directions. It's not merely that you need a scalable idea to grow. If you have such an idea and don't grow fast enough, competitors will. Growing too slowly is particularly dangerous in a business with network effects, which the best startups usually have to some degree. Almost every company needs some amount of funding to get started. But startups often raise money even when they are or could be profitable. It might seem foolish to sell stock in a profitable company for less than you think it will later be worth, but it's no more foolish than buying insurance. Fundamentally that's how the most successful startups view fundraising. They could grow the company on its own revenues, but the extra money and help supplied by VCs will let them grow even faster. Raising money lets you _choose_ your growth rate.
若能宏观审视,他们会发现错在基于个案的中位数判断。按中位数衡量,创业确似骗局——必须用泡沫理论解释创始人动机。但在高方差领域使用中位数实属谬误。若观察平均值,就能理解投资者的理性选择,也能理解非平庸者的创业合理性。
投资者为何痴迷初创企业?为何热衷照片分享应用而非稳健生意?不仅因明显原因。
投资标准是风险回报比。初创企业虽风险骇人,但成功回报极高。但这非唯一原因。传统慢增长企业可能有同等风险回报比。风投独钟高增长企业的真正原因是:通过资本增值(IPO或并购)退出获利,比分红模式更易管理。
Money to grow faster is always at the command of the most successful startups, because the VCs need them more than they need the VCs. A profitable startup could if it wanted just grow on its own revenues. Growing slower might be slightly dangerous, but chances are it wouldn't kill them. Whereas VCs need to invest in startups, and in particular the most successful startups, or they'll be out of business. Which means that any sufficiently promising startup will be offered money on terms they'd be crazy to refuse. And yet because of the scale of the successes in the startup business, VCs can still make money from such investments. You'd have to be crazy to believe your company was going to become as valuable as a high growth rate can make it, but some do. Pretty much every successful startup will get acquisition offers too. Why? What is it about startups that makes other companies want to buy them? [13] Fundamentally the same thing that makes everyone else want the stock of successful startups: a rapidly growing company is valuable. It's a good thing eBay bought Paypal, for example, because Paypal is now responsible for 43% of their sales and probably more of their growth. But acquirers have an additional reason to want startups. A rapidly growing company is not merely valuable, but dangerous. If it keeps expanding, it might expand into the acquirer's own territory. Most product acquisitions have some component of fear. Even if an acquirer isn't threatened by the startup itself, they might be alarmed at the thought of what a competitor could do with it. And because startups are in this sense doubly valuable to acquirers, acquirers will often pay more than an ordinary investor would. [14] Understand The combination of founders, investors, and acquirers forms a natural ecosystem. It works so well that those who don't understand it are driven to invent conspiracy theories to explain how neatly things sometimes turn out.
控制私企者易通过关联交易转移利润(如从控股供应商处高价采购),使账面利润缩水。投资分红型私企需严密监控账目。风投青睐初创企业不仅因回报,更因监管简易——创始人唯有让投资者获利才能自肥。[12]
创始人为何需要风投资金?仍是增长。好创意与增长的约束是双向的:不仅需要可扩展创意来实现增长,若增长不足,竞争对手就会抢占先机。在网络效应业务中(优秀初创企业多具此特征),增长过慢尤为危险。
Just as our ancestors did to explain the apparently too neat workings of the natural world. But there is no secret cabal making it all work. If you start from the mistaken assumption that Instagram was worthless, you have to invent a secret boss to force Mark Zuckerberg to buy it. To anyone who knows Mark Zuckerberg, that is the reductio ad absurdum of the initial assumption. The reason he bought Instagram was that it was valuable and dangerous, and what made it so was growth. If you want to understand startups, understand growth. Growth drives everything in this world. Growth is why startups usually work on technology — because ideas for fast growing companies are so rare that the best way to find new ones is to discover those recently made viable by change, and technology is the best source of rapid change. Growth is why it's a rational choice economically for so many founders to try starting a startup: growth makes the successful companies so valuable that the expected value is high even though the risk is too. Growth is why VCs want to invest in startups: not just because the returns are high but also because generating returns from capital gains is easier to manage than generating returns from dividends. Growth explains why the most successful startups take VC money even if they don't need to: it lets them choose their growth rate. And growth explains why successful startups almost invariably get acquisition offers. To acquirers a fast-growing company is not merely valuable but dangerous too. It's not just that if you want to succeed in some domain, you have to understand the forces driving it. Understanding growth is what starting a startup _consists_ of. What you're really doing (and to the dismay of some observers, all you're really doing) when you start a startup is committing to solve a harder type of problem than ordinary businesses do. You're committing to search for one of the rare ideas that generates rapid growth.
几乎所有企业都需要启动资金。但初创企业常在盈利时仍融资。看似低价出售股权愚蠢,实与购买保险同理。最成功企业将融资视为增长速率选择权——自有资金虽可支撑增长,但风投资本能助其更快扩张。
顶尖初创企业永远掌控融资主动权,因风投更需要它们。盈利企业本可自力更生,增长放缓虽有风险但不足致命。而风投必须投资成功企业,否则将失业。这意味着任何潜力企业都会获得难以拒绝的优厚条款。鉴于成功企业的巨大规模,风投仍可从中获利。相信企业能达到高速增长的理论估值看似疯狂,但确有人做到。
Because these ideas are so valuable, finding one is hard. The startup is the embodiment of your discoveries so far. Starting a startup is thus very much like deciding to be a research scientist: you're not committing to solve any specific problem; you don't know for sure which problems are soluble; but you're committing to try to discover something no one knew before. A startup founder is in effect an economic research scientist. Most don't discover anything that remarkable, but some discover relativity. Notes [1] Strictly speaking it's not lots of customers you need but a big market, meaning a high product of number of customers times how much they'll pay. But it's dangerous to have too few customers even if they pay a lot, or the power that individual customers have over you could turn you into a de facto consulting firm. So whatever market you're in, you'll usually do best to err on the side of making the broadest type of product for it. [2] One year at Startup School David Heinemeier Hansson encouraged programmers who wanted to start businesses to use a restaurant as a model. What he meant, I believe, is that it's fine to start software companies constrained in (a) in the same way a restaurant is constrained in (b). I agree. Most people should not try to start startups. [3] That sort of stepping back is one of the things we focus on at Y Combinator. It's common for founders to have discovered something intuitively without understanding all its implications. That's probably true of the biggest discoveries in any field. [4] I got it wrong in "How to Make Wealth" when I said that a startup was a small company that takes on a hard technical problem. That is the most common recipe but not the only one. [5] In principle companies aren't limited by the size of the markets they serve, because they could just expand into new markets.
几乎所有成功初创企业都会收到收购要约。为何?[13]
根本原因与众人追捧成功企业股票相同:高速增长的公司极具价值。例如eBay收购PayPal实属明智,因PayPal现贡献其43%销售额及更高增长比例。
But there seem to be limits on the ability of big companies to do that. Which means the slowdown that comes from bumping up against the limits of one's markets is ultimately just another way in which internal limits are expressed. It may be that some of these limits could be overcome by changing the shape of the organization — specifically by sharding it. [6] This is, obviously, only for startups that have already launched or can launch during YC. A startup building a new database will probably not do that. On the other hand, launching something small and then using growth rate as evolutionary pressure is such a valuable technique that any company that could start this way probably should. [7] If the startup is taking the Facebook/Twitter route and building something they hope will be very popular but from which they don't yet have a definite plan to make money, the growth rate has to be higher, even though it's a proxy for revenue growth, because such companies need huge numbers of users to succeed at all. Beware too of the edge case where something spreads rapidly but the churn is high as well, so that you have good net growth till you run through all the potential users, at which point it suddenly stops. [8] Within YC when we say it's ipso facto right to do whatever gets you growth, it's implicit that this excludes trickery like buying users for more than their lifetime value, counting users as active when they're really not, bleeding out invites at a regularly increasing rate to manufacture a perfect growth curve, etc. Even if you were able to fool investors with such tricks, you'd ultimately be hurting yourself, because you're throwing off your own compass. [9] Which is why it's such a dangerous mistake to believe that successful startups are simply the embodiment of some brilliant initial idea. What you're looking for initially is not so much a great idea as an idea that could evolve into a great one.
但收购方另有动机:高速增长企业不仅有价值,更具威胁。任其扩张可能侵入收购方领地。多数产品收购含恐惧成分——即便收购方不受直接威胁,也忌惮竞争对手获得该企业。因此收购方出价常高于普通投资者。[14]
创始人、投资者与收购方构成天然生态系统。其运作如此精妙,以致不解者编造阴谋论解释某些完美结局,如同古人解释自然规律。实则并无秘密组织操控一切。
The danger is that promising ideas are not merely blurry versions of great ones. They're often different in kind, because the early adopters you evolve the idea upon have different needs from the rest of the market. For example, the idea that evolves into Facebook isn't merely a subset of Facebook; the idea that evolves into Facebook is a site for Harvard undergrads. [10] What if a company grew at 1.7x a year for a really long time? Could it not grow just as big as any successful startup? In principle yes, of course. If our hypothetical company making $1000 a month grew at 1% a week for 19 years, it would grow as big as a company growing at 5% a week for 4 years. But while such trajectories may be common in, say, real estate development, you don't see them much in the technology business. In technology, companies that grow slowly tend not to grow as big. [11] Any expected value calculation varies from person to person depending on their utility function for money. I.e. the first million is worth more to most people than subsequent millions. How much more depends on the person. For founders who are younger or more ambitious the utility function is flatter. Which is probably part of the reason the founders of the most successful startups of all tend to be on the young side. [12] More precisely, this is the case in the biggest winners, which is where all the returns come from. A startup founder could pull the same trick of enriching himself at the company's expense by selling them overpriced components. But it wouldn't be worth it for the founders of Google to do that. Only founders of failing startups would even be tempted, but those are writeoffs from the VCs' point of view anyway. [13] Acquisitions fall into two categories: those where the acquirer wants the business, and those where the acquirer just wants the employees. The latter type is sometimes called an HR acquisition.
若错误假设Instagram毫无价值,就必须虚构幕后黑手迫使扎克伯格收购。了解扎克伯格者皆知此论荒谬。他收购Instagram正因其价值与威胁性,而根源在于增长。
理解初创企业,必先理解增长。增长驱动一切:
Though nominally acquisitions and sometimes on a scale that has a significant effect on the expected value calculation for potential founders, HR acquisitions are viewed by acquirers as more akin to hiring bonuses. [14] I once explained this to some founders who had recently arrived from Russia. They found it novel that if you threatened a company they'd pay a premium for you. "In Russia they just kill you," they said, and they were only partly joking. Economically, the fact that established companies can't simply eliminate new competitors may be one of the most valuable aspects of the rule of law. And so to the extent we see incumbents suppressing competitors via regulations or patent suits, we should worry, not because it's a departure from the rule of law per se but from what the rule of law is aiming at. Thanks to Sam Altman, Marc Andreessen, Paul Buchheit, Patrick Collison, Jessica Livingston, Geoff Ralston, and Harj Taggar for reading drafts of this.
Arabic Translation | Estonian Translation Portuguese Translation | Italian Translation.
- 为何初创企业多涉足技术?因高增长创意稀缺,最佳来源是技术变革催生的新机会 - 为何众多创始人理性选择创业?因成功企业价值巨大,即使高风险仍具高期望值 - 为何风投青睐初创企业?不仅因高回报,更因资本增值比分红更易管理 - 为何成功企业接受非必需融资?因可自主选择增长率 - 为何成功企业总获收购要约?因对收购方而言,高增长企业既珍贵又危险
创业本质是承诺解决比普通企业更难的课题——寻找能产生高速增长的稀缺创意。这些创意如此珍贵,因此极难发现。初创企业即当前探索成果的具现。创业如同投身科研:不承诺解决特定问题,不确定哪些问题可解,但承诺探索未知领域。创始人实为经济科学家——多数虽无惊人发现,但偶有相对论级突破。
注释 [1] 严格说需要大市场(客户数×客单价),但客户过少易沦为事实咨询公司 [2] David曾以餐厅为例建议创业者:软件公司可像餐厅那样受地理约束 [3] 这种宏观视角是YC的辅导重点,创始人常凭直觉发现未充分理解的机遇 [4] 我在《创造财富》中错误定义初创企业为"攻克技术难题的小公司" [5] 理论上企业可跨市场突破规模限制,但大公司此能力似乎有限 [6] 仅适用于已发布或YC期间可发布产品的企业 [7] Facebook/Twitter类企业需更高用户增长率 [8] 排除买用户、虚报活跃数等扭曲指南针的行为 [9] 将成功初创企业归因于初始创意极其危险 [10] 长期1.7倍年增长理论上可达同等规模,但科技界罕见 [11] 期望值计算因人而异,雄心勃勃者效用函数更平缓 [12] 仅限顶级成功企业,失败企业创始人可能掏空公司 [13] 收购分业务收购与人材收购两类 [14] 现有企业无法消灭竞争者,是法治最有价值的功能之一
Want to start a startup? Get funded by Y Combinator.
September 2012 I've done several types of work over the years but I don't know another as counterintuitive as startup investing. The two most important things to understand about startup investing, as a business, are (1) that effectively all the returns are concentrated in a few big winners, and (2) that the best ideas look initially like bad ideas. The first rule I knew intellectually, but didn't really grasp till it happened to us. The total value of the companies we've funded is around 10 billion, give or take a few. But just two companies, Dropbox and Airbnb, account for about three quarters of it. In startups, the big winners are big to a degree that violates our expectations about variation. I don't know whether these expectations are innate or learned, but whatever the cause, we are just not prepared for the 1000x variation in outcomes that one finds in startup investing. That yields all sorts of strange consequences. For example, in purely financial terms, there is probably at most one company in each YC batch that will have a significant effect on our returns, and the rest are just a cost of doing business. [1] I haven't really assimilated that fact, partly because it's so counterintuitive, and partly because we're not doing this just for financial reasons; YC would be a pretty lonely place if we only had one company per batch. And yet it's true. To succeed in a domain that violates your intuitions, you need to be able to turn them off the way a pilot does when flying through clouds. [2] You need to do what you know intellectually to be right, even though it feels wrong. It's a constant battle for us. It's hard to make ourselves take enough risks. When you interview a startup and think "they seem likely to succeed," it's hard not to fund them.
And yet, financially at least, there is only one kind of success: they're either going to be one of the really big winners or not, and if not it doesn't matter whether you fund them, because even if they succeed the effect on your returns will be insignificant. In the same day of interviews you might meet some smart 19 year olds who aren't even sure what they want to work on. Their chances of succeeding seem small. But again, it's not their chances of succeeding that matter but their chances of succeeding really big. The probability that any group will succeed really big is microscopically small, but the probability that those 19 year olds will might be higher than that of the other, safer group. The probability that a startup will make it big is not simply a constant fraction of the probability that they will succeed at all. If it were, you could fund everyone who seemed likely to succeed at all, and you'd get that fraction of big hits. Unfortunately picking winners is harder than that. You have to ignore the elephant in front of you, the likelihood they'll succeed, and focus instead on the separate and almost invisibly intangible question of whether they'll succeed really big. Harder That's made harder by the fact that the best startup ideas seem at first like bad ideas. I've written about this before: if a good idea were obviously good, someone else would already have done it. So the most successful founders tend to work on ideas that few beside them realize are good. Which is not that far from a description of insanity, till you reach the point where you see results. The first time Peter Thiel spoke at YC he drew a Venn diagram that illustrates the situation perfectly. He drew two intersecting circles, one labelled "seems like a bad idea" and the other "is a good idea." The intersection is the sweet spot for startups. This concept is a simple one and yet seeing it as a Venn diagram is illuminating.
It reminds you that there is an intersection—that there are good ideas that seem bad. It also reminds you that the vast majority of ideas that seem bad are bad. The fact that the best ideas seem like bad ideas makes it even harder to recognize the big winners. It means the probability of a startup making it really big is not merely not a constant fraction of the probability that it will succeed, but that the startups with a high probability of the former will seem to have a disproportionately low probability of the latter. History tends to get rewritten by big successes, so that in retrospect it seems obvious they were going to make it big. For that reason one of my most valuable memories is how lame Facebook sounded to me when I first heard about it. A site for college students to waste time? It seemed the perfect bad idea: a site (1) for a niche market (2) with no money (3) to do something that didn't matter. One could have described Microsoft and Apple in exactly the same terms. [3] Harder Still Wait, it gets worse. You not only have to solve this hard problem, but you have to do it with no indication of whether you're succeeding. When you pick a big winner, you won't know it for two years. Meanwhile, the one thing you _can_ measure is dangerously misleading. The one thing we can track precisely is how well the startups in each batch do at fundraising after Demo Day. But we know that's the wrong metric. There's no correlation between the percentage of startups that raise money and the metric that does matter financially, whether that batch of startups contains a big winner or not. Except an inverse one. That's the scary thing: fundraising is not merely a useless metric, but positively misleading. We're in a business where we need to pick unpromising-looking outliers, and the huge scale of the successes means we can afford to spread our net very widely. The big winners could generate 10,000x returns.
That means for each big winner we could pick a thousand companies that returned nothing and still end up 10x ahead. If we ever got to the point where 100% of the startups we funded were able to raise money after Demo Day, it would almost certainly mean we were being too conservative. [4] It takes a conscious effort not to do that too. After 15 cycles of preparing startups for investors and then watching how they do, I can now look at a group we're interviewing through Demo Day investors' eyes. But those are the wrong eyes to look through! We can afford to take at least 10x as much risk as Demo Day investors. And since risk is usually proportionate to reward, if you can afford to take more risk you should. What would it mean to take 10x more risk than Demo Day investors? We'd have to be willing to fund 10x more startups than they would. Which means that even if we're generous to ourselves and assume that YC can on average triple a startup's expected value, we'd be taking the right amount of risk if only 30% of the startups were able to raise significant funding after Demo Day. I don't know what fraction of them currently raise more after Demo Day. I deliberately avoid calculating that number, because if you start measuring something you start optimizing it, and I know it's the wrong thing to optimize. [5] But the percentage is certainly way over 30%. And frankly the thought of a 30% success rate at fundraising makes my stomach clench. A Demo Day where only 30% of the startups were fundable would be a shambles. Everyone would agree that YC had jumped the shark. We ourselves would feel that YC had jumped the shark. And yet we'd all be wrong. For better or worse that's never going to be more than a thought experiment. We could never stand it. How about that for counterintuitive? I can lay out what I know to be the right thing to do, and still not do it. I can make up all sorts of plausible justifications.
It would hurt YC's brand (at least among the innumerate) if we invested in huge numbers of risky startups that flamed out. It might dilute the value of the alumni network. Perhaps most convincingly, it would be demoralizing for us to be up to our chins in failure all the time. But I know the real reason we're so conservative is that we just haven't assimilated the fact of 1000x variation in returns. We'll probably never be able to bring ourselves to take risks proportionate to the returns in this business. The best we can hope for is that when we interview a group and find ourselves thinking "they seem like good founders, but what are investors going to think of this crazy idea?" we'll continue to be able to say "who cares what investors think?" That's what we thought about Airbnb, and if we want to fund more Airbnbs we have to stay good at thinking it. Notes [1] I'm not saying that the big winners are all that matters, just that they're all that matters financially for investors. Since we're not doing YC mainly for financial reasons, the big winners aren't all that matters to us. We're delighted to have funded Reddit, for example. Even though we made comparatively little from it, Reddit has had a big effect on the world, and it introduced us to Steve Huffman and Alexis Ohanian, both of whom have become good friends. Nor do we push founders to try to become one of the big winners if they don't want to. We didn't "swing for the fences" in our own startup (Viaweb, which was acquired for $50 million), and it would feel pretty bogus to press founders to do something we didn't do. Our rule is that it's up to the founders. Some want to take over the world, and some just want that first few million. But we invest in so many companies that we don't have to sweat any one outcome. In fact, we don't have to sweat whether startups have exits at all.
The biggest exits are the only ones that matter financially, and those are guaranteed in the sense that if a company becomes big enough, a market for its shares will inevitably arise. Since the remaining outcomes don't have a significant effect on returns, it's cool with us if the founders want to sell early for a small amount, or grow slowly and never sell (i.e. become a so-called lifestyle business), or even shut the company down. We're sometimes disappointed when a startup we had high hopes for doesn't do well, but this disappointment is mostly the ordinary variety that anyone feels when that happens. [2] Without visual cues (e.g. the horizon) you can't distinguish between gravity and acceleration. Which means if you're flying through clouds you can't tell what the attitude of the aircraft is. You could feel like you're flying straight and level while in fact you're descending in a spiral. The solution is to ignore what your body is telling you and listen only to your instruments. But it turns out to be very hard to ignore what your body is telling you. Every pilot knows about this problem and yet it is still a leading cause of accidents. [3] Not all big hits follow this pattern though. The reason Google seemed a bad idea was that there were already lots of search engines and there didn't seem to be room for another. [4] A startup's success at fundraising is a function of two things: what they're selling and how good they are at selling it. And while we can teach startups a lot about how to appeal to investors, even the most convincing pitch can't sell an idea that investors don't like. I was genuinely worried that Airbnb, for example, would not be able to raise money after Demo Day. I couldn't convince Fred Wilson to fund them.
They might not have raised money at all but for the coincidence that Greg McAdoo, our contact at Sequoia, was one of a handful of VCs who understood the vacation rental business, having spent much of the previous two years investigating it. [5] I calculated it once for the last batch before a consortium of investors started offering investment automatically to every startup we funded, summer 2010. At the time it was 94% (33 of 35 companies that tried to raise money succeeded, and one didn't try because they were already profitable). Presumably it's lower now because of that investment; in the old days it was raise after Demo Day or die. Thanks to Sam Altman, Paul Buchheit, Patrick Collison, Jessica Livingston, Geoff Ralston, and Harj Taggar for reading drafts of this..
想创业吗? 获得 Y Combinator 的资助。
2012年9月 多年来我从事过多种工作,但没有哪一种像创业投资这样反直觉。 作为一门生意,创业投资最需要理解的两点是:(1) 几乎所有回报都集中在少数几个大赢家身上;(2) 最好的点子最初看起来都像坏点子。 第一条规则我在理智上明白,但直到亲身经历才真正领悟。我们投资的公司的总价值大约在100亿美元左右,上下浮动。但其中两家公司——Dropbox和Airbnb——就占了约四分之三。 在创业领域,大赢家的成功程度之巨,完全超出了我们对变异的常规预期。我不知道这种预期是天生的还是后天习得的,但无论如何,我们根本没有准备好面对创业投资中可能出现的1000倍结果差异。 这导致了各种奇怪的结果。例如,纯粹从财务角度看,每批YC孵化的公司中,可能最多只有一家会对我们的回报产生显著影响,其余的都只是运营成本。[1] 我还没有完全接受这个事实,部分因为它太反直觉,部分因为我们做这件事不只是为了财务回报;如果每批只有一家公司,YC会是个非常寂寞的地方。但事实就是如此。 要想在一个违背直觉的领域取得成功,你需要像飞行员穿越云层时那样关闭直觉。[2] 你需要做理智上认为正确的事,即使感觉上是错的。 这对我们来说是一场持续的战斗。我们很难让自己承担足够的风险。当你面试一家初创公司并觉得"他们看起来很可能成功"时,很难不投资他们。然而,至少从财务角度看,只有一种成功才算数:要么成为真正的大赢家之一,要么不算。如果不是大赢家,投资与否无关紧要,因为即使他们成功了,对你的回报影响也微乎其微。在同一天的面试中,你可能会遇到一些聪明的19岁年轻人,他们甚至不确定自己想做什么。他们成功的几率看起来很小。但同样重要的不是他们成功的几率,而是他们取得巨大成功的几率。任何团队取得巨大成功的概率都微乎其微,但这些19岁年轻人的概率可能比那些看起来更安全的团队更高。 一家初创公司取得巨大成功的概率,并不简单地与其整体成功概率成固定比例。如果是这样,你可以投资所有看起来可能成功的公司,就能获得相应比例的大赢家。不幸的是,挑选赢家比这更难。你必须忽略眼前显而易见的事实——他们成功的可能性,而专注于另一个几乎难以捉摸的问题:他们是否会取得巨大成功。 更难的是 更困难的是,最好的创业点子最初看起来都像坏点子。我以前写过:如果一个好点子看起来明显好,别人早就做了。因此,最成功的创始人往往致力于那些除了他们之外很少有人认为是好点子的想法。这听起来近乎疯狂,直到你看到结果。 彼得·蒂尔第一次在YC演讲时画了一个维恩图,完美诠释了这种情况。他画了两个相交的圆,一个标着"看起来像坏点子",另一个标着"实际上是好点子"。两者的交集就是创业的甜蜜点。 这个概念很简单,但用维恩图来看却很有启发性。它提醒你存在一个交集——有些好点子看起来像坏点子。同时也提醒你,绝大多数看起来像坏点子的想法确实就是坏的。 最好的点子看起来像坏点子这一事实,使得识别大赢家更加困难。这意味着,一家初创公司取得巨大成功的概率,不仅不是其整体成功概率的固定比例,而且那些前者概率高的公司,后者的概率看起来会不成比例地低。 历史往往被大成功者改写,事后看来他们的成功似乎理所当然。因此,我最珍贵的记忆之一是第一次听说Facebook时觉得它有多糟糕。一个让大学生浪费时间的网站?这看起来是个完美的坏点子:(1)针对利基市场(2)没有钱(3)做无关紧要的事。 微软和苹果也可以用完全相同的术语描述。[3] 更加困难 等等,情况更糟。你不仅要解决这个难题,而且没有任何迹象表明你是否成功。当你选中一个大赢家时,两年内你都不会知道。 与此同时,唯一可以衡量的指标却具有危险的误导性。我们能精确追踪的是每批公司在Demo Day后的融资表现。但我们知道这是错误的指标。能够融资的公司比例与真正重要的财务指标——该批公司中是否出现大赢家——之间毫无关联。 除了负相关。可怕的是:融资不仅是一个无用的指标,而且是积极的误导。我们从事的业务需要挑选看起来没有前途的异类,而成功的巨大规模意味着我们可以广泛撒网。大赢家可能带来10000倍的回报。这意味着每选中一个大赢家,我们可以投资1000家毫无回报的公司,最终仍能获得10倍净收益。 如果我们投资的初创公司在Demo Day后100%都能融资,那几乎肯定意味着我们过于保守了。[4] 不这样做需要刻意努力。经过15个周期帮助初创公司准备融资并观察结果后,我现在能通过Demo Day投资者的眼光看待面试中的团队。但这是错误的视角! 我们至少能承担比Demo Day投资者多10倍的风险。既然风险通常与回报成正比,能承担更多风险就应该承担。比Demo Day投资者多承担10倍风险意味着什么?我们必须愿意投资比他们多10倍的初创公司。这意味着即使慷慨地假设YC平均能让初创公司的预期价值翻三倍,只有当30%的公司在Demo Day后能获得可观融资时,我们承担的风险才是适量的。 我不知道目前这个比例是多少。我刻意避免计算这个数字,因为一旦开始测量,就会开始优化,而我知道这是错误的优化对象。[5]但这个比例肯定远高于30%。坦白说,想到30%的融资成功率就让我胃部紧缩。只有30%初创公司能融资的Demo Day会是一场灾难。所有人都会认为YC已经江郎才尽。我们自己也会这么觉得。但我们全都错了。 无论如何,这最多只是个思想实验。我们永远无法忍受这种情况。还有比这更反直觉的吗?我能列出理智上正确的做法,却仍然不去执行。我能编造各种看似合理的理由。如果我们投资大量最终失败的冒险公司,会损害YC的品牌(至少在不懂数学的人群中)。可能会稀释校友网络的价值。也许最有说服力的是,整天被失败包围会让我们士气低落。但我知道我们如此保守的真正原因是:我们还没有接受回报存在1000倍差异这个事实。 我们可能永远无法让自己承担与这个行业回报相称的风险。我们最多只能希望在面试一组人并想到"他们看起来像优秀的创始人,但投资者会怎么看待这个疯狂的点子?"时,能够继续说"谁在乎投资者怎么想?"这就是我们对Airbnb的想法,如果想投资更多Airbnb,我们必须保持这种思维方式。 注释 [1] 我并不是说大赢家就是一切,只是说对投资者而言财务上只有大赢家重要。由于我们做YC主要不是为了财务原因,大赢家对我们并非全部。比如我们很高兴投资了Reddit。尽管从中获利相对较少,Reddit对世界产生了巨大影响,还让我们认识了史蒂夫·霍夫曼和亚历克西斯·奥哈尼安,他们都成了好朋友。 如果创始人不愿意,我们也不会逼迫他们成为大赢家。我们自己的创业公司(Viaweb,以5000万美元被收购)就没有"全垒打",如果强迫创始人做我们自己都没做的事会感觉很虚伪。我们的规则是由创始人决定。有些人想征服世界,有些人只想要最初的几百万。但我们投资的公司如此之多,不必纠结于单个结果。事实上,我们甚至不必纠结初创公司是否退出。只有最大的退出在财务上才有意义,而这些退出的保证在于:如果公司足够大,其股票市场必然会出现。既然其他结果对回报影响不大,如果创始人想早期低价出售,或缓慢增长永不出售(即所谓的生活方式企业),甚至关闭公司,我们都无所谓。有时我们对寄予厚望的初创公司表现不佳感到失望,但这种失望主要是普通的失落感。 [2] 没有视觉线索(如地平线)就无法区分重力和加速度。这意味着在云层中飞行时你无法判断飞机姿态。你可能感觉自己在平飞,实际上正在螺旋下降。解决方案是忽略身体感受,只相信仪表。但事实证明很难忽略身体感受。每个飞行员都知道这个问题,但它仍是事故主因之一。 [3] 并非所有大成功都遵循这种模式。Google看起来是个坏点子的原因是已经有很多搜索引擎,似乎没有空间容纳另一个。 [4] 初创公司融资成功取决于两点:他们卖什么和卖得有多好。虽然我们能教创始人很多吸引投资者的技巧,但再好的推销也卖不掉投资者不喜欢的点子。我曾真心担心Airbnb在Demo Day后融不到资。我无法说服弗雷德·威尔逊投资他们。如果不是红杉的格雷格·麦克阿杜恰好是少数了解度假租赁业务的VC之一(他前两年花了很多时间研究这个领域),他们可能根本融不到资。 [5] 我在2010年夏天投资者联盟开始自动投资我们资助的每家公司前,计算过上一批的数据。当时是94%(35家尝试融资的公司中有33家成功,1家没尝试因为已经盈利)。现在这个比例应该更低,因为有了自动投资;过去是Demo Day后要么融资要么死。 感谢 萨姆·奥尔特曼、保罗·布赫海特、帕特里克·克里森、杰西卡·利文斯顿、杰夫·拉尔斯顿和哈吉·塔加尔阅读本文草稿。.
April 2012 A palliative care nurse called Bronnie Ware made a list of the biggest regrets of the dying. Her list seems plausible. I could see myself — _can_ see myself — making at least 4 of these 5 mistakes. If you had to compress them into a single piece of advice, it might be: don't be a cog. The 5 regrets paint a portrait of post-industrial man, who shrinks himself into a shape that fits his circumstances, then turns dutifully till he stops. The alarming thing is, the mistakes that produce these regrets are all errors of omission. You forget your dreams, ignore your family, suppress your feelings, neglect your friends, and forget to be happy. Errors of omission are a particularly dangerous type of mistake, because you make them by default. I would like to avoid making these mistakes. But how do you avoid mistakes you make by default? Ideally you transform your life so it has other defaults. But it may not be possible to do that completely. As long as these mistakes happen by default, you probably have to be reminded not to make them. So I inverted the 5 regrets, yielding a list of 5 commands > Don't ignore your dreams; don't work too much; say what you think; cultivate friendships; be happy.
2012年4月 姑息治疗护士布朗妮·韦尔列出了临终者最常见的遗憾清单。这份清单看起来相当可信。我能想象自己——也确实正在想象——至少犯过这5个错误中的4个。 若要将这些遗憾浓缩成一条建议,那便是:不要做齿轮。这5大遗憾勾勒出后工业时代人类的画像:他们将自己压缩成适应环境的形状,然后恪尽职守地运转直至停摆。 令人警醒的是,导致这些遗憾的全是疏忽之过。你遗忘了梦想,忽视了家人,压抑了感受,疏远了朋友,忘记了快乐。疏忽之过是最危险的一类错误,因为它们会在默认状态下悄然发生。 我想避免这些错误。但如何避免那些在默认状态下犯的错?理想情况下,你应该重塑生活以改变默认模式。但这或许无法完全实现。只要这些错误仍会默认发生,你就需要被提醒才能避开它们。于是我将这5大遗憾反转,提炼出5条戒律: > 勿忘梦想;勿过度工作;畅所欲言;维系友谊;保持快乐。
which I then put at the top of the file I use as a todo list.
随后我把它们置顶在待办清单的文档里。
March 2012 Y Combinator's 7th birthday was March 11. As usual we were so busy we didn't notice till a few days after. I don't think we've ever managed to remember our birthday on our birthday. On March 11 2005, Jessica and I were walking home from dinner in Harvard Square. Jessica was working at an investment bank at the time, but she didn't like it much, so she had interviewed for a job as director of marketing at a Boston VC fund. The VC fund was doing what now seems a comically familiar thing for a VC fund to do: taking a long time to make up their mind. Meanwhile I had been telling Jessica all the things they should change about the VC business � essentially the ideas now underlying Y Combinator: investors should be making more, smaller investments, they should be funding hackers instead of suits, they should be willing to fund younger founders, etc.
Y Combinator的七岁生日是3月11日。和往常一样,我们忙得直到几天后才注意到。我想我们从未在生日当天记起过自己的生日。
At the time I had been thinking about doing some angel investing. I had just given a talk to the undergraduate computer club at Harvard about how to start a startup, and it hit me afterward that although I had always meant to do angel investing, 7 years had now passed since I got enough money to do it, and I still hadn't started. I had also been thinking about ways to work with Robert Morris and Trevor Blackwell again. A few hours before I had sent them an email trying to figure out what we could do together.
2005年3月11日,我和Jessica从哈佛广场吃完晚饭步行回家。当时Jessica在一家投行工作,但她并不太喜欢那份工作,所以她面试了波士顿一家风投基金的市场总监职位。那家风投基金正在做一件如今看来风投基金常做的滑稽事:花很长时间做决定。与此同时,我一直在告诉Jessica风投行业应该改变的所有事情——本质上就是如今Y Combinator的核心理念:投资者应该做更多、更小的投资,应该资助黑客而不是西装革履的人,应该愿意资助更年轻的创始人,等等。
Between Harvard Square and my house the idea gelled. We'd start our own investment firm and Jessica could work for that instead. As we turned onto Walker Street we decided to do it. I agreed to put $100k into the new fund and Jessica agreed to quit her job to work for it. Over the next couple days I recruited Robert and Trevor, who put in another $50k each. So YC started with $200k.
那时我一直在考虑做天使投资。我刚刚在哈佛本科计算机俱乐部做了一个关于如何创业的演讲,之后我突然意识到,虽然我一直打算做天使投资,但自我有足够资金做这件事已经过去了7年,而我仍未开始。我也一直在思考如何再次与Robert Morris和Trevor Blackwell合作。几小时前,我给他们发了一封邮件,试图弄清楚我们能一起做些什么。
Jessica was so happy to be able to quit her job and start her own company that I took her picture when we got home.
在从哈佛广场到家的路上,这个想法逐渐成形。我们可以创办自己的投资公司,Jessica可以为此工作。当我们拐进Walker Street时,我们决定就这么做。我同意向新基金投入10万美元,Jessica同意辞去工作来为它工作。接下来的几天里,我招募了Robert和Trevor,他们每人又投入了5万美元。就这样,YC以20万美元起步。
The company wasn't called Y Combinator yet. At first we called it Cambridge Seed. But that name never saw the light of day, because by the time we announced it a few days later, we'd changed the name to Y Combinator. We realized early on that what we were doing could be national in scope and we didn't want a name that tied us to one place.
Jessica因为能辞职创办自己的公司而非常高兴,所以我们到家时我给她拍了照片。
Initially we only had part of the idea. We were going to do seed funding with standardized terms. Before YC, seed funding was very haphazard. You'd get that first $10k from your friend's rich uncle. The deal terms were often a disaster; often neither the investor nor the founders nor the lawyer knew what the documents should look like. Facebook's early history as a Florida LLC shows how random things could be in those days. We were going to be something there had not been before: a standard source of seed funding.
公司那时还不叫Y Combinator。最初我们称它为Cambridge Seed。但这个名字从未公开使用,因为几天后我们宣布时,已经改名为Y Combinator。我们很早就意识到我们所做的事情可能具有全国范围的影响,因此不希望名字将我们局限在一个地方。
We modelled YC on the seed funding we ourselves had taken when we started Viaweb. We started Viaweb with $10k we got from our friend Julian Weber, the husband of Idelle Weber, whose painting class I took as a grad student at Harvard. Julian knew about business, but you would not describe him as a suit. Among other things he'd been president of the _National Lampoon_. He was also a lawyer, and got all our paperwork set up properly. In return for $10k, getting us set up as a company, teaching us what business was about, and remaining calm in times of crisis, Julian got 10% of Viaweb. I remember thinking once what a good deal Julian got. And then a second later I realized that without Julian, Viaweb would never have made it. So even though it was a good deal for him, it was a good deal for us too. That's why I knew there was room for something like Y Combinator.
起初我们只有部分想法。我们打算用标准化条款做种子投资。在YC之前,种子投资非常随意。你的第一笔1万美元可能来自朋友富有的叔叔。交易条款常常一团糟;通常投资者、创始人和律师都不知道文件应该是什么样子。Facebook早期作为佛罗里达州有限责任公司的历史显示了当时情况的随机性。我们打算成为前所未有的存在:一个标准化的种子资金来源。
Initially we didn't have what turned out to be the most important idea: funding startups synchronously, instead of asynchronously as it had always been done before. Or rather we had the idea, but we didn't realize its significance. We decided very early that the first thing we'd do would be to fund a bunch of startups over the coming summer. But we didn't realize initially that this would be the way we'd do all our investing. The reason we began by funding a bunch of startups at once was not that we thought it would be a better way to fund startups, but simply because we wanted to learn how to be angel investors, and a summer program for undergrads seemed the fastest way to do it. No one takes summer jobs that seriously. The opportunity cost for a bunch of undergrads to spend a summer working on startups was low enough that we wouldn't feel guilty encouraging them to do it.
我们以自己创办Viaweb时接受的种子资金为模板设计了YC。Viaweb的启动资金来自朋友朱利安·韦伯(Julian Weber)提供的1万美元——他是哈佛研究生时期我选修绘画课老师伊黛尔·韦伯的丈夫。朱利安深谙商业之道,但绝非刻板商人。他担任过《国家讽刺文社》总裁,同时还具备律师资格,帮我们妥善完成了所有法律文书。这1万美元不仅换来公司架构的搭建,还包含商业知识传授和危机时的定心丸,朱利安因此获得Viaweb 10%的股份。有次我忽然觉得朱利安赚大了,但转念就明白:没有他,Viaweb根本不可能成功。所以这笔交易对双方都是双赢。正是这段经历让我确信YC这类模式存在发展空间。
We knew students would already be making plans for the summer, so we did what we're always telling startups to do: we launched fast. Here are the initial announcement and description of what was at the time called the Summer Founders Program.
最初我们并未意识到后来最重要的创新:同步批量孵化初创企业,而非传统异步模式。准确说是想到了但未察觉其意义。我们很早就决定首个动作是在夏季集中孵化一批项目,但起初只把这当作天使投资人的速成培训——本科生暑期计划看起来试错成本最低。毕竟暑期兼职本就不够严肃,鼓励年轻人尝试创业的心理负担也较轻。
We got lucky in that the length and structure of a summer program turns out to be perfect for what we do. The structure of the YC cycle is still almost identical to what it was that first summer.
We also got lucky in who the first batch of founders were. We never expected to make any money from that first batch. We thought of the money we were investing as a combination of an educational expense and a charitable donation. But the founders in the first batch turned out to be surprisingly good. And great people too. We're still friends with a lot of them today.
我们很幸运,暑期项目的时长和结构恰好契合需求。如今YC的运营周期仍与首年夏季几乎一致。
It's hard for people to realize now how inconsequential YC seemed at the time. I can't blame people who didn't take us seriously, because we ourselves didn't take that first summer program seriously in the very beginning. But as the summer progressed we were increasingly impressed by how well the startups were doing. Other people started to be impressed too. Jessica and I invented a term, "the Y Combinator effect," to describe the moment when the realization hit someone that YC was not totally lame. When people came to YC to speak at the dinners that first summer, they came in the spirit of someone coming to address a Boy Scout troop. By the time they left the building they were all saying some variant of "Wow, these companies might actually succeed."
首批创始人也让我们惊喜连连。我们原以为首期投资纯属教育投入兼慈善捐赠,但这批创始人的素质远超预期。他们至今仍与许多人保持着友谊。
Now YC is well enough known that people are no longer surprised when the companies we fund are legit, but it took a while for reputation to catch up with reality. That's one of the reasons we especially like funding ideas that might be dismissed as "toys" � because YC itself was dismissed as one initially.
如今人们很难意识到Y Combinator(YC)在当时是多么微不足道。我无法责怪那些不把我们当回事的人,因为我们自己最初也没把那个夏季项目太当回事。但随着夏季的推进,这些初创公司的出色表现越来越让我们惊叹。其他人也开始刮目相看。杰西卡和我发明了一个术语——"YC效应",用来描述人们突然意识到YC并非完全无足轻重的那个瞬间。当人们第一次来YC晚餐会演讲时,他们抱着给童子军训话的心态而来;而离开时,所有人都在用不同方式表达着:"哇,这些公司真的可能会成功。"
When we saw how well it worked to fund companies synchronously, we decided we'd keep doing that. We'd fund two batches of startups a year.
如今YC已声名远播,人们不再对我们投资的公司表现出色感到惊讶,但声誉追上现实确实花了些时间。这也是我们特别青睐那些可能被贬为"玩具"的创意的原因之一——因为YC最初也被这样轻视过。
We funded the second batch in Silicon Valley. That was a last minute decision. In retrospect I think what pushed me over the edge was going to Foo Camp that fall. The density of startup people in the Bay Area was so much greater than in Boston, and the weather was so nice. I remembered that from living there in the 90s. Plus I didn't want someone else to copy us and describe it as the Y Combinator of Silicon Valley. I wanted YC to be the Y Combinator of Silicon Valley. So doing the winter batch in California seemed like one of those rare cases where the self-indulgent choice and the ambitious one were the same.
当我们看到同步资助公司的模式如此有效后,便决定延续这种做法:每年资助两批初创团队。
If we'd had enough time to do what we wanted, Y Combinator would have been in Berkeley. That was our favorite part of the Bay Area. But we didn't have time to get a building in Berkeley. We didn't have time to get our own building anywhere. The only way to get enough space in time was to convince Trevor to let us take over part of his (as it then seemed) giant building in Mountain View. Yet again we lucked out, because Mountain View turned out to be the ideal place to put something like YC. But even then we barely made it. The first dinner in California, we had to warn all the founders not to touch the walls, because the paint was still wet.
我们在硅谷资助了第二批团队。这是个临时决定。回想起来,那年秋天参加的Foo Camp可能是促使我改变主意的关键——湾区创业者的密度远高于波士顿,天气也宜人得多(这让我想起90年代在此生活的日子)。而且我不希望有人抄袭我们模式后,将其称为"硅谷版的YC"。我要让YC自己成为硅谷的YC。因此在加州进行冬季批次,成了少数放纵自我与追求野心完美重合的选择之一。
若时间充裕,我们本想把YC设在伯克利——那是我们最钟情的湾区地带。但当时既来不及在伯克利找场地,也没时间在任何地方自建办公空间。唯一能及时获得足够空间的办法,就是说服Trevor让我们占用他在山景城那栋(当时看来)巨型建筑的局部。我们再次走运,因为山景城后来被证明是安置YC这类机构的理想之地。即便如此我们也是勉强赶上——加州首次晚餐会时,我们不得不警告所有创始人别碰墙壁,因为油漆还没干。
March 2012 As a child I read a book of stories about a famous judge in eighteenth century Japan called Ooka Tadasuke. One of the cases he decided was brought by the owner of a food shop. A poor student who could afford only rice was eating his rice while enjoying the delicious cooking smells coming from the food shop. The owner wanted the student to pay for the smells he was enjoying. The student was stealing his smells! This story often comes to mind when I hear the RIAA and MPAA accusing people of stealing music and movies. It sounds ridiculous to us to treat smells as property. But I can imagine scenarios in which one could charge for smells. Imagine we were living on a moon base where we had to buy air by the liter. I could imagine air suppliers adding scents at an extra charge. The reason it seems ridiculous to us to treat smells as property is that it wouldn't work to. It would work on a moon base, though. What counts as property depends on what works to treat as property. And that not only can change, but has changed. Humans may always (for some definition of human and always) have treated small items carried on one's person as property. But hunter gatherers didn't treat land, for example, as property in the way we do. [1] The reason so many people think of property as having a single unchanging definition is that its definition changes very slowly. [2] But we are in the midst of such a change now. The record labels and movie studios used to distribute what they made like air shipped through tubes on a moon base. But with the arrival of networks, it's as if we've moved to a planet with a breathable atmosphere. Data moves like smells now.
小时候我读过一本关于日本十八世纪著名法官大冈忠相的故事集。他审理的一起案件中,一位小吃店老板状告一个穷学生——这个学生只买得起米饭,却一边吃饭一边享受店里飘出的美食香气。店主坚持要学生为闻到的香味付钱。
这学生是在偷他的香味!
每当听到美国唱片业协会和电影协会指控人们盗版音乐电影时,我总会想起这个故事。
将气味视为财产在我们看来荒谬至极。但我能设想到需要为气味付费的场景:假设我们生活在按升购买空气的月球基地,空气供应商很可能会额外收取香味添加费。
气味之所以不适合作为财产,是因为这种设定在现实中行不通——但在月球基地却可行。
And through a combination of wishful thinking and short-term greed, the labels and studios have put themselves in the position of the food shop owner, accusing us all of stealing their smells. (The reason I say short-term greed is that the underlying problem with the labels and studios is that the people who run them are driven by bonuses rather than equity. If they were driven by equity they'd be looking for ways to take advantage of technological change instead of fighting it. But building new things takes too long. Their bonuses depend on this year's revenues, and the best way to increase those is to extract more money from stuff they do already.) So what does this mean? Should people not be able to charge for content? There's not a single yes or no answer to that question. People should be able to charge for content when it works to charge for content. But by "works" I mean something more subtle than "when they can get away with it." I mean when people can charge for content without warping society in order to do it. After all, the companies selling smells on the moon base could continue to sell them on the Earth, if they lobbied successfully for laws requiring us all to continue to breathe through tubes down here too, even though we no longer needed to. The crazy legal measures that the labels and studios have been taking have a lot of that flavor. Newspapers and magazines are just as screwed, but they are at least declining gracefully. The RIAA and MPAA would make us breathe through tubes if they could. Ultimately it comes down to common sense. When you're abusing the legal system by trying to use mass lawsuits against randomly chosen people as a form of exemplary punishment, or lobbying for laws that would break the Internet if they passed, that's ipso facto evidence you're using a definition of property that doesn't work. This is where it's helpful to have working democracies and multiple sovereign countries.
财产的定义取决于何种事物适合被视作财产。这种标准不仅可能改变,而且已经改变。人类或许自古(以某种定义下的"人类"和"自古")就将随身小物件视为财产,但狩猎采集者对待土地的方式就与我们截然不同[1]。
人们常误以为财产具有永恒不变的定义,只因它的演变速度极其缓慢[2]。但眼下我们正经历这样的变革。唱片公司和电影工作室过去分发作品的方式,就像月球基地通过管道输送空气。而网络的出现,宛如我们移居到了拥有可呼吸大气层的星球。如今数据像气味般自由流动,但这些公司却因一厢情愿和短视贪婪,把自己变成了小吃店主,指控所有人都在偷窃他们的"香味"。
(所谓短视贪婪,是因为这些企业的掌舵者被奖金而非股权驱动。若为股权考虑,他们本该利用技术变革而非抗拒它。但创新耗时太久,奖金取决于当年收入,而提高收入最快捷的方式就是从现有业务榨取更多利润。)
那么这意味着什么?人们不该为内容收费吗?这个问题没有非黑即白的答案。当收费模式行得通时,内容收费自然合理。
但"行得通"并非指"能侥幸成功",而是指收费时无需扭曲社会规则。就像月球空气商若成功游说法律,强迫地球人继续通过管道呼吸本可自由获取的空气,他们确实能继续收费——但这显然荒谬。
If the world had a single, autocratic government, the labels and studios could buy laws making the definition of property be whatever they wanted. But fortunately there are still some countries that are not copyright colonies of the US, and even in the US, politicians still seem to be afraid of actual voters, in sufficient numbers. [3] The people running the US may not like it when voters or other countries refuse to bend to their will, but ultimately it's in all our interest that there's not a single point of attack for people trying to warp the law to serve their own purposes. Private property is an extremely useful idea — arguably one of our greatest inventions. So far, each new definition of it has brought us increasing material wealth. [4] It seems reasonable to suppose the newest one will too. It would be a disaster if we all had to keep running an obsolete version just because a few powerful people were too lazy to upgrade. Notes [1] If you want to learn more about hunter gatherers I strongly recommend Elizabeth Marshall Thomas's _The Harmless People_ and _The Old Way_. [2] Change in the definition of property is driven mostly by technological progress, however, and since technological progress is accelerating, so presumably will the rate of change in the definition of property. Which means it's all the more important for societies to be able to respond gracefully to such changes, because they will come at an ever increasing rate. [3] As far as I know, the term "copyright colony" was first used by Myles Peterson. [4] The state of technology isn't simply a function of the definition of property.
唱片电影公司的疯狂法律手段正是如此。报业杂志业同样处境艰难,但至少它们在优雅衰退。而美国唱片业协会和电影协会恨不能让我们都戴上呼吸管。
归根结底这是常识问题:当你滥用法律体系,用大规模诉讼随机惩罚普通民众,或推动足以摧毁互联网的法案时,这本身就证明你采用的财产定义已然失效。
此时运转良好的民主制度和多主权国家体系就显现出价值。若世界由单一专制政府统治,这些公司完全能用金钱塑造法律。所幸仍有些国家不是美国的版权殖民地,即便在美国,政客们对真实选民仍存有足够敬畏[3]。
美国掌权者或许不乐见选民或其他国家违抗其意志,但从根本上看,法律不被单一势力扭曲符合全人类利益。私有财产是极具价值的概念——可说是最伟大的发明之一。迄今为止,财产定义的每次更新都带来物质财富增长[4]。有理由相信这次变革也将如此。若因权贵怠惰而强迫全人类运行过时的财产版本,那将是场灾难。
[1] 推荐伊丽莎白·马歇尔·托马斯的《无害之人》与《古老之道》了解狩猎采集者。
They each constrain the other. But that being so, you can't mess with the definition of property without affecting (and probably harming) the state of technology. The history of the USSR offers a vivid illustration of that. Thanks to Sam Altman and Geoff Ralston for reading drafts of this.
[2] 财产定义变化主要受技术进步驱动。随着技术加速发展,财产定义的更新速率也将提升。社会更需要从容应对这些日益频繁的变革。
[3] "版权殖民地"一词据我所知由迈尔斯·彼得森首创。
[4] 技术状况与财产定义相互制约。苏联历史生动证明:扭曲财产定义必然影响(通常损害)技术发展。
致谢 萨姆·奥尔特曼和杰夫·拉尔斯通对本文初稿的审阅。
Want to start a startup? Get funded by Y Combinator.
March 2012 One of the more surprising things I've noticed while working on Y Combinator is how frightening the most ambitious startup ideas are. In this essay I'm going to demonstrate this phenomenon by describing some. Any one of them could make you a billionaire. That might sound like an attractive prospect, and yet when I describe these ideas you may notice you find yourself shrinking away from them. Don't worry, it's not a sign of weakness. Arguably it's a sign of sanity. The biggest startup ideas are terrifying. And not just because they'd be a lot of work. The biggest ideas seem to threaten your identity: you wonder if you'd have enough ambition to carry them through. There's a scene in _Being John Malkovich_ where the nerdy hero encounters a very attractive, sophisticated woman. She says to him:
想创业吗? 获得 Y Combinator 的资金支持。
2012年3月 在Y Combinator工作期间,我注意到一个令人惊讶的现象:最具野心的创业想法往往令人望而生畏。在这篇文章中,我将通过描述其中一些想法来展示这一现象。任何一个都可能让你成为亿万富翁。这听起来或许是个诱人的前景,但当我描述这些想法时,你可能会发现自己正在退缩。 别担心,这不是软弱的表现。可以说这是理智的标志。最宏大的创业想法是令人恐惧的。不仅仅因为它们需要付出巨大的努力。最宏大的想法似乎会威胁到你的身份认同:你会怀疑自己是否有足够的野心去实现它们。 在《成为约翰·马尔科维奇》中有一个场景,书呆子主角遇到了一位非常迷人、世故的女人。她对他说:
> 问题是:如果你真的得到了我,你根本不知道该怎么对待我。
这正是这些想法向我们传达的信息。 这一现象是理解初创企业时最关键的认知之一。[1] 人们往往以为宏大的创业构想会充满吸引力,但实际上它们常常令人望而却步。这带来了一系列连锁反应:绝大多数人在构思创业方向时,潜意识会将这些想法过滤掉,使得它们成为隐形的存在。即便是最具野心的人,或许也需要以迂回的方式接近这些领域。
> Here's the thing: If you ever got me, you wouldn't have a clue what to do with me.
1. 打造新搜索引擎 最优秀的创意往往游走在可能与不可能的边界。我不确定这个构想能否实现,但已有迹象显示其可行性。开发新搜索引擎意味着与谷歌竞争——而最近我注意到这座堡垒已出现裂痕。
当年微软决定进军搜索业务时,我就意识到这家公司迷失了方向。对微软而言,这绝非自然延伸的决策。他们因恐惧谷歌而仓促应战,却意味着:(a) 谷歌开始主导微软的战略议程;(b) 微软被迫在自己不擅长的领域作战。
微软与谷歌的关系,恰如谷歌与脸书的关系。
这本身不意味着新搜索引擎存在机会,但近来使用谷歌搜索时,我常怀念它昔日坚守极客精神的模样。曾经的谷歌能快速呈现简洁精准的结果页面,如今却充斥着"科学教派式"的个性化答案(所谓真相即你认定的真相),页面设计也失去了昔日的干净利落。过去的搜索结果如同Unix命令行工具的输出,如今光标稍有不慎就会触发不可预知的反应。
That's what these ideas say to us. This phenomenon is one of the most important things you can understand about startups. [1] You'd expect big startup ideas to be attractive, but actually they tend to repel you. And that has a bunch of consequences. It means these ideas are invisible to most people who try to think of startup ideas, because their subconscious filters them out. Even the most ambitious people are probably best off approaching them obliquely. 1\. A New Search Engine The best ideas are just on the right side of impossible. I don't know if this one is possible, but there are signs it might be. Making a new search engine means competing with Google, and recently I've noticed some cracks in their fortress. The point when it became clear to me that Microsoft had lost their way was when they decided to get into the search business. That was not a natural move for Microsoft. They did it because they were afraid of Google, and Google was in the search business. But this meant (a) Google was now setting Microsoft's agenda, and (b) Microsoft's agenda consisted of stuff they weren't good at. Microsoft : Google :: Google : Facebook. That does not by itself mean there's room for a new search engine, but lately when using Google search I've found myself nostalgic for the old days, when Google was true to its own slightly aspy self. Google used to give me a page of the right answers, fast, with no clutter. Now the results seem inspired by the Scientologist principle that what's true is what's true for you. And the pages don't have the clean, sparse feel they used to. Google search results used to look like the output of a Unix utility. Now if I accidentally put the cursor in the wrong place, anything might happen. The way to win here is to build the search engine all the hackers use.
制胜之道在于打造黑客专属的搜索引擎。即便用户仅限顶尖的1万名黑客,这个小众引擎仍将拥有非凡影响力——正如当年的谷歌。十余年来,我第一次感到转换搜索工具具有现实可能性。
既然能创建这种公司的人必在这1万黑客之列,路径便异常清晰:打造你自己理想中的搜索引擎。尽可赋予其浓厚的极客气质,比如强化代码搜索功能。让搜索查询支持图灵完备又如何?任何能吸引这1万名用户的设计,本质上都是正确的。
不必顾虑某些设计会限制长期发展——若无法获得核心用户群,根本不存在"长期"。只要做出你和朋友们真心认为优于谷歌的产品,你就已经走完了IPO之路的10%,正如当年覆盖哈佛全体本科生的脸书(尽管他们当时未必意识到)。
2. 重构电子邮件 电子邮件的设计初衷与当下使用方式严重脱节。它本非通讯协议,而是待办清单——确切地说,收件箱是待办清单,邮件则是任务的投放渠道。但作为任务管理系统,它糟糕透顶。
A search engine whose users consisted of the top 10,000 hackers and no one else would be in a very powerful position despite its small size, just as Google was when it was that search engine. And for the first time in over a decade the idea of switching seems thinkable to me. Since anyone capable of starting this company is one of those 10,000 hackers, the route is at least straightforward: make the search engine you yourself want. Feel free to make it excessively hackerish. Make it really good for code search, for example. Would you like search queries to be Turing complete? Anything that gets you those 10,000 users is ipso facto good. Don't worry if something you want to do will constrain you in the long term, because if you don't get that initial core of users, there won't be a long term. If you can just build something that you and your friends genuinely prefer to Google, you're already about 10% of the way to an IPO, just as Facebook was (though they probably didn't realize it) when they got all the Harvard undergrads. 2\. Replace Email Email was not designed to be used the way we use it now. Email is not a messaging protocol. It's a todo list. Or rather, my inbox is a todo list, and email is the way things get onto it. But it is a disastrously bad todo list. I'm open to different types of solutions to this problem, but I suspect that tweaking the inbox is not enough, and that email has to be replaced with a new protocol. This new protocol should be a todo list protocol, not a messaging protocol, although there is a degenerate case where what someone wants you to do is: read the following text. As a todo list protocol, the new protocol should give more power to the recipient than email does. I want there to be more restrictions on what someone can put on my todo list. And when someone can put something on my todo list, I want them to tell me more about what they want from me.
解决方案可以多样,但我怀疑修修补补无济于事,必须用新协议彻底取代。这个新协议应是任务管理协议(尽管存在"请阅读以下文字"这类退化用例),赋予收件人更大掌控权:对他人投放任务设置更多限制;当任务被投放时,要求发送方明确说明需求(是否需要执行操作?优先级如何?截止时间?需建立防滥用机制)。
这就像不可抗力遭遇不可撼动之物:既有协议极难取代,但百年后的人类不可能仍困于当下的邮件地狱。既然终将被颠覆,为何不是现在?
若能设计得当,或可规避新协议常见的"鸡生蛋"困境——因为全球最具影响力的人群将率先倒戈,他们同样饱受邮件折磨。
无论构建什么,速度至上。Gmail已慢得令人痛苦[2]。即便功能相当,仅凭速度优势就能从Gmail分流用户。谷歌无力在邮件服务投入重金,但用户愿意付费——我完全接受月付50美元。考虑到耗费在邮件上的时间,月付1000美元都物有所值。
Do they want me to do something beyond just reading some text? How important is it? (There obviously has to be some mechanism to prevent people from saying everything is important.) When does it have to be done? This is one of those ideas that's like an irresistible force meeting an immovable object. On one hand, entrenched protocols are impossible to replace. On the other, it seems unlikely that people in 100 years will still be living in the same email hell we do now. And if email is going to get replaced eventually, why not now? If you do it right, you may be able to avoid the usual chicken and egg problem new protocols face, because some of the most powerful people in the world will be among the first to switch to it. They're all at the mercy of email too. Whatever you build, make it fast. GMail has become painfully slow. [2] If you made something no better than GMail, but fast, that alone would let you start to pull users away from GMail. GMail is slow because Google can't afford to spend a lot on it. But people will pay for this. I'd have no problem paying $50 a month. Considering how much time I spend in email, it's kind of scary to think how much I'd be justified in paying. At least $1000 a month. If I spend several hours a day reading and writing email, that would be a cheap way to make my life better. 3\. Replace Universities People are all over this idea lately, and I think they're onto something. I'm reluctant to suggest that an institution that's been around for a millennium is finished just because of some mistakes they made in the last few decades, but certainly in the last few decades US universities seem to have been headed down the wrong path. One could do a lot better for a lot less money. I don't think universities will disappear. They won't be replaced wholesale. They'll just lose the de facto monopoly on certain types of learning that they once had.
3. 颠覆高等教育 近年这一构想备受关注,确实切中要害。虽不愿断言存在千年的机构会因近几十年的错误走向终结,但美国大学显然已误入歧途。完全可以用更低成本实现更好教育。
大学不会消失,也不会被整体替代,只是将丧失在某些学习领域的事实垄断地位。未来会出现多元化的学习方式,有些可能与传统大学截然不同——Y Combinator本身就可视为一种新型教育形态。
学习是根本性问题,其变革将引发连锁反应。例如大学文凭作为独立 credential 的现状可能改变,认证体系或与学习过程分离。甚至可能需要重建校园社交生活的替代方案(有趣的是YC已具备这类特征)。
There will be many different ways to learn different things, and some may look quite different from universities. Y Combinator itself is arguably one of them. Learning is such a big problem that changing the way people do it will have a wave of secondary effects. For example, the name of the university one went to is treated by a lot of people (correctly or not) as a credential in its own right. If learning breaks up into many little pieces, credentialling may separate from it. There may even need to be replacements for campus social life (and oddly enough, YC even has aspects of that). You could replace high schools too, but there you face bureaucratic obstacles that would slow down a startup. Universities seem the place to start. 4\. Internet Drama Hollywood has been slow to embrace the Internet. That was a mistake, because I think we can now call a winner in the race between delivery mechanisms, and it is the Internet, not cable. A lot of the reason is the horribleness of cable clients, also known as TVs. Our family didn't wait for Apple TV. We hated our last TV so much that a few months ago we replaced it with an iMac bolted to the wall. It's a little inconvenient to control it with a wireless mouse, but the overall experience is much better than the nightmare UI we had to deal with before. Some of the attention people currently devote to watching movies and TV can be stolen by things that seem completely unrelated, like social networking apps. More can be stolen by things that are a little more closely related, like games. But there will probably always remain some residual demand for conventional drama, where you sit passively and watch as a plot happens. So how do you deliver drama via the Internet? Whatever you make will have to be on a larger scale than Youtube clips.
中学教育同样需要革新,但官僚体系会阻碍初创企业进展。大学是更理想的切入点。
4. 互联网剧集 好莱坞对互联网的接纳过于迟缓。如今传播渠道之争已见分晓:互联网胜出,有线电视落败。
关键原因在于电视作为终端设备的糟糕体验。我家等不及苹果电视问世——数月前直接将iMac固定在墙上取代电视。无线鼠标操控虽稍不便,但体验远胜从前噩梦般的电视界面。
当前人们观看影视的注意力,部分已被社交应用等看似不相关的产品夺取,更多则被游戏等相近形态瓜分。但被动观看剧情的传统需求仍将存在。如何通过互联网输送剧集?内容必须超越YouTube短片规模——观众需要明确预期:或是熟悉角色的系列剧,或是已知基本设定的长片。
When people sit down to watch a show, they want to know what they're going to get: either part of a series with familiar characters, or a single longer "movie" whose basic premise they know in advance. There are two ways delivery and payment could play out. Either some company like Netflix or Apple will be the app store for entertainment, and you'll reach audiences through them. Or the would-be app stores will be too overreaching, or too technically inflexible, and companies will arise to supply payment and streaming a la carte to the producers of drama. If that's the way things play out, there will also be a need for such infrastructure companies. 5\. The Next Steve Jobs I was talking recently to someone who knew Apple well, and I asked him if the people now running the company would be able to keep creating new things the way Apple had under Steve Jobs. His answer was simply "no." I already feared that would be the answer. I asked more to see how he'd qualify it. But he didn't qualify it at all. No, there will be no more great new stuff beyond whatever's currently in the pipeline. Apple's revenues may continue to rise for a long time, but as Microsoft shows, revenue is a lagging indicator in the technology business. So if Apple's not going to make the next iPad, who is? None of the existing players. None of them are run by product visionaries, and empirically you can't seem to get those by hiring them. Empirically the way you get a product visionary as CEO is for him to found the company and not get fired. So the company that creates the next wave of hardware is probably going to have to be a startup. I realize it sounds preposterously ambitious for a startup to try to become as big as Apple. But no more ambitious than it was for Apple to become as big as Apple, and they did it. Plus a startup taking on this problem now has an advantage the original Apple didn't: the example of Apple. Steve Jobs has shown us what's possible.
分发与支付可能呈现两种形态:Netflix或苹果等公司成为娱乐应用商店;或者这些平台因过度扩张或技术僵化,催生专门为内容生产者提供支付与流媒体服务的公司。
5. 下一个乔布斯 某位熟悉苹果的人士告诉我,现任管理层无法延续乔布斯时代的创新。苹果或许会像微软那样,营收长期增长但再无突破性产品——在科技行业,营收是滞后指标。
若苹果不再创造新一代iPad,谁会接手?现有厂商均无产品远见,而实践表明这种人才无法雇佣获得,只能来自创始人。因此下一代硬件浪潮必将由初创企业引领。
初创企业比肩苹果看似痴人说梦,但当年苹果白手起家时同样不可思议。如今创业者还拥有苹果不曾具备的优势:乔布斯证明了可能性。他像罗杰·班尼斯特(首个突破四分钟跑一英里的人)那样展示极限,又像奥古斯都大帝那样让用户相信个人可以开创未来。
That helps would-be successors both directly, as Roger Bannister did, by showing how much better you can do than people did before, and indirectly, as Augustus did, by lodging the idea in users' minds that a single person could unroll the future for them. [3] Now Steve is gone there's a vacuum we can all feel. If a new company led boldly into the future of hardware, users would follow. The CEO of that company, the "next Steve Jobs," might not measure up to Steve Jobs. But he wouldn't have to. He'd just have to do a better job than Samsung and HP and Nokia, and that seems pretty doable. 6\. Bring Back Moore's Law The last 10 years have reminded us what Moore's Law actually says. Till about 2002 you could safely misinterpret it as promising that clock speeds would double every 18 months. Actually what it says is that circuit densities will double every 18 months. It used to seem pedantic to point that out. Not any more. Intel can no longer give us faster CPUs, just more of them. This Moore's Law is not as good as the old one. Moore's Law used to mean that if your software was slow, all you had to do was wait, and the inexorable progress of hardware would solve your problems. Now if your software is slow you have to rewrite it to do more things in parallel, which is a lot more work than waiting. It would be great if a startup could give us something of the old Moore's Law back, by writing software that could make a large number of CPUs look to the developer like one very fast CPU. There are several ways to approach this problem. The most ambitious is to try to do it automatically: to write a compiler that will parallelize our code for us. There's a name for this compiler, _the sufficiently smart compiler,_ and it is a byword for impossibility.
如今我们都能感受到乔布斯留下的真空。若有公司勇敢开拓硬件未来,用户自会追随。这位"新乔布斯"或许不及本尊,但只需超越三星、惠普和诺基亚——这完全可行。
6. 重启摩尔定律 过去十年让我们重新认识摩尔定律的本质:2002年前人们误以为它承诺每18个月时钟速度翻倍,实则指晶体管密度提升。如今英特尔无法提供更快CPU,只能增加核心数量。
这种"新摩尔定律"远不如旧版理想——曾经只需等待硬件进步解决性能问题,现在必须重写并行化软件。若有初创企业能通过软件让大量CPU在开发者眼中宛若单个超快CPU,将意义非凡。
最激进的方法是开发自动并行化编译器(传说中的"足够智能的编译器")。虽被视为不可能,但真的无法实现吗?若只是极其困难,就值得尝试——即便成功概率低,预期价值仍极高。
But is it really impossible? Is there no configuration of the bits in memory of a present day computer that is this compiler? If you really think so, you should try to prove it, because that would be an interesting result. And if it's not impossible but simply very hard, it might be worth trying to write it. The expected value would be high even if the chance of succeeding was low. The reason the expected value is so high is web services. If you could write software that gave programmers the convenience of the way things were in the old days, you could offer it to them as a web service. And that would in turn mean that you got practically all the users. Imagine there was another processor manufacturer that could still translate increased circuit densities into increased clock speeds. They'd take most of Intel's business. And since web services mean that no one sees their processors anymore, by writing the sufficiently smart compiler you could create a situation indistinguishable from you being that manufacturer, at least for the server market. The least ambitious way of approaching the problem is to start from the other end, and offer programmers more parallelizable Lego blocks to build programs out of, like Hadoop and MapReduce. Then the programmer still does much of the work of optimization. There's an intriguing middle ground where you build a semi-automatic weapon—where there's a human in the loop. You make something that looks to the user like the sufficiently smart compiler, but inside has people, using highly developed optimization tools to find and eliminate bottlenecks in users' programs. These people might be your employees, or you might create a marketplace for optimization. An optimization marketplace would be a way to generate the sufficiently smart compiler piecemeal, because participants would immediately start writing bots.
高预期价值源于网络服务:若能恢复旧式编程体验,作为服务提供将赢得几乎所有用户。这相当于在服务器市场创造了虚拟的"超频芯片制造商"。
最保守的方法是提供Hadoop/MapReduce等并行化组件,将优化工作留给开发者。折中方案则是构建"半自动武器"——表面是智能编译器,内部由人类专家使用高级工具优化程序。这些专家可以是雇员,也可建立优化市场。
优化市场将逐步催生足够智能的编译器——参与者会立即编写自动化工具。有趣的是当一切皆可由机器人完成时,编译器就已存在,却无人拥有其完整版本。
It would be a curious state of affairs if you could get to the point where everything could be done by bots, because then you'd have made the sufficiently smart compiler, but no one person would have a complete copy of it. I realize how crazy all this sounds. In fact, what I like about this idea is all the different ways in which it's wrong. The whole idea of focusing on optimization is counter to the general trend in software development for the last several decades. Trying to write the sufficiently smart compiler is by definition a mistake. And even if it weren't, compilers are the sort of software that's supposed to be created by open source projects, not companies. Plus if this works it will deprive all the programmers who take pleasure in making multithreaded apps of so much amusing complexity. The forum troll I have by now internalized doesn't even know where to begin in raising objections to this project. Now that's what I call a startup idea. 7\. Ongoing Diagnosis But wait, here's another that could face even greater resistance: ongoing, automatic medical diagnosis. One of my tricks for generating startup ideas is to imagine the ways in which we'll seem backward to future generations. And I'm pretty sure that to people 50 or 100 years in the future, it will seem barbaric that people in our era waited till they had symptoms to be diagnosed with conditions like heart disease and cancer. For example, in 2004 Bill Clinton found he was feeling short of breath. Doctors discovered that several of his arteries were over 90% blocked and 3 days later he had a quadruple bypass. It seems reasonable to assume Bill Clinton has the best medical care available. And yet even he had to wait till his arteries were over 90% blocked to learn that the number was over 90%. Surely at some point in the future we'll know these numbers the way we now know something like our weight. Ditto for cancer.
我清楚这听起来多么疯狂。正因它在多个维度上"错误",才格外迷人:聚焦优化违背数十年软件开发趋势;编译器本应是开源项目而非公司产品;成功将剥夺程序员处理多线程复杂性的乐趣。连我内心的论坛杠精都不知从何吐槽——这才配称真正的创业构想。
7. 持续医疗诊断 这个可能遭遇更大阻力的构想是:持续自动化医疗诊断。
我的创业构思技巧之一是假想未来人如何看待当下的落后。我确信50-100年后的人类会认为,等到出现症状才诊断心脏病/癌症的我们堪称野蛮。例如2004年克林顿感到气短就医时,冠状动脉已堵塞超90%。即便顶级医疗资源也未能更早发现。未来这些指标应像体重般随时可知。癌症诊断同样如此——等待症状出现才会像雷达屏显示敌机般立即预警。
(当然,"雷达癌症"可能不同于现有认知。人体或许时刻存在数十甚至数百处微型癌变,通常无关紧要。)
It will seem preposterous to future generations that we wait till patients have physical symptoms to be diagnosed with cancer. Cancer will show up on some sort of radar screen immediately. (Of course, what shows up on the radar screen may be different from what we think of now as cancer. I wouldn't be surprised if at any given time we have ten or even hundreds of microcancers going at once, none of which normally amount to anything.) A lot of the obstacles to ongoing diagnosis will come from the fact that it's going against the grain of the medical profession. The way medicine has always worked is that patients come to doctors with problems, and the doctors figure out what's wrong. A lot of doctors don't like the idea of going on the medical equivalent of what lawyers call a "fishing expedition," where you go looking for problems without knowing what you're looking for. They call the things that get discovered this way "incidentalomas," and they are something of a nuisance. For example, a friend of mine once had her brain scanned as part of a study. She was horrified when the doctors running the study discovered what appeared to be a large tumor. After further testing, it turned out to be a harmless cyst. But it cost her a few days of terror. A lot of doctors worry that if you start scanning people with no symptoms, you'll get this on a giant scale: a huge number of false alarms that make patients panic and require expensive and perhaps even dangerous tests to resolve. But I think that's just an artifact of current limitations. If people were scanned all the time and we got better at deciding what was a real problem, my friend would have known about this cyst her whole life and known it was harmless, just as we do a birthmark. There is room for a lot of startups here.
主要阻力来自医疗传统:患者带着问题求诊,医生负责诊断。许多医生反感"钓鱼式"检查(无明确目标地寻找问题),将偶然发现称为"意外瘤"视作麻烦。例如我朋友参与研究时脑部扫描发现疑似肿瘤,经历数日恐慌后确诊为无害囊肿。医生担心无症状筛查会导致大规模误报,引发恐慌和昂贵甚至危险的检查。但我认为这只是当前技术局限的产物——若持续监测且能更好判别真实问题,朋友本可终生知晓这个如同胎记般无害的囊肿。
该领域存在大量创业机会。除了技术障碍和医疗初创的官僚壁垒,还需对抗数千年医疗传统。但这终将实现,其伟大程度会让未来人如同我们看待没有麻醉和抗生素的时代般怜悯当代人。
战术建议 最后提供具体策略:应对如此宏大的问题时,切忌正面强攻。例如别说要"取代电子邮件",这会引发过高期待。员工和投资人会不断追问进展,还有大批看衰者等着见证失败。只需宣称开发待办清单软件——听起来人畜无害。当木已成舟时,人们自会发现邮件已被取代。
实践表明,成就伟业往往始于看似微不足道的事物:欲主宰微机软件?先从几千用户机器的BASIC解释器起步;要建立全球网站?先做哈佛学生互窥主页。
In addition to the technical obstacles all startups face, and the bureaucratic obstacles all medical startups face, they'll be going against thousands of years of medical tradition. But it will happen, and it will be a great thing—so great that people in the future will feel as sorry for us as we do for the generations that lived before anaesthesia and antibiotics. Tactics Let me conclude with some tactical advice. If you want to take on a problem as big as the ones I've discussed, don't make a direct frontal attack on it. Don't say, for example, that you're going to replace email. If you do that you raise too many expectations. Your employees and investors will constantly be asking "are we there yet?" and you'll have an army of haters waiting to see you fail. Just say you're building todo-list software. That sounds harmless. People can notice you've replaced email when it's a _fait accompli_. [4] Empirically, the way to do really big things seems to be to start with deceptively small things. Want to dominate microcomputer software? Start by writing a Basic interpreter for a machine with a few thousand users. Want to make the universal web site? Start by building a site for Harvard undergrads to stalk one another. Empirically, it's not just for other people that you need to start small. You need to for your own sake. Neither Bill Gates nor Mark Zuckerberg knew at first how big their companies were going to get. All they knew was that they were onto something. Maybe it's a bad idea to have really big ambitions initially, because the bigger your ambition, the longer it's going to take, and the further you project into the future, the more likely you'll get it wrong. I think the way to use these big ideas is not to try to identify a precise point in the future and then ask yourself how to get from here to there, like the popular image of a visionary.
这种"从小起步"不仅为迷惑外界,更是自我需求。比尔·盖茨和扎克伯格最初都不知公司会发展到多大规模,只知道自己抓住了什么。或许初期设定过大野心反而不利——野心越大,实现周期越长,对未来预判失误概率越高。
运用宏大构想的关键,不在于精确预测未来节点(如同流行印象中的远见者),而应像哥伦布那样锁定大致西方航向。别把未来当建筑蓝图来设计——当前方案几乎必然错误。从已知可行的基点出发,逐步向西扩张。
远见者的流行形象是清晰预见未来,但实践证明模糊的愿景或许更优。
注释 [1] 这也是风投对初创企业最普遍的认知盲区。多数人期望创始人带着清晰计划而来,并据此评判。很少有人意识到:最伟大的成功往往与初始计划关联最小。
You'll be better off if you operate like Columbus and just head in a general westerly direction. Don't try to construct the future like a building, because your current blueprint is almost certainly mistaken. Start with something you know works, and when you expand, expand westward. The popular image of the visionary is someone with a clear view of the future, but empirically it may be better to have a blurry one. Notes [1] It's also one of the most important things VCs fail to understand about startups. Most expect founders to walk in with a clear plan for the future, and judge them based on that. Few consciously realize that in the biggest successes there is the least correlation between the initial plan and what the startup eventually becomes. [2] This sentence originally read "GMail is painfully slow." Thanks to Paul Buchheit for the correction. [3] Roger Bannister is famous as the first person to run a mile in under 4 minutes. But his world record only lasted 46 days. Once he showed it could be done, lots of others followed. Ten years later Jim Ryun ran a 3:59 mile as a high school junior. [4] If you want to be the next Apple, maybe you don't even want to start with consumer electronics. Maybe at first you make something hackers use. Or you make something popular but apparently unimportant, like a headset or router. All you need is a bridgehead. Thanks to Sam Altman, Trevor Blackwell, Paul Buchheit, Patrick Collison, Aaron Iba, Jessica Livingston, Robert Morris, Harj Taggar and Garry Tan for reading drafts of this..
[2] 原句为"Gmail慢得痛苦",感谢Paul Buchheit指正。
[3] 罗杰·班尼斯特以首破四分钟跑一英里闻名,但其世界纪录仅保持46天。证明可能性后,追随者众。十年后高中生吉姆·瑞安就跑出3分59秒。
[4] 若要成为下一个苹果,或许起步时根本不该做消费电子产品。可以先服务黑客群体,或制造看似无关紧要的耳机/路由器等产品。只需一个桥头堡。
致谢 Sam Altman等九人阅读了本文草稿。
March 2012 I'm not a very good speaker. I say "um" a lot. Sometimes I have to pause when I lose my train of thought. I wish I were a better speaker. But I don't wish I were a better speaker like I wish I were a better writer. What I really want is to have good ideas, and that's a much bigger part of being a good writer than being a good speaker. Having good ideas is most of writing well. If you know what you're talking about, you can say it in the plainest words and you'll be perceived as having a good style. With speaking it's the opposite: having good ideas is an alarmingly small component of being a good speaker. I first noticed this at a conference several years ago. There was another speaker who was much better than me. He had all of us roaring with laughter. I seemed awkward and halting by comparison. Afterward I put my talk online like I usually do. As I was doing it I tried to imagine what a transcript of the other guy's talk would be like, and it was only then I realized he hadn't said very much. Maybe this would have been obvious to someone who knew more about speaking, but it was a revelation to me how much less ideas mattered in speaking than writing. [1] A few years later I heard a talk by someone who was not merely a better speaker than me, but a famous speaker. Boy was he good. So I decided I'd pay close attention to what he said, to learn how he did it. After about ten sentences I found myself thinking "I don't want to be a good speaker." Being a really good speaker is not merely orthogonal to having good ideas, but in many ways pushes you in the opposite direction. For example, when I give a talk, I usually write it out beforehand. I know that's a mistake; I know delivering a prewritten talk makes it harder to engage with an audience.
The way to get the attention of an audience is to give them _your_ full attention, and when you're delivering a prewritten talk, your attention is always divided between the audience and the talk — even if you've memorized it. If you want to engage an audience, it's better to start with no more than an outline of what you want to say and ad lib the individual sentences. But if you do that, you might spend no more time thinking about each sentence than it takes to say it. [2] Occasionally the stimulation of talking to a live audience makes you think of new things, but in general this is not going to generate ideas as well as writing does, where you can spend as long on each sentence as you want. If you rehearse a prewritten speech enough, you can get asymptotically close to the sort of engagement you get when speaking ad lib. Actors do. But here again there's a tradeoff between smoothness and ideas. All the time you spend practicing a talk, you could instead spend making it better. Actors don't face that temptation, except in the rare cases where they've written the script, but any speaker does. Before I give a talk I can usually be found sitting in a corner somewhere with a copy printed out on paper, trying to rehearse it in my head. But I always end up spending most of the time rewriting it instead. Every talk I give ends up being given from a manuscript full of things crossed out and rewritten. Which of course makes me um even more, because I haven't had any time to practice the new bits. [3] Depending on your audience, there are even worse tradeoffs than these. Audiences like to be flattered; they like jokes; they like to be swept off their feet by a vigorous stream of words. As you decrease the intelligence of the audience, being a good speaker is increasingly a matter of being a good bullshitter. That's true in writing too of course, but the descent is steeper with talks. Any given person is dumber as a member of an audience than as a reader.
Just as a speaker ad libbing can only spend as long thinking about each sentence as it takes to say it, a person hearing a talk can only spend as long thinking about each sentence as it takes to hear it. Plus people in an audience are always affected by the reactions of those around them, and the reactions that spread from person to person in an audience are disproportionately the more brutish sort, just as low notes travel through walls better than high ones. Every audience is an incipient mob, and a good speaker uses that. Part of the reason I laughed so much at the talk by the good speaker at that conference was that everyone else did. [4] So are talks useless? They're certainly inferior to the written word as a source of ideas. But that's not all talks are good for. When I go to a talk, it's usually because I'm interested in the speaker. Listening to a talk is the closest most of us can get to having a conversation with someone like the president, who doesn't have time to meet individually with all the people who want to meet him. Talks are also good at motivating me to do things. It's probably no coincidence that so many famous speakers are described as motivational speakers. That may be what public speaking is really for. It's probably what it was originally for. The emotional reactions you can elicit with a talk can be a powerful force. I wish I could say that this force was more often used for good than ill, but I'm not sure. Notes [1] I'm not talking here about academic talks, which are a different type of thing. While the audience at an academic talk might appreciate a joke, they will (or at least should) make a conscious effort to see what new ideas you're presenting. [2] That's the lower bound. In practice you can often do better, because talks are usually about things you've written or talked about before, and when you ad lib, you end up reproducing some of those sentences.
Like early medieval architecture, impromptu talks are made of spolia. Which feels a bit dishonest, incidentally, because you have to deliver these sentences as if you'd just thought of them. [3] Robert Morris points out that there is a way in which practicing talks makes them better: reading a talk out loud can expose awkward parts. I agree and in fact I read most things I write out loud at least once for that reason. [4] For sufficiently small audiences, it may not be true that being part of an audience makes people dumber. The real decline seems to set in when the audience gets too big for the talk to feel like a conversation — maybe around 10 people. Thanks to Sam Altman and Robert Morris for reading drafts of this..
2012年3月 我不是一个很好的演讲者。我经常说“嗯”。有时思路中断时不得不停顿。我希望自己能成为更好的演讲者。但这种渴望远不及我对成为更好作家的渴望。我真正想要的是拥有好想法,而这对于成为好作家而言,远比成为好演讲者重要得多。 拥有好想法是写好文章的大部分。如果你清楚自己在说什么,用最平实的语言表达也能让人感受到你的优秀风格。演讲则相反:好想法在成为优秀演讲者中所占的比重小得惊人。 几年前在一次会议上,我第一次注意到这点。有位演讲者远比我出色,他让全场哄堂大笑。相比之下,我显得笨拙又磕绊。后来我像往常一样把讲稿发到网上。整理时我试着想象那个人的演讲实录会是什么样,这才意识到他其实没讲多少实质内容。 对于更懂演讲的人或许显而易见,但演讲中想法的重要性远低于写作,这对我犹如启示。[1] 几年后我听了一位著名演讲家的演讲,他不仅比我优秀,更是行业翘楚。天啊,他太厉害了。于是我决定仔细聆听,学习他的技巧。听了约十句话后,我却开始想“我不想成为优秀的演讲者”。 成为真正优秀的演讲者不仅与拥有好想法无关,很多时候还会背道而驰。比如我演讲前通常会写完整讲稿。我知道这是错误做法——预写讲稿会阻碍与观众互动。吸引观众的关键是给予他们全部注意力,而当你背诵讲稿时,注意力始终分散在观众和文稿之间,即便已倒背如流。要想抓住观众,最好只准备大纲,现场组织语句。但这样做的话,你思考每句话的时间可能仅够说出它。[2] 虽然现场观众有时会激发新想法,但总体而言这远不如写作能催生好点子——写作时你可以无限打磨每个句子。 若对预写讲稿反复排练,理论上可以无限接近即兴演讲的互动效果。演员就是这么做的。但这又面临流畅度与思想深度的权衡。你花在排练的时间本可用于改进内容。演员很少面临这种抉择(除非自编剧本),但演讲者总会遇到。演讲前我常拿着打印稿在角落默诵,结果总是把时间花在改写而非排练上。最终我拿着的总是布满修改痕迹的讲稿——这自然让我说得更多“嗯”,因为新内容根本没时间练习。[3] 根据观众类型,还可能面临更严峻的权衡。观众喜欢被奉承,喜欢笑话,喜欢被滔滔雄辩征服。观众群体智商越低,优秀演讲就越等同于擅长胡扯。写作亦然,但演讲的堕落曲线更陡峭。人在群体中总比独处时愚蠢。正如即兴演讲者只能花说一句话的时间思考,听众也只能花听一句话的时间理解。何况观众总会受周围人影响,而人群中传播的往往是最原始的情绪反应,就像低频声波更能穿透墙壁。每个观众群体都是潜在的乌合之众,优秀演讲者深谙此道。我在那场会议上大笑的部分原因,正是受周围人感染。[4] 那么演讲毫无价值吗?作为思想载体,它确实逊于文字。但演讲另有用途。我听演讲通常是因为对演讲者感兴趣。对大多数人而言,听演讲是接近大人物的最近距离——比如总统根本没时间单独接见所有求见者。 演讲也擅长激励行动。众多著名演讲家被称为“励志演说家”绝非偶然。这或许才是公开演讲的真正意义,也可能是其最初的意义。演讲激发的情感力量异常强大。但愿这种力量多用于善而非恶,但我并不确定。 注释 [1] 此处不讨论学术演讲,那是另一回事。学术演讲观众虽也喜欢笑话,但会(至少应该)有意识地关注你提出的新观点。 [2] 这是下限。实际上常能做得更好,因为演讲内容多基于过往写作或演讲,即兴时会自然复用部分语句。如同中世纪早期建筑,即兴演讲由“战利品”拼凑而成。顺便说,这感觉有点不诚实,因为你得假装这些句子是刚想到的。 [3] 罗伯特·莫里斯指出,排练能使演讲更好:朗读能暴露拗口之处。我赞同这点,事实上我写的东西大多会至少朗读一遍。 [4] 对小规模观众,群体未必使人变笨。当观众多到失去对话感(约10人以上),智力水平才明显下降。 致谢 萨姆·奥尔特曼和罗伯特·莫里斯审阅了本文草稿。
Want to start a startup? Get funded by Y Combinator.
January 2012 There are great startup ideas lying around unexploited right under our noses. One reason we don't see them is a phenomenon I call _schlep blindness_. Schlep was originally a Yiddish word but has passed into general use in the US. It means a tedious, unpleasant task. No one likes schleps, but hackers especially dislike them. Most hackers who start startups wish they could do it by just writing some clever software, putting it on a server somewhere, and watching the money roll in—without ever having to talk to users, or negotiate with other companies, or deal with other people's broken code. Maybe that's possible, but I haven't seen it. One of the many things we do at Y Combinator is teach hackers about the inevitability of schleps. No, you can't start a startup by just writing code. I remember going through this realization myself. There was a point in 1995 when I was still trying to convince myself I could start a company by just writing code. But I soon learned from experience that schleps are not merely inevitable, but pretty much what business consists of. A company is defined by the schleps it will undertake. And schleps should be dealt with the same way you'd deal with a cold swimming pool: just jump in. Which is not to say you should seek out unpleasant work per se, but that you should never shrink from it if it's on the path to something great. The most dangerous thing about our dislike of schleps is that much of it is unconscious. Your unconscious won't even let you see ideas that involve painful schleps. That's schlep blindness. The phenomenon isn't limited to startups. Most people don't consciously decide not to be in as good physical shape as Olympic athletes, for example. Their unconscious mind decides for them, shrinking from the work involved.
The most striking example I know of schlep blindness is Stripe, or rather Stripe's idea. For over a decade, every hacker who'd ever had to process payments online knew how painful the experience was. Thousands of people must have known about this problem. And yet when they started startups, they decided to build recipe sites, or aggregators for local events. Why? Why work on problems few care much about and no one will pay for, when you could fix one of the most important components of the world's infrastructure? Because schlep blindness prevented people from even considering the idea of fixing payments. Probably no one who applied to Y Combinator to work on a recipe site began by asking "should we fix payments, or build a recipe site?" and chose the recipe site. Though the idea of fixing payments was right there in plain sight, they never saw it, because their unconscious mind shrank from the complications involved. You'd have to make deals with banks. How do you do that? Plus you're moving money, so you're going to have to deal with fraud, and people trying to break into your servers. Plus there are probably all sorts of regulations to comply with. It's a lot more intimidating to start a startup like this than a recipe site. That scariness makes ambitious ideas doubly valuable. In addition to their intrinsic value, they're like undervalued stocks in the sense that there's less demand for them among founders. If you pick an ambitious idea, you'll have less competition, because everyone else will have been frightened off by the challenges involved. (This is also true of starting a startup generally.) How do you overcome schlep blindness? Frankly, the most valuable antidote to schlep blindness is probably ignorance. Most successful founders would probably say that if they'd known when they were starting their company about the obstacles they'd have to overcome, they might never have started it.
Maybe that's one reason the most successful startups of all so often have young founders. In practice the founders grow with the problems. But no one seems able to foresee that, not even older, more experienced founders. So the reason younger founders have an advantage is that they make two mistakes that cancel each other out. They don't know how much they can grow, but they also don't know how much they'll need to. Older founders only make the first mistake. Ignorance can't solve everything though. Some ideas so obviously entail alarming schleps that anyone can see them. How do you see ideas like that? The trick I recommend is to take yourself out of the picture. Instead of asking "what problem should I solve?" ask "what problem do I wish someone else would solve for me?" If someone who had to process payments before Stripe had tried asking that, Stripe would have been one of the first things they wished for. It's too late now to be Stripe, but there's plenty still broken in the world, if you know how to see it. Thanks to Sam Altman, Paul Buchheit, Patrick Collison, Aaron Iba, Jessica Livingston, Emmett Shear, and Harj Taggar for reading drafts of this..
想创办一家初创公司? 获得 Y Combinator 的资助。
2012年1月 如今,有许多绝佳的创业点子就摆在我们眼前,却无人问津。其中一个原因是我们对它们视而不见,这种现象我称之为“苦差盲区”。“Schlep”原本是意第绪语词汇,如今已在美国广泛使用,意指枯燥乏味的苦差事。 没人喜欢苦差事,但黑客尤其厌恶。大多数创业的黑客都希望只需写点聪明代码,往服务器上一扔,就能坐等收钱——既不用和用户打交道,也不必与其他公司谈判,更不用处理别人的烂代码。或许这能实现,但我从未见过。 在Y Combinator,我们做的诸多事情之一就是让黑客明白:苦差事无可避免。不,单靠写代码无法创业。记得我自己也曾经历这种顿悟。1995年时,我一度试图说服自己仅靠写代码就能开公司。但经验很快让我明白,苦差事不仅是必然的,甚至构成了商业的主体。一家公司的本质,就是它愿意承担的苦差事。面对苦差事,就该像跳进冰冷的泳池一样:直接扎进去。这并非鼓励你自找苦吃,而是说如果某件事能通向伟大,就绝不要退缩。 我们对苦差事的厌恶最危险之处在于,这种厌恶大多是无意识的。你的潜意识甚至会屏蔽那些伴随痛苦苦差事的点子。这就是“苦差盲区”。 这种现象不仅限于创业。例如,大多数人并非有意识地决定不练出奥运选手般的体格,而是潜意识替他们做了决定,让他们对相关训练望而却步。 我见过最典型的“苦差盲区”案例是Stripe,或者说Stripe的创意。十多年来,每个处理过线上支付的黑客都深知其痛苦。成千上万人肯定都意识到了这个问题。然而当他们创业时,却选择做菜谱网站或本地活动聚合平台。为什么?明明可以修复全球基础设施中最关键的组件之一,为何偏要解决那些无人关心也无人付费的问题?因为“苦差盲区”让他们根本不曾考虑过改造支付系统。 或许没有一个申请Y Combinator做菜谱网站的团队曾自问:“该改造支付系统还是做菜谱网站?”然后选择了后者。尽管支付问题明明近在眼前,他们却视而不见,因为潜意识畏惧其中的复杂:要和银行谈判——怎么谈?还要处理资金流动——必然面临欺诈和黑客攻击。更别提还有各种法规要遵守。相比菜谱网站,这种创业显然令人望而生畏。 正是这种恐惧感,让雄心勃勃的点子具备双重价值。除了内在价值,它们还像被低估的股票——创始人群体对其需求更少。选择宏大的创意,竞争会更少,因为其他人已被挑战吓退(广义的创业亦是如此)。 如何克服“苦差盲区”?坦率说,最有效的解药或许是“无知”。多数成功创始人会承认:如果创业之初就知道要跨越多少障碍,他们可能根本不会开始。这或许解释了为何史上最成功的初创公司往往由年轻人创立。 实践中,创始人会与问题共同成长。但似乎无人能预见到这点,包括更年长、更有经验的创始人。因此年轻创始人的优势在于,他们犯的两个错误相互抵消:既不知道自己能成长多少,也不清楚需要成长多少。而年长创始人只犯第一个错误。 但无知无法解决一切。有些点子明显伴随骇人的苦差事,谁都看得见。如何发现这类创意?我推荐的诀窍是:跳出自我视角。别问“我该解决什么问题?”,而要问“我希望别人帮我解决什么问题?”如果Stripe出现前,那些受支付问题困扰的人这样自问,“改造支付系统”必定是他们的首要愿望。 如今成为Stripe为时已晚,但世界上仍有无数待修复的漏洞——只要你能看见它们。 感谢 Sam Altman、Paul Buchheit、Patrick Collison、Aaron Iba、Jessica Livingston、Emmett Shear和Harj Taggar阅读本文草稿。
Want to start a startup? Get funded by Y Combinator.
January 2012 A year ago I noticed a pattern in the least successful startups we'd funded: they all seemed hard to talk to. It felt as if there was some kind of wall between us. I could never quite tell if they understood what I was saying. This caught my attention because earlier we'd noticed a pattern among the most successful startups, and it seemed to hinge on a different quality. We found the startups that did best were the ones with the sort of founders about whom we'd say "they can take care of themselves." The startups that do best are fire-and-forget in the sense that all you have to do is give them a lead, and they'll close it, whatever type of lead it is. When they're raising money, for example, you can do the initial intros knowing that if you wanted to you could stop thinking about it at that point. You won't have to babysit the round to make sure it happens. That type of founder is going to come back with the money; the only question is how much on what terms. It seemed odd that the outliers at the two ends of the spectrum could be detected by what appeared to be unrelated tests. You'd expect that if the founders at one end were distinguished by the presence of quality x, at the other end they'd be distinguished by lack of x. Was there some kind of inverse relation between resourcefulness and being hard to talk to? It turns out there is, and the key to the mystery is the old adage "a word to the wise is sufficient." Because this phrase is not only overused, but overused in an indirect way (by prepending the subject to some advice), most people who've heard it don't know what it means. What it means is that if someone is wise, all you have to do is say one word to them, and they'll understand immediately. You don't have to explain in detail; they'll chase down all the implications.
想创立一家创业公司? 获得 Y Combinator 的资助。
一年前,我注意到我们资助过的最不成功的创业公司有一个共同点:它们似乎都很难沟通。感觉我们之间隔着一堵墙。我始终无法确定他们是否理解我说的话。
这一点引起了我的注意,因为早些时候我们发现最成功的创业公司也有一个共同点,而这个共同点似乎取决于另一种特质。我们发现,表现最好的创业公司往往拥有那种我们称之为“能照顾好自己”的创始人。这些创业公司之所以表现最佳,是因为它们像“发射后不管”一样——你只需要给他们一个线索,他们就能搞定,无论这个线索是什么类型。例如,当他们融资时,你只需要做最初的介绍,之后就可以完全放手。你不需要像保姆一样盯着整个融资过程确保它完成。这类创始人总能带着钱回来,唯一的问题是金额和条款。
奇怪的是,光谱两端的异常值似乎可以通过看似无关的测试来检测。你可能会认为,如果一端的创始人以拥有特质x为标志,那么另一端的创始人应该以缺乏x为标志。难道应变能力和难以沟通之间存在某种反向关系?
In much the same way that all you have to do is give the right sort of founder a one line intro to a VC, and he'll chase down the money. That's the connection. Understanding all the implications — even the inconvenient implications — of what someone tells you is a subset of resourcefulness. It's conversational resourcefulness. Like real world resourcefulness, conversational resourcefulness often means doing things you don't want to. Chasing down all the implications of what's said to you can sometimes lead to uncomfortable conclusions. The best word to describe the failure to do so is probably "denial," though that seems a bit too narrow. A better way to describe the situation would be to say that the unsuccessful founders had the sort of conservatism that comes from weakness. They traversed idea space as gingerly as a very old person traverses the physical world. [1] The unsuccessful founders weren't stupid. Intellectually they were as capable as the successful founders of following all the implications of what one said to them. They just weren't eager to. So being hard to talk to was not what was killing the unsuccessful startups. It was a sign of an underlying lack of resourcefulness. That's what was killing them. As well as failing to chase down the implications of what was said to them, the unsuccessful founders would also fail to chase down funding, and users, and sources of new ideas. But the most immediate evidence I had that something was amiss was that I couldn't talk to them. Notes [1] A YC partner wrote: My feeling with the bad groups is that coming into office hours, they've already decided what they're going to do and everything I say is being put through an internal process in their heads, which either desperately tries to munge what I've said into something that conforms with their decision or just outright dismisses it and creates a rationalization for doing so.
事实证明,确实如此,而解开这个谜团的关键是一句古老的格言:“智者一言已足。”由于这句话不仅被过度使用,而且是以间接方式被过度使用(通常是在建议前加上这句话),大多数听过它的人并不明白它的真正含义。它的意思是,如果一个人足够明智,你只需要对他说一个词,他就能立刻理解。你不需要详细解释;他们会自己推敲出所有隐含的意义。
这与你只需要给合适的创始人一行简短的介绍,他就能搞定风投的情况非常相似。这就是两者的联系。理解别人告诉你的一切隐含意义——甚至是不便言明的意义——是应变能力的一部分。这是一种对话中的应变能力。
就像现实世界中的应变能力一样,对话中的应变能力通常意味着做你不想做的事。推敲别人话语中的所有隐含意义有时会得出令人不安的结论。描述未能做到这一点的最佳词汇可能是“否认”,尽管这似乎有点狭隘。更好的描述方式是,不成功的创始人有一种源于软弱的保守主义。他们在思想空间中的探索就像一位老人在现实世界中小心翼翼行走一样。[1]
不成功的创始人并不愚蠢。在智力上,他们完全有能力像成功的创始人一样理解别人话语中的隐含意义。他们只是不愿意这么做。
They may not even be conscious of this process but that's what I think is happening when you say something to bad groups and they have that glazed over look. I don't think it's confusion or lack of understanding per se, it's this internal process at work. With the good groups, you can tell that everything you say is being looked at with fresh eyes and even if it's dismissed, it's because of some logical reason e.g. "we already tried that" or "from speaking to our users that isn't what they'd like," etc. Those groups never have that glazed over look. Thanks to Sam Altman, Patrick Collison, Aaron Iba, Jessica Livingston, Robert Morris, Harj Taggar, and Garry Tan for reading drafts of this..
因此,难以沟通并不是导致这些创业公司失败的原因。它只是反映了深层次应变能力的缺乏。这才是真正的致命问题。除了未能推敲别人话语中的隐含意义,不成功的创始人还往往无法搞定融资、用户和新想法的来源。但对我来说,最直接的迹象是:我无法和他们沟通。
[1] 一位YC合伙人写道:
我的感觉是,那些表现糟糕的团队在进入办公室之前,已经决定了他们要做什么,而我说的一切都会在他们头脑中经历一个内部处理过程——要么拼命扭曲我的话以符合他们的决定,要么直接驳回并为此编造理由。他们甚至可能没有意识到这个过程,但这就是当你对糟糕的团队说些什么时,他们眼神呆滞的原因。我认为这不是单纯的困惑或缺乏理解,而是这种内部机制在起作用。
而对于优秀的团队,你可以感觉到他们用全新的眼光看待你说的每一句话,即使他们选择忽略,也是基于某种逻辑原因,比如“我们已经试过了”或“通过与用户交流,他们并不喜欢这样”等等。这些团队从来不会眼神呆滞。
感谢 Sam Altman、Patrick Collison、Aaron Iba、Jessica Livingston、Robert Morris、Harj Taggar 和 Garry Tan 阅读本文草稿。
Want to start a startup? Get funded by Y Combinator.
October 2011 If you look at a list of US cities sorted by population, the number of successful startups per capita varies by orders of magnitude. Somehow it's as if most places were sprayed with startupicide. I wondered about this for years. I could see the average town was like a roach motel for startup ambitions: smart, ambitious people went in, but no startups came out. But I was never able to figure out exactly what happened inside the motel—exactly what was killing all the potential startups. [1] A couple weeks ago I finally figured it out. I was framing the question wrong. The problem is not that most towns kill startups. It's that death is the default for startups, and most towns don't save them. Instead of thinking of most places as being sprayed with startupicide, it's more accurate to think of startups as all being poisoned, and a few places being sprayed with the antidote. Startups in other places are just doing what startups naturally do: fail. The real question is, what's _saving_ startups in places like Silicon Valley? [2] Environment I think there are two components to the antidote: being in a place where startups are the cool thing to do, and chance meetings with people who can help you. And what drives them both is the number of startup people around you. The first component is particularly helpful in the first stage of a startup's life, when you go from merely having an interest in starting a company to actually doing it. It's quite a leap to start a startup. It's an unusual thing to do. But in Silicon Valley it seems normal. [3] In most places, if you start a startup, people treat you as if you're unemployed. People in the Valley aren't automatically impressed with you just because you're starting a company, but they pay attention.
Anyone who's been here any amount of time knows not to default to skepticism, no matter how inexperienced you seem or how unpromising your idea sounds at first, because they've all seen inexperienced founders with unpromising sounding ideas who a few years later were billionaires. Having people around you care about what you're doing is an extraordinarily powerful force. Even the most willful people are susceptible to it. About a year after we started Y Combinator I said something to a partner at a well known VC firm that gave him the (mistaken) impression I was considering starting another startup. He responded so eagerly that for about half a second I found myself considering doing it. In most other cities, the prospect of starting a startup just doesn't seem real. In the Valley it's not only real but fashionable. That no doubt causes a lot of people to start startups who shouldn't. But I think that's ok. Few people are suited to running a startup, and it's very hard to predict beforehand which are (as I know all too well from being in the business of trying to predict beforehand), so lots of people starting startups who shouldn't is probably the optimal state of affairs. As long as you're at a point in your life when you can bear the risk of failure, the best way to find out if you're suited to running a startup is to try it. Chance The second component of the antidote is chance meetings with people who can help you. This force works in both phases: both in the transition from the desire to start a startup to starting one, and the transition from starting a company to succeeding. The power of chance meetings is more variable than people around you caring about startups, which is like a sort of background radiation that affects everyone equally, but at its strongest it is far stronger. Chance meetings produce miracles to compensate for the disasters that characteristically befall startups.
In the Valley, terrible things happen to startups all the time, just like they do to startups everywhere. The reason startups are more likely to make it here is that great things happen to them too. In the Valley, lightning has a sign bit. For example, you start a site for college students and you decide to move to the Valley for the summer to work on it. And then on a random suburban street in Palo Alto you happen to run into Sean Parker, who understands the domain really well because he started a similar startup himself, and also knows all the investors. And moreover has advanced views, for 2004, on founders retaining control of their companies. You can't say precisely what the miracle will be, or even for sure that one will happen. The best one can say is: if you're in a startup hub, unexpected good things will probably happen to you, especially if you deserve them. I bet this is true even for startups we fund. Even with us working to make things happen for them on purpose rather than by accident, the frequency of helpful chance meetings in the Valley is so high that it's still a significant increment on what we can deliver. Chance meetings play a role like the role relaxation plays in having ideas. Most people have had the experience of working hard on some problem, not being able to solve it, giving up and going to bed, and then thinking of the answer in the shower in the morning. What makes the answer appear is letting your thoughts drift a bit—and thus drift off the wrong path you'd been pursuing last night and onto the right one adjacent to it. Chance meetings let your acquaintance drift in the same way taking a shower lets your thoughts drift. The critical thing in both cases is that they drift just the right amount. The meeting between Larry Page and Sergey Brin was a good example. They let their acquaintance drift, but only a little; they were both meeting someone they had a lot in common with.
For Larry Page the most important component of the antidote was Sergey Brin, and vice versa. The antidote is people. It's not the physical infrastructure of Silicon Valley that makes it work, or the weather, or anything like that. Those helped get it started, but now that the reaction is self-sustaining what drives it is the people. Many observers have noticed that one of the most distinctive things about startup hubs is the degree to which people help one another out, with no expectation of getting anything in return. I'm not sure why this is so. Perhaps it's because startups are less of a zero sum game than most types of business; they are rarely killed by competitors. Or perhaps it's because so many startup founders have backgrounds in the sciences, where collaboration is encouraged. A large part of YC's function is to accelerate that process. We're a sort of Valley within the Valley, where the density of people working on startups and their willingness to help one another are both artificially amplified. Numbers Both components of the antidote—an environment that encourages startups, and chance meetings with people who help you—are driven by the same underlying cause: the number of startup people around you. To make a startup hub, you need a _lot_ of people interested in startups. There are three reasons. The first, obviously, is that if you don't have enough density, the chance meetings don't happen. [4] The second is that different startups need such different things, so you need a lot of people to supply each startup with what they need most. Sean Parker was exactly what Facebook needed in 2004. Another startup might have needed a database guy, or someone with connections in the movie business. This is one of the reasons we fund such a large number of companies, incidentally. The bigger the community, the greater the chance it will contain the person who has that one thing you need most.
The third reason you need a lot of people to make a startup hub is that once you have enough people interested in the same problem, they start to set the social norms. And it is a particularly valuable thing when the atmosphere around you encourages you to do something that would otherwise seem too ambitious. In most places the atmosphere pulls you back toward the mean. I flew into the Bay Area a few days ago. I notice this every time I fly over the Valley: somehow you can sense something is going on. Obviously you can sense prosperity in how well kept a place looks. But there are different kinds of prosperity. Silicon Valley doesn't look like Boston, or New York, or LA, or DC. I tried asking myself what word I'd use to describe the feeling the Valley radiated, and the word that came to mind was optimism. Notes [1] I'm not saying it's impossible to succeed in a city with few other startups, just harder. If you're sufficiently good at generating your own morale, you can survive without external encouragement. Wufoo was based in Tampa and they succeeded. But the Wufoos are exceptionally disciplined. [2] Incidentally, this phenomenon is not limited to startups. Most unusual ambitions fail, unless the person who has them manages to find the right sort of community. [3] Starting a company is common, but starting a startup is rare. I've talked about the distinction between the two elsewhere, but essentially a startup is a new business designed for scale. Most new businesses are service businesses and except in rare cases those don't scale. [4] As I was writing this, I had a demonstration of the density of startup people in the Valley. Jessica and I bicycled to University Ave in Palo Alto to have lunch at the fabulous Oren's Hummus. As we walked in, we met Charlie Cheever sitting near the door. Selina Tobaccowala stopped to say hello on her way out. Then Josh Wilson came in to pick up a take out order.
After lunch we went to get frozen yogurt. On the way we met Rajat Suri. When we got to the yogurt place, we found Dave Shen there, and as we walked out we ran into Yuri Sagalov. We walked with him for a block or so and we ran into Muzzammil Zaveri, and then a block later we met Aydin Senkut. This is everyday life in Palo Alto. I wasn't trying to meet people; I was just having lunch. And I'm sure for every startup founder or investor I saw that I knew, there were 5 more I didn't. If Ron Conway had been with us he would have met 30 people he knew. Thanks to Sam Altman, Paul Buchheit, Jessica Livingston, and Harj Taggar for reading drafts of this..
想创业吗? 获得 Y Combinator 的资助。
2011年10月 如果你查看按人口排序的美国城市列表,会发现人均成功创业公司的数量存在数量级的差异。仿佛大多数地方都被喷上了“创业灭绝剂”。 多年来我对此感到困惑。普通城镇就像一家针对创业抱负的“蟑螂旅馆”:聪明有野心的人走进去,却没有创业公司走出来。但我始终无法确切理解旅馆内部发生了什么——究竟是什么扼杀了所有潜在的创业公司。[1] 几周前我终于想明白了。我的问题框架错了。问题不在于大多数城镇扼杀创业公司,而是创业公司天生就注定失败,而大多数城镇未能拯救它们。与其认为大多数地方被喷洒了“创业灭绝剂”,不如说所有创业公司都中了毒,而少数地方喷洒了解药。 其他地方的创业公司只是在做自然会发生的事:失败。真正的问题是,像硅谷这样的地方是如何拯救创业公司的?[2] 环境 我认为解药包含两个要素:身处一个创业被视为潮流的地方,以及偶遇能帮助你的人。而驱动这两者的核心,是你周围创业者的数量。 第一个要素在创业初期尤为重要——当你从仅仅有兴趣创立公司转变为真正付诸行动时。创业是一个巨大的跨越,是件非比寻常的事。但在硅谷,这显得稀松平常。[3] 在大多数地方,如果你创业,人们会把你当作无业游民。硅谷的人不会仅仅因为你创业就对你刮目相看,但他们会关注你。任何在这里待过的人都知道不该轻易持怀疑态度,无论你看起来多么缺乏经验,或你的想法起初听起来多么不靠谱,因为他们都见过看似毫无希望、缺乏经验的创始人,几年后却成为亿万富翁。 周围人对你所作所为的关注是一种异常强大的力量。即使意志最坚定的人也难以抗拒。在我们创立Y Combinator约一年后,我对某知名风投机构的合伙人说了些话,让他(错误地)以为我在考虑再次创业。他热切的反应让我在瞬间真的考虑起这个可能性。 在其他大多数城市,创业的前景显得不真实。在硅谷,它不仅真实,而且时髦。这无疑会让许多不该创业的人投身其中。但我认为这没关系。适合经营创业公司的人本就稀少,且很难提前预测谁适合(作为从事预测工作的人,我深有体会),因此大量本不该创业的人尝试创业,可能是最优状态。只要处于能承受失败风险的人生阶段,判断自己是否适合创业的最佳方式就是亲自尝试。 机遇 解药的第二个要素是偶遇能帮助你的人。这种力量在两个阶段都起作用:从渴望创业到真正创业的过渡期,以及从创立公司到取得成功的阶段。偶遇的力量比周围人对创业的关注更具变数——后者如同影响每个人的背景辐射,但前者在最强时威力远超后者。 偶遇能创造奇迹,弥补创业公司常遭遇的灾难。在硅谷,创业公司随时可能遭遇糟糕的事,和其他地方一样。这里的创业公司更可能成功,是因为它们也会遇到美好的事。在硅谷,闪电带着正负号。 例如,你创建了一个面向大学生的网站,决定夏天搬到硅谷推进项目。然后在帕洛阿尔托某条普通的郊区街道上,你偶遇肖恩·帕克——他非常了解这个领域(因为他自己创办过类似公司),还认识所有投资人。更重要的是,在2004年他就持有创始人应保持公司控制权的超前观点。 你无法精确预知会出现什么奇迹,甚至不能保证一定会有奇迹。只能说:如果你在创业中心,意外的好事很可能会发生,尤其当你值得拥有时。 我敢说这对我们投资的创业公司也成立。尽管我们努力为他们创造机会而非依赖偶然,但硅谷高频率的助力型偶遇,仍为我们能提供的帮助带来显著增量。 偶遇的作用类似于放松对创意的激发。多数人都有过这样的经历:苦苦思索某个问题无果,放弃睡觉,次日清晨却在淋浴时想到答案。答案浮现的关键是让思维稍微游荡——从而脱离昨晚错误的思路,滑向与之相邻的正确路径。 偶遇让人际关系如同淋浴时的思绪般自然流动。两者的关键在于“恰到好处的偏离”。拉里·佩奇与谢尔盖·布林的相遇就是典范:他们的人际网络自然延伸,但幅度刚好;他们遇到的都是与自己高度契合的人。 对拉里·佩奇而言,解药最重要的成分是谢尔盖·布林,反之亦然。解药就是人。让硅谷运转的不是物理基础设施、气候或其他类似因素。这些只是初始条件,如今维持这个生态自我运转的核心是人。 许多观察者注意到,创业中心最显著的特征之一是人们不计回报互相帮助的程度。我不确定原因。或许因为创业不像多数商业活动那样是零和游戏——它们很少被竞争对手扼杀。又或许因为太多创业者有科学背景,而科学鼓励协作。 YC的重要功能就是加速这个过程。我们像是硅谷中的硅谷,通过人为方式放大创业者的密度及其互助意愿。 数量 解药的两个要素——鼓励创业的环境与助力型偶遇——都由同一根本原因驱动:你周围创业者的数量。要打造创业中心,你需要大量对创业感兴趣的人。 这有三点原因。第一,若密度不足,偶遇就不会发生。[4] 第二,不同创业公司需求迥异,需要大量人来满足它们最迫切的需求。2004年的Facebook正需要肖恩·帕克,另一家公司可能需要数据库专家或电影业人脉。 这也是我们投资大量公司的原因之一:社区越大,越可能包含能提供你最需要资源的人。 第三,只有当足够多人关注同一问题时,他们才会建立社会规范。当周围氛围鼓励你尝试原本看似过于雄心勃勃的事情时,这种氛围尤其珍贵。大多数地方的环境会将你拉回平庸。 几天前我飞抵湾区。每次飞越硅谷上空时我都能察觉到异常:你能感觉到某些事情正在发生。显然,从城市的整洁程度能感知繁荣。但繁荣有不同形态。硅谷与波士顿、纽约、洛杉矶或华盛顿都不同。当我试图用词汇描述硅谷散发的气质时,跃入脑海的是“乐观”。 注释 [1] 我并非说在缺乏创业公司的城市不可能成功,只是更难。如果你足够擅长自我激励,无需外部鼓励也能生存。Wufoo总部位于坦帕,但他们成功了。不过Wufoo团队异常自律。 [2] 这种现象不仅限于创业。多数非常规抱负都会失败,除非其持有者找到合适的社群。 [3] 创立公司很常见,但创立创业公司很罕见。我曾 elsewhere 讨论过二者的区别:本质上,创业公司是为规模化设计的新业务。多数新业务是服务业,除少数例外通常无法规模化。 [4] 写作本文时,我亲历了硅谷创业者的高密度。我和Jessica骑车去帕洛阿尔托的University Ave,在美味的Oren's Hummus吃午餐。进门时遇见坐在门口的Charlie Cheever;Selina Tobaccowala出门时驻足问候;随后Josh Wilson进来取外卖。午餐后我们去买冻酸奶,途中遇见Rajat Suri;到达酸奶店发现Dave Shen在场;离开时偶遇Yuri Sagalov;与他同行一个街区又遇见Muzzammil Zaveri;再过一个街区见到Aydin Senkut。这就是帕洛阿尔托的日常。我并非刻意社交,只是吃个午饭。我确信,每遇见一个认识的创业者或投资人,就有五个我不认识的擦肩而过。如果Ron Conway同行,他会遇见30个熟人。 致谢 Sam Altman、Paul Buchheit、Jessica Livingston和Harj Taggar阅读了本文草稿。.
August 2011 I realized recently that we may be able to solve part of the patent problem without waiting for the government. I've never been 100% sure whether patents help or hinder technological progress. When I was a kid I thought they helped. I thought they protected inventors from having their ideas stolen by big companies. Maybe that was truer in the past, when more things were physical. But regardless of whether patents are in general a good thing, there do seem to be bad ways of using them. And since bad uses of patents seem to be increasing, there is an increasing call for patent reform. The problem with patent reform is that it has to go through the government. That tends to be slow. But recently I realized we can also attack the problem downstream. As well as pinching off the stream of patents at the point where they're issued, we may in some cases be able to pinch it off at the point where they're used. One way of using patents that clearly does not encourage innovation is when established companies with bad products use patents to suppress small competitors with good products. This is the type of abuse we may be able to decrease without having to go through the government. The way to do it is to get the companies that are above pulling this sort of trick to pledge publicly not to. Then the ones that won't make such a pledge will be very conspicuous. Potential employees won't want to work for them. And investors, too, will be able to see that they're the sort of company that competes by litigation rather than by making good products. Here's the pledge: > No first use of software patents against companies with less than 25 people.
2011年8月 我最近意识到,我们或许能在不依赖政府的情况下解决部分专利问题。 关于专利究竟是促进还是阻碍技术进步,我从未百分百确定。小时候我以为专利能保护发明者,防止大公司窃取他们的创意。在过去以实体发明为主的时代,这种看法或许更接近事实。但无论专利制度整体是否合理,某些滥用专利的行为显然存在问题。随着专利滥用现象日益增多,要求专利改革的呼声也愈发高涨。 专利改革的问题在于必须通过政府推动,这一过程往往进展缓慢。但最近我发现,我们也可以从下游环节入手解决。除了在专利授权环节进行限制外,在某些情况下我们还能在专利使用环节加以制约。 当拥有劣质产品的老牌企业利用专利打压拥有优质产品的小型竞争对手时,这种专利使用方式显然无益于创新。这类滥用行为或许无需政府介入就能减少。 解决方案是让那些不屑于耍这种手段的企业公开承诺不滥用专利。如此一来,拒绝承诺的企业就会格外显眼。潜在员工将不愿为其效力,投资者也能清楚识别出这些靠诉讼而非优质产品参与竞争的企业。 具体承诺如下: > 绝不率先对员工少于25人的企业使用软件专利。
我刻意牺牲了精确性以换取简洁。专利承诺并不具有法律约束力。它就像谷歌的"不作恶"原则。他们没有定义何为恶,但通过公开声明这一点,他们表明自己愿意遵守比奥驰亚集团更高的标准。尽管有所约束,"不作恶"原则对谷歌大有裨益。科技公司通过吸引最具创造力的人才取胜,而这些人才往往青睐那些自我要求高于法律规定的雇主。[1]
专利承诺实质上是一个更具体但开源的"不作恶"版本。我鼓励每家科技公司都采纳它。如果你想帮助改善专利制度,就推动你的雇主行动吧。
I've deliberately traded precision for brevity. The patent pledge is not legally binding. It's like Google's "Don't be evil." They don't define what evil is, but by publicly saying that, they're saying they're willing to be held to a standard that, say, Altria is not. And though constraining, "Don't be evil" has been good for Google. Technology companies win by attracting the most productive people, and the most productive people are attracted to employers who hold themselves to a higher standard than the law requires. [1] The patent pledge is in effect a narrower but open source "Don't be evil." I encourage every technology company to adopt it. If you want to help fix patents, encourage your employer to. Already most technology companies wouldn't sink to using patents on startups. You don't see Google or Facebook suing startups for patent infringement. They don't need to. So for the better technology companies, the patent pledge requires no change in behavior. They're just promising to do what they'd do anyway. And when all the companies that won't use patents on startups have said so, the holdouts will be very conspicuous. The patent pledge doesn't fix every problem with patents. It won't stop patent trolls, for example; they're already pariahs. But the problem the patent pledge does fix may be more serious than the problem of patent trolls. Patent trolls are just parasites. A clumsy parasite may occasionally kill the host, but that's not its goal. Whereas companies that sue startups for patent infringement generally do it with explicit goal of keeping their product off the market. Companies that use patents on startups are attacking innovation at the root.
事实上,多数科技公司本就不会对初创企业动用专利武器。你从没见过谷歌或Facebook因专利侵权起诉初创公司。他们不需要这样做。因此对优秀的科技公司而言,专利承诺无需改变现有行为——他们只是承诺继续做本就在做的事。当所有不愿对初创企业使用专利的公司都公开表态后,那些拒不表态者将格外显眼。
专利承诺并不能解决所有专利问题。例如它无法阻止专利流氓——他们早已声名狼藉。但专利承诺所能解决的问题,可能比专利流氓更严重。专利流氓只是寄生虫,笨拙的寄生虫偶尔会害死宿主,但这并非其本意。而那些起诉初创公司专利侵权的企业,通常明确以将对手产品逐出市场为目标。
对初创企业动用专利武器的公司,正在扼杀创新根基。如今每个人都能为此做些事情,无需等待政府行动:直接询问企业的立场。
Now there's something any individual can do about this problem, without waiting for the government: ask companies where they stand. Patent Pledge Site Notes: [1] Because the pledge is deliberately vague, we're going to need common sense when intepreting it. And even more vice versa: the pledge is vague in order to make people use common sense when interpreting it. So for example I've deliberately avoided saying whether the 25 people have to be employees, or whether contractors count too. If a company has to split hairs that fine about whether a suit would violate the patent pledge, it's probably still a dick move.
March 2011 Yesterday Fred Wilson published a remarkable post about missing Airbnb. VCs miss good startups all the time, but it's extraordinarily rare for one to talk about it publicly till long afterward. So that post is further evidence what a rare bird Fred is. He's probably the nicest VC I know. Reading Fred's post made me go back and look at the emails I exchanged with him at the time, trying to convince him to invest in Airbnb. It was quite interesting to read. You can see Fred's mind at work as he circles the deal. Fred and the Airbnb founders have generously agreed to let me publish this email exchange (with one sentence redacted about something that's strategically important to Airbnb and not an important part of the conversation). It's an interesting illustration of an element of the startup ecosystem that few except the participants ever see: investors trying to convince one another to invest in their portfolio companies. Hundreds if not thousands of conversations of this type are happening now, but if one has ever been published, I haven't seen it. The Airbnbs themselves never even saw these emails at the time. We do a lot of this behind the scenes stuff at YC, because we invest in such a large number of companies, and we invest so early that investors sometimes need a lot of convincing to see their merits. I don't always try as hard as this though. Fred must have found me quite annoying.
from: Paul Graham to: Fred Wilson, AirBedAndBreakfast Founders date: Fri, Jan 23, 2009 at 11:42 AM subject: meet the airbeds One of the startups from the batch that just started, AirbedAndBreakfast, is in NYC right now meeting their users. (NYC is their biggest market.) I'd recommend meeting them if your schedule allows.
I'd been thinking to myself that though these guys were going to do really well, I should introduce them to angels, because VCs would never go for it. But then I thought maybe I should give you more credit. You'll certainly like meeting them. Be sure to ask about how they funded themselves with breakfast cereal. There's no reason this couldn't be as big as Ebay. And this team is the right one to do it. --pg from: Brian Chesky to: Paul Graham cc: Nathan Blecharczyk, Joe Gebbia date: Fri, Jan 23, 2009 at 11:40 AM subject: Re: meet the airbeds PG, Thanks for the intro! Brian from: Paul Graham to: Brian Chesky cc: Nathan Blecharczyk, Joe Gebbia date: Fri, Jan 23, 2009 at 12:38 PM subject: Re: meet the airbeds It's a longshot, at this stage, but if there was any VC who'd get you guys, it would be Fred. He is the least suburban-golf-playing VC I know. He likes to observe startups for a while before acting, so don't be bummed if he seems ambivalent. --pg from: Fred Wilson to: Paul Graham, date: Sun, Jan 25, 2009 at 5:28 PM subject: Re: meet the airbeds Thanks Paul We are having a bit of a debate inside our partnership about the airbed concept. We'll finish that debate tomorrow in our weekly meeting and get back to you with our thoughts Thanks Fred from: Paul Graham to: Fred Wilson date: Sun, Jan 25, 2009 at 10:48 PM subject: Re: meet the airbeds I'd recommend having the debate after meeting them instead of before.
2011年3月 昨天弗雷德·威尔逊发表了一篇引人注目的文章,讲述他错过投资Airbnb的经历。风险投资家错过优秀初创公司是常有的事,但很少有人会在多年后公开谈论此事。因此这篇文章进一步证明了弗雷德是多么与众不同。他可能是我认识的最友善的风险投资家。 阅读弗雷德的文章让我回顾了当时与他交换的邮件,那时我试图说服他投资Airbnb。重读这些邮件非常有趣。你可以看到弗雷德在反复权衡这笔交易时的思考过程。 弗雷德和Airbnb的创始人们慷慨地同意我公开这些邮件往来(其中删减了一句话,涉及对Airbnb具有战略重要性但并非对话核心的内容)。这生动展示了初创企业生态系统中鲜为人知的一面:投资者之间如何相互说服对方投资自己投资组合中的公司。类似这样的对话此刻正在发生成百上千次,但此前从未见诸公开——就连Airbnb团队当时也没见过这些邮件。 在YC(Y Combinator),我们经常在幕后做这类工作,因为我们投资了大量公司,而且投资阶段非常早期,有时需要花很大力气才能让其他投资者看到这些公司的潜力。不过,我很少像这次这样极力推荐。弗雷德当时一定觉得我很烦人。
发件人:保罗·格雷厄姆 收件人:弗雷德·威尔逊,AirBedAndBreakfast创始团队 日期:2009年1月23日 上午11:42 主题:见见Airbed团队 我们这期孵化项目中刚起步的AirBedAndBreakfast团队正在纽约拜访用户(纽约是他们最大的市场)。如果你时间允许,我建议和他们见面。 我原本觉得虽然这帮人将来会做得很好,但应该把他们介绍给天使投资人,因为风投肯定不会感兴趣。但转念一想,或许我该对你更有信心。你一定会喜欢和他们见面。记得问问他们怎么靠卖麦片解决启动资金的。 这个项目完全有可能做到eBay的规模。而他们正是能实现这个目标的团队。 ——pg 发件人:布莱恩·切斯基 收件人:保罗·格雷厄姆 抄送:内森·布莱查克泽克,乔·杰比亚 日期:2009年1月23日 上午11:40 主题:回复:见见Airbed团队 PG, 感谢引荐! 布莱恩 发件人:保罗·格雷厄姆 收件人:布莱恩·切斯基 抄送:内森·布莱查克泽克,乔·杰比亚 日期:2009年1月23日 中午12:38 主题:回复:见见Airbed团队 现阶段希望渺茫,但如果真有哪个风投能理解你们,那一定是弗雷德。他是我认识的最不像"郊区高尔夫球手"类型的风投。 他习惯先观察初创公司一段时间再行动,所以如果他显得犹豫也别沮丧。 ——pg 发件人:弗雷德·威尔逊 收件人:保罗·格雷厄姆 日期:2009年1月25日 下午5:28 主题:回复:见见Airbed团队 谢谢保罗 我们合伙团队内部对气垫床这个概念有些分歧。明天周会上我们会讨论出结果并反馈想法。 致谢 弗雷德 发件人:保罗·格雷厄姆 收件人:弗雷德·威尔逊 日期:2009年1月25日 晚上10:48 主题:回复:见见Airbed团队 我建议先见面再讨论。我们当初对这个点子也充满疑虑,但见到他们后所有疑虑都消失了。 发件人:弗雷德·威尔逊 收件人:保罗·格雷厄姆 日期:2009年1月26日 上午11:08 主题:回复:见见Airbed团队 我们仍对这个想法存疑,但会按你建议安排会面。 谢谢 弗雷德 发件人:弗雷德·威尔逊 收件人:保罗·格雷厄姆,AirBedAndBreakfast创始团队 日期:2009年1月26日 上午11:09 主题:回复:见见Airbed团队 Airbed团队: 你们还在纽约吗? 如果方便我们希望见面。 致谢 弗雷德 发件人:保罗·格雷厄姆 收件人:弗雷德·威尔逊 日期:2009年1月26日 下午1:42 主题:回复:见见Airbed团队 商业构想会进化。几乎所有成功的初创公司五年后都可以说:"信不信由你,我们最初是做___的。"让我特别看好的是,这帮人真的扎根纽约,亲自寻找(并理解)他们的用户——这已经是他们展现的多个积极信号之一。 ——pg 发件人:弗雷德·威尔逊 收件人:保罗·格雷厄姆 日期:2009年2月1日 早上7:15 主题:回复:见见Airbed团队 有意思 我们两位年轻同事很热情 三位"老家伙"没搞明白 发件人:保罗·格雷厄姆 收件人:弗雷德·威尔逊 日期:2009年2月9日 下午5:58 主题:airbnb Airbed团队刚刚以压倒性优势赢得同期所有YC初创公司的首轮内部投票。历史数据表明这虽非百分之百的成功预兆(要真有这种指标就好了),但比随机选择强得多。 ——pg 发件人:弗雷德·威尔逊 收件人:保罗·格雷厄姆 日期:2009年2月13日 下午5:29 主题:回复:airbnb 今天见了他们 业务模式挺有趣 只是不确定能发展到多大规模 弗雷德 发件人:保罗·格雷厄姆 收件人:弗雷德·威尔逊 日期:2009年2月14日 上午9:50 主题:回复:airbnb 他们解释过长期目标是要像eBay整合商品市场那样整合住宿市场吗?这个前景应该非常广阔。现在的酒店业就像1970年代的航空公司——还没学会如何提升负载率。 发件人:弗雷德·威尔逊 收件人:保罗·格雷厄姆 日期:2009年2月17日 下午2:05 主题:回复:airbnb 他们提过,但我不太认同 ABNB让我想起Etsy,都是通过市场模式直接促成个人间的真实交易 所以我认为它能覆盖整个民宿市场 但不确定能否撼动酒店业 当然我可能判断错误 不过即便只算短租、度假屋、民宿等细分市场,机会也足够大了 弗雷德 发件人:保罗·格雷厄姆 收件人:弗雷德·威尔逊 日期:2009年2月18日 凌晨12:21 主题:回复:airbnb 那就投资他们啊!他们资金使用效率极高,能让投资人的钱发挥最大价值。 而且这还是个抗周期项目。他们刚从纽约回来,当我问及最重要的观察发现时,答案是许多用户确实需要靠出租房间来支付房租。 ——pg 发件人:弗雷德·威尔逊 收件人:保罗·格雷厄姆 日期:2009年2月18日 凌晨2:21 主题:回复:airbnb 确实有很多亮点 我已经做了些工作,比如引荐给Foundry的朋友们——他们投资过Service Metrics,理解这种模式 还在和马克·平卡斯交流,他几年前就有过类似想法 所以我们正在推进 感谢推荐 弗雷德 发件人:保罗·格雷厄姆 收件人:弗雷德·威尔逊 日期:2009年2月20日 晚上10:00 主题:airbnb已开始吸引专业房东 我知道你怀疑他们能否进入酒店领域,但从私人沙发到酒店房间是个连续谱系,而他们刚刚向前迈进了一步。 [Airbnb用户链接] 这才运营几个月。我打赌他们最终会拿下酒店市场,从小型酒店开始。想象罗马那些10间房的小旅馆发现这个平台时的场景吧。一旦蔓延到酒店业,连锁集团的规模界限在哪里?当某个市场平台足够大时,忽视它就是冒险。 ——pg 发件人:弗雷德·威尔逊 收件人:保罗·格雷厄姆 日期:2009年2月21日 凌晨4:26 主题:回复:airbnb已开始吸引专业房东 有道理。但同样真实的是,市场上已存在不少同类服务平台 很多在ABNB挂牌的房东也在其他平台发布信息 我对这个项目并不悲观,只是仍在数据收集阶段。 弗雷德.
We had big doubts about this idea, but they vanished on meeting the guys. from: Fred Wilson to: Paul Graham date: Mon, Jan 26, 2009 at 11:08 AM subject: RE: meet the airbeds We are still very suspect of this idea but will take a meeting as you suggest Thanks fred from: Fred Wilson to: Paul Graham, AirBedAndBreakfast Founders date: Mon, Jan 26, 2009 at 11:09 AM subject: RE: meet the airbeds Airbed team - Are you still in NYC? We'd like to meet if you are Thanks fred from: Paul Graham to: Fred Wilson date: Mon, Jan 26, 2009 at 1:42 PM subject: Re: meet the airbeds Ideas can morph. Practically every really big startup could say, five years later, "believe it or not, we started out doing ___." It just seemed a very good sign to me that these guys were actually on the ground in NYC hunting down (and understanding) their users. On top of several previous good signs. --pg from: Fred Wilson to: Paul Graham date: Sun, Feb 1, 2009 at 7:15 AM subject: Re: meet the airbeds It's interesting Our two junior team members were enthusiastic The three "old guys" didn't get it from: Paul Graham to: Fred Wilson date: Mon, Feb 9, 2009 at 5:58 PM subject: airbnb The Airbeds just won the first poll among all the YC startups in their batch by a landslide.
In the past this has not been a 100% indicator of success (if only anything were) but much better than random. --pg from: Fred Wilson to: Paul Graham date: Fri, Feb 13, 2009 at 5:29 PM subject: Re: airbnb I met them today They have an interesting business I'm just not sure how big it's going to be fred from: Paul Graham to: Fred Wilson date: Sat, Feb 14, 2009 at 9:50 AM subject: Re: airbnb Did they explain the long-term goal of being the market in accommodation the way eBay is in stuff? That seems like it would be huge. Hotels now are like airlines in the 1970s before they figured out how to increase their load factors. from: Fred Wilson to: Paul Graham date: Tue, Feb 17, 2009 at 2:05 PM subject: Re: airbnb They did but I am not sure I buy that ABNB reminds me of Etsy in that it facilitates real commerce in a marketplace model directly between two people So I think it can scale all the way to the bed and breakfast market But I am not sure they can take on the hotel market I could be wrong But even so, if you include short term room rental, second home rental, bed and breakfast, and other similar classes of accommodations, you get to a pretty big opportunity fred from: Paul Graham to: Fred Wilson date: Wed, Feb 18, 2009 at 12:21 AM subject: Re: airbnb So invest in them! They're very capital efficient. They would make an investor's money go a long way. It's also counter-cyclical.
They just arrived back from NYC, and when I asked them what was the most significant thing they'd observed, it was how many of their users actually needed to do these rentals to pay their rents. --pg from: Fred Wilson to: Paul Graham date: Wed, Feb 18, 2009 at 2:21 AM subject: Re: airbnb There's a lot to like I've done a few things, like intro it to my friends at Foundry who were investors in Service Metrics and understand this model I am also talking to my friend Mark Pincus who had an idea like this a few years ago. So we are working on it Thanks for the lead Fred from: Paul Graham to: Fred Wilson date: Fri, Feb 20, 2009 at 10:00 PM subject: airbnb already spreading to pros I know you're skeptical they'll ever get hotels, but there's a continuum between private sofas and hotel rooms, and they just moved one step further along it. [link to an airbnb user] This is after only a few months. I bet you they will get hotels eventually. It will start with small ones. Just wait till all the 10-room pensiones in Rome discover this site. And once it spreads to hotels, where is the point (in size of chain) at which it stops? Once something becomes a big marketplace, you ignore it at your peril. --pg from: Fred Wilson to: Paul Graham date: Sat, Feb 21, 2009 at 4:26 AM subject: Re: airbnb already spreading to pros That's true. It's also true that there are quite a few marketplaces out there that serve this same market If you look at many of the people who list at ABNB, they list elsewhere too I am not negative on this one, I am interested, but we are still in the gathering data phase. fred.
主题:Airbnb(第2部分,共2部分)
Want to start a startup? Get funded by Y Combinator.
December 2010 Someone we funded is talking to VCs now, and asked me how common it was for a startup's founders to retain control of the board after a series A round. He said VCs told him this almost never happened. Ten years ago that was true. In the past, founders rarely kept control of the board through a series A. The traditional series A board consisted of two founders, two VCs, and one independent member. More recently the recipe is often one founder, one VC, and one independent. In either case the founders lose their majority. But not always. Mark Zuckerberg kept control of Facebook's board through the series A and still has it today. Mark Pincus has kept control of Zynga's too. But are these just outliers? How common is it for founders to keep control after an A round? I'd heard of several cases among the companies we've funded, but I wasn't sure how many there were, so I emailed the ycfounders list. The replies surprised me. In a dozen companies we've funded, the founders still had a majority of the board seats after the series A round. I feel like we're at a tipping point here. A lot of VCs still act as if founders retaining board control after a series A is unheard-of. A lot of them try to make you feel bad if you even ask — as if you're a noob or a control freak for wanting such a thing. But the founders I heard from aren't noobs or control freaks. Or if they are, they are, like Mark Zuckerberg, the kind of noobs and control freaks VCs should be trying to fund more of. Founders retaining control after a series A is clearly heard-of. And barring financial catastrophe, I think in the coming year it will become the norm. Control of a company is a more complicated matter than simply outvoting other parties in board meetings.
Investors usually get vetos over certain big decisions, like selling the company, regardless of how many board seats they have. And board votes are rarely split. Matters are decided in the discussion preceding the vote, not in the vote itself, which is usually unanimous. But if opinion is divided in such discussions, the side that knows it would lose in a vote will tend to be less insistent. That's what board control means in practice. You don't simply get to do whatever you want; the board still has to act in the interest of the shareholders; but if you have a majority of board seats, then your opinion about what's in the interest of the shareholders will tend to prevail. So while board control is not total control, it's not imaginary either. There's inevitably a difference in how things feel within the company. Which means if it becomes the norm for founders to retain board control after a series A, that will change the way things feel in the whole startup world. The switch to the new norm may be surprisingly fast, because the startups that can retain control tend to be the best ones. They're the ones that set the trends, both for other startups and for VCs. A lot of the reason VCs are harsh when negotiating with startups is that they're embarrassed to go back to their partners looking like they got beaten. When they sign a termsheet, they want to be able to brag about the good terms they got. A lot of them don't care that much personally about whether founders keep board control. They just don't want to seem like they had to make concessions. Which means if letting the founders keep control stops being perceived as a concession, it will rapidly become much more common. Like a lot of changes that have been forced on VCs, this change won't turn out to be as big a problem as they might think. VCs will still be able to convince; they just won't be able to compel.
And the startups where they have to resort to compulsion are not the ones that matter anyway. VCs make most of their money from a few big hits, and those aren't them. Knowing that founders will keep control of the board may even help VCs pick better. If they know they can't fire the founders, they'll have to choose founders they can trust. And that's who they should have been choosing all along. Thanks to Sam Altman, John Bautista, Trevor Blackwell, Paul Buchheit, Brian Chesky, Bill Clerico, Patrick Collison, Adam Goldstein, James Lindenbaum, Jessica Livingston, and Fred Wilson for reading drafts of this..
想创立一家初创公司? 获得 Y Combinator 的资助。
2010年12月 我们资助的一位创始人正在与风投机构洽谈,他问我初创公司在A轮融资后创始人仍能掌控董事会的情况是否常见。他提到风投告诉他这几乎从未发生过。 十年前确实如此。过去,创始人很少能在A轮融资后保持对董事会的控制权。传统A轮董事会的构成是两名创始人、两名风投代表和一名独立成员。近年来则通常变为一名创始人、一名风投代表和一名独立成员。无论哪种情况,创始人都失去了多数席位。 但并非总是如此。马克·扎克伯格在Facebook的A轮融资后仍掌控着董事会,至今如此。马克·平卡斯也一直保持着对Zynga董事会的控制。但这些只是特例吗?创始人在A轮后保持控制权的情况有多普遍?我听说过几家我们资助的公司存在这种情况,但不确定具体数量,于是我给ycfounders邮件列表发了询问。 回复让我惊讶。在我们资助的十几家公司中,创始人在A轮后仍拥有董事会多数席位。 我感觉我们正处于一个转折点。许多风投仍表现得好像创始人在A轮后保持董事会控制权闻所未闻。他们甚至会让你因提出这种要求而感到难堪——仿佛你是新手或控制狂。但我接触的这些创始人既非新手也非控制狂。即便他们是,他们也像马克·扎克伯格一样,是风投应该争相投资的那类"新手"和"控制狂"。 创始人A轮后保持控制权显然已有先例。除非遭遇财务灾难,我认为未来一年这将逐渐成为常态。 公司控制权比单纯在董事会投票中压倒对方更复杂。投资者通常对某些重大决策(如出售公司)拥有否决权,无论其董事会席位多少。而且董事会投票很少出现分歧。决策通常在投票前的讨论中就已确定,投票本身往往只是全体一致的形式。但如果讨论中出现分歧,自知会在投票中落败的一方往往会不那么坚持。这就是董事会控制权的实际意义。你并不能为所欲为;董事会仍需以股东利益为准;但若你拥有多数席位,你对股东利益的理解往往会占上风。 因此,虽然董事会控制权不等于绝对控制,但也并非虚幻。公司内部的氛围必然有所不同。这意味着如果创始人A轮后保持董事会控制权成为常态,整个初创企业界的氛围都将改变。 这一新常态的转变可能快得出奇,因为能保持控制权的往往是优质初创企业。他们才是为其他初创企业和风投设定趋势的人。 风投在与初创企业谈判时态度强硬,很大程度上是因为他们不愿在合伙人面前显得处于下风。签署投资条款书时,他们想炫耀自己争取到的有利条款。许多风投个人并不太在意创始人是否保持董事会控制权,只是不想显得被迫让步。这意味着如果允许创始人保持控制权不再被视为让步,这种现象将迅速普及。 如同风投被迫接受的许多变革一样,这一变化不会如他们预想的那般严重。风投仍能说服创始人,只是无法强制要求。而那些需要动用强制手段的初创企业,本就无关紧要。风投的大部分收益来自少数明星项目,而它们不在此列。 知道创始人将保持董事会控制权甚至可能帮助风投更好地筛选项目。如果明白自己无法解雇创始人,他们就只能选择值得信赖的创始人。而这本就是他们一直应该做的选择。 感谢 Sam Altman、John Bautista、Trevor Blackwell、Paul Buchheit、Brian Chesky、Bill Clerico、Patrick Collison、Adam Goldstein、James Lindenbaum、Jessica Livingston和Fred Wilson审阅本文草稿。
December 2010 I was thinking recently how inconvenient it was not to have a general term for iPhones, iPads, and the corresponding things running Android. The closest to a general term seems to be "mobile devices," but that (a) applies to any mobile phone, and (b) doesn't really capture what's distinctive about the iPad. After a few seconds it struck me that what we'll end up calling these things is tablets. The only reason we even consider calling them "mobile devices" is that the iPhone preceded the iPad. If the iPad had come first, we wouldn't think of the iPhone as a phone; we'd think of it as a tablet small enough to hold up to your ear. The iPhone isn't so much a phone as a replacement for a phone. That's an important distinction, because it's an early instance of what will become a common pattern. Many if not most of the special-purpose objects around us are going to be replaced by apps running on tablets. This is already clear in cases like GPSes, music players, and cameras. But I think it will surprise people how many things are going to get replaced. We funded one startup that's replacing keys. The fact that you can change font sizes easily means the iPad effectively replaces reading glasses. I wouldn't be surprised if by playing some clever tricks with the accelerometer you could even replace the bathroom scale. The advantages of doing things in software on a single device are so great that everything that can get turned into software will. So for the next couple years, a good recipe for startups will be to look around you for things that people haven't realized yet can be made unnecessary by a tablet app. In 1938 Buckminster Fuller coined the term ephemeralization to describe the increasing tendency of physical machinery to be replaced by what we would now call software.
最近我在思考,对于iPhone、iPad以及运行Android系统的类似设备,没有一个统称是多么不便。最接近的通用术语似乎是“移动设备”,但这(a)适用于任何移动电话,(b)并未真正捕捉到iPad的独特之处。
几秒钟后,我突然意识到,我们最终会称这些东西为“平板设备”。我们甚至考虑称它们为“移动设备”的唯一原因是iPhone先于iPad出现。如果iPad先问世,我们就不会把iPhone看作手机;我们会认为它是一个小到可以举到耳边的平板设备。
iPhone与其说是手机,不如说是手机的替代品。这是一个重要的区别,因为它将成为一种常见模式的早期实例。我们周围的许多(如果不是大多数)专用物品将被平板设备上运行的应用程序所取代。
在GPS、音乐播放器和相机等案例中,这一点已经很明显。但我认为,被取代的物品数量之多会让人惊讶。我们资助了一家替代钥匙的初创公司。由于可以轻松调整字体大小,iPad实际上替代了老花镜。如果通过加速计的一些巧妙运用,甚至能替代浴室秤,我也不会感到意外。
The reason tablets are going to take over the world is not (just) that Steve Jobs and Co are industrial design wizards, but because they have this force behind them. The iPhone and the iPad have effectively drilled a hole that will allow ephemeralization to flow into a lot of new areas. No one who has studied the history of technology would want to underestimate the power of that force. I worry about the power Apple could have with this force behind them. I don't want to see another era of client monoculture like the Microsoft one in the 80s and 90s. But if ephemeralization is one of the main forces driving the spread of tablets, that suggests a way to compete with Apple: be a better platform for it. It has turned out to be a great thing that Apple tablets have accelerometers in them. Developers have used the accelerometer in ways Apple could never have imagined. That's the nature of platforms. The more versatile the tool, the less you can predict how people will use it. So tablet makers should be thinking: what else can we put in there? Not merely hardware, but software too. What else can we give developers access to? Give hackers an inch and they'll take you a mile. Thanks to Sam Altman, Paul Buchheit, Jessica Livingston, and Robert Morris for reading drafts of this..
在单一设备上通过软件完成任务的优点如此之大,以至于一切可以转化为软件的东西都会如此。因此,在未来几年,初创企业的好配方就是环顾四周,寻找那些人们尚未意识到可以被平板应用取代的东西。
1938年,巴克敏斯特·富勒创造了“短暂化”一词,描述物理机械日益被我们现在称为软件的东西取代的趋势。平板设备将席卷世界的原因(不仅仅)在于史蒂夫·乔布斯及其团队是工业设计的奇才,而是因为他们背后有这种力量。iPhone和iPad实际上已经打开了一个缺口,让短暂化涌入许多新领域。研究过技术史的人都不会低估这种力量的影响。
我担心苹果在这种力量支持下可能拥有的权力。我不想看到另一个像80年代和90年代微软那样的客户端单一文化时代。但如果短暂化是推动平板设备传播的主要力量之一,那么与苹果竞争的方法就是成为一个更好的平台。
事实证明,苹果平板设备内置加速计是一件了不起的事。开发者以苹果从未想象过的方式使用了加速计。这就是平台的本质。工具越多功能,你就越难预测人们会如何使用它。因此,平板设备制造商应该思考:我们还能加入什么?不仅仅是硬件,还有软件。我们还能为开发者提供什么访问权限?给黑客一寸,他们会带你走一英里。
感谢萨姆·奥尔特曼、保罗·布赫海特、杰西卡·利文斯顿和罗伯特·莫里斯阅读本文草稿。
Want to start a startup? Get funded by Y Combinator.
October 2010 Silicon Valley proper is mostly suburban sprawl. At first glance it doesn't seem there's anything to see. It's not the sort of place that has conspicuous monuments. But if you look, there are subtle signs you're in a place that's different from other places. 1.Stanford University Stanford is a strange place. Structurally it is to an ordinary university what suburbia is to a city. It's enormously spread out, and feels surprisingly empty much of the time. But notice the weather. It's probably perfect. And notice the beautiful mountains to the west. And though you can't see it, cosmopolitan San Francisco is 40 minutes to the north. That combination is much of the reason Silicon Valley grew up around this university and not some other one. 2.University Ave A surprising amount of the work of the Valley is done in the cafes on or just off University Ave in Palo Alto. If you visit on a weekday between 10 and 5, you'll often see founders pitching investors. In case you can't tell, the founders are the ones leaning forward eagerly, and the investors are the ones sitting back with slightly pained expressions. 3.The Lucky Office The office at 165 University Ave was Google's first. Then it was Paypal's. (Now it's Wepay's.) The interesting thing about it is the location. It's a smart move to put a startup in a place with restaurants and people walking around instead of in an office park, because then the people who work there want to stay there, instead of fleeing as soon as conventional working hours end. They go out for dinner together, talk about ideas, and then come back and implement them.
It's important to realize that Google's current location in an office park is not where they started; it's just where they were forced to move when they needed more space. Facebook was till recently across the street, till they too had to move because they needed more space. 4.Old Palo Alto Palo Alto was not originally a suburb. For the first 100 years or so of its existence, it was a college town out in the countryside. Then in the mid 1950s it was engulfed in a wave of suburbia that raced down the peninsula. But Palo Alto north of Oregon expressway still feels noticeably different from the area around it. It's one of the nicest places in the Valley. The buildings are old (though increasingly they are being torn down and replaced with generic McMansions) and the trees are tall. But houses are very expensive—around $1000 per square foot. This is post-exit Silicon Valley. 5.Sand Hill Road It's interesting to see the VCs' offices on the north side of Sand Hill Road precisely because they're so boringly uniform. The buildings are all more or less the same, their exteriors express very little, and they are arranged in a confusing maze. (I've been visiting them for years and I still occasionally get lost.) It's not a coincidence. These buildings are a pretty accurate reflection of the VC business. If you go on a weekday you may see groups of founders there to meet VCs. But mostly you won't see anyone; bustling is the last word you'd use to describe the atmos. Visiting Sand Hill Road reminds you that the opposite of "down and dirty" would be "up and clean." 6.Castro Street It's a tossup whether Castro Street or University Ave should be considered the heart of the Valley now. University Ave would have been 10 years ago.
But Palo Alto is getting expensive. Increasingly startups are located in Mountain View, and Palo Alto is a place they come to meet investors. Palo Alto has a lot of different cafes, but there is one that clearly dominates in Mountain View: Red Rock. 7.Google Google spread out from its first building in Mountain View to a lot of the surrounding ones. But because the buildings were built at different times by different people, the place doesn't have the sterile, walled-off feel that a typical large company's headquarters have. It definitely has a flavor of its own though. You sense there is something afoot. The general atmos is vaguely utopian; there are lots of Priuses, and people who look like they drive them. You can't get into Google unless you know someone there. It's very much worth seeing inside if you can, though. Ditto for Facebook, at the end of California Ave in Palo Alto, though there is nothing to see outside. 8.Skyline Drive Skyline Drive runs along the crest of the Santa Cruz mountains. On one side is the Valley, and on the other is the sea—which because it's cold and foggy and has few harbors, plays surprisingly little role in the lives of people in the Valley, considering how close it is. Along some parts of Skyline the dominant trees are huge redwoods, and in others they're live oaks. Redwoods mean those are the parts where the fog off the coast comes in at night; redwoods condense rain out of fog. The MROSD manages a collection of great walking trails off Skyline. 9.280 Silicon Valley has two highways running the length of it: 101, which is pretty ugly, and 280, which is one of the more beautiful highways in the world.
I always take 280 when I have a choice. Notice the long narrow lake to the west? That's the San Andreas Fault. It runs along the base of the hills, then heads uphill through Portola Valley. One of the MROSD trails runs right along the fault. A string of rich neighborhoods runs along the foothills to the west of 280: Woodside, Portola Valley, Los Altos Hills, Saratoga, Los Gatos. SLAC goes right under 280 a little bit south of Sand Hill Road. And a couple miles south of that is the Valley's equivalent of the "Welcome to Las Vegas" sign: The Dish. Notes I skipped the Computer History Museum because this is a list of where to see the Valley itself, not where to see artifacts from it. I also skipped San Jose. San Jose calls itself the capital of Silicon Valley, but when people in the Valley use the phrase "the city," they mean San Francisco. San Jose is a dotted line on a map. Thanks to Sam Altman, Paul Buchheit, Patrick Collison, and Jessica Livingston for reading drafts of this..
想创业吗? 获得 Y Combinator 的资助。
2010年10月 硅谷本身大多是郊区蔓延的景象。乍一看似乎没什么值得看的。这里不是那种拥有显眼地标的地方。但如果你仔细观察,会发现一些细微的迹象表明这里与其他地方不同。 1.斯坦福大学 斯坦福是个奇怪的地方。从结构上看,它与普通大学的关系就像郊区与城市的关系。它非常分散,大部分时间都出奇地空旷。但请注意这里的天气——几乎完美无缺。再看看西边美丽的群山。虽然你看不到,但国际化大都市旧金山就在北边40分钟车程的地方。这些因素的结合是硅谷围绕这所大学而非其他大学兴起的重要原因。 2.大学路 硅谷的许多工作都是在帕洛阿尔托大学路或其附近的咖啡馆里完成的。如果你在工作日上午10点到下午5点之间到访,经常会看到创始人向投资人推销项目。如果你分不清,那些热切前倾的是创始人,而那些略带痛苦表情后仰坐着的是投资人。 3.幸运办公室 大学路165号的办公室是谷歌的第一间办公室。后来成了Paypal的办公室(现在是Wepay的)。有趣的是它的位置——把初创公司放在一个有餐馆和人流的地方,而不是办公园区里,是个明智之举。因为这样员工会愿意留下来,而不是一到常规工作时间结束就逃离。他们会一起出去吃晚饭,讨论想法,然后回来实现它们。 重要的是要意识到,谷歌现在所在的办公园区并非他们的起点,而是他们因需要更多空间而被迫搬去的地方。Facebook直到不久前还在街对面,后来也因空间不足而搬离。 4.老帕洛阿尔托 帕洛阿尔托最初并不是郊区。在其存在的前100年左右,它是一个位于乡村的大学城。然后在20世纪50年代中期,它被席卷半岛的郊区化浪潮吞没。但俄勒冈高速公路以北的帕洛阿尔托仍然明显感觉与周边地区不同。这里是硅谷最宜人的地方之一。建筑古老(尽管越来越多被拆除,取而代之的是千篇一律的豪宅),树木高大。但房价非常昂贵——每平方英尺约1000美元。这是成功后的硅谷。 5.沙山路 看看沙山路北侧的风投公司办公室很有趣,因为它们出奇地千篇一律。建筑都大同小异,外观几乎没有任何特色,而且布局像一个令人困惑的迷宫(我去过多年,偶尔还是会迷路)。这不是巧合。这些建筑相当准确地反映了风投行业的特质。 如果你在工作日去,可能会看到创始人们组团去见风投。但大多数时候你谁也不会看到;“繁忙”是形容这里氛围最不贴切的词。参观沙山路会让你想起,“光鲜亮丽”的反义词是“脚踏实地”。 6.卡斯特罗街 现在很难说卡斯特罗街和大学路哪个才是硅谷的中心。十年前肯定是大学路。但帕洛阿尔托越来越贵。越来越多的初创公司选择山景城,帕洛阿尔托成了他们见投资人的地方。帕洛阿尔托有很多不同的咖啡馆,但山景城有一家明显占主导地位:红岩咖啡。 7.谷歌 谷歌从山景城的第一栋大楼扩展到周围的许多建筑。但由于这些建筑是由不同的人在不同时期建造的,这里没有典型大公司总部那种封闭隔绝的感觉。但它确实有自己的特色。你能感觉到这里正在发生什么。整体氛围隐约带有乌托邦色彩;有很多普锐斯汽车,以及看起来像是会开这种车的人。 除非你认识内部人员,否则无法进入谷歌。但如果能进去,非常值得一看。帕洛阿尔托加州大道尽头的Facebook也是如此,尽管外面没什么可看的。 8.天际线大道 天际线大道沿着圣克鲁斯山脉的山脊延伸。一边是硅谷,另一边是大海——尽管近在咫尺,但由于寒冷、多雾且港口稀少,大海在硅谷人生活中扮演的角色出奇地少。天际线大道的某些路段以巨大的红杉为主,另一些则是常绿橡树。红杉意味着这些地方夜晚会有海岸的雾气涌入;红杉能从雾中凝结雨水。MROSD管理着天际线大道旁一系列很棒的徒步小径。 9.280号公路 硅谷有两条纵贯南北的高速公路:101号公路相当丑陋,而280号公路是世界上最美丽的高速公路之一。有选择时我总是走280号公路。注意到西边狭长的湖泊了吗?那是圣安德烈亚斯断层。它沿着山脚延伸,然后穿过波托拉谷上山。MROSD的一条小径就沿着断层延伸。280号公路以西的山麓地带有一连串富裕社区:伍德赛德、波托拉谷、洛斯阿尔托斯山、萨拉托加、洛斯加托斯。 SLAC就在沙山路以南一点的地方从280号公路下方穿过。再往南几英里是硅谷的“欢迎来到拉斯维加斯”标志:The Dish。 备注 我跳过了计算机历史博物馆,因为这是一份关于硅谷本身的清单,而不是关于其历史文物。我也跳过了圣何塞。圣何塞自称是硅谷的首都,但当硅谷人说“the city”时,他们指的是旧金山。圣何塞只是地图上的一条虚线。 感谢 Sam Altman、Paul Buchheit、Patrick Collison和Jessica Livingston阅读本文草稿。.
Want to start a startup? Get funded by Y Combinator.
October 2010 After barely changing at all for decades, the startup funding business is now in what could, at least by comparison, be called turmoil. At Y Combinator we've seen dramatic changes in the funding environment for startups. Fortunately one of them is much higher valuations. The trends we've been seeing are probably not YC-specific. I wish I could say they were, but the main cause is probably just that we see trends first—partly because the startups we fund are very plugged into the Valley and are quick to take advantage of anything new, and partly because we fund so many that we have enough data points to see patterns clearly. What we're seeing now, everyone's probably going to be seeing in the next couple years. So I'm going to explain what we're seeing, and what that will mean for you if you try to raise money. Super-Angels Let me start by describing what the world of startup funding used to look like. There used to be two sharply differentiated types of investors: angels and venture capitalists. Angels are individual rich people who invest small amounts of their own money, while VCs are employees of funds that invest large amounts of other people's. For decades there were just those two types of investors, but now a third type has appeared halfway between them: the so-called super-angels. [1] And VCs have been provoked by their arrival into making a lot of angel-style investments themselves. So the previously sharp line between angels and VCs has become hopelessly blurred. There used to be a no man's land between angels and VCs. Angels would invest $20k to $50k apiece, and VCs usually a million or more. So an angel round meant a collection of angel investments that combined to maybe $200k, and a VC round meant a series A round in which a single VC fund (or occasionally two) invested $1-5 million.
想创立一家初创公司? 获得Y Combinator的资助。
在几十年几乎毫无变化之后,初创企业的融资业务如今正经历着——至少相比之下——可以称之为动荡的局面。在Y Combinator,我们见证了初创企业融资环境的剧烈变化。幸运的是,其中一项变化是估值的大幅提升。
我们观察到的趋势可能并非YC独有。虽然我希望如此,但主要原因或许只是我们更早地捕捉到了这些趋势——部分因为我们资助的初创企业与硅谷紧密相连,能够迅速利用任何新机会;部分因为我们资助的企业数量众多,足以清晰地识别出模式。
我们现在看到的,很可能在未来几年内成为普遍现象。因此,我将解释我们的观察结果,以及这些变化对你融资的意义。
The no man's land between angels and VCs was a very inconvenient one for startups, because it coincided with the amount many wanted to raise. Most startups coming out of Demo Day wanted to raise around $400k. But it was a pain to stitch together that much out of angel investments, and most VCs weren't interested in investments so small. That's the fundamental reason the super-angels have appeared. They're responding to the market. The arrival of a new type of investor is big news for startups, because there used to be only two and they rarely competed with one another. Super-angels compete with both angels and VCs. That's going to change the rules about how to raise money. I don't know yet what the new rules will be, but it looks like most of the changes will be for the better. A super-angel has some of the qualities of an angel, and some of the qualities of a VC. They're usually individuals, like angels. In fact many of the current super-angels were initially angels of the classic type. But like VCs, they invest other people's money. This allows them to invest larger amounts than angels: a typical super-angel investment is currently about $100k. They make investment decisions quickly, like angels. And they make a lot more investments per partner than VCs—up to 10 times as many. The fact that super-angels invest other people's money makes them doubly alarming to VCs. They don't just compete for startups; they also compete for investors. What super-angels really are is a new form of fast-moving, lightweight VC fund. And those of us in the technology world know what usually happens when something comes along that can be described in terms like that. Usually it's the replacement. Will it be? As of now, few of the startups that take money from super-angels are ruling out taking VC money. They're just postponing it. But that's still a problem for VCs.
让我先描述一下初创企业融资领域过去的面貌。过去,投资者主要分为两类:天使投资人和风险投资家(VC)。天使投资人是富有的个人,用自己的钱进行小额投资;而VC则是基金雇员,用他人的资金进行大额投资。
几十年来,这两类投资者泾渭分明,但如今出现了介于两者之间的第三类:所谓的“超级天使”。[1] 超级天使的出现刺激了VC,促使他们也进行了大量类似天使投资的小额投资。因此,原本清晰的天使与VC界限已变得模糊不清。
过去,天使与VC之间有一片“无人区”。天使通常单笔投资2万至5万美元,而VC通常单笔投资100万美元以上。因此,天使轮融资意味着汇集多笔天使投资,总额约20万美元;而A轮融资则意味着单家VC基金(偶尔两家)投资100万至500万美元。
这片“无人区”对初创企业非常不便,因为它恰好是许多企业希望融资的金额。大多数从Demo Day走出的初创企业希望融资约40万美元。但通过天使投资拼凑这笔资金非常麻烦,而VC又对如此小额的投资兴趣寥寥。这正是超级天使出现的根本原因——他们回应了市场需求。
新型投资者的出现对初创企业意义重大,因为过去只有两类投资者,且很少相互竞争。超级天使同时与天使和VC竞争,这将改变融资规则。虽然新规则尚不明确,但大多数变化似乎对初创企业更有利。
Some of the startups that postpone raising VC money may do so well on the angel money they raise that they never bother to raise more. And those who do raise VC rounds will be able to get higher valuations when they do. If the best startups get 10x higher valuations when they raise series A rounds, that would cut VCs' returns from winners at least tenfold. [2] So I think VC funds are seriously threatened by the super-angels. But one thing that may save them to some extent is the uneven distribution of startup outcomes: practically all the returns are concentrated in a few big successes. The expected value of a startup is the percentage chance it's Google. So to the extent that winning is a matter of absolute returns, the super-angels could win practically all the battles for individual startups and yet lose the war, if they merely failed to get those few big winners. And there's a chance that could happen, because the top VC funds have better brands, and can also do more for their portfolio companies. [3] Because super-angels make more investments per partner, they have less partner per investment. They can't pay as much attention to you as a VC on your board could. How much is that extra attention worth? It will vary enormously from one partner to another. There's no consensus yet in the general case. So for now this is something startups are deciding individually. Till now, VCs' claims about how much value they added were sort of like the government's. Maybe they made you feel better, but you had no choice in the matter, if you needed money on the scale only VCs could supply. Now that VCs have competitors, that's going to put a market price on the help they offer. The interesting thing is, no one knows yet what it will be.
超级天使兼具天使和VC的部分特质。他们通常是个人,像天使一样。事实上,许多超级天使最初是传统意义上的天使。但和VC一样,他们用他人的资金投资,这使得他们能比天使投资更大金额——目前典型的超级天使单笔投资约10万美元。他们像天使一样快速决策,但每位合伙人投资的项目数量远超VC——可达10倍之多。
超级天使使用他人资金的事实让VC倍感压力。他们不仅在争夺初创企业,也在争夺投资者。超级天使本质上是快速、轻量化的新型VC基金。科技行业的经验告诉我们,此类新事物往往会成为替代者。
会吗?目前,接受超级天使投资的初创企业很少完全排除未来接受VC投资的可能性,只是推迟而已。但这仍对VC构成问题:部分初创企业可能凭借天使投资表现出色,不再需要更多融资;而那些最终进行A轮融资的企业将获得更高估值。如果最优秀的初创企业在A轮融资时估值提升10倍,VC从成功项目中获得的回报将至少缩水90%。[2]
因此,我认为VC基金正受到超级天使的严重威胁。但VC可能因初创企业成果的极端不均衡分布而部分幸免——几乎所有回报都集中在少数巨大成功案例中。初创企业的期望价值取决于它成为“下一个谷歌”的概率。因此,若胜负取决于绝对回报,超级天使可能赢得绝大多数初创企业的争夺战,却因错失少数巨头而输掉整场战争。这种可能性确实存在,因为顶级VC基金拥有更强的品牌效应,也能为被投企业提供更多支持。[3]
Do startups that want to get really big need the sort of advice and connections only the top VCs can supply? Or would super-angel money do just as well? The VCs will say you need them, and the super-angels will say you don't. But the truth is, no one knows yet, not even the VCs and super-angels themselves. All the super-angels know is that their new model seems promising enough to be worth trying, and all the VCs know is that it seems promising enough to worry about. Rounds Whatever the outcome, the conflict between VCs and super-angels is good news for founders. And not just for the obvious reason that more competition for deals means better terms. The whole shape of deals is changing. One of the biggest differences between angels and VCs is the amount of your company they want. VCs want a lot. In a series A round they want a third of your company, if they can get it. They don't care much how much they pay for it, but they want a lot because the number of series A investments they can do is so small. In a traditional series A investment, at least one partner from the VC fund takes a seat on your board. [4] Since board seats last about 5 years and each partner can't handle more than about 10 at once, that means a VC fund can only do about 2 series A deals per partner per year. And that means they need to get as much of the company as they can in each one. You'd have to be a very promising startup indeed to get a VC to use up one of his 10 board seats for only a few percent of you. Since angels generally don't take board seats, they don't have this constraint. They're happy to buy only a few percent of you. And although the super-angels are in most respects mini VC funds, they've retained this critical property of angels. They don't take board seats, so they don't need a big percentage of your company. Though that means you'll get correspondingly less attention from them, it's good news in other respects.
由于超级天使每位合伙人负责更多项目,他们对单个项目的关注度低于VC董事。这种额外关注的价值有多大?不同合伙人差异巨大,目前尚无共识。因此,初创企业需自行权衡。
迄今为止,VC关于其附加价值的宣称有点像政府的承诺——或许让你感觉良好,但若你需要只有VC能提供的大额资金,你别无选择。如今VC有了竞争者,他们的帮助将被市场定价。有趣的是,目前无人知晓这个价格会是多少。
立志做大的初创企业是否需要顶级VC才能提供的建议和人脉?还是超级天使的资金同样有效?VC会说你离不开他们,超级天使则持相反观点。但真相是,目前无人知晓——包括VC和超级天使自己。超级天使只知道新模式前景广阔值得尝试,VC只知道它值得警惕。
无论结果如何,VC与超级天使的竞争对创始人都是好消息——不仅因为更激烈的竞争意味着更优条款,更因为交易的整体形态正在改变。
天使与VC的最大区别之一在于他们希望占有的股权比例。VC想要很多——在A轮融资中,他们希望拿到公司1/3的股份(如果可能)。他们不太在意价格,但需要大比例持股,因为能进行的A轮投资数量有限。传统A轮投资中,VC基金至少派一名合伙人进入董事会。[4] 由于董事任期约5年且每位合伙人最多同时担任10家公司的董事,这意味着VC基金每年每位合伙人只能进行约2笔A轮投资。因此他们需要在每笔交易中尽可能多地获取股份。除非你极其出色,否则VC不会为区区几个百分点动用宝贵的董事席位。
Founders never really liked giving up as much equity as VCs wanted. It was a lot of the company to give up in one shot. Most founders doing series A deals would prefer to take half as much money for half as much stock, and then see what valuation they could get for the second half of the stock after using the first half of the money to increase its value. But VCs never offered that option. Now startups have another alternative. Now it's easy to raise angel rounds about half the size of series A rounds. Many of the startups we fund are taking this route, and I predict that will be true of startups in general. A typical big angel round might be $600k on a convertible note with a valuation cap of $4 million premoney. Meaning that when the note converts into stock (in a later round, or upon acquisition), the investors in that round will get .6 / 4.6, or 13% of the company. That's a lot less than the 30 to 40% of the company you usually give up in a series A round if you do it so early. [5] But the advantage of these medium-sized rounds is not just that they cause less dilution. You also lose less control. After an angel round, the founders almost always still have control of the company, whereas after a series A round they often don't. The traditional board structure after a series A round is two founders, two VCs, and a (supposedly) neutral fifth person. Plus series A terms usually give the investors a veto over various kinds of important decisions, including selling the company. Founders usually have a lot of de facto control after a series A, as long as things are going well. But that's not the same as just being able to do what you want, like you could before. A third and quite significant advantage of angel rounds is that they're less stressful to raise. Raising a traditional series A round has in the past taken weeks, if not months. When a VC firm can only do 2 deals per partner per year, they're careful about which they do.
天使通常不占董事席位,因此不受此限制。他们乐意只持有几个百分点。尽管超级天使在多数方面类似迷你VC基金,但他们保留了天使的这一关键特性——不占董事席位,因此无需大比例持股。
虽然这意味着你获得的关注会相应减少,但在其他方面这是好消息。创始人从未真正喜欢过VC要求的高比例股权出让——一次性放弃大量股份令人心痛。多数进行A轮融资的创始人更希望用一半股权换取一半资金,然后用前半资金提升价值后,再以更高估值出让剩余股权。但VC从不提供这种选择。
现在初创企业有了新选择:轻松完成规模约为A轮一半的天使轮融资。我们资助的许多初创企业正走这条路,我预测这将成普遍趋势。
典型的大额天使轮可能是60万美元的可转债,估值上限为400万美元(融资前)。这意味着当债券转为股权时(在后轮融资或收购时),该轮投资者将获得0.6/4.6,即13%的股份——远低于早期A轮通常出让的30%-40%。[5]
To get a traditional series A round you have to go through a series of meetings, culminating in a full partner meeting where the firm as a whole says yes or no. That's the really scary part for founders: not just that series A rounds take so long, but at the end of this long process the VCs might still say no. The chance of getting rejected after the full partner meeting averages about 25%. At some firms it's over 50%. Fortunately for founders, VCs have been getting a lot faster. Nowadays Valley VCs are more likely to take 2 weeks than 2 months. But they're still not as fast as angels and super-angels, the most decisive of whom sometimes decide in hours. Raising an angel round is not only quicker, but you get feedback as it progresses. An angel round is not an all or nothing thing like a series A. It's composed of multiple investors with varying degrees of seriousness, ranging from the upstanding ones who commit unequivocally to the jerks who give you lines like "come back to me to fill out the round." You usually start collecting money from the most committed investors and work your way out toward the ambivalent ones, whose interest increases as the round fills up. But at each point you know how you're doing. If investors turn cold you may have to raise less, but when investors in an angel round turn cold the process at least degrades gracefully, instead of blowing up in your face and leaving you with nothing, as happens if you get rejected by a VC fund after a full partner meeting. Whereas if investors seem hot, you can not only close the round faster, but now that convertible notes are becoming the norm, actually raise the price to reflect demand. Valuation However, the VCs have a weapon they can use against the super-angels, and they have started to use it. VCs have started making angel-sized investments too.
但中等规模融资的优势不仅在于稀释更少,还意味着控制权流失更少。天使轮后,创始人几乎总能保持公司控制权;而A轮后往往不然。传统A轮后的董事会结构是两位创始人、两位VC和一位(理论上)中立的第五人。此外,A轮条款通常赋予投资者对重大决策(包括出售公司)的否决权。只要进展顺利,创始人通常在A轮后仍拥有实际控制权——但这与融资前随心所欲的状态截然不同。
天使轮的第三个重要优势是融资压力更小。传统A轮融资过去需要数周甚至数月时间。当VC基金每年每位合伙人只能进行2笔交易时,他们会精挑细选。要获得传统A轮融资,你必须经历一系列会议,最终由全体合伙人会议决定是否通过——对创始人来说,最可怕的不仅是漫长的等待,更是在漫长过程后仍可能被拒绝。全体合伙人会议后的平均拒绝率约为25%,某些基金甚至超过50%。
幸运的是,VC的决策速度已大幅提升。如今硅谷VC更可能在两周而非两个月内做出决定。但他们仍不如天使和超级天使迅速——最果断的超级天使有时几小时内就能拍板。
天使轮融资不仅更快,还能获得渐进式反馈。天使轮不像A轮那样“全有或全无”,而是由多名态度各异的投资者组成——从明确承诺的可靠投资人,到“等轮次快结束时再来找我”的滑头。你通常从最坚定的投资者开始收钱,逐步接触犹豫者——随着轮次临近完成,后者的兴趣会增强。
但整个过程你都能掌握进展。如果投资者兴趣降温,你可能需要降低融资目标;但天使轮融资遇冷时,过程至少会平缓退化,而非像VC全体合伙人会议拒绝后那样彻底崩盘。反之,如果投资者热情高涨,你不仅能更快完成融资,在可转债成为主流的当下,还能根据需求提高价格。
The term "angel round" doesn't mean that all the investors in it are angels; it just describes the structure of the round. Increasingly the participants include VCs making investments of a hundred thousand or two. And when VCs invest in angel rounds they can do things that super-angels don't like. VCs are quite valuation-insensitive in angel rounds—partly because they are in general, and partly because they don't care that much about the returns on angel rounds, which they still view mostly as a way to recruit startups for series A rounds later. So VCs who invest in angel rounds can blow up the valuations for angels and super-angels who invest in them. [6] Some super-angels seem to care about valuations. Several turned down YC-funded startups after Demo Day because their valuations were too high. This was not a problem for the startups; by definition a high valuation means enough investors were willing to accept it. But it was mysterious to me that the super-angels would quibble about valuations. Did they not understand that the big returns come from a few big successes, and that it therefore mattered far more which startups you picked than how much you paid for them? After thinking about it for a while and observing certain other signs, I have a theory that explains why the super-angels may be smarter than they seem. It would make sense for super-angels to want low valuations if they're hoping to invest in startups that get bought early. If you're hoping to hit the next Google, you shouldn't care if the valuation is 20 million. But if you're looking for companies that are going to get bought for 30 million, you care. If you invest at 20 and the company gets bought for 30, you only get 1.5x. You might as well buy Apple. So if some of the super-angels were looking for companies that could get acquired quickly, that would explain why they'd care about valuations.
然而,VC拥有对抗超级天使的武器,并已开始使用——VC也开始进行天使规模的投资。“天使轮”并非指所有投资者都是天使,而是描述轮次结构。参与者越来越多地包括进行10-20万美元投资的VC。当VC参与天使轮时,他们能做超级天使不喜欢的事——VC在天使轮中对估值极不敏感,部分源于其一贯风格,部分因为他们不太在意天使轮的回报(仍将其视为后期A轮投资的铺垫)。因此,参与天使轮的VC可以抬高估值,打击同轮次的天使和超级天使。[6]
部分超级天使似乎在意估值。数家YC资助的初创企业在Demo Day后因估值过高被超级天使拒绝。这对初创企业不是问题——高估值本身就意味着足够多投资者愿意接受。但令我困惑的是,超级天使为何会纠结估值?他们难道不明白巨大回报来自少数巨大成功,因此选对公司远比价格重要?
经过思考和观察其他迹象,我得出一个理论解释超级天使可能比表面更聪明:如果超级天使希望投资早期被收购的初创企业,追求低估值就合理了。若目标是“下一个谷歌”,2000万估值无关紧要;但若目标是以3000万被收购的公司,估值就至关重要——以2000万估值投资,公司以3000万出售,回报仅1.5倍,还不如买苹果股票。
因此,若部分超级天使寻求快速被收购的公司,就能解释他们为何在意估值。但为何要寻找这类公司?因为取决于“快速”的定义,这实际上可能非常有利可图——对VC而言,3000万出售的公司是失败,但对天使可能是10倍回报,且是快速的10倍。投资的关键是回报率——不是倍数,而是年化倍数。若超级天使一年获得10倍回报,其回报率远超VC需6年才能上市的公司。为达到相同回报率,VC需要10^6(百万倍)的回报——连谷歌也远未达到。
But why would they be looking for those? Because depending on the meaning of "quickly," it could actually be very profitable. A company that gets acquired for 30 million is a failure to a VC, but it could be a 10x return for an angel, and moreover, a _quick_ 10x return. Rate of return is what matters in investing—not the multiple you get, but the multiple per year. If a super-angel gets 10x in one year, that's a higher rate of return than a VC could ever hope to get from a company that took 6 years to go public. To get the same rate of return, the VC would have to get a multiple of 10^6—one million x. Even Google didn't come close to that. So I think at least some super-angels are looking for companies that will get bought. That's the only rational explanation for focusing on getting the right valuations, instead of the right companies. And if so they'll be different to deal with than VCs. They'll be tougher on valuations, but more accommodating if you want to sell early. Prognosis Who will win, the super-angels or the VCs? I think the answer to that is, some of each. They'll each become more like one another. The super-angels will start to invest larger amounts, and the VCs will gradually figure out ways to make more, smaller investments faster. A decade from now the players will be hard to tell apart, and there will probably be survivors from each group. What does that mean for founders? One thing it means is that the high valuations startups are presently getting may not last forever. To the extent that valuations are being driven up by price-insensitive VCs, they'll fall again if VCs become more like super-angels and start to become more miserly about valuations. Fortunately if this does happen it will take years. The short term forecast is more competition between investors, which is good news for you.
因此,我认为至少部分超级天使在寻找将被收购的公司。这是关注合理估值而非优秀公司的唯一合理解释。若真如此,与他们打交道将不同于VC——他们会在估值上更苛刻,但若你想早期出售会更包容。
超级天使与VC谁会胜出?我认为答案是各有胜负——双方会越来越像。超级天使将开始更大额投资,VC将逐渐找到快速进行更多小额投资的方法。十年后,两类投资者可能难以区分,且各自都会有幸存者。
这对创始人意味着什么?其一,当前初创企业的高估值可能不会永久持续。若高估值由对价格不敏感的VC推动,当VC变得更像超级天使并开始计较估值时,估值将回落。幸运的是,即使发生也需要数年时间。
短期预测是投资者间更激烈的竞争——这对你是好消息。超级天使将通过快速行动削弱VC,VC则通过抬高估值打击超级天使。对创始人而言,这将形成完美组合:快速完成的高估值融资。
但记住,要获得这种组合,你的初创企业必须同时吸引超级天使和VC。若你看起来没有上市潜力,就无法利用VC抬高天使轮估值。
The super-angels will try to undermine the VCs by acting faster, and the VCs will try to undermine the super-angels by driving up valuations. Which for founders will result in the perfect combination: funding rounds that close fast, with high valuations. But remember that to get that combination, your startup will have to appeal to both super-angels and VCs. If you don't seem like you have the potential to go public, you won't be able to use VCs to drive up the valuation of an angel round. There is a danger of having VCs in an angel round: the so-called signalling risk. If VCs are only doing it in the hope of investing more later, what happens if they don't? That's a signal to everyone else that they think you're lame. How much should you worry about that? The seriousness of signalling risk depends on how far along you are. If by the next time you need to raise money, you have graphs showing rising revenue or traffic month after month, you don't have to worry about any signals your existing investors are sending. Your results will speak for themselves. [7] Whereas if the next time you need to raise money you won't yet have concrete results, you may need to think more about the message your investors might send if they don't invest more. I'm not sure yet how much you have to worry, because this whole phenomenon of VCs doing angel investments is so new. But my instincts tell me you don't have to worry much. Signalling risk smells like one of those things founders worry about that's not a real problem. As a rule, the only thing that can kill a good startup is the startup itself. Startups hurt themselves way more often than competitors hurt them, for example. I suspect signalling risk is in this category too. One thing YC-funded startups have been doing to mitigate the risk of taking money from VCs in angel rounds is not to take too much from any one VC. Maybe that will help, if you have the luxury of turning down money.
天使轮引入VC存在一种风险:所谓的“信号风险”。若VC投资只为后期追加,当他们不追加时会发生什么?这向所有人传递出他们认为你不行的信号。
你该多担心这点?信号风险的严重性取决于你的发展阶段。若下次融资时你能展示收入或流量逐月增长的图表,就无需担心现有投资者发出的任何信号——结果会说明一切。[7]
但若下次融资时你尚无具体成果,可能需要更多考虑投资者不追加传递的信息。由于VC进行天使投资的现象太新,我不确定你该多担心。但直觉告诉我无需过度担忧——信号风险像是创始人过度担忧的伪问题。通常,只有初创企业自己能毁掉一个好项目。例如,初创企业自我伤害的频率远高于竞争对手造成的伤害。我怀疑信号风险也属此类。
YC资助的初创企业为降低天使轮引入VC的风险,采取的一种做法是不从单家VC获取过多资金。如果你有拒绝资金的奢侈,或许这能有所帮助。
Fortunately, more and more startups will. After decades of competition that could best be described as intramural, the startup funding business is finally getting some real competition. That should last several years at least, and maybe a lot longer. Unless there's some huge market crash, the next couple years are going to be a good time for startups to raise money. And that's exciting because it means lots more startups will happen. Notes [1] I've also heard them called "Mini-VCs" and "Micro-VCs." I don't know which name will stick. There were a couple predecessors. Ron Conway had angel funds starting in the 1990s, and in some ways First Round Capital is closer to a super-angel than a VC fund. [2] It wouldn't cut their overall returns tenfold, because investing later would probably (a) cause them to lose less on investments that failed, and (b) not allow them to get as large a percentage of startups as they do now. So it's hard to predict precisely what would happen to their returns. [3] The brand of an investor derives mostly from the success of their portfolio companies. The top VCs thus have a big brand advantage over the super-angels. They could make it self-perpetuating if they used it to get all the best new startups. But I don't think they'll be able to. To get all the best startups, you have to do more than make them want you. You also have to want them; you have to recognize them when you see them, and that's much harder. Super-angels will snap up stars that VCs miss. And that will cause the brand gap between the top VCs and the super-angels gradually to erode. [4] Though in a traditional series A round VCs put two partners on your board, there are signs now that VCs may begin to conserve board seats by switching to what used to be considered an angel-round board, consisting of two founders and one VC.
幸运的是,越来越多的初创企业将拥有这种奢侈。在数十年近乎内部竞争的融资环境后,初创企业融资业务终于迎来真正竞争。这种局面至少会持续数年,甚至更久。除非市场剧烈崩溃,未来几年将是初创企业融资的好时机。这令人兴奋,因为它意味着更多初创企业将涌现。
[1] 我也听过“迷你VC”、“微型VC”等称呼,不确定哪种会流行。
早有先驱——Ron Conway在1990年代就开始运作天使基金,某种程度上First Round Capital更接近超级天使而非VC基金。
[2] 不会使总体回报缩水90%,因为后期投资可能(a)减少失败项目的损失,(b)无法获得当前水平的持股比例。因此难以精确预测对其回报的影响。
[3] 投资者品牌主要来自被投企业的成功。顶级VC因此比超级天使拥有巨大品牌优势。若能用此优势获取所有顶尖新创企业,他们就能形成良性循环。但我认为他们做不到——要获取所有顶尖企业,光让它们想要你还不够,你还需要想要它们(即在相遇时识别它们,这困难得多)。超级天使会抢走VC错过的明星企业,这将逐渐侵蚀顶级VC与超级天使间的品牌差距。
Which is also to the founders' advantage if it means they still control the company. [5] In a series A round, you usually have to give up more than the actual amount of stock the VCs buy, because they insist you dilute yourselves to set aside an "option pool" as well. I predict this practice will gradually disappear though. [6] The best thing for founders, if they can get it, is a convertible note with no valuation cap at all. In that case the money invested in the angel round just converts into stock at the valuation of the next round, no matter how large. Angels and super-angels tend not to like uncapped notes. They have no idea how much of the company they're buying. If the company does well and the valuation of the next round is high, they may end up with only a sliver of it. So by agreeing to uncapped notes, VCs who don't care about valuations in angel rounds can make offers that super-angels hate to match. [7] Obviously signalling risk is also not a problem if you'll never need to raise more money. But startups are often mistaken about that. Thanks to Sam Altman, John Bautista, Patrick Collison, James Lindenbaum, Reid Hoffman, Jessica Livingston and Harj Taggar for reading drafts of this..
[4] 虽然传统A轮VC会派两位合伙人进入董事会,但有迹象表明VC可能开始转向“天使轮式”董事会(两位创始人加一位VC)以节省董事席位——若这意味着创始人仍控制公司,也对他们有利。
[5] A轮融资中,你通常需出让比VC实际购买更多的股份,因为他们坚持要你稀释股权以预留“期权池”。但我预测这种做法将逐渐消失。
[6] 对创始人最有利的是无估值上限的可转债——天使轮资金直接按下一轮估值(无论多高)转为股权。天使和超级天使通常不喜欢无上限票据(因无法预知将获得多少股权)。若公司表现优异且下轮估值极高,他们最终可能只获得极小比例。因此,通过接受无上限票据,不在意天使轮估值的VC可以提出超级天使难以匹配的报价。
[7] 若你永远不需要再融资,信号风险显然也不是问题。但初创企业常在此问题上判断错误。
致谢 Sam Altman、John Bautista、Patrick Collison、James Lindenbaum、Reid Hoffman、Jessica Livingston和Harj Taggar阅读了本文草稿。
Want to start a startup? Get funded by Y Combinator.
October 2010
想创立一家初创公司? 获得Y Combinator的资金支持。
2010年10月
(本文应《福布斯》邀请而作,他们让我写写我们看重的创始人特质。印刷版因篇幅限制删去了最后一项。)
事实证明这是创业者最重要的品质。Y Combinator创立之初,我们曾以为智力才是关键——硅谷向来推崇这种神话。当然创始人绝不能愚钝,但只要智力超过某个阈值,最重要的就是咬定青山不放松的劲头。创业路上障碍重重,你绝不能是那种轻易泄气的人。
_(I wrote this for Forbes, who asked me to write something about the qualities we look for in founders. In print they had to cut the last item because they didn't have room.)_ 1\. Determination This has turned out to be the most important quality in startup founders. We thought when we started Y Combinator that the most important quality would be intelligence. That's the myth in the Valley. And certainly you don't want founders to be stupid. But as long as you're over a certain threshold of intelligence, what matters most is determination. You're going to hit a lot of obstacles. You can't be the sort of person who gets demoralized easily. Bill Clerico and Rich Aberman of WePay are a good example. They're doing a finance startup, which means endless negotiations with big, bureaucratic companies. When you're starting a startup that depends on deals with big companies to exist, it often feels like they're trying to ignore you out of existence. But when Bill Clerico starts calling you, you may as well do what he asks, because he is not going away. 2\. Flexibility You do not however want the sort of determination implied by phrases like "don't give up on your dreams." The world of startups is so unpredictable that you need to be able to modify your dreams on the fly. The best metaphor I've found for the combination of determination and flexibility you need is a running back. He's determined to get downfield, but at any given moment he may need to go sideways or even backwards to get there. The current record holder for flexibility may be Daniel Gross of Greplin. He applied to YC with some bad ecommerce idea. We told him we'd fund him if he did something else. He thought for a second, and said ok. He then went through two more ideas before settling on Greplin.
WePay的比尔·克莱里科和里奇·阿伯曼就是典范。他们从事金融创业,意味着要和无休止地与官僚化大公司周旋。当你的创业项目需要依赖与大公司合作才能存活时,常会感觉对方正用冷处理逼你出局。但如果是比尔·克莱里科开始给你打电话,你最好乖乖配合——因为他绝不会放弃。
但这不意味着要像"永不放弃梦想"这类口号暗示的那样固执。创业世界充满变数,你必须具备随时调整目标的能力。我对这种"坚定又灵活"特质的最佳比喻是橄榄球跑卫:他矢志不渝地冲向底线,但在任何时刻都可能需要横向迂回甚至短暂后退。
Greplin的丹尼尔·格罗斯堪称灵活性标杆。他带着漏洞百出的电商点子申请YC,我们表示换项目才给投资。他思考片刻就爽快答应,之后又迭代两个创意才锁定Greplin。在演示日向投资人推介时,这个项目才启动几天,却收获大量青睐。他总能在绝境中漂亮翻身。
智力当然举足轻重,但最关键的是天马行空的想象力。比起快速解决预设问题,能诞生令人拍案的新构想更为珍贵。在创业领域,所有好点子初看都像糟糕主意——如果它们明显靠谱,早被人捷足先登了。你需要那种能孕育恰到好处疯狂感的智慧。
He'd only been working on it for a couple days when he presented to investors at Demo Day, but he got a lot of interest. He always seems to land on his feet. 3\. Imagination Intelligence does matter a lot of course. It seems like the type that matters most is imagination. It's not so important to be able to solve predefined problems quickly as to be able to come up with surprising new ideas. In the startup world, most good ideas seem bad initially. If they were obviously good, someone would already be doing them. So you need the kind of intelligence that produces ideas with just the right level of craziness. Airbnb is that kind of idea. In fact, when we funded Airbnb, we thought it was too crazy. We couldn't believe large numbers of people would want to stay in other people's places. We funded them because we liked the founders so much. As soon as we heard they'd been supporting themselves by selling Obama and McCain branded breakfast cereal, they were in. And it turned out the idea was on the right side of crazy after all. 4\. Naughtiness Though the most successful founders are usually good people, they tend to have a piratical gleam in their eye. They're not Goody Two-Shoes type good. Morally, they care about getting the big questions right, but not about observing proprieties. That's why I'd use the word naughty rather than evil. They delight in breaking rules, but not rules that matter. This quality may be redundant though; it may be implied by imagination. Sam Altman of Loopt is one of the most successful alumni, so we asked him what question we could put on the Y Combinator application that would help us discover more people like him. He said to ask about a time when they'd hacked something to their advantage—hacked in the sense of beating the system, not breaking into computers.
Airbnb正是此类典范。事实上我们投资时觉得这个点子疯狂过头,难以相信大众会愿意寄宿陌生人家。最终打动我们的是创始人特质——听说他们靠售卖奥巴马和麦凯恩主题麦片维持生计时,我们立即拍板。后来证明这个创意恰恰站在了疯狂的黄金分割点上。
4. 叛逆精神
最成功的创始人通常是好人,但眼中总闪烁着海盗般的狡黠。他们绝非循规蹈矩的乖宝宝,在道德层面只把控大是大非,对繁文缛节不屑一顾。因此我愿用"顽皮"而非"邪恶"形容他们。他们热衷打破规则,但只挑战无伤大雅的条框。不过这个特质或许与想象力存在交集。
It has become one of the questions we pay most attention to when judging applications. 5\. Friendship Empirically it seems to be hard to start a startup with just one founder. Most of the big successes have two or three. And the relationship between the founders has to be strong. They must genuinely like one another, and work well together. Startups do to the relationship between the founders what a dog does to a sock: if it can be pulled apart, it will be. Emmett Shear and Justin Kan of Justin.tv are a good example of close friends who work well together. They've known each other since second grade. They can practically read one another's minds. I'm sure they argue, like all founders, but I have never once sensed any unresolved tension between them. Thanks to Jessica Livingston and Chris Steiner for reading drafts of this..
Loopt的山姆·奥特曼是最成功的校友之一。当我们请教如何在YC申请中甄别同类人时,他建议询问"利用系统漏洞谋利的经历"——这里指钻规则空子而非黑客行为。这已成为我们评估申请时最关注的问题之一。
数据显示单人创业异常艰难,绝大多数成功案例都有两到三位创始人。创始人之间的关系必须坚若磐石,他们需要真心欣赏彼此且配合默契。创业对创始人关系的考验,就像恶犬撕咬袜子——但凡存在裂缝,必会被彻底扯破。
Justin.tv的埃米特·希尔和贾斯汀·坎就是典范。这对从小学二年级就相识的伙伴几乎能读心。虽然也会像所有搭档那样争执,但两人之间从未流露过未化解的紧张感。
感谢杰西卡·利文斯顿和克里斯·施泰纳审阅本文草稿。
Want to start a startup? Get funded by Y Combinator.
September 2010 The reason startups have been using more convertible notes in angel rounds is that they make deals close faster. By making it easier for startups to give different prices to different investors, they help them break the sort of deadlock that happens when investors all wait to see who else is going to invest. By far the biggest influence on investors' opinions of a startup is the opinion of other investors. There are very, very few who simply decide for themselves. Any startup founder can tell you the most common question they hear from investors is not about the founders or the product, but "who else is investing?" That tends to produce deadlocks. Raising an old-fashioned fixed-size equity round can take weeks, because all the angels sit around waiting for the others to commit, like competitors in a bicycle sprint who deliberately ride slowly at the start so they can follow whoever breaks first. Convertible notes let startups beat such deadlocks by rewarding investors willing to move first with lower (effective) valuations. Which they deserve because they're taking more risk. It's much safer to invest in a startup Ron Conway has already invested in; someone who comes after him should pay a higher price. The reason convertible notes allow more flexibility in price is that valuation caps aren't actual valuations, and notes are cheap and easy to do. So you can do high-resolution fundraising: if you wanted you could have a separate note with a different cap for each investor. That cap need not simply rise monotonically. A startup could also give better deals to investors they expected to help them most.
The point is simply that different investors, whether because of the help they offer or their willingness to commit, have different values for startups, and their terms should reflect that. Different terms for different investors is clearly the way of the future. Markets always evolve toward higher resolution. You may not need to use convertible notes to do it. With sufficiently lightweight standardized equity terms (and some changes in investors' and lawyers' expectations about equity rounds) you might be able to do the same thing with equity instead of debt. Either would be fine with startups, so long as they can easily change their valuation. Deadlocks weren't the only problem with fixed-size equity rounds. Another was that startups had to decide in advance how much to raise. I think it's a mistake for a startup to fix upon a specific number. If investors are easily convinced, the startup should raise more now, and if investors are skeptical, the startup should take a smaller amount and use that to get the company to the point where it's more convincing. It's just not reasonable to expect startups to pick an optimal round size in advance, because that depends on the reactions of investors, and those are impossible to predict. Fixed-size, multi-investor angel rounds are such a bad idea for startups that one wonders why things were ever done that way. One possibility is that this custom reflects the way investors like to collude when they can get away with it. But I think the actual explanation is less sinister. I think angels (and their lawyers) organized rounds this way in unthinking imitation of VC series A rounds. In a series A, a fixed-size equity round with a lead makes sense, because there is usually just one big investor, who is unequivocally the lead. Fixed-size series A rounds already are high res. But the more investors you have in a round, the less sense it makes for everyone to get the same price.
The most interesting question here may be what high res fundraising will do to the world of investors. Bolder investors will now get rewarded with lower prices. But more important, in a hits-driven business, is that they'll be able to get into the deals they want. Whereas the "who else is investing?" type of investors will not only pay higher prices, but may not be able to get into the best deals at all. Thanks to Immad Akhund, Sam Altman, John Bautista, Pete Koomen, Jessica Livingston, Dan Siroker, Harj Taggar, and Fred Wilson for reading drafts of this..
想创立一家初创公司? 获得Y Combinator的资金支持。
2010年9月 初创公司在天使轮融资中越来越多地使用可转换债券,是因为这种工具能让交易更快达成。通过让初创公司更容易为不同投资者设定不同价格,可转换债券帮助它们打破了投资者们互相观望、等待他人先投资的僵局。 迄今为止,投资者对初创公司看法最大的影响因素,就是其他投资者的态度。真正能独立做决定的人少之又少。任何初创公司创始人都能告诉你,他们从投资者那里最常听到的问题不是关于创始人或产品,而是"还有谁在投资?" 这往往会导致僵局。传统的固定规模股权融资可能需要数周时间,因为所有天使投资人都坐着等待其他人先承诺,就像自行车短距离赛的选手们在起跑时故意慢骑,以便跟随第一个冲刺的人。 可转换债券让初创公司能够通过给予愿意率先行动的投资者更低(实际)估值来打破这种僵局。这些投资者理应获得更低估值,因为他们承担了更大风险。投资罗恩·康威已经投过的初创公司要安全得多;后来者应该支付更高价格。 可转换债券之所以能提供更灵活的价格,是因为估值上限并非实际估值,而且债券操作成本低、手续简单。因此你可以进行高精度融资:如果需要,你可以为每个投资者设置不同上限的单独债券。 这个上限不必单调递增。初创公司也可以给那些预期能提供最大帮助的投资者更优惠的条件。关键在于,不同投资者——无论是因其能提供的帮助还是其投资意愿——对初创公司的价值不同,条款应该反映这一点。 为不同投资者设定不同条款显然是未来的趋势。市场总是向着更高精度的方向发展。你不一定非要使用可转换债券来实现这一点。如果有足够轻量化的标准化股权条款(以及投资者和律师对股权轮预期的一些改变),你完全可以用股权而非债权达到同样效果。对初创公司来说两种方式都可以,只要它们能轻松调整估值。 固定规模股权轮的问题不止是会导致僵局。另一个问题是初创公司必须提前决定融资金额。我认为初创公司确定一个具体数字是错误的。如果投资者很容易被说服,公司现在就应该多融资;如果投资者持怀疑态度,公司就应该少融些资金,并用这笔钱让公司发展到更具说服力的阶段。 期望初创公司提前选择最优融资规模是不合理的,因为这取决于投资者的反应,而这些反应无法预测。 对初创公司来说,固定规模、多投资者参与的天使轮是个如此糟糕的主意,以至于人们不禁要问为什么过去会采用这种方式。一种可能是这个惯例反映了投资者在可能的情况下喜欢串通的做法。但我认为实际解释没那么险恶。我认为天使投资人(及其律师)不加思考地模仿VC的A轮融资方式组织了这些轮次。在A轮融资中,由领投方参与的固定规模股权轮是有意义的,因为通常只有一个明确的大投资者作为领投方。固定规模的A轮融资本身已经是高精度的。但一轮中的投资者越多,让所有人获得相同价格就越不合理。 这里最有趣的问题可能是高精度融资会对投资者世界产生什么影响。更大胆的投资者现在将获得更低价格的奖励。但更重要的是,在这个由爆款驱动的行业里,他们将能够进入他们想要的交易。而那些"还有谁在投资?"类型的投资者不仅会支付更高价格,还可能根本无法进入最好的交易。 感谢 Immad Akhund、Sam Altman、John Bautista、Pete Koomen、Jessica Livingston、Dan Siroker、Harj Taggar和Fred Wilson阅读本文草稿。
Want to start a startup? Get funded by Y Combinator.
August 2010 When I went to work for Yahoo after they bought our startup in 1998, it felt like the center of the world. It was supposed to be the next big thing. It was supposed to be what Google turned out to be. What went wrong? The problems that hosed Yahoo go back a long time, practically to the beginning of the company. They were already very visible when I got there in 1998. Yahoo had two problems Google didn't: easy money, and ambivalence about being a technology company. Money The first time I met Jerry Yang, we thought we were meeting for different reasons. He thought we were meeting so he could check us out in person before buying us. I thought we were meeting so we could show him our new technology, Revenue Loop. It was a way of sorting shopping search results. Merchants bid a percentage of sales for traffic, but the results were sorted not by the bid but by the bid times the average amount a user would buy. It was like the algorithm Google uses now to sort ads, but this was in the spring of 1998, before Google was founded. Revenue Loop was the optimal sort for shopping search, in the sense that it sorted in order of how much money Yahoo would make from each link. But it wasn't just optimal in that sense. Ranking search results by user behavior also makes search better. Users train the search: you can start out finding matches based on mere textual similarity, and as users buy more stuff the search results get better and better. Jerry didn't seem to care. I was confused. I was showing him technology that extracted the maximum value from search traffic, and he didn't care? I couldn't tell whether I was explaining it badly, or he was just very poker faced. I didn't realize the answer till later, after I went to work at Yahoo. It was neither of my guesses.
The reason Yahoo didn't care about a technique that extracted the full value of traffic was that advertisers were already overpaying for it. If Yahoo merely extracted the actual value, they'd have made less. Hard as it is to believe now, the big money then was in banner ads. Advertisers were willing to pay ridiculous amounts for banner ads. So Yahoo's sales force had evolved to exploit this source of revenue. Led by a large and terrifyingly formidable man called Anil Singh, Yahoo's sales guys would fly out to Procter & Gamble and come back with million dollar orders for banner ad impressions. The prices seemed cheap compared to print, which was what advertisers, for lack of any other reference, compared them to. But they were expensive compared to what they were worth. So these big, dumb companies were a dangerous source of revenue to depend on. But there was another source even more dangerous: other Internet startups. By 1998, Yahoo was the beneficiary of a de facto Ponzi scheme. Investors were excited about the Internet. One reason they were excited was Yahoo's revenue growth. So they invested in new Internet startups. The startups then used the money to buy ads on Yahoo to get traffic. Which caused yet more revenue growth for Yahoo, and further convinced investors the Internet was worth investing in. When I realized this one day, sitting in my cubicle, I jumped up like Archimedes in his bathtub, except instead of "Eureka!" I was shouting "Sell!" Both the Internet startups and the Procter & Gambles were doing brand advertising. They didn't care about targeting. They just wanted lots of people to see their ads. So traffic became the thing to get at Yahoo. It didn't matter what type. [1] It wasn't just Yahoo. All the search engines were doing it.
This was why they were trying to get people to start calling them "portals" instead of "search engines." Despite the actual meaning of the word portal, what they meant by it was a site where users would find what they wanted on the site itself, instead of just passing through on their way to other destinations, as they did at a search engine. I remember telling David Filo in late 1998 or early 1999 that Yahoo should buy Google, because I and most of the other programmers in the company were using it instead of Yahoo for search. He told me that it wasn't worth worrying about. Search was only 6% of our traffic, and we were growing at 10% a month. It wasn't worth doing better. I didn't say "But search traffic is worth more than other traffic!" I said "Oh, ok." Because I didn't realize either how much search traffic was worth. I'm not sure even Larry and Sergey did then. If they had, Google presumably wouldn't have expended any effort on enterprise search. If circumstances had been different, the people running Yahoo might have realized sooner how important search was. But they had the most opaque obstacle in the world between them and the truth: money. As long as customers were writing big checks for banner ads, it was hard to take search seriously. Google didn't have that to distract them. Hackers But Yahoo also had another problem that made it hard to change directions. They'd been thrown off balance from the start by their ambivalence about being a technology company. One of the weirdest things about Yahoo when I went to work there was the way they insisted on calling themselves a "media company." If you walked around their offices, it seemed like a software company. The cubicles were full of programmers writing code, product managers thinking about feature lists and ship dates, support people (yes, there were actually support people) telling users to restart their browsers, and so on, just like a software company.
So why did they call themselves a media company? One reason was the way they made money: by selling ads. In 1995 it was hard to imagine a technology company making money that way. Technology companies made money by selling their software to users. Media companies sold ads. So they must be a media company. Another big factor was the fear of Microsoft. If anyone at Yahoo considered the idea that they should be a technology company, the next thought would have been that Microsoft would crush them. It's hard for anyone much younger than me to understand the fear Microsoft still inspired in 1995. Imagine a company with several times the power Google has now, but way meaner. It was perfectly reasonable to be afraid of them. Yahoo watched them crush the first hot Internet company, Netscape. It was reasonable to worry that if they tried to be the next Netscape, they'd suffer the same fate. How were they to know that Netscape would turn out to be Microsoft's last victim? It would have been a clever move to pretend to be a media company to throw Microsoft off their scent. But unfortunately Yahoo actually tried to be one, sort of. Project managers at Yahoo were called "producers," for example, and the different parts of the company were called "properties." But what Yahoo really needed to be was a technology company, and by trying to be something else, they ended up being something that was neither here nor there. That's why Yahoo as a company has never had a sharply defined identity. The worst consequence of trying to be a media company was that they didn't take programming seriously enough. Microsoft (back in the day), Google, and Facebook have all had hacker-centric cultures. But Yahoo treated programming as a commodity. At Yahoo, user-facing software was controlled by product managers and designers. The job of programmers was just to take the work of the product managers and designers the final step, by translating it into code.
One obvious result of this practice was that when Yahoo built things, they often weren't very good. But that wasn't the worst problem. The worst problem was that they hired bad programmers. Microsoft (back in the day), Google, and Facebook have all been obsessed with hiring the best programmers. Yahoo wasn't. They preferred good programmers to bad ones, but they didn't have the kind of single-minded, almost obnoxiously elitist focus on hiring the smartest people that the big winners have had. And when you consider how much competition there was for programmers when they were hiring, during the Bubble, it's not surprising that the quality of their programmers was uneven. In technology, once you have bad programmers, you're doomed. I can't think of an instance where a company has sunk into technical mediocrity and recovered. Good programmers want to work with other good programmers. So once the quality of programmers at your company starts to drop, you enter a death spiral from which there is no recovery. [2] At Yahoo this death spiral started early. If there was ever a time when Yahoo was a Google-style talent magnet, it was over by the time I got there in 1998. The company felt prematurely old. Most technology companies eventually get taken over by suits and middle managers. At Yahoo it felt as if they'd deliberately accelerated this process. They didn't want to be a bunch of hackers. They wanted to be suits. A media company should be run by suits. The first time I visited Google, they had about 500 people, the same number Yahoo had when I went to work there. But boy did things seem different. It was still very much a hacker-centric culture. I remember talking to some programmers in the cafeteria about the problem of gaming search results (now known as SEO), and they asked "what should we do?" Programmers at Yahoo wouldn't have asked that. Theirs was not to reason why; theirs was to build what product managers spec'd.
I remember coming away from Google thinking "Wow, it's still a startup." There's not much we can learn from Yahoo's first fatal flaw. It's probably too much to hope any company could avoid being damaged by depending on a bogus source of revenue. But startups can learn an important lesson from the second one. In the software business, you can't afford not to have a hacker-centric culture. Probably the most impressive commitment I've heard to having a hacker-centric culture came from Mark Zuckerberg, when he spoke at Startup School in 2007. He said that in the early days Facebook made a point of hiring programmers even for jobs that would not ordinarily consist of programming, like HR and marketing. So which companies need to have a hacker-centric culture? Which companies are "in the software business" in this respect? As Yahoo discovered, the area covered by this rule is bigger than most people realize. The answer is: any company that needs to have good software. Why would great programmers want to work for a company that didn't have a hacker-centric culture, as long as there were others that did? I can imagine two reasons: if they were paid a huge amount, or if the domain was interesting and none of the companies in it were hacker-centric. Otherwise you can't attract good programmers to work in a suit-centric culture. And without good programmers you won't get good software, no matter how many people you put on a task, or how many procedures you establish to ensure "quality." Hacker culture often seems kind of irresponsible. That's why people proposing to destroy it use phrases like "adult supervision." That was the phrase they used at Yahoo. But there are worse things than seeming irresponsible.
Losing, for example. Notes [1] The closest we got to targeting when I was there was when we created pets.yahoo.com in order to provoke a bidding war between 3 pet supply startups for the spot as top sponsor. [2] In theory you could beat the death spiral by buying good programmers instead of hiring them. You can get programmers who would never have come to you as employees by buying their startups. But so far the only companies smart enough to do this are companies smart enough not to need to. Thanks to Trevor Blackwell, Jessica Livingston, and Geoff Ralston for reading drafts of this..
想创业吗? 获得Y Combinator的资金支持。
2010年8月 1998年雅虎收购我们的初创公司后,我去那里工作时,感觉那里就是世界的中心。它本应成为下一个巨头。它本应成为如今的谷歌。 问题出在哪里?雅虎的困境由来已久,几乎可以追溯到公司创立之初。1998年我到那里时,问题已经非常明显。雅虎有两个谷歌没有的问题:轻易获得的金钱,以及对技术公司身份的摇摆不定。 金钱 第一次见到杨致远时,我们以为会面的目的不同。他以为会面是为了在收购前亲自考察我们。我以为会面是为了向他展示我们的新技术Revenue Loop。这是一种购物搜索结果的排序方式。商家为流量支付销售额的一定比例,但排序依据并非出价,而是出价乘以用户的平均购买金额。这与谷歌现在用来排序广告的算法类似,但这是在1998年春天,谷歌尚未成立。 Revenue Loop是购物搜索的最优排序,因为它是按照雅虎从每个链接中获得的收入排序的。但它不仅仅在这方面最优。根据用户行为排序搜索结果也能提升搜索质量。用户训练了搜索:最初可以基于文本相似性匹配,随着用户购买增多,搜索结果会越来越好。 杨致远似乎并不在意。我很困惑。我向他展示的是能从搜索流量中提取最大价值的技术,而他竟然不在意?我不知道是我解释得不好,还是他太不动声色。 直到后来去了雅虎工作,我才明白答案。我的两个猜测都不对。雅虎不在意这种能提取流量全部价值的技术,是因为广告主已经为此支付了过高的费用。如果雅虎只是提取实际价值,收入反而会减少。 尽管现在难以置信,但当时的大钱来自横幅广告。广告主愿意为横幅广告支付荒谬的价格。因此雅虎的销售团队逐渐演变为利用这一收入来源。在一位名叫Anil Singh的强势人物带领下,雅虎的销售团队会飞往宝洁公司,带着百万美元的横幅广告订单回来。 与印刷广告相比,这些价格看起来很便宜(广告主缺乏其他参照物),但相对于实际价值仍然昂贵。因此这些庞大而愚蠢的公司是危险的收入来源。但还有一个更危险的来源:其他互联网初创公司。 到了1998年,雅虎成为一场事实上的庞氏骗局的受益者。投资者对互联网感到兴奋,部分原因是雅虎的收入增长。于是他们投资新的互联网初创公司,这些公司用这些钱在雅虎上购买广告获取流量。这又进一步推动了雅虎的收入增长,让投资者更加确信互联网值得投资。有一天我在小隔间里意识到这一点时,像阿基米德在浴缸里一样跳了起来,只不过我喊的不是“尤里卡!”,而是“卖出!” 互联网初创公司和宝洁这样的公司都在做品牌广告。他们不在乎定向投放,只希望很多人看到广告。因此在雅虎,流量成了关键,类型并不重要。[1] 不仅仅是雅虎,所有搜索引擎都在这样做。这就是为什么他们试图让人们称他们为“门户”而非“搜索引擎”。尽管“门户”一词的实际含义不同,但他们想表达的是:用户可以在网站上找到所需内容,而不是像搜索引擎那样只是通往其他目的地的中转站。 我记得在1998年底或1999年初告诉David Filo,雅虎应该收购谷歌,因为我和公司里大多数程序员都在用谷歌而不是雅虎搜索。他告诉我这不必担心,搜索只占我们流量的6%,而我们每月增长10%。不值得做得更好。 我没有说“但搜索流量比其他流量更有价值!”,而是说“哦,好吧。”因为我也没意识到搜索流量的价值。甚至不确定拉里和谢尔盖当时是否清楚。如果他们知道,谷歌可能就不会在企业搜索上浪费精力了。 如果情况不同,雅虎的管理层可能会更早意识到搜索的重要性。但他们与真相之间隔着世界上最不透明的障碍:金钱。只要客户还在为横幅广告开出大额支票,就很难认真对待搜索。谷歌没有这种干扰。 黑客 但雅虎还有另一个问题使其难以转向。从一开始,他们对技术公司身份的摇摆态度就让他们失去了平衡。 我在雅虎工作时最奇怪的事情之一是他们坚持称自己为“媒体公司”。如果你在他们的办公室走动,会发现它看起来像一家软件公司。小隔间里满是写代码的程序员、思考功能列表和发布日期的产品经理、让用户重启浏览器的支持人员(是的,他们真的有支持人员),等等,就像一家软件公司。那为什么他们称自己为媒体公司? 一个原因是他们的赚钱方式:卖广告。1995年很难想象技术公司能这样赚钱。技术公司通过向用户出售软件赚钱,媒体公司则卖广告。所以他们一定是媒体公司。 另一个重要因素是对微软的恐惧。如果雅虎有人考虑他们应该是技术公司,下一个想法就是微软会碾碎他们。 对于比我年轻很多的人来说,很难理解1995年微软仍然激发的恐惧。想象一家比现在的谷歌强大几倍但更无情的公司。害怕他们是完全合理的。雅虎目睹他们碾碎了第一家热门互联网公司网景。担心如果试图成为下一个网景会遭遇同样的命运是合理的。他们怎么知道网景会成为微软的最后一个受害者? 假装是媒体公司以迷惑微软本来是聪明的策略。但不幸的是,雅虎某种程度上真的试图成为媒体公司。例如,雅虎的项目经理被称为“制作人”,公司的不同部分被称为“资产”。但雅虎真正需要成为的是技术公司,试图成为其他东西的结果是他们变得不伦不类。这就是为什么雅虎作为一家公司从未有明确的身份认同。 试图成为媒体公司的最坏后果是他们没有足够重视编程。微软(当年)、谷歌和Facebook都有以黑客为中心的文化。但雅虎将编程视为商品。在雅虎,面向用户的软件由产品经理和设计师控制。程序员的工作只是将产品经理和设计师的成果转化为代码。 这种做法的一个明显结果是雅虎构建的东西往往不太出色。但最糟糕的问题是他们雇佣了糟糕的程序员。 微软(当年)、谷歌和Facebook都痴迷于雇佣最优秀的程序员。雅虎没有。他们更喜欢好程序员,但没有那种一心一意、近乎偏执地专注于雇佣最聪明人的态度,而这正是大赢家的特点。考虑到他们在泡沫时期招聘程序员时的激烈竞争,他们的程序员质量参差不齐并不奇怪。 在技术领域,一旦有了糟糕的程序员,你就注定失败。我想不出有哪家公司陷入技术平庸后又恢复的例子。优秀的程序员希望与其他优秀的程序员共事。因此一旦公司程序员的质量开始下降,就会进入无法逆转的死亡螺旋。[2] 雅虎的这种死亡螺旋开始得很早。如果雅虎曾经有过谷歌式的人才吸引力,那在我1998年到那里时已经结束了。 公司给人一种过早衰老的感觉。大多数技术公司最终会被西装革履的中层管理者接管。在雅虎,感觉他们有意加速了这一过程。他们不想成为一群黑客,他们想成为西装革履的人。媒体公司应该由西装革履的人管理。 我第一次访问谷歌时,他们大约有500人,与我去雅虎工作时的人数相同。但感觉天差地别。那里仍然是以黑客为中心的文化。我记得在食堂与一些程序员讨论操纵搜索结果的问题(现在称为SEO),他们问“我们该怎么办?”雅虎的程序员不会这么问。他们的任务不是思考为什么,而是按照产品经理的规格构建产品。我记得离开谷歌时想:“哇,它仍然是一家初创公司。” 我们从雅虎的第一个致命缺陷中学不到太多。指望任何公司避免依赖虚假收入来源的损害可能要求过高。但初创公司可以从第二个缺陷中学到重要的一课。在软件行业,你不能不以黑客文化为中心。 我听说过的对黑客文化最坚定的承诺来自马克·扎克伯格。他在2007年Startup School演讲时说,早期Facebook坚持为通常不需要编程的职位(如人力资源和市场营销)雇佣程序员。 那么哪些公司需要以黑客文化为中心?哪些公司在这方面属于“软件行业”?正如雅虎所发现的,这条规则的适用范围比大多数人想象的要大。答案是:任何需要优秀软件的公司。 只要还有其他公司以黑客文化为中心,优秀的程序员为什么要为不以黑客文化为中心的公司工作?我能想到两个原因:如果他们获得巨额报酬,或者领域很有趣且该领域的公司都不以黑客文化为中心。否则你无法吸引优秀程序员进入以西装文化为中心的公司。而没有优秀程序员,无论投入多少人或建立多少流程来确保“质量”,都无法获得优秀软件。 黑客文化常常显得有些不负责任。这就是为什么那些试图破坏它的人会用“成人监督”这样的词。这就是雅虎用过的词。但还有比显得不负责任更糟糕的事情。比如失败。 注释 [1] 我在那里时最接近定向投放的做法是创建pets.yahoo.com,以引发三家宠物用品初创公司竞标顶部赞助商位置。 [2] 理论上你可以通过收购而非雇佣来打破死亡螺旋。通过收购初创公司,你可以得到那些永远不会成为你员工的程序员。但迄今为止,唯一足够聪明做到这一点的公司是那些聪明到不需要这么做的公司。 感谢 Trevor Blackwell、Jessica Livingston和Geoff Ralston阅读本文草稿。.
Want to start a startup? Get funded by Y Combinator.
August 2010 Two years ago I wrote about what I called "a huge, unexploited opportunity in startup funding:" the growing disconnect between VCs, whose current business model requires them to invest large amounts, and a large class of startups that need less than they used to. Increasingly, startups want a couple hundred thousand dollars, not a couple million. [1] The opportunity is a lot less unexploited now. Investors have poured into this territory from both directions. VCs are much more likely to make angel-sized investments than they were a year ago. And meanwhile the past year has seen a dramatic increase in a new type of investor: the super-angel, who operates like an angel, but using other people's money, like a VC. Though a lot of investors are entering this territory, there is still room for more. The distribution of investors should mirror the distribution of startups, which has the usual power law dropoff. So there should be a lot more people investing tens or hundreds of thousands than millions. [2] In fact, it may be good for angels that there are more people doing angel-sized deals, because if angel rounds become more legitimate, then startups may start to opt for angel rounds even when they could, if they wanted, raise series A rounds from VCs. One reason startups prefer series A rounds is that they're more prestigious. But if angel investors become more active and better known, they'll increasingly be able to compete with VCs in brand. Of course, prestige isn't the main reason to prefer a series A round. A startup will probably get more attention from investors in a series A round than an angel round.
想创业吗? 获得 Y Combinator 的资助。
2010年8月 两年前,我曾撰文讨论过我所称的“创业融资领域一个巨大且未被开发的机遇”:风投机构与大量初创企业之间日益扩大的脱节。当前风投的业务模式要求他们进行大额投资,而许多初创企业所需的资金却比过去少得多。越来越多的初创企业只需要几十万美元,而不是几百万美元。[1] 如今,这个机遇已不再那么未被开发。投资者从两个方向涌入这一领域。与一年前相比,风投机构更倾向于进行天使投资规模的注资。与此同时,过去一年见证了一类新型投资者的激增:超级天使。他们运作方式像天使投资人,但像风投一样使用他人的资金。 尽管大量投资者正在进入这一领域,但仍有更多空间。投资者的分布应当反映初创企业的分布,遵循常见的幂律衰减规律。因此,投资数万或数十万美元的人应该比投资数百万的人多得多。[2] 事实上,更多投资者参与天使规模的投资对天使投资人可能是好事,因为如果天使轮融资变得更主流,初创企业可能会开始选择天使轮融资,即使他们本可以选择从风投那里获得A轮融资。初创企业偏爱A轮融资的一个原因是其更具声望。但如果天使投资人变得更活跃、更知名,他们将逐渐能在品牌上与风投竞争。 当然,声望并非选择A轮融资的主要原因。在A轮融资中,初创企业可能会比天使轮获得投资者更多关注。因此,如果一家初创企业需要在天使轮和一家优秀风投基金的A轮之间选择,我通常会建议他们选择A轮。[3] 尽管A轮融资不会消失,但我认为风投机构应该比超级天使更担心对方。尽管名为“超级天使”,他们实际上是迷你风投基金,且显然将现有风投机构视为目标。 他们似乎站在历史正确的一边。这里的模式似乎与初创企业和老牌公司进入新市场时的情况相同。在线视频成为可能,YouTube立即全力投入,而现有媒体公司则半心半意地拥抱它,更多是出于恐惧而非希望,目标更多是保护自己的地盘而非为用户创造伟大产品。PayPal也是如此。这种模式一再重复,而胜利者通常是入侵者。在这种情况下,超级天使就是入侵者。天使轮融资是他们的全部业务,就像在线视频之于YouTube。而进行天使投资的风投大多将其作为为A轮融资获取项目流的手段。[4] 另一方面,初创企业投资是一个非常奇怪的行业。几乎所有回报都集中在少数几个大赢家身上。如果超级天使仅仅未能投资(并在某种程度上培育)这些大赢家,即使他们投资了所有其他企业,他们也会倒闭。 风投机构 为什么风投不开始进行规模较小的A轮融资?症结在于董事会席位。在传统的A轮融资中,负责该项目的合伙人会在初创企业的董事会中占有一席。如果我们假设一家初创企业平均运营6年,一位合伙人可以同时担任12家公司的董事,那么一家风投基金每年每位合伙人可以进行2笔A轮交易。 在我看来,解决方案一直是减少董事会席位。你不必进入董事会就能帮助一家初创企业。也许风投认为他们需要董事会成员带来的权力,以确保他们的钱不会被浪费。但他们测试过这一理论吗?除非他们尝试过不担任董事并发现回报降低,否则他们并未真正解决问题。 我并不是说风投不帮助初创企业。优秀的风投会提供大量帮助。我想说的是,真正重要的帮助,可能不必通过董事会成员的身份来提供。[5] 这一切将如何发展?一些风投可能会通过进行更多、更小的交易来适应。如果风投基金通过简化选择流程和减少董事会席位,能在不损失质量的情况下进行2到3倍的A轮融资,我不会感到惊讶。 但其他风投只会做出表面改变。风投是保守的,且他们面临的威胁并非致命。不适应的风投基金不会被暴力取代。他们会逐渐进入一个不同的业务领域而不自知。他们仍会进行他们所谓的A轮融资,但这些将越来越多地成为事实上的B轮融资。[6] 在这样的轮次中,他们将无法获得现在25%到40%的公司股份。除非出现严重问题,否则在后续轮次中你不会放弃那么多公司股份。由于不适应的风投将在后期投资,他们从赢家中获得的回报可能会更小。但后期投资也应意味着他们的失败者更少。因此,他们的风险回报比可能相同甚至更好。他们只是变成了一种更保守的不同投资类型。 天使投资人 在与A轮融资日益竞争的大规模天使轮融资中,投资者不会像现在的风投那样获得那么多股权。而试图通过进行更多、更小的交易与天使投资人竞争的风投可能会发现,他们必须减少股权要求才能做到这一点。这对创始人来说是个好消息:他们将能保留更多公司股份。 天使轮融资的条款也将变得不那么严格——不仅比A轮条款宽松,而且比传统的天使条款宽松。 未来,天使轮融资将更少针对特定金额或设有领投人。过去,初创企业的标准做法是找到一位天使投资人作为领投人。你会与领投人协商融资金额和估值,领投人会提供部分但不是全部资金。然后初创企业和领投人会合作寻找剩余资金。 天使轮融资的未来看起来更像这样:初创企业不会设定固定融资金额,而是进行滚动式融资,从投资者那里逐一获取资金,直到他们认为足够为止。[7]尽管会有一位投资者开出第一张支票,且他或她在招募其他投资者方面的帮助当然会受到欢迎,但这位初始投资者将不再像过去那样作为管理融资轮次的领投人。初创企业现在将自行管理。 在“建议”初创企业方面发挥主导作用的领投人仍将存在。他们也可能进行最大投资。但他们不必总是像过去那样成为条款谈判的对象或第一个出资人。标准化的文件将消除除估值外的一切谈判需求,而估值谈判也会变得更简单。 如果多位投资者必须共享一个估值,那将是初创企业能从第一个开出支票的投资者那里获得的估值,受限于他们对这是否会让后续投资者犹豫的猜测。但可能不必只有一个估值。初创企业越来越多地通过可转换债券融资,而可转换债券没有估值,最多只有估值上限:即债务转换为股权时(在后续轮次或收购时)的有效估值上限。这是一个重要区别,因为它意味着初创企业可以同时进行多笔不同上限的可转换债券融资。这种情况已经开始出现,我预测它将变得更普遍。 羊群效应 事情朝这个方向发展的原因是旧方式对初创企业不利。领投人可以(也确实)利用固定金额的融资轮作为一种看似合理的方式,说出所有创始人不愿听到的话:如果其他人投资,我就投资。大多数投资者无法自行判断初创企业,转而依赖其他投资者的意见。如果所有人都想参与,他们也想;如果不参与,他们也不参与。创始人讨厌这一点,因为这是僵局的根源,而拖延是初创企业最无法承受的。大多数投资者知道这种做法很糟糕,很少有人公开承认他们在这样做。但更狡猾的人通过提出领投固定金额的融资轮并只提供部分资金来达到同样效果。如果初创企业无法筹集剩余资金,领投人也会退出。他们怎么能继续这笔交易?初创企业会资金不足! 未来,投资者将越来越无法以其他人投资为条件提供投资。或者说,这样做的投资者将排在队伍最后。初创企业只会找他们来填补大部分已认购的融资轮。由于热门初创企业的融资轮往往超额认购,排在最后意味着他们可能会错过热门交易。热门交易与成功的初创企业并不完全相同,但存在显著相关性。[8]因此,不愿单方面投资的投资者回报会更低。 投资者可能会发现,即使失去这一拐杖,他们也能做得更好。追逐热门交易并不会让投资者做出更好的选择;它只是让他们对自己的选择感觉更好。我多次目睹抢购狂潮的形成与瓦解,据我所知,它们大多是随机的。[9]如果投资者不能再依赖他们的从众本能,他们将不得不在投资前更仔细地思考每家初创企业。他们可能会惊讶于这种方式的效果。 让领投人管理天使轮融资的弊端不仅是僵局。投资者们经常串通压低估值。而且融资轮结束耗时过长,因为无论领投人多么有动力完成融资轮,他的动力都不及初创企业的十分之一。 越来越多的初创企业正在自行管理天使轮融资。目前这么做的还不多,但我认为我们已经可以宣布旧方式已死,因为这些少数企业是最优秀的初创企业。他们有能力告诉投资者融资轮将如何运作。如果你想投资的初创企业以某种方式行事,其他企业怎么做又有什么关系? 吸引力 事实上,说天使轮融资将越来越多地取代A轮融资可能略有误导。真正发生的是由初创企业主导的融资轮正在取代由投资者主导的融资轮。 这是一个非常重要的元趋势的实例,Y Combinator从一开始就基于这一趋势:创始人相对于投资者正变得越来越强大。因此,如果你想预测风险投资的未来会是什么样子,只需问:创始人希望它是什么样子?创始人讨厌的融资问题将逐一被消除。[10] 根据这一启发,我再预测几件事。一是投资者将越来越无法等到初创企业具有“吸引力”后才投入大量资金。提前预测哪些初创企业会成功很难。因此,大多数投资者如果可能,更愿意等到初创企业已经成功,然后迅速介入提出报价。初创企业也讨厌这一点,部分是因为它容易导致僵局,部分是因为它显得有点卑鄙。如果你是一家有前途但尚未显著增长的初创企业,所有投资者口头上都是你的朋友,但行动上寥寥无几。他们都说爱你,但都等待投资。然后当你开始看到增长时,他们声称一直是你的朋友,并惊讶于你竟会如此不忠,将他们排除在你的融资轮之外。如果创始人变得更强大,他们将能让投资者提前投入更多资金。 (这种行为最糟糕的变体是分期交易,投资者先进行少量初始投资,如果初创企业表现良好,再追加投资。这种结构实际上给了投资者下一轮融资的免费期权,他们只会在对初创企业比公开市场更不利时行使。分期交易是一种滥用。它们越来越罕见,并将变得更罕见。)[11] 投资者不喜欢尝试预测哪些初创企业会成功,但他们将不得不越来越多地这样做。尽管这一变化的方式不一定是现有投资者的行为会改变;而可能是他们将被行为不同的其他投资者取代——那些足够了解初创企业、能够承担预测其发展轨迹这一难题的投资者,将倾向于取代那些技能更多在于从有限合伙人那里筹集资金的西装革履者。 速度 创始人最讨厌融资的另一件事是耗时过长。因此,随着创始人变得更强大,融资轮应该会更快完成。 融资对初创企业来说仍然非常分散注意力。如果你是一位正在融资的创始人,融资是你脑海中的首要想法,这意味着你无法专注于公司工作。如果一轮融资需要2个月完成(按目前标准已经算快),这意味着公司基本上在原地踏步2个月。这是初创企业能做的最糟糕的事。 因此,如果投资者想获得最佳交易,方法就是更快完成融资。无论如何,投资者不需要几周时间来做决定。我们根据约10分钟的申请阅读加10分钟的面对面面试做出决定,且只对约10%的决定感到遗憾。如果我们能在20分钟内决定,下一轮投资者当然可以在几天内决定。[12] 初创企业融资中有许多制度化的延迟:与投资者长达数周的“求偶舞蹈”;条款清单与交易之间的区别;每一轮A轮融资都有极其复杂的定制文件。创始人和投资者往往认为这些是理所当然的。事情一直是这样。但归根结底,这些延迟存在的原因是它们对投资者有利。更多时间让投资者能获取更多关于初创企业发展的信息,也往往让初创企业在谈判中更易妥协,因为他们通常资金短缺。 这些惯例并非设计来拖延融资过程,但这就是它们得以持续的原因。缓慢对投资者有利,而过去他们是权力更大的一方。但融资轮不需要数月甚至数周才能完成,一旦创始人意识到这一点,这种情况就会停止。不仅天使轮如此,A轮融资也是如此。未来将是条款简单、快速完成的交易。 在这一过程中将得到纠正的一个小弊端是期权池。在传统的A轮融资中,风投在投资前会让公司为未来员工预留一部分股票——通常占公司的10%到30%。目的是确保这种稀释由现有股东承担。这种做法并非不诚实;创始人知道发生了什么。但它让交易变得不必要地复杂。实际上估值是两个数字。没有必要继续这样做。[13] 创始人想要的最后一件事是能够在后续轮次中出售部分自己的股票。这不会是一个变化,因为这种做法现在已经相当普遍。许多投资者讨厌这个想法,但世界并未因此崩溃,所以它会更多、更公开地发生。 惊喜 我在这里谈到了随着创始人变得更强大,投资者将被迫做出的一系列改变。现在有个好消息:投资者实际上可能因此赚更多钱。 几天前,一位采访者问我,创始人拥有更多权力对世界是好是坏。我很惊讶,因为我从未考虑过这个问题。无论好坏,它正在发生。但经过一秒钟的思考,答案似乎显而易见。创始人比投资者更了解他们的公司,而知识更丰富的人拥有更多权力一定是好事。 新手飞行员常犯的一个错误是过度控制飞机:过于猛烈地施加修正,导致飞机在期望配置附近振荡而非渐进接近。投资者迄今为止可能平均对他们的投资组合公司过度控制。在许多初创企业中,创始人最大的压力来源不是竞争对手,而是投资者。对我们Viaweb来说确实如此。而且这不是新现象:投资者也是詹姆斯·瓦特的最大问题。如果权力减少能防止投资者过度控制初创企业,这不仅对创始人更好,对投资者也应如此。 投资者最终可能从每家初创企业获得的股份减少,但由创始人更多控制的初创企业可能会做得更好,而且初创企业的数量几乎肯定会增加。投资者彼此竞争交易,但他们彼此并非主要竞争对手。我们的主要竞争对手是雇主。到目前为止,这个竞争对手正在碾压我们。只有极少数有能力创业的人真正创业。几乎所有客户都选择了竞争产品——一份工作。为什么?好吧,看看我们提供的产品。一个公正的评论大概是这样的:.
So if a startup is choosing between an angel round and an A round from a good VC fund, I usually advise them to take the A round. [3] But while series A rounds aren't going away, I think VCs should be more worried about super-angels than vice versa. Despite their name, the super-angels are really mini VC funds, and they clearly have existing VCs in their sights. They would seem to have history on their side. The pattern here seems the same one we see when startups and established companies enter a new market. Online video becomes possible, and YouTube plunges right in, while existing media companies embrace it only half-willingly, driven more by fear than hope, and aiming more to protect their turf than to do great things for users. Ditto for PayPal. This pattern is repeated over and over, and it's usually the invaders who win. In this case the super-angels are the invaders. Angel rounds are their whole business, as online video was for YouTube. Whereas VCs who make angel investments mostly do it as a way to generate deal flow for series A rounds. [4] On the other hand, startup investing is a very strange business. Nearly all the returns are concentrated in a few big winners. If the super-angels merely fail to invest in (and to some extent produce) the big winners, they'll be out of business, even if they invest in all the others. VCs Why don't VCs start doing smaller series A rounds? The sticking point is board seats. In a traditional series A round, the partner whose deal it is takes a seat on the startup's board. If we assume the average startup runs for 6 years and a partner can bear to be on 12 boards at once, then a VC fund can do 2 series A deals per partner per year. It has always seemed to me the solution is to take fewer board seats. You don't have to be on the board to help a startup. Maybe VCs feel they need the power that comes with board membership to ensure their money isn't wasted.
创办一家初创企业能给你更多自由,也有机会比打工赚得多得多,但这也意味着艰苦的工作,有时压力会非常大。
But have they tested that theory? Unless they've tried not taking board seats and found their returns are lower, they're not bracketing the problem. I'm not saying VCs don't help startups. The good ones help them a lot. What I'm saying is that the kind of help that matters, you may not have to be a board member to give. [5] How will this all play out? Some VCs will probably adapt, by doing more, smaller deals. I wouldn't be surprised if by streamlining their selection process and taking fewer board seats, VC funds could do 2 to 3 times as many series A rounds with no loss of quality. But other VCs will make no more than superficial changes. VCs are conservative, and the threat to them isn't mortal. The VC funds that don't adapt won't be violently displaced. They'll edge gradually into a different business without realizing it. They'll still do what they will call series A rounds, but these will increasingly be de facto series B rounds. [6] In such rounds they won't get the 25 to 40% of the company they do now. You don't give up as much of the company in later rounds unless something is seriously wrong. Since the VCs who don't adapt will be investing later, their returns from winners may be smaller. But investing later should also mean they have fewer losers. So their ratio of risk to return may be the same or even better. They'll just have become a different, more conservative, type of investment. Angels In the big angel rounds that increasingly compete with series A rounds, the investors won't take as much equity as VCs do now. And VCs who try to compete with angels by doing more, smaller deals will probably find they have to take less equity to do it. Which is good news for founders: they'll get to keep more of the company. The deal terms of angel rounds will become less restrictive too—not just less restrictive than series A terms, but less restrictive than angel terms have traditionally been.
大部分压力来自与投资人的周旋。如果能通过改革投资流程消除这种压力,我们的产品将更具吸引力。优秀的初创企业创始人并不介意解决技术难题——他们甚至乐在其中——但他们厌恶投资人带来的那类问题。
投资人不会意识到,当他们苛待一家初创公司时,实际上间接扼杀了另外十家潜在企业的诞生。当投资人不再执着于从现有交易中榨取额外利益时,他们会发现整体收益反而增长,因为更多新交易将如雨后春笋般涌现。
In the future, angel rounds will less often be for specific amounts or have a lead investor. In the old days, the standard m.o. for startups was to find one angel to act as the lead investor. You'd negotiate a round size and valuation with the lead, who'd supply some but not all of the money. Then the startup and the lead would cooperate to find the rest. The future of angel rounds looks more like this: instead of a fixed round size, startups will do a rolling close, where they take money from investors one at a time till they feel they have enough. [7] And though there's going to be one investor who gives them the first check, and his or her help in recruiting other investors will certainly be welcome, this initial investor will no longer be the lead in the old sense of managing the round. The startup will now do that themselves. There will continue to be lead investors in the sense of investors who take the lead in _advising_ a startup. They may also make the biggest investment. But they won't always have to be the one terms are negotiated with, or be the first money in, as they have in the past. Standardized paperwork will do away with the need to negotiate anything except the valuation, and that will get easier too. If multiple investors have to share a valuation, it will be whatever the startup can get from the first one to write a check, limited by their guess at whether this will make later investors balk. But there may not have to be just one valuation. Startups are increasingly raising money on convertible notes, and convertible notes have not valuations but at most valuation _caps_ : caps on what the effective valuation will be when the debt converts to equity (in a later round, or upon acquisition if that happens first). That's an important difference because it means a startup could do multiple notes at once with different caps.
Y Combinator的核心理念之一,就是不把项目源视为零和游戏。我们专注的是催生更多初创企业,而非争夺现有市场的份额。这条原则已被证明极具价值,我们相信随着其推广,后期投资者也将受益。
This is now starting to happen, and I predict it will become more common. Sheep The reason things are moving this way is that the old way sucked for startups. Leads could (and did) use a fixed size round as a legitimate-seeming way of saying what all founders hate to hear: I'll invest if other people will. Most investors, unable to judge startups for themselves, rely instead on the opinions of other investors. If everyone wants in, they want in too; if not, not. Founders hate this because it's a recipe for deadlock, and delay is the thing a startup can least afford. Most investors know this m.o. is lame, and few say openly that they're doing it. But the craftier ones achieve the same result by offering to lead rounds of fixed size and supplying only part of the money. If the startup can't raise the rest, the lead is out too. How could they go ahead with the deal? The startup would be underfunded! In the future, investors will increasingly be unable to offer investment subject to contingencies like other people investing. Or rather, investors who do that will get last place in line. Startups will go to them only to fill up rounds that are mostly subscribed. And since hot startups tend to have rounds that are oversubscribed, being last in line means they'll probably miss the hot deals. Hot deals and successful startups are not identical, but there is a significant correlation. [8] So investors who won't invest unilaterally will have lower returns. Investors will probably find they do better when deprived of this crutch anyway. Chasing hot deals doesn't make investors choose better; it just makes them feel better about their choices. I've seen feeding frenzies both form and fall apart many times, and as far as I can tell they're mostly random. [9] If investors can no longer rely on their herd instincts, they'll have to think more about each startup before investing. They may be surprised how well this works.
"创造人们需要的东西"这条法则同样适用于我们自身。
注释 [1] 本文主要探讨软件类初创企业,不适用于能源、生物科技等高成本创业领域。即便是低成本创业项目,在需要大规模招聘时通常也会进行大额融资。变化在于它们在此之前能达成多少成果。
Deadlock wasn't the only disadvantage of letting a lead investor manage an angel round. The investors would not infrequently collude to push down the valuation. And rounds took too long to close, because however motivated the lead was to get the round closed, he was not a tenth as motivated as the startup. Increasingly, startups are taking charge of their own angel rounds. Only a few do so far, but I think we can already declare the old way dead, because those few are the best startups. They're the ones in a position to tell investors how the round is going to work. And if the startups you want to invest in do things a certain way, what difference does it make what the others do? Traction In fact, it may be slightly misleading to say that angel rounds will increasingly take the place of series A rounds. What's really happening is that startup-controlled rounds are taking the place of investor-controlled rounds. This is an instance of a very important meta-trend, one that Y Combinator itself has been based on from the beginning: founders are becoming increasingly powerful relative to investors. So if you want to predict what the future of venture funding will be like, just ask: how would founders like it to be? One by one, all the things founders dislike about raising money are going to get eliminated. [10] Using that heuristic, I'll predict a couple more things. One is that investors will increasingly be unable to wait for startups to have "traction" before they put in significant money. It's hard to predict in advance which startups will succeed. So most investors prefer, if they can, to wait till the startup is already succeeding, then jump in quickly with an offer. Startups hate this as well, partly because it tends to create deadlock, and partly because it seems kind of slimy. If you're a promising startup but don't yet have significant growth, all the investors are your friends in words, but few are in actions.
[2] 呈现幂律衰减的并非优质初创企业的分布,而是潜在优质项目(即优质交易)的分布。存在大量潜在赢家,其中少数最终会以超线性确定性脱颖而出。
They all say they love you, but they all wait to invest. Then when you start to see growth, they claim they were your friend all along, and are aghast at the thought you'd be so disloyal as to leave them out of your round. If founders become more powerful, they'll be able to make investors give them more money upfront. (The worst variant of this behavior is the tranched deal, where the investor makes a small initial investment, with more to follow if the startup does well. In effect, this structure gives the investor a free option on the next round, which they'll only take if it's worse for the startup than they could get in the open market. Tranched deals are an abuse. They're increasingly rare, and they're going to get rarer.) [11] Investors don't like trying to predict which startups will succeed, but increasingly they'll have to. Though the way that happens won't necessarily be that the behavior of existing investors will change; it may instead be that they'll be replaced by other investors with different behavior—that investors who understand startups well enough to take on the hard problem of predicting their trajectory will tend to displace suits whose skills lie more in raising money from LPs. Speed The other thing founders hate most about fundraising is how long it takes. So as founders become more powerful, rounds should start to close faster. Fundraising is still terribly distracting for startups. If you're a founder in the middle of raising a round, the round is the top idea in your mind, which means working on the company isn't. If a round takes 2 months to close, which is reasonably fast by present standards, that means 2 months during which the company is basically treading water. That's the worst thing a startup could do. So if investors want to get the best deals, the way to do it will be to close faster. Investors don't need weeks to make up their minds anyway.
[3] 撰写本文时,我询问过几位接受顶级风投A轮融资的创始人是否值得,他们一致给出肯定答案。不过投资人质量比轮次类型更重要:我宁愿选择优秀天使投资人的早期注资,也不要平庸风投的A轮。
[4] 创始人还担心:若接受某风投的天使投资却未获后续跟投,会影响企业形象。由于风投天使化趋势太新,这种担忧的合理性尚难判定。米切尔·卡普尔指出另一风险:若风投仅将天使投资视为获取A轮项目的手段,其利益就与创始人相悖——创始人希望下轮估值更高,风投则希望压低。同样难以预料其影响程度。
We decide based on about 10 minutes of reading an application plus 10 minutes of in person interview, and we only regret about 10% of our decisions. If we can decide in 20 minutes, surely the next round of investors can decide in a couple days. [12] There are a lot of institutionalized delays in startup funding: the multi-week mating dance with investors; the distinction between termsheets and deals; the fact that each series A has enormously elaborate, custom paperwork. Both founders and investors tend to take these for granted. It's the way things have always been. But ultimately the reason these delays exist is that they're to the advantage of investors. More time gives investors more information about a startup's trajectory, and it also tends to make startups more pliable in negotiations, since they're usually short of money. These conventions weren't designed to drag out the funding process, but that's why they're allowed to persist. Slowness is to the advantage of investors, who have in the past been the ones with the most power. But there is no need for rounds to take months or even weeks to close, and once founders realize that, it's going to stop. Not just in angel rounds, but in series A rounds too. The future is simple deals with standard terms, done quickly. One minor abuse that will get corrected in the process is option pools. In a traditional series A round, before the VCs invest they make the company set aside a block of stock for future hires—usually between 10 and 30% of the company. The point is to ensure this dilution is borne by the existing shareholders. The practice isn't dishonest; founders know what's going on. But it makes deals unnecessarily complicated. In effect the valuation is 2 numbers. There's no need to keep doing this. [13] The final thing founders want is to be able to sell some of their own stock in later rounds. This won't be a change, because the practice is now quite common.
[5] 乔什·科佩尔曼提出,减少同时在任董事席位的另一方式是缩短董事任期。
A lot of investors hated the idea, but the world hasn't exploded as a result, so it will happen more, and more openly. Surprise I've talked here about a bunch of changes that will be forced on investors as founders become more powerful. Now the good news: investors may actually make more money as a result. A couple days ago an interviewer asked me if founders having more power would be better or worse for the world. I was surprised, because I'd never considered that question. Better or worse, it's happening. But after a second's reflection, the answer seemed obvious. Founders understand their companies better than investors, and it has to be better if the people with more knowledge have more power. One of the mistakes novice pilots make is overcontrolling the aircraft: applying corrections too vigorously, so the aircraft oscillates about the desired configuration instead of approaching it asymptotically. It seems probable that investors have till now on average been overcontrolling their portfolio companies. In a lot of startups, the biggest source of stress for the founders is not competitors but investors. Certainly it was for us at Viaweb. And this is not a new phenomenon: investors were James Watt's biggest problem too. If having less power prevents investors from overcontrolling startups, it should be better not just for founders but for investors too. Investors may end up with less stock per startup, but startups will probably do better with founders more in control, and there will almost certainly be more of them. Investors all compete with one another for deals, but they aren't one another's main competitor. Our main competitor is employers. And so far that competitor is crushing us. Only a tiny fraction of people who could start a startup do. Nearly all customers choose the competing product, a job. Why? Well, let's look at the product we're offering.
[6] 谷歌在这方面如同其他许多领域一样,为未来树立了范式。若回报率也能如此相似,风投将获益匪浅——这或许过于理想,但如后文所述,回报率可能会有所提升。
An unbiased review would go something like this:.
[7] 滚动交割不意味着公司持续融资(这会分散精力),而是为了缩短筹资周期。传统固定规模融资需所有投资人达成一致才能放款,常导致互相观望的僵局,滚动交割通常能避免这点。
[8] 热门交易有两大(非互斥)成因:公司质量与投资人间的多米诺效应,前者显然是更可靠的成功指标。
> Starting a startup gives you more freedom and the opportunity to make a lot more money than a job, but it's also hard work and at times very stressful.
[9] 部分随机性被"投资即自我实现预言"的现象所掩盖。
Much of the stress comes from dealing with investors. If reforming the investment process removed that stress, we'd make our product much more attractive. The kind of people who make good startup founders don't mind dealing with technical problems—they enjoy technical problems—but they hate the type of problems investors cause. Investors have no idea that when they maltreat one startup, they're preventing 10 others from happening, but they are. Indirectly, but they are. So when investors stop trying to squeeze a little more out of their existing deals, they'll find they're net ahead, because so many more new deals appear. One of our axioms at Y Combinator is not to think of deal flow as a zero-sum game. Our main focus is to encourage more startups to happen, not to win a larger share of the existing stream. We've found this principle very useful, and we think as it spreads outward it will help later stage investors as well. "Make something people want" applies to us too. Notes [1] In this essay I'm talking mainly about software startups. These points don't apply to types of startups that are still expensive to start, e.g. in energy or biotech. Even the cheap kinds of startups will generally raise large amounts at some point, when they want to hire a lot of people. What has changed is how much they can get done before that. [2] It's not the distribution of good startups that has a power law dropoff, but the distribution of potentially good startups, which is to say, good deals. There are lots of potential winners, from which a few actual winners emerge with superlinear certainty. [3] As I was writing this, I asked some founders who'd taken series A rounds from top VC funds whether it was worth it, and they unanimously said yes. The quality of investor is more important than the type of round, though.
[10] 创始人话语权增强的现象因卖方市场被夸大,下次低谷时会显得言过其实。但在随后的复苏期,创始人的主导地位将更甚以往。
[11] 广义而言,同一投资人连续多轮注资的情况将减少(行权维持股权比例除外)。这种情况往往意味着企业未获市场公允估值。虽然创始人可能不介意选择熟悉投资人,但随着投资市场效率提升,获取公允估值将越来越便捷,这将促使投资圈层化加剧。
I'd take an angel round from good angels over a series A from a mediocre VC. [4] Founders also worry that taking an angel investment from a VC means they'll look bad if the VC declines to participate in the next round. The trend of VC angel investing is so new that it's hard to say how justified this worry is. Another danger, pointed out by Mitch Kapor, is that if VCs are only doing angel deals to generate series A deal flow, then their incentives aren't aligned with the founders'. The founders want the valuation of the next round to be high, and the VCs want it to be low. Again, hard to say yet how much of a problem this will be. [5] Josh Kopelman pointed out that another way to be on fewer boards at once is to take board seats for shorter periods. [6] Google was in this respect as so many others the pattern for the future. It would be great for VCs if the similarity extended to returns. That's probably too much to hope for, but the returns may be somewhat higher, as I explain later. [7] Doing a rolling close doesn't mean the company is always raising money. That would be a distraction. The point of a rolling close is to make fundraising take less time, not more. With a classic fixed sized round, you don't get any money till all the investors agree, and that often creates a situation where they all sit waiting for the others to act. A rolling close usually prevents this. [8] There are two (non-exclusive) causes of hot deals: the quality of the company, and domino effects among investors. The former is obviously a better predictor of success. [9] Some of the randomness is concealed by the fact that investment is a self fulfilling prophecy. [10] The shift in power to founders is exaggerated now because it's a seller's market. On the next downtick it will seem like I overstated the case.
[12] 两次十分钟会谈间隔三周是为方便创始人购买低价机票,否则完全可以连续进行。
But on the next uptick after that, founders will seem more powerful than ever. [11] More generally, it will become less common for the same investor to invest in successive rounds, except when exercising an option to maintain their percentage. When the same investor invests in successive rounds, it often means the startup isn't getting market price. They may not care; they may prefer to work with an investor they already know; but as the investment market becomes more efficient, it will become increasingly easy to get market price if they want it. Which in turn means the investment community will tend to become more stratified. [12] The two 10 minuteses have 3 weeks between them so founders can get cheap plane tickets, but except for that they could be adjacent. [13] I'm not saying option pools themselves will go away. They're an administrative convenience. What will go away is investors requiring them. Thanks to Sam Altman, John Bautista, Trevor Blackwell, Paul Buchheit, Jeff Clavier, Patrick Collison, Ron Conway, Matt Cohler, Chris Dixon, Mitch Kapor, Josh Kopelman, Pete Koomen, Carolynn Levy, Jessica Livingston, Ariel Poler, Geoff Ralston, Naval Ravikant, Dan Siroker, Harj Taggar, and Fred Wilson for reading drafts of this..
[13] 期权池作为管理工具不会消失,但投资人强制要求期权池的做法终将消亡。
致谢 感谢萨姆·奥尔特曼、约翰·鲍蒂斯塔、特雷弗·布莱克韦尔、保罗·布赫海特、杰夫·克拉维尔、帕特里克·科里森、罗恩·康威、马特·科勒、克里斯·迪克森、米切尔·卡普尔、乔什·科佩尔曼、皮特·库门、卡罗琳·利维、杰西卡·利文斯顿、阿里尔·波勒、杰夫·拉尔斯顿、纳瓦尔·拉维肯特、丹·西罗克、哈吉·塔加和弗雷德·威尔逊审阅本文草稿。
July 2010 What hard liquor, cigarettes, heroin, and crack have in common is that they're all more concentrated forms of less addictive predecessors. Most if not all the things we describe as addictive are. And the scary thing is, the process that created them is accelerating. We wouldn't want to stop it. It's the same process that cures diseases: technological progress. Technological progress means making things do more of what we want. When the thing we want is something we want to want, we consider technological progress good. If some new technique makes solar cells x% more efficient, that seems strictly better. When progress concentrates something we don't want to want — when it transforms opium into heroin — it seems bad. But it's the same process at work. [1] No one doubts this process is accelerating, which means increasing numbers of things we like will be transformed into things we like too much. [2] As far as I know there's no word for something we like too much. The closest is the colloquial sense of "addictive." That usage has become increasingly common during my lifetime. And it's clear why: there are an increasing number of things we need it for. At the extreme end of the spectrum are crack and meth. Food has been transformed by a combination of factory farming and innovations in food processing into something with way more immediate bang for the buck, and you can see the results in any town in America. Checkers and solitaire have been replaced by World of Warcraft and FarmVille. TV has become much more engaging, and even so it can't compete with Facebook. The world is more addictive than it was 40 years ago. And unless the forms of technological progress that produced these things are subject to different laws than technological progress in general, the world will get more addictive in the next 40 years than it did in the last 40. The next 40 years will bring us some wonderful things.
保罗·格雷厄姆《成瘾性加速》第一部分(共两部分)
烈酒、香烟、海洛因和可卡因的共同点在于,它们都是低成瘾性前身物质的浓缩形态。几乎所有被我们称为"成瘾性"的事物皆如此。可怕的是,催生它们的技术进程正在加速。
我们无法阻止这一进程。这与治愈疾病的力量同源:技术进步。技术进步意味着让事物更高效地满足我们的需求。当这种需求是我们认可的需求时,我们认为技术进步是良性的。若某项新技术使太阳能电池效率提升x%,这显然是好事。但当进步强化的是我们不愿沉迷的需求——比如将鸦片提纯为海洛因——就变成了坏事。然而两者本质是同一进程的产物。[1]
技术进步正在加速已是不争的事实,这意味着越来越多我们喜爱的事物将异化为过度沉迷的对象。[2]
据我所知,英语中尚无专门词汇描述"过度喜爱的事物"。最接近的是口语化的"addictive(成瘾性)"。这个用法在我有生之年日益普及,原因显而易见:需要用它指代的事物正越来越多。光谱的极端是可卡因和冰毒。工业化养殖与食品加工创新联手改造了食物,使其单位成本带来的即时快感大幅提升,美国任何城镇都能看到其后果。跳棋和纸牌接龙已被《魔兽世界》和《开心农场》取代。电视节目变得更具吸引力,却仍难与Facebook抗衡。
I don't mean to imply they're all to be avoided. Alcohol is a dangerous drug, but I'd rather live in a world with wine than one without. Most people can coexist with alcohol; but you have to be careful. More things we like will mean more things we have to be careful about. Most people won't, unfortunately. Which means that as the world becomes more addictive, the two senses in which one can live a normal life will be driven ever further apart. One sense of "normal" is statistically normal: what everyone else does. The other is the sense we mean when we talk about the normal operating range of a piece of machinery: what works best. These two senses are already quite far apart. Already someone trying to live well would seem eccentrically abstemious in most of the US. That phenomenon is only going to become more pronounced. You can probably take it as a rule of thumb from now on that if people don't think you're weird, you're living badly. Societies eventually develop antibodies to addictive new things. I've seen that happen with cigarettes. When cigarettes first appeared, they spread the way an infectious disease spreads through a previously isolated population. Smoking rapidly became a (statistically) normal thing. There were ashtrays everywhere. We had ashtrays in our house when I was a kid, even though neither of my parents smoked. You had to for guests. As knowledge spread about the dangers of smoking, customs changed. In the last 20 years, smoking has been transformed from something that seemed totally normal into a rather seedy habit: from something movie stars did in publicity shots to something small huddles of addicts do outside the doors of office buildings. A lot of the change was due to legislation, of course, but the legislation couldn't have happened if customs hadn't already changed. It took a while though—on the order of 100 years.
相比40年前,这个世界更具成瘾性。除非催生成瘾物的技术进步遵循特殊规律,否则未来40年的成瘾性增速将超越过去40年。
未来40年将带来诸多美妙事物,我并非暗示所有都该回避。酒精是危险药物,但我宁愿生活在有葡萄酒的世界。多数人能与之共处,但需保持警惕。我们喜爱的事物越多,需要警惕的对象就越多。
遗憾的是多数人做不到。这意味着随着世界成瘾性增强,"正常生活"的两种定义将越发割裂:统计学意义上的正常(多数人的行为模式),与机械学意义上的正常(最佳运作状态)。
这两种标准已相距甚远。在美国大部分地区,追求健康生活者已被视为古怪的苦行者。这种现象只会愈发显著。不妨将此作为经验法则:若无人觉得你怪异,说明你活得很糟糕。
社会最终会对成瘾性新事物产生抗体。香烟的演变就是例证。当香烟首次出现时,其传播犹如传染病席卷与世隔绝的部落。吸烟迅速成为(统计学上的)常态。烟灰缸无处不在——我幼时家中虽无人吸烟,仍备有烟灰缸招待客人。
随着吸烟危害的认知普及,习俗开始改变。过去20年里,吸烟从全民行为沦为边缘嗜好:从电影明星的宣传照标配,变为写字楼门外瘾君子的扎堆活动。立法固然推动改变,但若习俗未先转变,立法亦无从谈起。
And unless the rate at which social antibodies evolve can increase to match the accelerating rate at which technological progress throws off new addictions, we'll be increasingly unable to rely on customs to protect us. [3] Unless we want to be canaries in the coal mine of each new addiction—the people whose sad example becomes a lesson to future generations—we'll have to figure out for ourselves what to avoid and how. It will actually become a reasonable strategy (or a more reasonable strategy) to suspect everything new. In fact, even that won't be enough. We'll have to worry not just about new things, but also about existing things becoming more addictive. That's what bit me. I've avoided most addictions, but the Internet got me because it became addictive while I was using it. [4] Most people I know have problems with Internet addiction. We're all trying to figure out our own customs for getting free of it. That's why I don't have an iPhone, for example; the last thing I want is for the Internet to follow me out into the world. [5] My latest trick is taking long hikes. I used to think running was a better form of exercise than hiking because it took less time. Now the slowness of hiking seems an advantage, because the longer I spend on the trail, the longer I have to think without interruption. Sounds pretty eccentric, doesn't it? It always will when you're trying to solve problems where there are no customs yet to guide you. Maybe I can't plead Occam's razor; maybe I'm simply eccentric. But if I'm right about the acceleration of addictiveness, then this kind of lonely squirming to avoid it will increasingly be the fate of anyone who wants to get things done. We'll increasingly be defined by what we say no to. Notes [1] Could you restrict technological progress to areas where you wanted it? Only in a limited way, without becoming a police state.
这个过程耗时约百年。除非社会抗体的进化速度能匹配技术进步催生成瘾物的加速趋势,否则习俗的保护作用将日益式微。[3] 若不甘愿成为每种新成瘾物的"矿井金丝雀"(用悲惨遭遇警示后人),我们必须自行判断规避对象及方法。怀疑一切新生事物终将成为合理策略(或更趋合理)。
事实上这仍不足够。我们不仅需警惕新事物,还要防范旧事物增强的成瘾性。这正是我的切肤之痛——我避开了多数成瘾物,却栽在互联网手上,因其在我使用过程中逐渐变得令人沉迷。[4]
我认识的大多数人都受困于网瘾。我们都在摸索自我解救之道。例如我不用iPhone,就是不想让互联网如影随形。[5] 最近我开始长途徒步——曾以为跑步优于徒步因其省时,如今徒步的缓慢反成优势:行进时间越长,无干扰思考的时间就越久。
听起来很古怪吧?当缺乏既定习俗指引时,解决方案总会显得怪异。或许我不该搬出奥卡姆剃刀原则——可能我就是个怪人。但若我对成瘾性加速的判断正确,那么这种孤独的挣扎将成为所有实干者的宿命。拒绝什么,将日益定义我们是谁。
注释: [1] 技术进步能否定向限制?除非建立警察国家,否则收效有限。即便如此也会产生副作用。"良性"与"恶性"技术进步界限模糊,抑制后者必会拖累前者。何况禁酒令和"毒品战争"已证明,禁令往往弊大于利。
And even then your restrictions would have undesirable side effects. "Good" and "bad" technological progress aren't sharply differentiated, so you'd find you couldn't slow the latter without also slowing the former. And in any case, as Prohibition and the "war on drugs" show, bans often do more harm than good. [2] Technology has always been accelerating. By Paleolithic standards, technology evolved at a blistering pace in the Neolithic period. [3] Unless we mass produce social customs. I suspect the recent resurgence of evangelical Christianity in the US is partly a reaction to drugs. In desperation people reach for the sledgehammer; if their kids won't listen to them, maybe they'll listen to God. But that solution has broader consequences than just getting kids to say no to drugs. You end up saying no to science as well. I worry we may be heading for a future in which only a few people plot their own itinerary through no-land, while everyone else books a package tour. Or worse still, has one booked for them by the government. [4] People commonly use the word "procrastination" to describe what they do on the Internet. It seems to me too mild to describe what's happening as merely not-doing-work. We don't call it procrastination when someone gets drunk instead of working. [5] Several people have told me they like the iPad because it lets them bring the Internet into situations where a laptop would be too conspicuous. In other words, it's a hip flask. (This is true of the iPhone too, of course, but this advantage isn't as obvious because it reads as a phone, and everyone's used to those.) Thanks to Sam Altman, Patrick Collison, Jessica Livingston, and Robert Morris for reading drafts of this..
[2] 技术始终在加速。以旧石器时代标准衡量,新石器时代的技术发展已堪称迅猛。
[3] 除非能量产社会习俗。美国福音派基督教的复兴或许部分是对毒品的反应。当父母束手无策时,会祭出"上帝"这把重锤。但这种方法会让孩子连科学也一并拒绝。
我担忧未来可能只有少数人能自主规划人生路线,多数人只能参加旅行社套餐——更糟的是由政府代订套餐。
[4] 人们常用"拖延症"形容上网行为。这个词过于温和,仿佛只是消极怠工。没人会把借酒逃避称作"拖延症"。
[5] 多人表示青睐iPad因其能在笔记本电脑显眼的场合使用互联网。换言之,它是个时髦酒壶(iPhone亦然,只是手机属性掩盖了这点)。
致谢萨姆·奥尔特曼、帕特里克·科里森、杰西卡·利文斯顿和罗伯特·莫里斯审阅本文草稿。
July 2010 When we sold our startup in 1998 I suddenly got a lot of money. I now had to think about something I hadn't had to think about before: how not to lose it. I knew it was possible to go from rich to poor, just as it was possible to go from poor to rich. But while I'd spent a lot of the past several years studying the paths from poor to rich, I knew practically nothing about the paths from rich to poor. Now, in order to avoid them, I had to learn where they were. So I started to pay attention to how fortunes are lost. If you'd asked me as a kid how rich people became poor, I'd have said by spending all their money. That's how it happens in books and movies, because that's the colorful way to do it. But in fact the way most fortunes are lost is not through excessive expenditure, but through bad investments. It's hard to spend a fortune without noticing. Someone with ordinary tastes would find it hard to blow through more than a few tens of thousands of dollars without thinking "wow, I'm spending a lot of money." Whereas if you start trading derivatives, you can lose a million dollars (as much as you want, really) in the blink of an eye. In most people's minds, spending money on luxuries sets off alarms that making investments doesn't. Luxuries seem self-indulgent. And unless you got the money by inheriting it or winning a lottery, you've already been thoroughly trained that self-indulgence leads to trouble. Investing bypasses those alarms. You're not spending the money; you're just moving it from one asset to another. Which is why people trying to sell you expensive things say "it's an investment." The solution is to develop new alarms. This can be a tricky business, because while the alarms that prevent you from overspending are so basic that they may even be in our DNA, the ones that prevent you from making bad investments have to be learned, and are sometimes fairly counterintuitive.
1998年我们卖掉创业公司时,我突然获得了一大笔钱。那时我不得不开始思考一个从未考虑过的问题:如何避免失去它。我知道从富有到贫穷是有可能的,就像从贫穷到富有一样。但过去几年我花了大量时间研究从贫穷到富有的路径,却对从富有到贫穷的路径几乎一无所知。现在,为了避免重蹈覆辙,我必须弄清楚这些路径在哪里。
于是我开始关注财富是如何流失的。如果小时候有人问我富人如何变穷,我会说是因为花光了所有钱。书和电影里都是这么演的,因为这种过程更具戏剧性。但实际上,大多数财富的流失并非因为过度消费,而是因为糟糕的投资。
挥霍财富而不自知是很难的。一个有着普通消费习惯的人,花掉几万美元后就会意识到"哇,我花了好多钱"。而如果你开始交易金融衍生品,眨眼间就能损失一百万美元(实际上想亏多少都行)。
在大多数人心中,奢侈消费会触发警报,而投资则不会。奢侈看起来像是自我放纵。除非你的钱是继承或中彩票得来的,否则你早已被反复告诫自我放纵会招致麻烦。但投资绕过了这些警报。你不是在花钱,只是在将资产从一种形式转换为另一种形式。正因如此,推销昂贵商品的人总会说"这是项投资"。
A few days ago I realized something surprising: the situation with time is much the same as with money. The most dangerous way to lose time is not to spend it having fun, but to spend it doing fake work. When you spend time having fun, you know you're being self-indulgent. Alarms start to go off fairly quickly. If I woke up one morning and sat down on the sofa and watched TV all day, I'd feel like something was terribly wrong. Just thinking about it makes me wince. I'd start to feel uncomfortable after sitting on a sofa watching TV for 2 hours, let alone a whole day. And yet I've definitely had days when I might as well have sat in front of a TV all day — days at the end of which, if I asked myself what I got done that day, the answer would have been: basically, nothing. I feel bad after these days too, but nothing like as bad as I'd feel if I spent the whole day on the sofa watching TV. If I spent a whole day watching TV I'd feel like I was descending into perdition. But the same alarms don't go off on the days when I get nothing done, because I'm doing stuff that seems, superficially, like real work. Dealing with email, for example. You do it sitting at a desk. It's not fun. So it must be work. With time, as with money, avoiding pleasure is no longer enough to protect you. It probably was enough to protect hunter-gatherers, and perhaps all pre-industrial societies. So nature and nurture combine to make us avoid self-indulgence. But the world has gotten more complicated: the most dangerous traps now are new behaviors that bypass our alarms about self-indulgence by mimicking more virtuous types. And the worst thing is, they're not even fun. Thanks to Sam Altman, Trevor Blackwell, Patrick Collison, Jessica Livingston, and Robert Morris for reading drafts of this..
解决办法是建立新的警报机制。这很棘手,因为防止过度消费的警报根植于我们的本能,甚至可能刻在DNA里;而防止错误投资的警报必须后天习得,有时还相当反直觉。
几天前我意识到一个惊人的事实:时间与金钱的处境极为相似。最危险的浪费时间方式不是享乐,而是做伪工作。当你享乐时,你知道自己在放纵——警报很快就会响起。如果某天早晨我醒来后坐在沙发上看一整天电视,我会觉得大事不妙。光是想象这个场景就让我皱眉。看电视两小时后我就会感到不适,更不用说一整天了。
然而我确实经历过"不如看电视一整天"的日子——当我在一天结束时自问完成了什么,答案基本是:毫无建树。这些日子过后我也会感到糟糕,但远不如看电视一整天那么强烈。如果真看一整天电视,我会觉得自己正在堕落。但当我毫无产出时,同样的警报不会响起,因为我表面上在做看似正经的工作。比如处理邮件:你坐在办公桌前做着不愉快的事,所以这一定是工作。
和时间一样,仅仅规避享乐已不足以保护你的金钱。对狩猎采集者或前工业社会来说或许足够,因此先天与后天因素共同促使我们远离放纵。但世界变得更复杂了:最危险的陷阱是那些绕过放纵警报的新行为,它们伪装成更有价值的形式。最糟糕的是,它们甚至毫无乐趣可言。
感谢 Sam Altman、Trevor Blackwell、Patrick Collison、Jessica Livingston和Robert Morris阅读本文草稿。
Want to start a startup? Get funded by Y Combinator.
July 2010 I realized recently that what one thinks about in the shower in the morning is more important than I'd thought. I knew it was a good time to have ideas. Now I'd go further: now I'd say it's hard to do a really good job on anything you don't think about in the shower. Everyone who's worked on difficult problems is probably familiar with the phenomenon of working hard to figure something out, failing, and then suddenly seeing the answer a bit later while doing something else. There's a kind of thinking you do without trying to. I'm increasingly convinced this type of thinking is not merely helpful in solving hard problems, but necessary. The tricky part is, you can only control it indirectly. [1] I think most people have one top idea in their mind at any given time. That's the idea their thoughts will drift toward when they're allowed to drift freely. And this idea will thus tend to get all the benefit of that type of thinking, while others are starved of it. Which means it's a disaster to let the wrong idea become the top one in your mind. What made this clear to me was having an idea I didn't want as the top one in my mind for two long stretches. I'd noticed startups got way less done when they started raising money, but it was not till we ourselves raised money that I understood why. The problem is not the actual time it takes to meet with investors. The problem is that once you start raising money, raising money becomes the top idea in your mind. That becomes what you think about when you take a shower in the morning. And that means other questions aren't. I'd hated raising money when I was running Viaweb, but I'd forgotten why I hated it so much. When we raised money for Y Combinator, I remembered. Money matters are particularly likely to become the top idea in your mind. The reason is that they have to be.
想创立一家初创公司? 获得 Y Combinator 的资助。
2010年7月 我最近意识到,早晨淋浴时脑海中浮现的念头比我想象的更重要。我原本就知道这是灵感迸发的好时机。但现在我要更进一步:如今我会说,任何你淋浴时不曾思考的事情,都很难真正做好。 每个处理过难题的人可能都熟悉这种现象:拼命寻找答案却失败,而后在做其他事时突然灵光一现。这是一种无意识的思考方式。我越来越确信,这种思考方式不仅有助于解决难题,更是不可或缺的。关键在于,你只能间接控制它。[1] 我认为大多数人在任何时刻都有一个"首要念头"。这是思绪自由飘荡时最终会回归的主题。因此,这个念头能获得无意识思考的全部养分,而其他想法则被剥夺。这意味着让错误的念头占据首要位置将是场灾难。 让我认清这一点的是,曾有两次漫长时期,我不想要的念头盘踞在我的思维顶端。 我早就注意到初创公司在融资期间效率骤降,但直到我们自己融资时才明白原因。问题不在于面见投资人实际耗费的时间,而在于一旦启动融资,这件事就会成为你的首要念头。它会变成你清晨淋浴时思考的主题,这意味着其他问题被挤出了思考圈。 运营Viaweb时我曾厌恶融资,但已忘记为何如此反感。当为Y Combinator融资时,我想起来了。金钱问题特别容易成为思维的首要念头,因为它们必须如此。获取资金本就艰难,这不是能顺其自然达成的事。除非你让它成为淋浴时的思考主题,否则它不会实现——但这样你就无法在真正想推进的事务上取得进展。[2] (我听教授朋友们也发出过类似抱怨。如今的教授似乎成了专业筹款人,只是兼职做研究。或许该改变这种状况了。) 此事令我震撼,是因为此前十年间我大多能自由思考真正想做的事。因此当这种自由被剥夺时,对比格外鲜明。但这并非我独有的困境——几乎所有我见过的初创公司,都在启动融资或接触收购方时陷入停滞。 你无法直接控制思绪的飘向。能被控制的就不叫飘荡。但你可以通过选择所处环境来间接控制。这就是我学到的:谨慎选择那些对你至关重要的事物。尽量让自己处于最紧迫的问题恰好是你愿意思考的情境中。 当然你并非拥有绝对掌控。突发事件会挤占其他思绪。但排除紧急情况外,你对思维的首要念头拥有相当大的间接控制权。 我发现有两类念头尤其需要规避——它们就像尼罗河鲈鱼般会挤走更有趣的想法。其一是关于金钱的念头,前文已提及。获取资金本质上就会吞噬注意力。其二是争端纠纷。它们同样具有错误的吸引力:这类念头与真正有趣的想法有着相同的粘性特质,却缺乏实质内涵。因此若想完成真正的工作,请远离争端。[3] 即便牛顿也未能幸免。1672年发表色彩理论后,他发现自己被争论困扰数年,最终得出结论:唯一的解决之道就是停止发表。
It's hard to get money. It's not the sort of thing that happens by default. It's not going to happen unless you let it become the thing you think about in the shower. And then you'll make little progress on anything else you'd rather be working on. [2] (I hear similar complaints from friends who are professors. Professors nowadays seem to have become professional fundraisers who do a little research on the side. It may be time to fix that.) The reason this struck me so forcibly is that for most of the preceding 10 years I'd been able to think about what I wanted. So the contrast when I couldn't was sharp. But I don't think this problem is unique to me, because just about every startup I've seen grinds to a halt when they start raising money � or talking to acquirers. You can't directly control where your thoughts drift. If you're controlling them, they're not drifting. But you can control them indirectly, by controlling what situations you let yourself get into. That has been the lesson for me: be careful what you let become critical to you. Try to get yourself into situations where the most urgent problems are ones you want to think about. You don't have complete control, of course. An emergency could push other thoughts out of your head. But barring emergencies you have a good deal of indirect control over what becomes the top idea in your mind. I've found there are two types of thoughts especially worth avoiding � thoughts like the Nile Perch in the way they push out more interesting ideas. One I've already mentioned: thoughts about money. Getting money is almost by definition an attention sink. The other is disputes. These too are engaging in the wrong way: they have the same velcro-like shape as genuinely interesting ideas, but without the substance. So avoid disputes if you want to get real work done. [3] Even Newton fell into this trap.
我意识到自己已沦为哲学的奴隶,但若能摆脱林纳斯先生的事务纠缠,我将毅然决然地永远告别它——除非是为了个人消遣而研究,或留待身后发表的成果。因为我明白,一个人要么决心不发表任何新见解,要么就得沦为捍卫这些见解的奴隶。[4]
After publishing his theory of colors in 1672 he found himself distracted by disputes for years, finally concluding that the only solution was to stop publishing:.
林纳斯与其列日学派的学生们属于最为顽固的批评者之列。牛顿传记作者韦斯特福尔似乎认为牛顿反应过度:
> I see I have made myself a slave to Philosophy, but if I get free of Mr Linus's business I will resolutely bid adew to it eternally, excepting what I do for my privat satisfaction or leave to come out after me. For I see a man must either resolve to put out nothing new or become a slave to defend it. [4]
> 需知当时牛顿的"奴役"状态,不过是在一年间针对列日学派写了五篇回复,总计十四页印刷内容。
Linus and his students at Liege were among the more tenacious critics. Newton's biographer Westfall seems to feel he was overreacting:
我更能体谅牛顿的处境。问题不在于这十四页篇幅,而在于这场愚蠢的争论不断强行占据他思维的首要位置——这个渴望思考其他事物的大脑不得不反复处理这些纷扰。
> Recall that at the time he wrote, Newton's "slavery" consisted of five replies to Liege, totalling fourteen printed pages, over the course of a year.
选择宽恕实则蕴含利己之效。伤害你的人其实施加了双重伤害:先是伤害本身,继而占用你后续的时间反复思量。若学会无视伤害,至少能避免后者。我发现某种程度上可以通过自我告诫来避免纠结他人恶行:这事不配占据我的思维空间。每当发现自己已遗忘争执细节时,我总感到欣喜,这意味着我不曾为此耗费心神。妻子认为我比她更宽容,但我的动机纯粹出于自私。
I'm more sympathetic to Newton. The problem was not the 14 pages, but the pain of having this stupid controversy constantly reintroduced as the top idea in a mind that wanted so eagerly to think about other things. Turning the other cheek turns out to have selfish advantages. Someone who does you an injury hurts you twice: first by the injury itself, and second by taking up your time afterward thinking about it. If you learn to ignore injuries you can at least avoid the second half. I've found I can to some extent avoid thinking about nasty things people have done to me by telling myself: this doesn't deserve space in my head. I'm always delighted to find I've forgotten the details of disputes, because that means I hadn't been thinking about them. My wife thinks I'm more forgiving than she is, but my motives are purely selfish. I suspect a lot of people aren't sure what's the top idea in their mind at any given time. I'm often mistaken about it. I tend to think it's the idea I'd want to be the top one, rather than the one that is. But it's easy to figure this out: just take a shower. What topic do your thoughts keep returning to? If it's not what you want to be thinking about, you may want to change something. Notes [1] No doubt there are already names for this type of thinking, but I call it "ambient thought." [2] This was made particularly clear in our case, because neither of the funds we raised was difficult, and yet in both cases the process dragged on for months. Moving large amounts of money around is never something people treat casually.
我怀疑许多人对自身思维的首要议题缺乏清醒认知。我自己也常判断失误,倾向于将"希望思考之事"误认为"实际思考之事"。其实辨别方法很简单:冲澡时思绪总会飘向何处?若发现常驻心头的并非所愿,或许就该作出改变。
The attention required increases with the amount—maybe not linearly, but definitely monotonically. [3] Corollary: Avoid becoming an administrator, or your job will consist of dealing with money and disputes. [4] Letter to Oldenburg, quoted in Westfall, Richard, _Life of Isaac Newton_ , p. 107. Thanks to Sam Altman, Patrick Collison, Jessica Livingston, and Robert Morris for reading drafts of this..
注释 [1] 这类思维模式想必已有专业术语,我称之为"环境思维"。 [2] 我们的经历尤为明显:两次融资都不算艰难,却都耗时数月。大额资金流转从来不是能随意对待的事,所需关注度随金额递增——未必线性增长,但必然单调上升。 [3] 推论:避免成为管理者,否则工作将沦为处理资金与纠纷。 [4] 致奥尔登堡的信件,引自理查德·韦斯特福尔《艾萨克·牛顿传》第107页。
致谢 萨姆·奥尔特曼、帕特里克·科里森、杰西卡·利文斯顿和罗伯特·莫里斯审阅了本文草稿。
Want to start a startup? Get funded by Y Combinator.
April 2010 The best way to come up with startup ideas is to ask yourself the question: what do you wish someone would make for you? There are two types of startup ideas: those that grow organically out of your own life, and those that you decide, from afar, are going to be necessary to some class of users other than you. Apple was the first type. Apple happened because Steve Wozniak wanted a computer. Unlike most people who wanted computers, he could design one, so he did. And since lots of other people wanted the same thing, Apple was able to sell enough of them to get the company rolling. They still rely on this principle today, incidentally. The iPhone is the phone Steve Jobs wants. [1] Our own startup, Viaweb, was of the second type. We made software for building online stores. We didn't need this software ourselves. We weren't direct marketers. We didn't even know when we started that our users were called "direct marketers." But we were comparatively old when we started the company (I was 30 and Robert Morris was 29), so we'd seen enough to know users would need this type of software. [2] There is no sharp line between the two types of ideas, but the most successful startups seem to be closer to the Apple type than the Viaweb type. When he was writing that first Basic interpreter for the Altair, Bill Gates was writing something he would use, as were Larry and Sergey when they wrote the first versions of Google. Organic ideas are generally preferable to the made up kind, but particularly so when the founders are young. It takes experience to predict what other people will want. The worst ideas we see at Y Combinator are from young founders making things they think other people will want. So if you want to start a startup and don't know yet what you're going to do, I'd encourage you to focus initially on organic ideas.
What's missing or broken in your daily life? Sometimes if you just ask that question you'll get immediate answers. It must have seemed obviously broken to Bill Gates that you could only program the Altair in machine language. You may need to stand outside yourself a bit to see brokenness, because you tend to get used to it and take it for granted. You can be sure it's there, though. There are always great ideas sitting right under our noses. In 2004 it was ridiculous that Harvard undergrads were still using a Facebook printed on paper. Surely that sort of thing should have been online. There are ideas that obvious lying around now. The reason you're overlooking them is the same reason you'd have overlooked the idea of building Facebook in 2004: organic startup ideas usually don't seem like startup ideas at first. We know now that Facebook was very successful, but put yourself back in 2004. Putting undergraduates' profiles online wouldn't have seemed like much of a startup idea. And in fact, it wasn't initially a startup idea. When Mark spoke at a YC dinner this winter he said he wasn't trying to start a company when he wrote the first version of Facebook. It was just a project. So was the Apple I when Woz first started working on it. He didn't think he was starting a company. If these guys had thought they were starting companies, they might have been tempted to do something more "serious," and that would have been a mistake. So if you want to come up with organic startup ideas, I'd encourage you to focus more on the idea part and less on the startup part. Just fix things that seem broken, regardless of whether it seems like the problem is important enough to build a company on. If you keep pursuing such threads it would be hard not to end up making something of value to a lot of people, and when you do, surprise, you've got a company. [3] Don't be discouraged if what you produce initially is something other people dismiss as a toy.
In fact, that's a good sign. That's probably why everyone else has been overlooking the idea. The first microcomputers were dismissed as toys. And the first planes, and the first cars. At this point, when someone comes to us with something that users like but that we could envision forum trolls dismissing as a toy, it makes us especially likely to invest. While young founders are at a disadvantage when coming up with made-up ideas, they're the best source of organic ones, because they're at the forefront of technology. They use the latest stuff. They only just decided what to use, so why wouldn't they? And because they use the latest stuff, they're in a position to discover valuable types of fixable brokenness first. There's nothing more valuable than an unmet need that is just becoming fixable. If you find something broken that you can fix for a lot of people, you've found a gold mine. As with an actual gold mine, you still have to work hard to get the gold out of it. But at least you know where the seam is, and that's the hard part. Notes [1] This suggests a way to predict areas where Apple will be weak: things Steve Jobs doesn't use. E.g. I doubt he is much into gaming. [2] In retrospect, we should have _become_ direct marketers. If I were doing Viaweb again, I'd open our own online store. If we had, we'd have understood users a lot better. I'd encourage anyone starting a startup to become one of its users, however unnatural it seems. [3] Possible exception: It's hard to compete directly with open source software. You can build things for programmers, but there has to be some part you can charge for. Thanks to Sam Altman, Trevor Blackwell, and Jessica Livingston for reading drafts of this..
想创业吗? 获得 Y Combinator 的资金支持。
2010年4月 想出创业点子的最佳方式是问自己一个问题:你希望别人为你做什么? 创业点子分为两种:一种是从你自身生活中自然生长出来的,另一种是你从外部观察后认为某类用户(而非你自己)需要的。苹果属于第一种。苹果的诞生源于史蒂夫·沃兹尼亚克想要一台电脑。与大多数渴望电脑的人不同,他能自己设计,于是他就这么做了。由于许多人也有同样需求,苹果得以销售足够多的产品来推动公司运转。顺便说一句,他们至今仍遵循这一原则。iPhone就是史蒂夫·乔布斯想要的手机。[1] 我们自己的创业项目Viaweb属于第二种。我们开发了搭建在线商店的软件。我们自己并不需要这个软件——我们并非直销商,甚至在创业初期都不知道用户被称为"直销商"。但创业时我们年纪相对较大(我30岁,罗伯特·莫里斯29岁),已有足够阅历预见到用户会需要这类软件。[2] 这两类点子之间没有明确界限,但最成功的创业公司往往更接近苹果模式而非Viaweb模式。比尔·盖茨为Altair编写第一个Basic解释器时,他是在创造自己会使用的工具;拉里和谢尔盖开发谷歌最初版本时亦是如此。 自然生长的点子通常比凭空构想的更可取,对年轻创始人尤其如此。预测他人需求需要经验积累。我们在Y Combinator见过最糟糕的点子,往往来自年轻创业者试图打造他们认为别人会喜欢的东西。 因此,如果你打算创业却尚未确定方向,我建议你首先关注自然生长的点子。你的日常生活中缺少什么或存在哪些缺陷?有时只要提出这个问题,答案就会立即浮现。对比尔·盖茨而言,只能用机器语言为Altair编程显然是个亟待解决的问题。 你可能需要跳出自我才能发现这些缺陷,因为人往往会对习以为常的问题视而不见。但请相信问题确实存在——伟大创意总是近在眼前。2004年哈佛本科生还在使用纸质通讯录这件事就非常荒谬,那种东西早该上线了。 如今同样存在显而易见的创意。你忽视它们的原因,与2004年人们忽视创建Facebook的创意如出一辙:自然生长的创业点子最初往往不像"创业点子"。我们现在知道Facebook非常成功,但请回到2004年——把大学生资料搬上网看起来根本不像是创业点子。事实上,它最初确实不是。马克(扎克伯格)今年冬天在YC晚宴演讲时说,他编写Facebook第一版时并没打算创业,那只是个项目。沃兹最初研发Apple I时也是如此,他并未想过要开公司。如果这些人当时认为自己是在创业,可能会被诱惑去做更"严肃"的事情,那将是个错误。 因此,若要发掘自然生长的创业点子,我建议你多关注"点子"本身,少纠结"创业"属性。只需修复那些看似破损的东西,别在意这个问题是否重要到足以支撑一家公司。只要持续追踪这类线索,你终将创造出对许多人有价值的东西,而那时——惊喜地——你已经拥有了一家公司。[3] 如果最初做出的产品被人贬为"玩具",别气馁。这反而是好迹象,可能正是这个原因让其他人都忽视了这个点子。第一批微型计算机曾被视作玩具,最早的飞机、汽车也是如此。如今,当有人带着用户喜爱但可能被论坛喷子嘲笑为"玩具"的产品来找我们时,我们反而更可能投资。 年轻创始人在构思凭空设想的点子时处于劣势,但却是自然生长点子的最佳来源,因为他们站在技术前沿。他们使用最新工具(毕竟刚做出选择),正因如此,他们能率先发现那些可修复的价值洼地。 没有什么比"刚刚可被满足的未满足需求"更有价值。如果你发现某个广泛存在的可解决问题,就等于找到了金矿。就像真实金矿一样,你仍需努力开采,但至少已知矿脉所在——而这本是最困难的部分。 注释 [1] 这暗示了预测苹果弱项的方法:史蒂夫·乔布斯不使用的领域。例如我猜他对游戏兴趣不大。 [2] 事后看来,我们本应成为直销商。如果重做Viaweb,我会先开自己的网店。这样我们能更深入理解用户。我建议每位创业者都成为自己产品的用户,无论这看起来多么不自然。 [3] 例外情况:直接与开源软件竞争很困难。你可以为程序员开发工具,但必须保留可收费的部分。 致谢 感谢萨姆·奥尔特曼、特雷弗·布莱克韦尔和杰西卡·利文斯顿阅读本文草稿。
Want to start a startup? Get funded by Y Combinator.
November 2009 I don't think Apple realizes how badly the App Store approval process is broken. Or rather, I don't think they realize how much it matters that it's broken. The way Apple runs the App Store has harmed their reputation with programmers more than anything else they've ever done. Their reputation with programmers used to be great. It used to be the most common complaint you heard about Apple was that their fans admired them too uncritically. The App Store has changed that. Now a lot of programmers have started to see Apple as evil. How much of the goodwill Apple once had with programmers have they lost over the App Store? A third? Half? And that's just so far. The App Store is an ongoing karma leak.
How did Apple get into this mess? Their fundamental problem is that they don't understand software. They treat iPhone apps the way they treat the music they sell through iTunes. Apple is the channel; they own the user; if you want to reach users, you do it on their terms. The record labels agreed, reluctantly. But this model doesn't work for software. It doesn't work for an intermediary to own the user. The software business learned that in the early 1980s, when companies like VisiCorp showed that although the words "software" and "publisher" fit together, the underlying concepts don't. Software isn't like music or books. It's too complicated for a third party to act as an intermediary between developer and user. And yet that's what Apple is trying to be with the App Store: a software publisher. And a particularly overreaching one at that, with fussy tastes and a rigidly enforced house style. If software publishing didn't work in 1980, it works even less now that software development has evolved from a small number of big releases to a constant stream of small ones. But Apple doesn't understand that either.
想创业吗? 获得Y Combinator的资助。
2009年11月 我不认为苹果意识到App Store的审核流程已经糟糕到什么程度。更准确地说,他们没意识到这种糟糕状况的严重性。 苹果运营App Store的方式对程序员声誉的损害,超过了他们以往任何行为。过去,苹果在程序员心中的声誉极佳。那时最常见的抱怨不过是果粉对苹果的崇拜过于盲目。而App Store改变了这一切。如今许多程序员开始将苹果视为邪恶的代名词。 苹果因App Store失去了多少曾经在程序员群体中的好感?三分之一?一半?而这还只是开始。App Store正在持续消耗他们的信誉资本。
苹果为何陷入如此困境?根本问题在于他们不懂软件。 他们对待iPhone应用的方式,就像对待通过iTunes销售的音乐。苹果是渠道;他们拥有用户;如果你想触达用户,就必须遵守他们的规则。唱片公司勉强接受了这种模式。但这一套在软件领域行不通。让中间商掌控用户是行不通的。早在1980年代初期,软件行业就通过VisiCorp等公司的教训明白了这点——虽然"软件"和"出版商"这两个词能搭配,但底层逻辑根本不相容。软件不像音乐或图书。它过于复杂,第三方无法胜任开发者和用户之间的中介角色。然而苹果试图通过App Store成为的,正是这样一个软件出版商——而且还是品味刁钻、强制推行统一风格、尤其越界的出版商。 如果说软件出版在1980年行不通,那么在软件开发已从少量大版本演进为持续小版本更新的今天,就更行不通了。但苹果连这点也不明白。他们的产品开发模式源自硬件思维:反复打磨直至认为完美才发布。硬件必须如此,但软件因易于修改,其设计本可通过迭代持续优化。如今应用程序开发的标准方式是快速发布、持续迭代。这意味着每次版本更新若遭遇漫长且随机的审核延迟,后果将是灾难性的。 苹果的态度显然是:开发者在向App Store提交新版本时应该更加谨慎。他们当然会这么说。但即便强大如苹果,也不可能逆转技术演进的潮流。程序员采用快速迭代并非因为懒惰,而是因为这能产出最佳成果。苹果阻碍这一进程,实则是强迫开发者做出劣质作品——这种痛苦程序员体会得和苹果一样深刻。 假如苹果在OS X中发现严重漏洞时,不是立即发布更新,而是必须将代码提交给某个中间商——对方拖延一个月后以"图标不符合审美"为由拒绝通过,他们会作何感想? 这种破坏软件开发规律的做法,让苹果得到了与其初衷完全相反的结果:App Store里可下载的应用版本往往是陈旧且漏洞百出的。一位开发者告诉我:
由于他们的审核流程,App Store充斥着大量半成品应用。我几乎每天都会发布新版本给测试用户,而应用商店里的版本显得陈旧又糟糕。我敢肯定许多开发者都有同感:一方面觉得"对App Store上架的版本并不自豪",另一方面又认为"这其实是苹果的过错"。
Their model of product development derives from hardware. They work on something till they think it's finished, then they release it. You have to do that with hardware, but because software is so easy to change, its design can benefit from evolution. The standard way to develop applications now is to launch fast and iterate. Which means it's a disaster to have long, random delays each time you release a new version. Apparently Apple's attitude is that developers should be more careful when they submit a new version to the App Store. They would say that. But powerful as they are, they're not powerful enough to turn back the evolution of technology. Programmers don't use launch-fast-and-iterate out of laziness. They use it because it yields the best results. By obstructing that process, Apple is making them do bad work, and programmers hate that as much as Apple would. How would Apple like it if when they discovered a serious bug in OS X, instead of releasing a software update immediately, they had to submit their code to an intermediary who sat on it for a month and then rejected it because it contained an icon they didn't like? By breaking software development, Apple gets the opposite of what they intended: the version of an app currently available in the App Store tends to be an old and buggy one. One developer told me:.
我相信苹果认为他们的审核流程能通过质量把关来保护用户。但现实中像我们这样的漏洞总能通过审核,而修复这些漏洞的更新却需要4-8周才能获批,这让用户觉得iPhone应用有时就是会出问题。更糟的是,这些应用在其他采用即时审核机制的平台上运行完全正常。
事实上,我认为苹果还存在第三个误解:他们认为关于App Store审核的所有抱怨都不是什么严重问题。他们肯定听到了开发者的不满。但合作伙伴和供应商总是会抱怨。如果他们不抱怨反而糟糕,那意味着你对他们太纵容了。与此同时,iPhone的销量比以往任何时候都好。既然如此,他们何必改变现状?
> As a result of their process, the App Store is full of half-baked applications. I make a new version almost every day that I release to beta users. The version on the App Store feels old and crappy. I'm sure that a lot of developers feel this way: One emotion is "I'm not really proud about what's in the App Store", and it's combined with the emotion "Really, it's Apple's fault."
短期内,苹果之所以能如此苛待开发者却安然无恙,是因为他们制造的硬件实在太出色。几天前我刚买了一台27英寸的新款iMac。它令人惊叹。屏幕反光严重,硬盘噪音大得出奇,但它的设计美得让你根本不忍心挑剔。
于是我买下了它——但这是第一次,我带着顾虑购买苹果产品。那种感觉就像在人权记录糟糕的国家购物。这感觉前所未有。过去购买苹果产品时,那种喜悦是纯粹的。"太棒了!他们的产品无可挑剔。"而这次却像一场浮士德式的交易。"他们制造完美的产品,但行事却如此专横。我真的要继续支持这家公司吗?"
苹果需要在乎我这类人的想法吗?得罪一小部分用户又有什么关系?
Another wrote:
他们确实应该重视,原因有二。首先,这些用户正是他们想招募的员工人选。如果公司显得邪恶,最优秀的程序员就不会为你工作。微软从90年代开始就深受其害。程序员开始羞于为微软工作,那就像一种妥协。当微软员工与其他程序员交谈时,提到自己的雇主总会自嘲说"加入了黑暗阵营"。但微软真正的问题不在于现有员工的尴尬,而在于他们永远无法招揽的人才。知道这些人才去了哪里吗?谷歌和苹果。如果微软是帝国,它们就是反抗军同盟。正是由于获得了更多顶尖人才,谷歌和苹果如今才能远超微软。
为什么程序员对雇主的道德如此挑剔?部分原因是他们有选择的资本。顶尖程序员可以随心所欲选择雇主,不必为心存疑虑的公司效力。
> I believe that they think their approval process helps users by ensuring quality. In reality, bugs like ours get through all the time and then it can take 4-8 weeks to get that bug fix approved, leaving users to think that iPhone apps sometimes just don't work. Worse for Apple, these apps work just fine on other platforms that have immediate approval processes.
但我想,另一个原因是邪恶滋生愚蠢。依靠强权取胜的组织,会逐渐丧失通过卓越工作获胜的能力。对于聪明人而言,在最佳创意无法胜出的环境工作毫无乐趣。我认为谷歌之所以热切拥抱"不作恶"信条,与其说是为了对外示好,不如说是为了防止傲慢自大。[1]
这一原则至今仍在谷歌奏效。虽然官僚主义有所滋长,但他们似乎仍坚守着创立之初的理念。苹果的情况则不太乐观。如今再看那则著名的1984广告,人们更容易将苹果代入屏幕上的独裁者形象,而非挥锤的女性。[2] 事实上,细读独裁者的演说词,你会惊觉它简直像是对App Store的预言。
我们战胜了无原则的事实传播。
Actually I suppose Apple has a third misconception: that all the complaints about App Store approvals are not a serious problem. They must hear developers complaining. But partners and suppliers are always complaining. It would be a bad sign if they weren't; it would mean you were being too easy on them. Meanwhile the iPhone is selling better than ever. So why do they need to fix anything? They get away with maltreating developers, in the short term, because they make such great hardware. I just bought a new 27" iMac a couple days ago. It's fabulous. The screen's too shiny, and the disk is surprisingly loud, but it's so beautiful that you can't make yourself care. So I bought it, but I bought it, for the first time, with misgivings. I felt the way I'd feel buying something made in a country with a bad human rights record. That was new. In the past when I bought things from Apple it was an unalloyed pleasure. Oh boy! They make such great stuff. This time it felt like a Faustian bargain. They make such great stuff, but they're such assholes. Do I really want to support this company?
Should Apple care what people like me think? What difference does it make if they alienate a small minority of their users? There are a couple reasons they should care. One is that these users are the people they want as employees. If your company seems evil, the best programmers won't work for you. That hurt Microsoft a lot starting in the 90s. Programmers started to feel sheepish about working there. It seemed like selling out. When people from Microsoft were talking to other programmers and they mentioned where they worked, there were a lot of self-deprecating jokes about having gone over to the dark side. But the real problem for Microsoft wasn't the embarrassment of the people they hired. It was the people they never got. And you know who got them? Google and Apple. If Microsoft was the Empire, they were the Rebel Alliance.
我们有史以来第一次创造了一个纯粹意识形态的花园,在这里,每个工人都能免受矛盾与混乱真相这些害虫的侵扰,安然绽放。
苹果公司应该在意程序员对其看法的另一个原因是,当你销售一个平台时,开发者决定了你的成败。如果有人应该明白这一点,那一定是苹果。VisiCalc成就了Apple II。
And it's largely because they got more of the best people that Google and Apple are doing so much better than Microsoft today. Why are programmers so fussy about their employers' morals? Partly because they can afford to be. The best programmers can work wherever they want. They don't have to work for a company they have qualms about. But the other reason programmers are fussy, I think, is that evil begets stupidity. An organization that wins by exercising power starts to lose the ability to win by doing better work. And it's not fun for a smart person to work in a place where the best ideas aren't the ones that win. I think the reason Google embraced "Don't be evil" so eagerly was not so much to impress the outside world as to inoculate themselves against arrogance. [1] That has worked for Google so far. They've become more bureaucratic, but otherwise they seem to have held true to their original principles. With Apple that seems less the case. When you look at the famous 1984 ad now, it's easier to imagine Apple as the dictator on the screen than the woman with the hammer. [2] In fact, if you read the dictator's speech it sounds uncannily like a prophecy of the App Store..
程序员会为他们使用的平台开发应用。大多数应用——很可能大多数初创公司——都源于个人项目。苹果公司本身也是如此。苹果制造微型计算机,因为这就是史蒂夫·沃兹尼亚克自己想要的东西。他当时买不起小型计算机。[3] 微软同样起步于为小型微型计算机开发解释器,因为比尔·盖茨和保罗·艾伦对使用它们感兴趣。很少有初创公司不开发创始人自己会用的东西。
iPhone应用如此之多的主要原因是,太多程序员拥有iPhone。他们可能从文章中读到,黑莓拥有这样或那样的市场份额。但在实践中,RIM仿佛不存在。如果他们打算开发点什么,他们希望自己能使用它,这意味着开发一个iPhone应用。
> We have triumphed over the unprincipled dissemination of facts. > > We have created, for the first time in all history, a garden of pure ideology, where each worker may bloom secure from the pests of contradictory and confusing truths.
因此,程序员继续开发iPhone应用,尽管苹果继续虐待他们。他们就像陷入虐待关系中的人。他们对iPhone如此着迷,以至于无法离开。但他们正在寻找出路。有人写道:
> 虽然我确实喜欢为iPhone开发,但他们对App Store的控制让我无法按照自己的意愿开发应用。事实上,除非绝对必要,我不打算再开发任何iPhone应用了。[4]
有什么能打破这一循环吗?迄今为止我尚未见到任何设备能做到。Palm和RIM毫无希望,唯一可信的竞争者是Android。但Android是个孤儿——谷歌并不真正在意它,远不如苹果重视iPhone的程度。苹果对iPhone的重视,就如同谷歌对搜索的重视。
The other reason Apple should care what programmers think of them is that when you sell a platform, developers make or break you. If anyone should know this, Apple should. VisiCalc made the Apple II. And programmers build applications for the platforms they use. Most applications—most startups, probably—grow out of personal projects. Apple itself did. Apple made microcomputers because that's what Steve Wozniak wanted for himself. He couldn't have afforded a minicomputer. [3] Microsoft likewise started out making interpreters for little microcomputers because Bill Gates and Paul Allen were interested in using them. It's a rare startup that doesn't build something the founders use. The main reason there are so many iPhone apps is that so many programmers have iPhones. They may know, because they read it in an article, that Blackberry has such and such market share. But in practice it's as if RIM didn't exist. If they're going to build something, they want to be able to use it themselves, and that means building an iPhone app. So programmers continue to develop iPhone apps, even though Apple continues to maltreat them. They're like someone stuck in an abusive relationship. They're so attracted to the iPhone that they can't leave. But they're looking for a way out. One wrote:
手持设备的未来会被苹果牢牢掌控吗?这是个令人忧心的前景。若重现1990年代那种令人窒息的单一生态,将糟糕透顶。1995年时,为终端用户开发软件几乎等同于开发Windows应用。正是对这种前景的恐惧,促使我们开始构建网络应用。
至少我们现在知道如何打破苹果的垄断:必须让程序员们放下iPhone。如果程序员使用其他设备进行移动网络访问,他们就会转而开发适配该设备的应用。
> While I did enjoy developing for the iPhone, the control they place on the App Store does not give me the drive to develop applications as I would like. In fact I don't intend to make any more iPhone applications unless absolutely necessary. [4]
如何打造一款比iPhone更受程序员青睐的设备?想在设计上超越几无可能,苹果没给对手留任何空间。因此这款替代设备不可能靠大众吸引力取胜,必须凭借对程序员的特殊吸引力。
吸引程序员的方法之一是软件。如果能构想出程序员必备、却在iPhone封闭世界中无法实现的应用,或许就能促使他们转投新平台。
当程序员开始将手持设备作为开发机使用时——就像笔记本电脑取代台式机那样——这种转变必然发生。开发机所需的控制权限远超过苹果对iPhone的限制。
Can anything break this cycle? No device I've seen so far could. Palm and RIM haven't a hope. The only credible contender is Android. But Android is an orphan; Google doesn't really care about it, not the way Apple cares about the iPhone. Apple cares about the iPhone the way Google cares about search.
Is the future of handheld devices one locked down by Apple? It's a worrying prospect. It would be a bummer to have another grim monoculture like we had in the 1990s. In 1995, writing software for end users was effectively identical with writing Windows applications. Our horror at that prospect was the single biggest thing that drove us to start building web apps. At least we know now what it would take to break Apple's lock. You'd have to get iPhones out of programmers' hands. If programmers used some other device for mobile web access, they'd start to develop apps for that instead. How could you make a device programmers liked better than the iPhone? It's unlikely you could make something better designed. Apple leaves no room there. So this alternative device probably couldn't win on general appeal. It would have to win by virtue of some appeal it had to programmers specifically. One way to appeal to programmers is with software. If you could think of an application programmers had to have, but that would be impossible in the circumscribed world of the iPhone, you could presumably get them to switch. That would definitely happen if programmers started to use handhelds as development machines—if handhelds displaced laptops the way laptops displaced desktops. You need more control of a development machine than Apple will let you have over an iPhone. Could anyone make a device that you'd carry around in your pocket like a phone, and yet would also work as a development machine? It's hard to imagine what it would look like. But I've learned never to say never about technology.
真有人能造出口袋大小、堪比手机便携,又能充当开发机的设备吗?其形态难以想象。但在科技领域,我从不说"绝无可能"。以当今标准看,能作为开发机的手机设备,并不比1995年时人们眼中的iPhone更神奇。
我目前的开发机是MacBook Air,办公室搭配外接显示器键盘使用,出差时单独携带。若有半尺寸版本我会更青睐。虽然仍不及手机随身便携,但差距已缩小至四倍左右。这个鸿沟定能跨越。事实上,让我们将其列为征召项目:寻铁娘子执锤破局。
A phone-sized device that would work as a development machine is no more miraculous by present standards than the iPhone itself would have seemed by the standards of 1995. My current development machine is a MacBook Air, which I use with an external monitor and keyboard in my office, and by itself when traveling. If there was a version half the size I'd prefer it. That still wouldn't be small enough to carry around everywhere like a phone, but we're within a factor of 4 or so. Surely that gap is bridgeable. In fact, let's make it an RFS. Wanted: Woman with hammer. Notes [1] When Google adopted "Don't be evil," they were still so small that no one would have expected them to be, yet. [2] The dictator in the 1984 ad isn't Microsoft, incidentally; it's IBM. IBM seemed a lot more frightening in those days, but they were friendlier to developers than Apple is now. [3] He couldn't even afford a _monitor_. That's why the Apple I used a TV as a monitor. [4] Several people I talked to mentioned how much they liked the iPhone SDK. The problem is not Apple's products but their policies. Fortunately policies are software; Apple can change them instantly if they want to. Handy that, isn't it? Thanks to Sam Altman, Trevor Blackwell, Ross Boucher, James Bracy, Gabor Cselle, Patrick Collison, Jason Freedman, John Gruber, Joe Hewitt, Jessica Livingston, Robert Morris, Teng Siong Ong, Nikhil Pandit, Savraj Singh, and Jared Tame for reading drafts of this.
注释 [1] 谷歌提出"不作恶"时规模尚小,无人预料其日后地位。 [2] 1984广告中的独裁者并非微软,实为IBM。当年IBM更令人畏惧,但对开发者比如今苹果友善。 [3] 沃兹甚至买不起显示器,因此Apple I用电视机当显示器。 [4] 多位受访者盛赞iPhone SDK。问题不在苹果产品,而在其政策——所幸政策如同软件,苹果可随时更改。
致谢 Sam Altman等诸位审阅草稿。
Want to start a startup? Get funded by Y Combinator.
October 2009 _(This essay is derived from a talk at the 2009 Startup School.)_ I wasn't sure what to talk about at Startup School, so I decided to ask the founders of the startups we'd funded. What hadn't I written about yet? I'm in the unusual position of being able to test the essays I write about startups. I hope the ones on other topics are right, but I have no way to test them. The ones on startups get tested by about 70 people every 6 months. So I sent all the founders an email asking what surprised them about starting a startup. This amounts to asking what I got wrong, because if I'd explained things well enough, nothing should have surprised them. I'm proud to report I got one response saying:
想创办一家初创公司? 获得 Y Combinator 的资金支持。
2009年10月 _(本文源自2009年创业学校的一次演讲。)_ 在创业学校演讲前,我不确定该讲什么,于是决定向我们资助过的初创公司创始人们征求意见。还有什么是我没写过的? 我处于一个独特的位置,能够验证我写的关于初创公司的文章。我希望其他主题的文章也是正确的,但我无法验证。而关于初创公司的文章每6个月就会被大约70人验证。 于是我给所有创始人发了一封邮件,询问他们在创业过程中遇到的意外之事。这相当于在问我哪里写错了,因为如果我解释得足够清楚,他们本不该感到意外。 我很自豪地收到一条回复说:
> What surprised me the most is that everything was actually fairly predictable!
> 最让我意外的是,一切其实都相当可预测!
The bad news is that I got over 100 other responses listing the surprises they encountered. There were very clear patterns in the responses; it was remarkable how often several people had been surprised by exactly the same thing. These were the biggest: 1\. Be Careful with Cofounders This was the surprise mentioned by the most founders. There were two types of responses: that you have to be careful who you pick as a cofounder, and that you have to work hard to maintain your relationship. What people wished they'd paid more attention to when choosing cofounders was character and commitment, not ability. This was particularly true with startups that failed. The lesson: don't pick cofounders who will flake. Here's a typical reponse:
但坏消息是,我收到了100多条其他回复,列出了他们遇到的意外。 回复中有非常清晰的模式;令人惊讶的是,许多人被完全相同的事情所震惊。以下是最大的几点: 1\. 谨慎选择联合创始人 这是最多创始人提到的意外。有两类回复:一是选择联合创始人时必须谨慎,二是必须努力维护彼此的关系。 人们在选择联合创始人时,希望自己当初更关注的是品格和承诺,而非能力。这一点在失败的初创公司中尤为明显。教训是:不要选择会临阵退缩的联合创始人。 一个典型的回复是:
> 除非你与某人一起创业,否则你无法看清他们的真面目。
> You haven't seen someone's true colors unless you've worked with them on a startup.
品格之所以如此重要,是因为它在创业过程中受到的考验比大多数其他情况都更严峻。一位创始人明确表示,创始人之间的关系比能力更重要:
The reason character is so important is that it's tested more severely than in most other situations. One founder said explicitly that the relationship between founders was more important than ability:
> 我宁愿与朋友共同创业,也不愿与产出更高的陌生人合作。创业如此艰难且充满情绪波动,友谊带来的纽带和情感社会支持,远胜过损失的额外产出。
我们很久以前就明白了这一点。如果你查看YC的申请表,会发现关于创始人承诺和关系的问题比关于能力的问题更多。 成功的初创公司创始人较少谈论如何选择联合创始人,更多谈到他们如何努力维护彼此的关系。
> I would rather cofound a startup with a friend than a stranger with higher output. Startups are so hard and emotional that the bonds and emotional and social support that come with friendship outweigh the extra output lost.
> 让我意外的一点是,初创公司创始人的关系会从友谊转变为婚姻。我与联合创始人的关系从仅仅是朋友变成了整天见面,为财务发愁,还要收拾烂摊子。而这家初创公司就是我们的孩子。我曾这样总结:“就像我们结婚了,但没有性生活。”
We learned this lesson a long time ago. If you look at the YC application, there are more questions about the commitment and relationship of the founders than their ability. Founders of successful startups talked less about choosing cofounders and more about how hard they worked to maintain their relationship.
多人用了"婚姻"这个词来形容。这种关系远比普通同事间的关系更为紧密——部分原因是压力要大得多,部分原因是创始人在初期就是整个公司。因此这种关系必须用最优质的材料构建并精心维护。这是一切的根基。
> One thing that surprised me is how the relationship of startup founders goes from a friendship to a marriage. My relationship with my cofounder went from just being friends to seeing each other all the time, fretting over the finances and cleaning up shit. And the startup was our baby. I summed it up once like this: "It's like we're married, but we're not fucking."
2. 创业将占据你的全部生活 正如联合创始人之间的关系比普通同事更为紧密,创始人与公司之间的关系也同样如此。经营创业公司不像上班或当学生,因为它永不停歇。这与大多数人的生活经验如此迥异,以至于他们只有亲身经历才能明白。[1]
> 我没意识到自己会几乎把所有清醒时间都用来工作或思考公司事务。当你拥有自己的公司而非为他人打工时,就进入了一种完全不同的生活方式。
Several people used that word "married." It's a far more intense relationship than you usually see between coworkers—partly because the stresses are so much greater, and partly because at first the founders are the whole company. So this relationship has to be built of top quality materials and carefully maintained. It's the basis of everything. 2\. Startups Take Over Your Life Just as the relationship between cofounders is more intense than it usually is between coworkers, so is the relationship between the founders and the company. Running a startup is not like having a job or being a student, because it never stops. This is so foreign to most people's experience that they don't get it till it happens. [1]
创业公司的高速节奏加剧了这种状态,甚至让人产生时间变慢的错觉: > 最让我惊讶的是人对时间感知的转变。记得在创业时,时间仿佛被拉长,一个月就像漫长的跨度。
> I didn't realize I would spend almost every waking moment either working or thinking about our startup. You enter a whole different way of life when it's your company vs. working for someone else's company.
在最好的情况下,这种全情投入会令人兴奋: > 令人惊讶的是你会如此沉迷于自己的事业,日夜思考却从不觉得这是"工作"。
不过我必须说明,这段话来自我们今年夏天投资的一位创始人。几年后他的语气可能就不会这么轻快了。
It's exacerbated by the fast pace of startups, which makes it seem like time slows down:
3. 犹如情绪过山车 这是另一个让许多人始料未及的方面。情绪起伏的剧烈程度远超他们的预期。
> I think the thing that's been most surprising to me is how one's perspective on time shifts. Working on our startup, I remember time seeming to stretch out, so that a month was a huge interval.
在创业公司中,前一刻还形势大好,下一刻就可能希望渺茫。所谓下一刻,可能只是几小时之后。 > 情绪的大起大落最令我震惊。某天我们还自诩为下一个谷歌,幻想着购买私人岛屿;隔天就开始盘算如何向亲友交代自己的彻底失败;如此循环往复。
显然,最难熬的是低谷期。对许多创始人来说这才是最大的意外: > 在艰难时期(可能是几天或几周)保持团队士气有多难,也就是低谷能有多低。
In the best case, total immersion can be exciting:
持续一段时间后,如果没有重大成功来提振士气,这种状态会让人精疲力竭: > 你们给创始人的最基本建议是"活下去就行",但在缺乏重大突破时维持公司运转的精力并非凭空而来;它直接消耗着创始人自身的能量。
> It's surprising how much you become consumed by your startup, in that you think about it day and night, but never once does it feel like "work."
人的承受力终究有限。如果到了实在无法继续的地步,也并非世界末日。许多著名创始人都曾经历过失败。
Though I have to say, that quote is from someone we funded this summer. In a couple years he may not sound so chipper. 3\. It's an Emotional Roller-coaster This was another one lots of people were surprised about. The ups and downs were more extreme than they were prepared for. In a startup, things seem great one moment and hopeless the next. And by next, I mean a couple hours later.
4. 也可能充满乐趣 好消息是,高峰时刻同样令人振奋。几位创始人表示,创业最让他们惊喜的正是其中的乐趣:
我想你遗漏了创业有多么有趣这一点。比起那些没有创业的朋友们,我在工作中获得的成就感要多得多。
> The emotional ups and downs were the biggest surprise for me. One day, we'd think of ourselves as the next Google and dream of buying islands; the next, we'd be pondering how to let our loved ones know of our utter failure; and on and on.
> 令我惊讶的是,从事具有挑战性、创造性且自己深信不疑的事业,感觉远比之前当雇佣兵式的打工好得多。我预料到会更好,但没想到会好这么多。
The hard part, obviously, is the lows. For a lot of founders that was the big surprise:
不过坦白说,如果我在这点上误导了大家,我并不急于纠正。我宁愿所有人都认为创业是严峻而艰难的,也不愿创始人带着"这会很有趣"的期待开始,几个月后却抱怨:"这也能叫_有趣_?开玩笑吧?"
事实是,对大多数人而言这确实不有趣。我们在申请流程中做的很多筛选工作,就是为了剔除那些不会喜欢创业的人——既为我们好,也为他们好。
> How hard it is to keep everyone motivated during rough days or weeks, i.e. how low the lows can be.
或许可以这样形容:创业的乐趣,就像生存训练课程对爱好者的乐趣一样。换言之,如果你不是这类人,就完全体会不到这种乐趣。
After a while, if you don't have significant success to cheer you up, it wears you out:
5. 坚持是关键
许多创始人惊讶地发现,坚持在创业中有多么重要。这种惊讶既消极又积极:他们既惊讶于所需坚持的程度
> Your most basic advice to founders is "just don't die," but the energy to keep a company going in lieu of unburdening success isn't free; it is siphoned from the founders themselves.
> 虽然大家都说必须多么坚定和坚韧,但亲身经历让我明白,这种决心再怎么强调都不为过。
There's a limit to how much you can take. If you get to the point where you can't keep working anymore, it's not the end of the world. Plenty of famous founders have had some failures along the way. 4\. It Can Be Fun The good news is, the highs are also very high. Several founders said what surprised them most about doing a startup was how fun it was:
也惊讶于单凭坚持就能化解障碍的程度:
> I think you've left out just how fun it is to do a startup. I am more fulfilled in my work than pretty much any of my friends who did not start companies.
> 只要坚持,就连看似无法掌控的问题(比如移民手续)也会迎刃而解。
几位创始人特别提到,坚持远比智商重要得多。
What they like most is the freedom:
> 我一次又一次地惊讶发现,坚持远比原始智力重要得多。
> I'm surprised by how much better it feels to be working on something that is challenging and creative, something I believe in, as opposed to the hired-gun stuff I was doing before. I knew it would feel better; what's surprising is how much better.
这不仅适用于智力,也适用于整体能力。正因如此,许多人都说在选择联合创始人时,性格比能力更重要。
6. 长远思考
Frankly, though, if I've misled people here, I'm not eager to fix that. I'd rather have everyone think starting a startup is grim and hard than have founders go into it expecting it to be fun, and a few months later saying "This is supposed to be _fun_? Are you kidding?" The truth is, it wouldn't be fun for most people. A lot of what we try to do in the application process is to weed out the people who wouldn't like it, both for our sake and theirs. The best way to put it might be that starting a startup is fun the way a survivalist training course would be fun, if you're into that sort of thing. Which is to say, not at all, if you're not. 5\. Persistence Is the Key A lot of founders were surprised how important persistence was in startups. It was both a negative and a positive surprise: they were surprised both by the degree of persistence required
你需要坚持,因为所有事情都比预期耗时。这让很多人感到意外。
> Everyone said how determined and resilient you must be, but going through it made me realize that the determination required was still understated.
> 我不断被各种事情的耗时之长所震惊。除非你的产品能实现极少数产品才有的爆发式增长,否则从开发到交易(尤其是交易)的所有事情,耗时总是比我预想的要多2-3倍。
创始人感到惊讶的一个原因是,他们自己行动迅速,便以为其他人也是如此。每当创业公司与更官僚化的组织(如大公司或风投基金)接触时,都会遭遇惊人的摩擦阻力。这就是为什么融资和企业市场会摧毁或重创如此多的初创企业。[2]
and also by the degree to which persistence alone was able to dissolve obstacles:
但我认为大多数创始人之所以对耗时之长感到意外,主要是因为他们过于自信。他们以为自己会像YouTube或Facebook那样一夜成功。当你告诉他们,每100家成功的创业公司中只有1家能有这样的轨迹时,他们都会想"我们就是那1家"。
> If you are persistent, even problems that seem out of your control (i.e. immigration) seem to work themselves out.
或许他们会听进去某位更成功创始人的话:
Several founders mentioned specifically how much more important persistence was than intelligence.
> 我入行前最不理解的是,持久战才是关键。对绝大多数最终成功的初创企业而言,这将是段极其漫长的旅程——至少3年,很可能5年以上。
用长期视角思考也有积极意义。这不仅是接受所有事情都比预期耗时更久。如果你耐心工作,压力会更小,成果也会更好:
> I've been surprised again and again by just how much more important persistence is than raw intelligence.
> 因为我们心态放松,工作变得愉快多了。那种因害怕失败而产生的紧张不安能量消失了,它曾扭曲着我们的行动。现在我们可以专注于为公司、产品、员工和客户做最正确的事。
This applies not just to intelligence but to ability in general, and that's why so many people said character was more important in choosing cofounders. 6\. Think Long-Term You need persistence because everything takes longer than you expect. A lot of people were surprised by that.
这就是为什么达到"拉面盈利"后情况会大幅改善。你可以切换到另一种工作模式。
7. 无数琐事
> I'm continually surprised by how long everything can take. Assuming your product doesn't experience the explosive growth that very few products do, everything from development to dealmaking (especially dealmaking) seems to take 2-3x longer than I always imagine.
我们常强调,创业公司很少仅因某个绝妙点子就成功。如今创始人们已明白这点。但许多人惊讶地发现,这同样适用于公司内部运作。你必须处理大量杂务:
One reason founders are surprised is that because they work fast, they expect everyone else to. There's a shocking amount of shear stress at every point where a startup touches a more bureaucratic organization, like a big company or a VC fund. That's why fundraising and the enterprise market kill and maim so many startups. [2] But I think the reason most founders are surprised by how long it takes is that they're overconfident. They think they're going to be an instant success, like YouTube or Facebook. You tell them only 1 out of 100 successful startups has a trajectory like that, and they all think "we're going to be that 1." Maybe they'll listen to one of the more successful founders:
> 这更像是苦差而非光鲜活。随机截取某个工作片段,更可能发现我在排查瑞典版Windows的诡异DLL加载故障,或是在董事会前夜修正财务模型Excel表格的错误,而非迸发战略灵感的火花。
多数黑客出身的创始人希望整天编程。除非你失败,否则这不可能实现。换句话说:若你只编程,必将失败。
> The top thing I didn't understand before going into it is that persistence is the name of the game. For the vast majority of startups that become successful, it's going to be a _really_ long journey, at least 3 years and probably 5+.
这一原则甚至适用于编程本身。鲜少有什么天才代码能确保成功:
There is a positive side to thinking longer-term. It's not just that you have to resign yourself to everything taking longer than it should. If you work patiently it's less stressful, and you can do better work:
> 我学会永远不要押注于某个功能、交易或任何单一因素能带来成功。从来不存在单点突破。一切都是渐进积累,你必须持续做大量琐事,直到某件事真正奏效。
> Because we're relaxed, it's so much easier to have fun doing what we do. Gone is the awkward nervous energy fueled by the desperate need to not fail guiding our actions. We can concentrate on doing what's best for our company, product, employees and customers.
即便真有某个聪明代码让你走运,你也往往事后才知晓:
> 杀手级功能根本不存在。至少你无法预先识别它。
That's why things get so much better when you hit ramen profitability. You can shift into a different mode of working. 7\. Lots of Little Things We often emphasize how rarely startups win simply because they hit on some magic idea. I think founders have now gotten that into their heads. But a lot were surprised to find this also applies within startups. You have to do lots of different things:
因此,最佳策略是尝试多种不同方案。不要把鸡蛋放在一个篮子里的原因并非老生常谈——即便你知道哪个篮子最好时也要分散风险。而在创业中,你甚至不知道哪个篮子更好。
> It's much more of a grind than glamorous. A timeslice selected at random would more likely find me tracking down a weird DLL loading bug on Swedish Windows, or tracking down a bug in the financial model Excel spreadsheet the night before a board meeting, rather than having brilliant flashes of strategic insight.
8. 从最简版本起步
许多创始人提到,用最简单可行的产品启动至关重要。如今人人都明白应该快速发布并迭代,这几乎是YC的座右铭。但即便如此,仍有不少人因违背这条原则而付出代价:
Most hacker-founders would like to spend all their time programming. You won't get to, unless you fail. Which can be transformed into: If you spend all your time programming, you will fail. The principle extends even into programming. There is rarely a single brilliant hack that ensures success:
> 打造能被视作完整应用的最小化产品,然后立即发布。
> I learnt never to bet on any one feature or deal or anything to bring you success. It is never a single thing. Everything is just incremental and you just have to keep doing lots of those things until you strike something.
为何人们总在初版上耗费太久?主要是自尊心作祟。他们不愿发布尚有改进空间的产品,担心他人评价。但你必须克服这种心理:
Even in the rare cases where a clever hack makes your fortune, you probably won't know till later:
> 看似"简单"的初版,并不意味着你做的不是有意义、有壁垒或有价值的事。
别在意他人评价。如果你的初版完美到连网络喷子都无从嘲笑,那说明你发布得太迟了。[3]
> There is no such thing as a killer feature. Or at least you won't know what it is.
一位创始人认为这应成为所有编程的准则,而不仅限于创业,我深表赞同:
So the best strategy is to try lots of different things. The reason not to put all your eggs in one basket is not the usual one, which applies even when you know which basket is best. In a startup you don't even know that. 8\. Start with Something Minimal Lots of founders mentioned how important it was to launch with the simplest possible thing. By this point everyone knows you should release fast and iterate. It's practically a mantra at YC. But even so a lot of people seem to have been burned by not doing it:
> 如今写代码时,我会思考"怎样才能让看到代码的人惊叹于它的精简和功能之少?"
过度设计是毒药。它不像为额外学分做附加题,更像撒了一个必须时刻牢记的谎。
> Build the absolute smallest thing that can be considered a complete application and ship it.
9. 与用户互动
Why do people take too long on the first version? Pride, mostly. They hate to release something that could be better. They worry what people will say about them. But you have to overcome this:
产品开发是与用户的对话,而这场对话直到发布才算真正开始。发布前,你就像刑侦画师尚未向目击者展示素描初稿。
快速发布如此重要,或许你该将初版视为吸引用户开口的诱饵,而非正式产品:
> Doing something "simple" at first glance does not mean you aren't doing something meaningful, defensible, or valuable.
> 我学会将创业初期视为巨型实验。所有产品都应被看作实验,而有市场的产品会极速显现积极信号。
Don't worry what people will say. If your first version is so impressive that trolls don't make fun of it, you waited too long to launch. [3] One founder said this should be your approach to all programming, not just startups, and I tend to agree.
一旦开始与用户对话,他们的反馈定会让你惊讶:
> Now, when coding, I try to think "How can I write this such that if people saw my code, they'd be amazed at how little there is and how little it does?"
> 当允许客户表达需求时,他们常会透露关于价值认知和付费意愿的惊人细节。
惊喜往往既包含积极的一面,也有消极的一面。用户可能不喜欢你打造的产品,但他们总会提出一些微不足道却能轻易实现的需求。唯有当你推出错误产品开启对话时,他们才能表达(甚至意识到)自己真正的需求。
Over-engineering is poison. It's not like doing extra work for extra credit. It's more like telling a lie that you then have to remember so you don't contradict it. 9\. Engage Users Product development is a conversation with the user that doesn't really start till you launch. Before you launch, you're like a police artist before he's shown the first version of his sketch to the witness. It's so important to launch fast that it may be better to think of your initial version not as a product, but as a trick for getting users to start talking to you.
10. 调整你的创意
> I learned to think about the initial stages of a startup as a giant experiment. All products should be considered experiments, and those that have a market show promising results extremely quickly.
要从用户互动中获益,你必须保持开放心态调整创意。我们始终建议创始人将创业构想视为假设而非蓝图。但每当调整方向带来奇效时,他们仍会感到惊讶。
> 通常当人们抱怨事情艰难时,常规建议是加倍努力。但对初创企业,我认为应该寻找你擅长解决的难题。在解决方案层面的优化简单直接,但在问题层面的探索能带来巨大收益。
Once you start talking to users, I guarantee you'll be surprised by what they tell you.
固执己见而不懂变通,就像贪婪算法只能带给你平庸的局部最优解:
> When you let customers tell you what they're after, they will often reveal amazing details about what they find valuable as well what they're willing to pay for.
> 当某人固执己见时,仍可能历经艰辛却最终徒劳无功。
你需要勇往直前,同时灵活转向寻找最具潜力的路径。有位创始人总结得极为精辟:
The surprise is generally positive as well as negative. They won't like what you've built, but there will be other things they would like that would be trivially easy to implement. It's not till you start the conversation by launching the wrong thing that they can express (or perhaps even realize) what they're looking for. 10\. Change Your Idea To benefit from engaging with users you have to be willing to change your idea. We've always encouraged founders to see a startup idea as a hypothesis rather than a blueprint. And yet they're still surprised how well it works to change the idea.
> 快速迭代是成功的关键。
> Normally if you complain about something being hard, the general advice is to work harder. With a startup, I think you should find a problem that's easy for you to solve. Optimizing in solution-space is familiar and straightforward, but you can make enormous gains playing around in problem-space.
这条建议难以践行,因为人们往往低估了判断创业想法的难度——尤其是对自己的创意。经验丰富的创业者都懂得保持开放心态:
Whereas mere determination, without flexibility, is a greedy algorithm that may get you nothing more than a mediocre local maximum:
> 如今我再不会嘲笑任何创意,因为我已意识到自己根本无力判断它们的优劣。
你永远无法预知什么会成功,只能在每个节点做出最佳选择。YC本身也是如此运作——我们至今仍在验证这个看似合理的假设。
> When someone is determined, there's still a danger that they'll follow a long, hard path that ultimately leads nowhere.
11. 别担心竞争对手
You want to push forward, but at the same time twist and turn to find the most promising path. One founder put it very succinctly:
当你自认为拥有绝妙创意时,就像怀揣着不可告人的秘密。只要旁人投来异样眼光,你就会心惊:"天啊,他们发现了!"
这些警报几乎总是虚惊一场:
> Fast iteration is the key to success.
> 那些初看像是竞争对手的威胁者,经仔细审视后往往不足为虑。即便业务领域重合,他们的目标也截然不同。
One reason this advice is so hard to follow is that people don't realize how hard it is to judge startup ideas, particularly their own. Experienced founders learn to keep an open mind:
人们之所以对竞争对手过度反应,是因为高估了创意的价值。若创意真是成败关键,那么持有相同创意的竞争者确实构成威胁。但决定因素通常在于执行:
> 所有因新对手出现引发的恐慌,几周后都会被遗忘。最终决胜的永远是你自身的产品和市场策略。
> Now I don't laugh at ideas anymore, because I realized how terrible I was at knowing if they were good or not.
即便竞争对手获得大量关注,这个道理依然成立:
You can never tell what will work. You just have to do whatever seems best at each point. We do this with YC itself. We still don't know if it will work, but it seems like a decent hypothesis. 11\. Don't Worry about Competitors When you think you've got a great idea, it's sort of like having a guilty conscience about something. All someone has to do is look at you funny, and you think "Oh my God, _they know._ " These alarms are almost always false:
> 那些博得博主青睐的竞争者往往并非赢家,可能转瞬即逝。毕竟你真正需要征服的是终端消费者。
> Companies that seemed like competitors and threats at first glance usually never were when you really looked at it. Even if they were operating in the same area, they had a different goal.
炒作无法带来满意的用户,至少对技术这样复杂的事物是如此。
12. 获取用户很难 然而,许多创始人抱怨获取用户有多么困难。
One reason people overreact to competitors is that they overvalue ideas. If ideas really were the key, a competitor with the same idea would be a real threat. But it's usually execution that matters:
> 我完全没意识到获取用户需要投入多少时间和精力。
> All the scares induced by seeing a new competitor pop up are forgotten weeks later. It always comes down to your own product and approach to the market.
这是个复杂的问题。当你无法获取用户时,很难判断问题是缺乏曝光,还是产品本身不够好。即使是好产品,也可能被转换或集成成本所阻碍:
> 让人们使用一项新服务极其困难。对于其他公司可能使用的服务尤其如此,因为这需要他们的开发人员投入工作。如果你规模小,他们会觉得这事不紧急。[4]
This is generally true even if competitors get lots of attention.
对YC最尖锐的批评来自一位创始人,他认为我们对客户获取的重视不足:
> Competitors riding on lots of good blogger perception aren't really the winners and can disappear from the map quickly. You need consumers after all.
> YC宣扬“做人们想要的东西”是一项工程任务,通过不断添加功能,直到足够多的人满意,产品就会起飞。但对客户获取成本的关注极少。
这可能是事实;这可能是我们需要改进的地方,尤其是对游戏类应用。如果你做的产品挑战主要在于技术,你可以依赖口碑传播,就像谷歌那样。一位创始人惊讶于这种方式对他非常有效:
Hype doesn't make satisfied users, at least not for something as complicated as technology. 12\. It's Hard to Get Users A lot of founders complained about how hard it was to get users, though.
> 人们会非理性地担心没人买你的产品。但如果你努力并逐步改进它,就无需忧虑。
> I had no idea how much time and effort needed to go into attaining users.
但对于其他类型的初创公司,你可能更多依靠交易和营销而非功能来取胜。
This is a complicated topic. When you can't get users, it's hard to say whether the problem is lack of exposure, or whether the product's simply bad. Even good products can be blocked by switching or integration costs:
13. 对交易做最坏打算 交易会失败。这是初创世界的常态。初创公司缺乏话语权,而好的初创点子通常看起来不靠谱。因此,所有人对与你达成交易都心存疑虑,而你无法强迫他们。
这在投资者身上尤其明显:
> Getting people to use a new service is incredibly difficult. This is especially true for a service that other companies can use, because it requires their developers to do work. If you're small, they don't think it is urgent. [4]
> 事后看来,如果我们当初假设永远无法获得额外外部投资,情况会好得多。这会迫使我们更早寻找收入来源。
The sharpest criticism of YC came from a founder who said we didn't focus enough on customer acquisition:
我的建议通常是悲观的。假设你拿不到钱,如果有人愿意投,也假设这是最后一笔。
> 如果有人给你钱,就拿。你经常这么说,但我认为还需要更强调。我们去年本有机会融到更多钱,真希望当时那么做了。
> YC preaches "make something people want" as an engineering task, a never ending stream of feature after feature until enough people are happy and the application takes off. There's very little focus on the cost of customer acquisition.
创始人为何忽视这一点?主要是因为他们天性乐观。错误在于对无法控制的事情过于乐观。当然,你可以对做出伟大产品的能力保持乐观。但如果你对大公司或投资者也乐观,就是在自找麻烦。
This may be true; this may be something we need to fix, especially for applications like games. If you make something where the challenges are mostly technical, you can rely on word of mouth, like Google did. One founder was surprised by how well that worked for him:
14. 投资者毫无头绪 许多创始人提到,他们对投资者的无知感到震惊:
他们甚至不了解自己投资的项目。我遇到过一些投资了某款硬件设备的投资人,当我请他们演示设备时,他们连开机都手忙脚乱。
> There is an irrational fear that no one will buy your product. But if you work hard and incrementally make it better, there is no need to worry.
天使投资人比风投略胜一筹,因为他们通常自己就有创业经历:
But with other types of startups you may win less by features and more by deals and marketing. 13\. Expect the Worst with Deals Deals fall through. That's a constant of the startup world. Startups are powerless, and good startup ideas generally seem wrong. So everyone is nervous about closing deals with you, and you have no way to make them. This is particularly true with investors:
> 风投机构大半时候根本不懂自己在说什么,思维还停留在几年前。少数人很优秀,但95%打过交道的投资人都缺乏专业性,既不善经商也毫无创新视野。和天使投资人沟通通常顺畅得多。
> In retrospect, it would have been much better if we had operated under the assumption that we would never get any additional outside investment. That would have focused us on finding revenue streams early.
为何创始人会对风投的无知感到惊讶?我想是因为他们看起来太强势了。
风投显得强势的原因在于这是他们的职业要求。要成为风投,必须说服资产管理人将数亿美元托付给你。怎么做到?你必须表现得自信满满,还必须装作懂技术。[5]
My advice is generally pessimistic. Assume you won't get money, and if someone does offer you any, assume you'll never get any more.
15. 有时不得不玩弄把戏
> If someone offers you money, take it. You say it a lot, but I think it needs even more emphasizing. We had the opportunity to raise a lot more money than we did last year and I wish we had.
由于投资人缺乏判断力,你不得不耗费额外精力推销自己。一位创始人说最让他震惊的是:
> 假装胸有成竹对投资人的震撼程度超乎想象。
Why do founders ignore me? Mostly because they're optimistic by nature. The mistake is to be optimistic about things you can't control. By all means be optimistic about your ability to make something great. But you're asking for trouble if you're optimistic about big companies or investors. 14\. Investors Are Clueless A lot of founders mentioned how surprised they were by the cluelessness of investors:
这是YC创始人经历中最令我震惊的发现。今夏我们邀请校友给新创团队分享融资经验,他们100%的建议都围绕投资人心理。我自认对风投已足够怀疑,但创始人们更加愤世嫉俗。
> They don't even know about the stuff they've invested in. I met some investors that had invested in a hardware device and when I asked them to demo the device they had difficulty switching it on.
> 创业者很多行为不过是作秀,但确实有效。
Angels are a bit better than VCs, because they usually have startup experience themselves:
风投根本意识不到,他们看好的项目往往只是最擅长自我包装的。[6] 这与前文所述现象如出一辙:风投通过向LP展现自信获得资金,创始人则通过向风投展现自信拿到钱。
16. 运气至关重要
> VC investors don't know half the time what they are talking about and are years behind in their thinking. A few were great, but 95% of the investors we dealt with were unprofessional, didn't seem to be very good at business or have any kind of creative vision. Angels were generally much better to talk to.
在创业项目与资本之间隔着两道随机筛选的关卡,运气成为关键因素本不足为奇。但许多创始人仍感到意外:
Why are founders surprised that VCs are clueless? I think it's because they seem so formidable. The reason VCs seem formidable is that it's their profession to. You get to be a VC by convincing asset managers to trust you with hundreds of millions of dollars. How do you do that? You have to seem confident, and you have to seem like you understand technology. [5] 15\. You May Have to Play Games Because investors are so bad at judging you, you have to work harder than you should at selling yourself. One founder said the thing that surprised him most was
> 我从未意识到运气成分如此之大,有这么多不可控因素。
想想那些著名企业,运气的分量显而易见。如果IBM当年坚持要求DOS系统独家授权,微软还会有今天吗?
> The degree to which feigning certitude impressed investors.
为何创始人会被蒙蔽?商界人士或许不会,但黑客出身者习惯以能力论成败的规则,认为付出必有回报。
This is the thing that has surprised _me_ most about YC founders' experiences. This summer we invited some of the alumni to talk to the new startups about fundraising, and pretty much 100% of their advice was about investor psychology. I thought I was cynical about VCs, but the founders were much more cynical.
> 创业之初我深信那些创始人神话,以为这是实力博弈。某种程度上确实如此,能力很重要,毅力也关键。但运气才是决定性因素。
事实上,最好的模型是将创业结果视为技能、决心和运气的乘积。无论你拥有多少技能与决心,只要运气值为零,结果就会归零。
> A lot of what startup founders do is just posturing. It works.
这些关于运气的感悟并非来自失败的创业者。快速失败的创始人往往会自责,快速成功的创始人通常意识不到自己有多幸运。只有那些处于中间地带的人,才真正明白运气的重要性。
VCs themselves have no idea of the extent to which the startups they like are the ones that are best at selling themselves to VCs. [6] It's exactly the same phenomenon we saw a step earlier. VCs get money by seeming confident to LPs, and founders get money by seeming confident to VCs. 16\. Luck Is a Big Factor With two such random linkages in the path between startups and money, it shouldn't be surprising that luck is a big factor in deals. And yet a lot of founders are surprised by it.
17. 社群的价值
> I didn't realize how much of a role luck plays and how much is outside of our control.
令人惊讶的是,许多创始人表示创业过程中最出乎意料的是社群的价值。部分人指的是YC创始人微社群:
> YC同行圈子的巨大价值,在于大家会在相似时间面临相似挑战。
If you think about famous startups, it's pretty clear how big a role luck plays. Where would Microsoft be if IBM insisted on an exclusive license for DOS? Why are founders fooled by this? Business guys probably aren't, but hackers are used to a world where skill is paramount, and you get what you deserve.
这其实并不意外,因为YC本就是为此设计的。另一些人则对广义创业生态的价值感到惊喜:
> When we started our startup, I had bought the hype of the startup founder dream: that this is a game of skill. It is, in some ways. Having skill is valuable. So is being determined as all hell. But being lucky is the critical ingredient.
> 住在硅谷的优势超乎想象——在这里你会被动吸收最前沿的科技创业资讯,并持续邂逅能提供帮助的人。
最让他们震撼的是其中普遍的善意精神:
Actually the best model would be to say that the outcome is the _product_ of skill, determination, and luck. No matter how much skill and determination you have, if you roll a zero for luck, the outcome is zero. These quotes about luck are not from founders whose startups failed. Founders who fail quickly tend to blame themselves. Founders who succeed quickly don't usually realize how lucky they were. It's the ones in the middle who see how important luck is. 17\. The Value of Community A surprising number of founders said what surprised them most about starting a startup was the value of community. Some meant the micro-community of YC founders:
> 最令我惊讶的是人们愿意不求回报地帮助我们,甚至那些毫无利益关联的人也会主动伸出援手。
> The immense value of the peer group of YC companies, and facing similar obstacles at similar times.
这种氛围甚至延伸至顶层精英:
> 大人物的平易近人程度令人吃惊,你能轻松获得他们的即时反馈。
which shouldn't be that surprising, because that's why it's structured that way. Others were surprised at the value of the startup community in the larger sense:
这正是我热爱这个圈子的原因。创造财富并非零和游戏,你无需背后捅刀也能赢得胜利。
> How advantageous it is to live in Silicon Valley, where you can't help but hear all the cutting-edge tech and startup news, and run into useful people constantly.
18. 缺乏认同
The specific thing that surprised them most was the general spirit of benevolence:
有个被创始人提及的意外现象已被我遗忘:在创业圈之外,创始人往往得不到尊重。
> 社交场合中,说"我在微软Office部门工作"远比"我在某家无名初创公司x"获得更多敬意。
> One of the most surprising things I saw was the willingness of people to help us. Even people who had nothing to gain went out of their way to help our startup succeed.
部分原因在于外界对创业缺乏认知,另一部分则源于优质创业点子往往看似糟糕:
and particularly how it extended all the way to the top:
> 向普通人推介创意时,95%的情况下对方会本能认为这注定失败(尽管未必直言)。
这种偏见甚至影响婚恋市场:
> The surprise for me was how accessible important and interesting people are. It's amazing how easily you can reach out to people and get immediate feedback.
> 令人惊讶的是,创业者身份并未让我在异性眼中更具魅力。
This is one of the reasons I like being part of this world. Creating wealth is not a zero-sum game, so you don't have to stab people in the back to win. 18\. You Get No Respect There was one surprise founders mentioned that I'd forgotten about: that outside the startup world, startup founders get no respect.
我原本知晓这点,只是遗忘了。
19. 成长带来的改变
> In social settings, I found that I got a lot more respect when I said, "I worked on Microsoft Office" instead of "I work at a small startup you've never heard of called x."
创始人提到的最后一大意外是公司成长带来的剧变。最显著的变化是编程时间进一步压缩:
Partly this is because the rest of the world just doesn't get startups, and partly it's yet another consequence of the fact that most good startup ideas seem bad:
作为技术创始人兼CEO,你的工作职责每6-12个月就会彻底改写。编码减少,管理/规划/公司建设、招聘、收拾烂摊子增多,总体上要为几个月后需要发生的事情做好准备。
> If you pitch your idea to a random person, 95% of the time you'll find the person instinctively thinks the idea will be a flop and you're wasting your time (although they probably won't say this directly).
特别是,你现在必须与员工打交道,他们的动机往往不同:
> 我早就明白创始人方程式,从19岁立志创业起就一直专注于此。但员工方程式截然不同,我花了好一阵子才摸清门道。
Unfortunately this extends even to dating:
幸运的是,当公司进入平稳发展阶段后,压力会大幅减轻:
> It surprised me that being a startup founder does not get you more admiration from women.
> 相比创业初期,现在75%的压力已经消散。经营公司变得愉快多了。我们更自信,更有耐心,争吵变少,睡眠更足。
我希望能说所有成功的初创企业都是如此,但75%的比例可能已经算高了。
I did know about that, but I'd forgotten. 19\. Things Change as You Grow The last big surprise founders mentioned is how much things changed as they grew. The biggest change was that you got to program even less:
还有其他一些模式,但以上这些是最主要的。看到这些模式后,人们首先会想:是否存在一个统摄所有模式的超级模式?
> Your job description as technical founder/CEO is completely rewritten every 6-12 months. Less coding, more managing/planning/company building, hiring, cleaning up messes, and generally getting things in place for what needs to happen a few months from now.
我立刻就发现了它,当我向一位YC创始人念出这份清单时,他也立刻意识到了。这些本该是令人意外的、我未曾告诉过人们的事情。它们的共同点是什么?全都是我反复告诫人们的内容。如果我用同样的提纲另写一篇文章而不说明这是对创始人们反馈的总结,所有人都会认为我江郎才尽只是在自我重复。
审视这些反馈时,我发现共同主题是:创业正如我所描述的那样——只是程度远超预期。人们似乎只有亲身经历才能真正理解其特殊性。为什么?解开这个谜题的关键在于追问:与什么相比如此不同?一旦这样设问,答案显而易见:与普通工作相比。每个人对工作的认知模板都是职场模式,这种观念根深蒂固。即使你从未工作过,你的父母和几乎所有你接触过的成年人都有职场经历。
In particular, you now have to deal with employees, who often have different motivations:
潜意识里,每个人都以为创业会像份工作,这解释了大多数意外发现。它说明了为何人们会惊讶于选择联合创始人的谨慎程度,以及维护这段关系需要付出的努力——这些在普通同事关系中都不需要。也解释了为何情绪起伏会极端得令人吃惊:职场中有更多缓冲机制。但同时揭示了为何巅峰时刻会美好得超乎想象:多数人无法设想这种自由度。顺着清单往下看,几乎所有意外之处都源于创业与打工的天壤之别。
> I knew the founder equation and had been focused on it since I knew I wanted to start a startup as a 19 year old. The employee equation is quite different so it took me a while to get it down.
你或许无法彻底摆脱成长环境中形成的职场认知模板。因此最佳解决方案是保持清醒认知。当你开始创业时,你会想"大家都说这非常极端",紧接着的想法可能是"但我不相信会糟糕到那种程度"。若要避免意外,接下来的念头应该是:"而我之所以不相信会那么糟糕,正是因为我的工作认知模板来自打工经历。"
Fortunately, it can become a lot less stressful once you reach cruising altitude:
[1] 研究生可能理解这种感受。读研时你总觉得自己应该在做论文,它不像课程那样每学期就结束。
[2] 初创企业与慢节奏机构打交道的最佳方式,是分支出独立流程来处理。当它们处于关键路径时——比如必须达成某项协议才能推进时——就会带来致命风险。值得采取极端措施避免这种情况。
> I'd say 75% of the stress is gone now from when we first started. Running a business is so much more enjoyable now. We're more confident. We're more patient. We fight less. We sleep more.
[3] 这符合Reid Hoffman的原则:如果发布产品时不感到尴尬,说明你发布得太晚了。
I wish I could say it was this way for every startup that succeeded, but 75% is probably on the high side. The Super-Pattern There were a few other patterns, but these were the biggest. One's first thought when looking at them all is to ask if there's a super-pattern, a pattern to the patterns. I saw it immediately, and so did a YC founder I read the list to. These are supposed to be the surprises, the things I didn't tell people. What do they all have in common? They're all things I tell people. If I wrote a new essay with the same outline as this that wasn't summarizing the founders' responses, everyone would say I'd run out of ideas and was just repeating myself. What is going on here? When I look at the responses, the common theme is that starting a startup was like I said, but way more so. People just don't seem to get how different it is till they do it. Why? The key to that mystery is to ask, how different _from what?_ Once you phrase it that way, the answer is obvious: from a job. Everyone's model of work is a job. It's completely pervasive. Even if you've never had a job, your parents probably did, along with practically every other adult you've met. Unconsciously, everyone expects a startup to be like a job, and that explains most of the surprises. It explains why people are surprised how carefully you have to choose cofounders and how hard you have to work to maintain your relationship. You don't have to do that with coworkers. It explains why the ups and downs are surprisingly extreme. In a job there is much more damping. But it also explains why the good times are surprisingly good: most people can't imagine such freedom. As you go down the list, almost all the surprises are surprising in how much a startup differs from a job. You probably can't overcome anything so pervasive as the model of work you grew up with. So the best solution is to be consciously aware of that.
[4] 评估产品的关键不是它是否完美,而是是否足够好以提供所需的启动能量。
[5] 有些风投确实懂技术,但这并非必需;决定性标准是能否说服有限合伙人。
As you go into a startup, you'll be thinking "everyone says it's really extreme." Your next thought will probably be "but I can't believe it will be that bad." If you want to avoid being surprised, the next thought after that should be: "and the reason I can't believe it will be that bad is that my model of work is a job." Notes [1] Graduate students might understand it. In grad school you always feel you should be working on your thesis. It doesn't end every semester like classes do. [2] The best way for a startup to engage with slow-moving organizations is to fork off separate processes to deal with them. It's when they're on the critical path that they kill you—when you depend on closing a deal to move forward. It's worth taking extreme measures to avoid that. [3] This is a variant of Reid Hoffman's principle that if you aren't embarrassed by what you launch with, you waited too long to launch. [4] The question to ask about what you've built is not whether it's good, but whether it's good enough to supply the activation energy required. [5] Some VCs seem to understand technology because they actually do, but that's overkill; the defining test is whether you can talk about it well enough to convince limited partners. [6] This is the same phenomenon you see with defense contractors or fashion brands.
[6] 这与军火商或时尚品牌的现象相同:客户越愚钝,你在销售过程投入的精力就越会超过产品本身。
The dumber the customers, the more effort you expend on the process of selling things to them rather than making the things you sell. Thanks: to Jessica Livingston for reading drafts of this, and to all the founders who responded to my email. Related:
Startups in 13 Sentences The Hardest Lessons for Startups to Learn How Not to Die The 18 Mistakes That Kill Startups A Fundraising Survival Guide Russian Translation Korean Translation Hebrew Translation.
致谢:感谢Jessica Livingston审阅本文草稿,以及所有回复邮件的创始人。
13句话讲透创业 初创企业最难掌握的教训 如何避免夭折 杀死初创企业的18个错误 融资生存指南 俄语版 韩语版 希伯来语版
September 2009 Publishers of all types, from news to music, are unhappy that consumers won't pay for content anymore. At least, that's how they see it. In fact consumers never really were paying for content, and publishers weren't really selling it either. If the content was what they were selling, why has the price of books or music or movies always depended mostly on the format? Why didn't better content cost more? [1] A copy of _Time_ costs $5 for 58 pages, or 8.6 cents a page. _The Economist_ costs $7 for 86 pages, or 8.1 cents a page. Better journalism is actually slightly cheaper. Almost every form of publishing has been organized as if the medium was what they were selling, and the content was irrelevant. Book publishers, for example, set prices based on the cost of producing and distributing books. They treat the words printed in the book the same way a textile manufacturer treats the patterns printed on its fabrics. Economically, the print media are in the business of marking up paper. We can all imagine an old-style editor getting a scoop and saying "this will sell a lot of papers!" Cross out that final S and you're describing their business model. The reason they make less money now is that people don't need as much paper. A few months ago I ran into a friend in a cafe. I had a copy of the _New York Times_ , which I still occasionally buy on weekends. As I was leaving I offered it to him, as I've done countless times before in the same situation. But this time something new happened. I felt that sheepish feeling you get when you offer someone something worthless. "Do you, er, want a printout of yesterday's news?" I asked. (He didn't.) Now that the medium is evaporating, publishers have nothing left to sell. Some seem to think they're going to sell content—that they were always in the content business, really.
But they weren't, and it's unclear whether anyone could be. Selling There have always been people in the business of selling information, but that has historically been a distinct business from publishing. And the business of selling information to consumers has always been a marginal one. When I was a kid there were people who used to sell newsletters containing stock tips, printed on colored paper that made them hard for the copiers of the day to reproduce. That is a different world, both culturally and economically, from the one publishers currently inhabit. People will pay for information they think they can make money from. That's why they paid for those stock tip newsletters, and why companies pay now for Bloomberg terminals and Economist Intelligence Unit reports. But will people pay for information otherwise? History offers little encouragement. If audiences were willing to pay more for better content, why wasn't anyone already selling it to them? There was no reason you couldn't have done that in the era of physical media. So were the print media and the music labels simply overlooking this opportunity? Or is it, rather, nonexistent? What about iTunes? Doesn't that show people will pay for content? Well, not really. iTunes is more of a tollbooth than a store. Apple controls the default path onto the iPod. They offer a convenient list of songs, and whenever you choose one they ding your credit card for a small amount, just below the threshold of attention. Basically, iTunes makes money by taxing people, not selling them stuff. You can only do that if you own the channel, and even then you don't make much from it, because a toll has to be ignorable to work. Once a toll becomes painful, people start to find ways around it, and that's pretty easy with digital content. The situation is much the same with digital books. Whoever controls the device sets the terms.
It's in their interest for content to be as cheap as possible, and since they own the channel, there's a lot they can do to drive prices down. Prices will fall even further once writers realize they don't need publishers. Getting a book printed and distributed is a daunting prospect for a writer, but most can upload a file. Is software a counterexample? People pay a lot for desktop software, and that's just information. True, but I don't think publishers can learn much from software. Software companies can charge a lot because (a) many of the customers are businesses, who get in trouble if they use pirated versions, and (b) though in form merely information, software is treated by both maker and purchaser as a different type of thing from a song or an article. A Photoshop user needs Photoshop in a way that no one needs a particular song or article. That's why there's a separate word, "content," for information that's not software. Software is a different business. Software and content blur together in some of the most lightweight software, like casual games. But those are usually free. To make money the way software companies do, publishers would have to become software companies, and being publishers gives them no particular head start in that domain. [2] The most promising countertrend is the premium cable channel. People still pay for those. But broadcasting isn't publishing: you're not selling a copy of something. That's one reason the movie business hasn't seen their revenues decline the way the news and music businesses have. They only have one foot in publishing. To the extent the movie business can avoid becoming publishers, they may avoid publishing's problems. But there are limits to how well they'll be able to do that.
Once publishing—giving people copies—becomes the most natural way of distributing your content, it probably doesn't work to stick to old forms of distribution just because you make more that way. If free copies of your content are available online, then you're competing with publishing's form of distribution, and that's just as bad as being a publisher. Apparently some people in the music business hope to retroactively convert it away from publishing, by getting listeners to pay for subscriptions. It seems unlikely that will work if they're just streaming the same files you can get as mp3s. Next What happens to publishing if you can't sell content? You have two choices: give it away and make money from it indirectly, or find ways to embody it in things people will pay for. The first is probably the future of most current media. Give music away and make money from concerts and t-shirts. Publish articles for free and make money from one of a dozen permutations of advertising. Both publishers and investors are down on advertising at the moment, but it has more potential than they realize. I'm not claiming that potential will be realized by the existing players. The optimal ways to make money from the written word probably require different words written by different people. It's harder to say what will happen to movies. They could evolve into ads. Or they could return to their roots and make going to the theater a treat. If they made the experience good enough, audiences might start to prefer it to watching pirated movies at home. [3] Or maybe the movie business will dry up, and the people working in it will go to work for game developers. I don't know how big embodying information in physical form will be. It may be surprisingly large; people overvalue physical stuff. There should remain some market for printed books, at least.
I can see the evolution of book publishing in the books on my shelves. Clearly at some point in the 1960s the big publishing houses started to ask: how cheaply can we make books before people refuse to buy them? The answer turned out to be one step short of phonebooks. As long as it isn't floppy, consumers still perceive it as a book. That worked as long as buying printed books was the only way to read them. If printed books are optional, publishers will have to work harder to entice people to buy them. There should be some market, but it's hard to foresee how big, because its size will depend not on macro trends like the amount people read, but on the ingenuity of individual publishers. [4] Some magazines may thrive by focusing on the magazine as a physical object. Fashion magazines could be made lush in a way that would be hard to match digitally, at least for a while. But this is probably not an option for most magazines. I don't know exactly what the future will look like, but I'm not too worried about it. This sort of change tends to create as many good things as it kills. Indeed, the really interesting question is not what will happen to existing forms, but what new forms will appear. The reason I've been writing about existing forms is that I don't _know_ what new forms will appear. But though I can't predict specific winners, I can offer a recipe for recognizing them. When you see something that's taking advantage of new technology to give people something they want that they couldn't have before, you're probably looking at a winner. And when you see something that's merely reacting to new technology in an attempt to preserve some existing source of revenue, you're probably looking at a loser. Notes [1] I don't like the word "content" and tried for a while to avoid using it, but I have to admit there's no other word that means the right thing. "Information" is too general.
Ironically, the main reason I don't like "content" is the thesis of this essay. The word suggests an undifferentiated slurry, but economically that's how both publishers and audiences treat it. Content is information you don't need. [2] Some types of publishers would be at a disadvantage trying to enter the software business. Record labels, for example, would probably find it more natural to expand into casinos than software, because the kind of people who run them would be more at home at the mafia end of the business spectrum than the don't-be-evil end. [3] I never watch movies in theaters anymore. The tipping point for me was the ads they show first. [4] Unfortunately, making physically nice books will only be a niche within a niche. Publishers are more likely to resort to expedients like selling autographed copies, or editions with the buyer's picture on the cover. Thanks to Michael Arrington, Trevor Blackwell, Steven Levy, Robert Morris, and Geoff Ralston for reading drafts of this..
2009年9月 从新闻到音乐,各类出版商都对消费者不再为内容付费感到不满。至少,这是他们的看法。 事实上,消费者从未真正为内容付过费,出版商也从未真正出售过内容。如果内容是他们所售之物,为何书籍、音乐或电影的价格始终主要取决于载体形式?为何更优质的内容没有更昂贵?[1] 一本58页的《时代》周刊售价5美元,合每页8.6美分;86页的《经济学人》售价7美元,合每页8.1美分。更优质的新闻反而略便宜些。 几乎所有出版形态都默认载体才是商品,内容无足轻重。例如图书出版商根据印制与发行成本定价,对待书中的文字就像纺织厂商对待布料印花——不过是装饰纹理。 从经济学角度看,纸质媒体本质是纸张加价生意。我们都能想象老派编辑抢到独家新闻时说"这能多卖不少报纸!"划掉末尾的"s"(注:papers变为paper),便是其商业模式本质。如今利润下滑,只因人们不再需要那么多纸张。 几个月前我在咖啡馆遇见朋友。当时我拿着周末偶尔会买的《纽约时报》,像往常一样临走时问他是否需要——但这次出现了新变化。当我递出报纸时,竟产生了一种递出垃圾般的窘迫感:"呃…你要昨天新闻的打印件吗?"(他拒绝了) 如今载体正在蒸发,出版商再无商品可售。有人似乎认为可以改卖内容——声称自己本就是内容生意。但他们不是,且尚不清楚是否存在真正的"内容生意"。 售卖 信息贩售自古有之,但历来与出版业泾渭分明。面向消费者的信息交易更是边缘产业。我小时候有人兜售股票内参,印在彩纸上防止复印——无论文化还是经济层面,都与当今出版业身处两个世界。 人们会为能赚钱的信息付费(股票内参如是,如今企业购买彭博终端和经济学人智库报告亦如是)。但其他信息呢?历史并不乐观。 若受众真愿为优质内容多付费,为何无人早做这门生意?实体媒介时代完全具备条件。是传统媒体与唱片公司集体忽略了商机?还是这商机本就不存在? iTunes呢?它不证明人们愿为内容付费吗?未必。iTunes更像收费站而非商店。苹果掌控着iPod的默认入口,提供便捷曲库,每当你点击歌曲,就在注意力阈值之下悄声扣款。本质上,iTunes靠征税而非卖货盈利。唯有垄断渠道方能如此,即便如此收益有限——过路费必须低至可忽略方能持续。数字内容本就极易绕开收费。 电子书境况相似。设备掌控者制定规则,他们天然希望内容越便宜越好。随着作者意识到不再需要出版商(相比传统出版的畏途,上传文件人人可为),价格还将进一步下跌。 软件是反例吗?人们为桌面软件支付高价,而它本质也是信息。但出版商难以效仿:软件公司能高价收费,因(a)企业客户使用盗版会惹麻烦,(b)尽管形式上是信息,买卖双方都将软件视为与歌曲文章截然不同之物——Photoshop用户对软件的需求强度,远非任何单曲或文章可比。 因此我们另造"内容"一词特指非软件信息。软件是另一门生意。轻度软件(如休闲游戏)虽与内容交融,但多为免费。出版业若想如软件公司般盈利,必须转型为软件公司——而出版经验对此毫无助益。[2] 最有望的逆流是付费电视频道。人们仍为此付费。但广播非出版:你出售的不是复制品。这也解释了为何电影业未如新闻音乐业般收入锐减——他们仅半只脚踏入出版业。 只要避免彻底成为出版商,电影业或可规避出版困局。但逃避终有极限——当复制分发成为最自然的传播方式,固守旧模式终将失效。若作品免费版充斥网络,你便被迫与出版分发模式竞争,这与成为出版商同样糟糕。 音乐界有人试图通过订阅制逆转型,但若仅提供可mp3下载的同质内容,此路恐难通。 未来 若内容无法售卖,出版业何去何从?两条路:免费+间接盈利,或将其转化为可售商品。 前者或是多数现有媒体的归宿。免费音乐+演唱会/周边盈利,免费文章+广告变现实。尽管当下出版商与投资者对广告悲观,但其潜力远超预期。 我并非断言现有玩家能兑现这潜力。文字变现的最优解,或许需要全新创作者与内容形态。 电影业前景更难预测。可能进化为广告载体,或回归影院体验本质——若观影体验足够优越,观众或愿放弃家庭盗版。[3]亦或电影业萎缩,人才流向游戏开发。 实体化信息的市场规模难以预估。人们对实体物的高估可能带来惊喜,至少精装书仍有市场。 我书架上的书籍揭示了出版业演变:1960年代某刻,大出版社开始试探"书籍质量下限在哪里?"最终答案离电话簿仅一步之遥——只要不软塌,消费者仍视其为书。 当纸质书是唯一选择时此招有效。若纸质书成为可选项,出版商必须更费心吸引购买。市场犹存,但规模取决于出版商创意而非宏观阅读量。[4] 部分杂志或可通过强化实体属性突围。时尚杂志可打造数字难以企及的奢华质感(至少暂时)。但这非普适之道。 虽难预言具体形态,但我毫不担忧。此类变革摧毁的与催生的价值往往相当。真正有趣的不是旧形态存亡,而是新形态为何。 我探讨现存形式,正因无法预知未来形态。虽难预测具体赢家,但可提供识别法则:当某事物利用新技术提供前所未有的需求满足时,它可能是赢家;当某事物仅为维持旧收入而被动应对新技术时,它注定是输家。 注释 [1] 我厌恶"内容"一词并曾竭力回避,但不得不承认它精准。"信息"过于宽泛。 讽刺的是,我反感"内容"的原因正是本文论点——这个词暗示均质浆糊,而经济层面出版方与受众确实如此对待它。内容即非必需信息。 [2] 某些出版商转型软件业存在劣势。例如唱片公司进军赌场比软件更自然——因其经营者更适应黑帮式而非"不作恶"的商业光谱。 [3] 我绝不再去影院观影。压垮我的最后一根稻草是映前广告。 [4] 遗憾的是,精美实体书只能是小众之选。出版商更可能采用签名版、封面定制照片等捷径。 致谢 Michael Arrington、Trevor Blackwell、Steven Levy、Robert Morris与Geoff Ralston的审阅。.
September 2009 I bet you the current issue of _Cosmopolitan_ has an article whose title begins with a number. "7 Things He Won't Tell You about Sex," or something like that. Some popular magazines feature articles of this type on the cover of every issue. That can't be happening by accident. Editors must know they attract readers. Why do readers like the list of n things so much? Mainly because it's easier to read than a regular article. [1] Structurally, the list of n things is a degenerate case of essay. An essay can go anywhere the writer wants. In a list of n things the writer agrees to constrain himself to a collection of points of roughly equal importance, and he tells the reader explicitly what they are. Some of the work of reading an article is understanding its structure—figuring out what in high school we'd have called its "outline." Not explicitly, of course, but someone who really understands an article probably has something in his brain afterward that corresponds to such an outline. In a list of n things, this work is done for you. Its structure is an exoskeleton. As well as being explicit, the structure is guaranteed to be of the simplest possible type: a few main points with few to no subordinate ones, and no particular connection between them. Because the main points are unconnected, the list of n things is random access. There's no thread of reasoning you have to follow. You could read the list in any order. And because the points are independent of one another, they work like watertight compartments in an unsinkable ship. If you get bored with, or can't understand, or don't agree with one point, you don't have to give up on the article. You can just abandon that one and skip to the next. A list of n things is parallel and therefore fault tolerant. There are times when this format is what a writer wants. One, obviously, is when what you have to say actually is a list of n things.
我敢打赌,最新一期的《时尚》杂志肯定有篇标题以数字开头的文章,比如《关于性爱的7件他不会告诉你的事》之类。某些流行杂志每期封面都会刊登这类文章,这绝非偶然。编辑们显然深知它们能吸引读者。
为什么读者如此钟爱"N件事"清单?主要因为它比普通文章更易读。从结构上看,N件事清单是议论文的退化形态。议论文可以自由发挥,而清单作者则承诺用若干重要性相当的观点来约束自己,并明确告知读者这些观点是什么。
阅读文章的部分工作在于理解其结构——即厘清我们在高中称为"提纲"的东西。N件事清单替你完成了这项工作,它的结构如同外骨骼般清晰可见。
I once wrote an essay about the mistakes that kill startups, and a few people made fun of me for writing something whose title began with a number. But in that case I really was trying to make a complete catalog of a number of independent things. In fact, one of the questions I was trying to answer was how many there were. There are other less legitimate reasons for using this format. For example, I use it when I get close to a deadline. If I have to give a talk and I haven't started it a few days beforehand, I'll sometimes play it safe and make the talk a list of n things. The list of n things is easier for writers as well as readers. When you're writing a real essay, there's always a chance you'll hit a dead end. A real essay is a train of thought, and some trains of thought just peter out. That's an alarming possibility when you have to give a talk in a few days. What if you run out of ideas? The compartmentalized structure of the list of n things protects the writer from his own stupidity in much the same way it protects the reader. If you run out of ideas on one point, no problem: it won't kill the essay. You can take out the whole point if you need to, and the essay will still survive. Writing a list of n things is so relaxing. You think of n/2 of them in the first 5 minutes. So bang, there's the structure, and you just have to fill it in. As you think of more points, you just add them to the end. Maybe you take out or rearrange or combine a few, but at every stage you have a valid (though initially low-res) list of n things. It's like the sort of programming where you write a version 1 very quickly and then gradually modify it, but at every point have working code—or the style of painting where you begin with a complete but very blurry sketch done in an hour, then spend a week cranking up the resolution. Because the list of n things is easier for writers too, it's not always a damning sign when readers prefer it.
这种结构不仅明确,而且保证是最简单的类型:几个主要观点,几乎没有从属观点,彼此间也无特定关联。
由于观点互不关联,N件事清单支持随机阅读。你不必遵循推理线索,可以按任意顺序阅读。观点的独立性就像不沉船的水密舱——若对某点感到乏味、不解或反对,你无需放弃整篇文章,跳过它读下一条即可。N件事清单具有并行性和容错性。
有时这正是作者需要的格式。比如当你要说的本就是若干独立事项时。我曾写过《创业失败的致命错误》,有人嘲笑标题带数字,但我确实是在罗列完整清单。其他情况下,这种格式可能不太正当——比如截稿前夕,我会把演讲做成N件事清单来确保安全。
It's not necessarily evidence readers are lazy; it could also mean they don't have much confidence in the writer. The list of n things is in that respect the cheeseburger of essay forms. If you're eating at a restaurant you suspect is bad, your best bet is to order the cheeseburger. Even a bad cook can make a decent cheeseburger. And there are pretty strict conventions about what a cheeseburger should look like. You can assume the cook isn't going to try something weird and artistic. The list of n things similarly limits the damage that can be done by a bad writer. You know it's going to be about whatever the title says, and the format prevents the writer from indulging in any flights of fancy. Because the list of n things is the easiest essay form, it should be a good one for beginning writers. And in fact it is what most beginning writers are taught. The classic 5 paragraph essay is really a list of n things for n = 3. But the students writing them don't realize they're using the same structure as the articles they read in _Cosmopolitan_. They're not allowed to include the numbers, and they're expected to spackle over the gaps with gratuitous transitions ("Furthermore...") and cap the thing at either end with introductory and concluding paragraphs so it will look superficially like a real essay. [2] It seems a fine plan to start students off with the list of n things. It's the easiest form. But if we're going to do that, why not do it openly? Let them write lists of n things like the pros, with numbers and no transitions or "conclusion." There is one case where the list of n things is a dishonest format: when you use it to attract attention by falsely claiming the list is an exhaustive one. I.e. if you write an article that purports to be about _the_ 7 secrets of success. That kind of title is the same sort of reflexive challenge as a whodunit. You have to at least look at the article to check whether they're the same 7 you'd list.
对作者而言,N件事清单同样省力。真正的议论文可能走进死胡同,而清单结构能保护作者免于思维枯竭的窘境。如果某点写不下去,删除它也不会毁掉全文。
撰写N件事清单令人放松。前5分钟就能想到n/2个点子,结构瞬间成型,只需填充内容。新增观点可以直接追加,整个过程就像快速编写可运行代码,或先完成模糊草图再逐步细化。
既然作者也觉轻松,读者偏爱清单未必说明他们懒惰,可能只是对作者缺乏信心。N件事清单如同议论文界的汉堡包——在可疑的餐厅点汉堡最保险,因为再差的厨师也能做出像样的汉堡,且汉堡有严格标准,不必担心厨师搞艺术创新。清单同样限制了糟糕作者的发挥空间。
Are you overlooking one of the secrets of success? Better check. It's fine to put "The" before the number if you really believe you've made an exhaustive list. But evidence suggests most things with titles like this are linkbait. The greatest weakness of the list of n things is that there's so little room for new thought. The main point of essay writing, when done right, is the new ideas you have while doing it. A real essay, as the name implies, is dynamic: you don't know what you're going to write when you start. It will be about whatever you discover in the course of writing it. This can only happen in a very limited way in a list of n things. You make the title first, and that's what it's going to be about. You can't have more new ideas in the writing than will fit in the watertight compartments you set up initially. And your brain seems to know this: because you don't have room for new ideas, you don't have them. Another advantage of admitting to beginning writers that the 5 paragraph essay is really a list of n things is that we can warn them about this. It only lets you experience the defining characteristic of essay writing on a small scale: in thoughts of a sentence or two. And it's particularly dangerous that the 5 paragraph essay buries the list of n things within something that looks like a more sophisticated type of essay. If you don't know you're using this form, you don't know you need to escape it. Notes [1] Articles of this type are also startlingly popular on Delicious, but I think that's because delicious/popular is driven by bookmarking, not because Delicious users are stupid. Delicious users are collectors, and a list of n things seems particularly collectible because it's a collection itself. [2] Most "word problems" in school math textbooks are similarly misleading.
作为最简单的文体,N件事清单本应是初学者的理想选择。事实上,传统的五段式议论文正是n=3的清单变体。但学生不知道自己在用《时尚》杂志的结构,只是被要求用多余过渡语("此外...")掩盖裂痕,并套上首尾段落伪装成正经议论文。
让学生从N件事清单起步本无不可,但为何不光明正大地教?何不让他们像专业人士那样,直接写出带编号、无过渡、无"结论"的清单?
唯有一种情况会使N件事清单沦为欺诈:当标题虚假宣称清单具有穷尽性时。比如《成功的7大秘诀》这类标题就像侦探小说般引发条件反射——你至少得看看是否与自己列出的7点一致,以免漏掉某个成功秘诀。若真相信自己的清单具有穷尽性,冠以"七大"未尝不可,但证据表明这类标题多为诱饵链接。
They look superficially like the application of math to real problems, but they're not. So if anything they reinforce the impression that math is merely a complicated but pointless collection of stuff to be memorized.
N件事清单的最大缺陷在于难容新思想。优秀议论文的精髓恰在于写作过程中萌发的新观点。正如"essay"本意所示,真正的议论文是动态的——你动笔时并不确知终稿内容,它关乎你在写作中的发现。
在N件事清单中,这种发现极其有限。你先定下标题,内容就被框定。大脑似乎明白这点:既然没有容纳新思想的空间,也就不会产生新思想。
若坦率告诉初学者五段式议论文实为N件事清单,我们还能警示其局限:它只允许你在单句层面体验议论文的本质特征。更危险的是,五段式将清单伪装成高级议论文。若不自知正在使用这种形式,你就不会意识到需要突破它。
Want to start a startup? Get funded by Y Combinator.
September 2009 Like all investors, we spend a lot of time trying to learn how to predict which startups will succeed. We probably spend more time thinking about it than most, because we invest the earliest. Prediction is usually all we have to rely on. We learned quickly that the most important predictor of success is determination. At first we thought it might be intelligence. Everyone likes to believe that's what makes startups succeed. It makes a better story that a company won because its founders were so smart. The PR people and reporters who spread such stories probably believe them themselves. But while it certainly helps to be smart, it's not the deciding factor. There are plenty of people as smart as Bill Gates who achieve nothing. In most domains, talent is overrated compared to determination—partly because it makes a better story, partly because it gives onlookers an excuse for being lazy, and partly because after a while determination starts to look like talent. I can't think of any field in which determination is overrated, but the relative importance of determination and talent probably do vary somewhat. Talent probably matters more in types of work that are purer, in the sense that one is solving mostly a single type of problem instead of many different types. I suspect determination would not take you as far in math as it would in, say, organized crime. I don't mean to suggest by this comparison that types of work that depend more on talent are always more admirable. Most people would agree it's more admirable to be good at math than memorizing long strings of digits, even though the latter depends more on natural ability. Perhaps one reason people believe startup founders win by being smarter is that intelligence does matter more in technology startups than it used to in earlier types of companies.
You probably do need to be a bit smarter to dominate Internet search than you had to be to dominate railroads or hotels or newspapers. And that's probably an ongoing trend. But even in the highest of high tech industries, success still depends more on determination than brains. If determination is so important, can we isolate its components? Are some more important than others? Are there some you can cultivate? The simplest form of determination is sheer willfulness. When you want something, you must have it, no matter what. A good deal of willfulness must be inborn, because it's common to see families where one sibling has much more of it than another. Circumstances can alter it, but at the high end of the scale, nature seems to be more important than nurture. Bad circumstances can break the spirit of a strong-willed person, but I don't think there's much you can do to make a weak-willed person stronger-willed. Being strong-willed is not enough, however. You also have to be hard on yourself. Someone who was strong-willed but self-indulgent would not be called determined. Determination implies your willfulness is balanced by discipline. That word balance is a significant one. The more willful you are, the more disciplined you have to be. The stronger your will, the less anyone will be able to argue with you except yourself. And someone has to argue with you, because everyone has base impulses, and if you have more will than discipline you'll just give into them and end up on a local maximum like drug addiction. We can imagine will and discipline as two fingers squeezing a slippery melon seed. The harder they squeeze, the further the seed flies, but they must both squeeze equally or the seed spins off sideways. If this is true it has interesting implications, because discipline can be cultivated, and in fact does tend to vary quite a lot in the course of an individual's life.
If determination is effectively the product of will and discipline, then you can become more determined by being more disciplined. [1] Another consequence of the melon seed model is that the more willful you are, the more dangerous it is to be undisciplined. There seem to be plenty of examples to confirm that. In some very energetic people's lives you see something like wing flutter, where they alternate between doing great work and doing absolutely nothing. Externally this would look a lot like bipolar disorder. The melon seed model is inaccurate in at least one respect, however: it's static. In fact the dangers of indiscipline increase with temptation. Which means, interestingly, that determination tends to erode itself. If you're sufficiently determined to achieve great things, this will probably increase the number of temptations around you. Unless you become proportionally more disciplined, willfulness will then get the upper hand, and your achievement will revert to the mean. That's why Shakespeare's Caesar thought thin men so dangerous. They weren't tempted by the minor perquisites of power. The melon seed model implies it's possible to be too disciplined. Is it? I think there probably are people whose willfulness is crushed down by excessive discipline, and who would achieve more if they weren't so hard on themselves. One reason the young sometimes succeed where the old fail is that they don't realize how incompetent they are. This lets them do a kind of deficit spending. When they first start working on something, they overrate their achievements. But that gives them confidence to keep working, and their performance improves. Whereas someone clearer-eyed would see their initial incompetence for what it was, and perhaps be discouraged from continuing. There's one other major component of determination: ambition. If willfulness and discipline are what get you to your destination, ambition is how you choose it.
I don't know if it's exactly right to say that ambition is a component of determination, but they're not entirely orthogonal. It would seem a misnomer if someone said they were very determined to do something trivially easy. And fortunately ambition seems to be quite malleable; there's a lot you can do to increase it. Most people don't know how ambitious to be, especially when they're young. They don't know what's hard, or what they're capable of. And this problem is exacerbated by having few peers. Ambitious people are rare, so if everyone is mixed together randomly, as they tend to be early in people's lives, then the ambitious ones won't have many ambitious peers. When you take people like this and put them together with other ambitious people, they bloom like dying plants given water. Probably most ambitious people are starved for the sort of encouragement they'd get from ambitious peers, whatever their age. [2] Achievements also tend to increase your ambition. With each step you gain confidence to stretch further next time. So here in sum is how determination seems to work: it consists of willfulness balanced with discipline, aimed by ambition. And fortunately at least two of these three qualities can be cultivated. You may be able to increase your strength of will somewhat; you can definitely learn self-discipline; and almost everyone is practically malnourished when it comes to ambition. I feel like I understand determination a bit better now. But only a bit: willfulness, discipline, and ambition are all concepts almost as complicated as determination. [3] Note too that determination and talent are not the whole story. There's a third factor in achievement: how much you like the work. If you really love working on something, you don't need determination to drive you; it's what you'd do anyway.
But most types of work have aspects one doesn't like, because most types of work consist of doing things for other people, and it's very unlikely that the tasks imposed by their needs will happen to align exactly with what you want to do. Indeed, if you want to create the most wealth, the way to do it is to focus more on their needs than your interests, and make up the difference with determination. Notes [1] Loosely speaking. What I'm claiming with the melon seed model is more like determination is proportionate to wd^m - k|w - d|^n, where w is will and d discipline. [2] Which means one of the best ways to help a society generally is to create events and institutions that bring ambitious people together. It's like pulling the control rods out of a reactor: the energy they emit encourages other ambitious people, instead of being absorbed by the normal people they're usually surrounded with. Conversely, it's probably a mistake to do as some European countries have done and try to ensure none of your universities is significantly better than the others. [3] For example, willfulness clearly has two subcomponents, stubbornness and energy. The first alone yields someone who's stubbornly inert. The second alone yields someone flighty. As willful people get older or otherwise lose their energy, they tend to become merely stubborn. Thanks to Sam Altman, Jessica Livingston, and Robert Morris for reading drafts of this.
Italian Translation | Portuguese Translation Russian Translation.
想创业吗? 获得Y Combinator的资助。
2009年9月 和所有投资者一样,我们花费大量时间试图预测哪些初创企业会成功。由于我们投资阶段最早,可能比大多数人思考得更深入。在早期阶段,预测往往是我们唯一的依据。 我们很快发现,成功最重要的预测因素是决心。起初我们以为是智力——人们总愿意相信聪明才智造就成功。创始人因智慧取胜的故事更吸引人,传播这些故事的公关人员和记者或许自己也深信不疑。但尽管聪明确有助益,却非决定性因素。世界上有无数和比尔·盖茨同等聪明的人碌碌无为。 在多数领域,相比决心,天赋往往被高估——部分因为天赋论更动听,部分因为它为旁观者的懒惰提供借口,还有部分原因是长期坚持的决心里程会逐渐显现出天赋的光辉。 我找不到任何低估决心的领域,但决心与天赋的相对重要性确实因领域而异。在更"纯粹"的工作类型中(指主要解决单一问题而非多种问题),天赋可能更重要。比如在数学领域,决心的作用可能远不如在有组织犯罪中显著。 这个类比并非暗示依赖天赋的工作更值得敬佩。多数人会认同擅长数学比记忆长串数字更令人钦佩,尽管后者更依赖天生能力。 人们认为初创企业创始人靠聪明取胜的原因之一,或许是智力在科技创业中的确比传统行业更重要。称霸互联网搜索确实需要比主导铁路、酒店或报业更高的智商。这种趋势可能持续存在。但即便在高科技行业,成功仍更依赖决心而非脑力。 既然决心如此重要,能否剖析其构成要素?哪些更为关键?哪些可以培养? 决心的最简形式是纯粹意志力。当你渴望某物时,无论如何都要得到它。 意志力多半与生俱来,常见于某些家庭成员间差异。环境能改变它,但在高强度区间,天性似乎比后天培养更重要。恶劣环境可能摧毁坚强意志,但我认为很难让意志薄弱者变得坚强。 仅有坚强意志并不够,还需严于律己。意志坚强却放纵自我者不配称为"坚定"。决心意味着意志力与自律的平衡。 "平衡"这个词至关重要。意志越强,所需自律越多。当你的意志强大到无人能反驳时,唯有自我约束能制衡——因为人人都有原始冲动,若意志压倒自律,终将沉溺于毒品成瘾这类局部最优解。 我们可以将意志与自律想象成挤压瓜子的两指。力度越大,瓜子飞得越远,但必须施力均衡否则瓜子会偏离。 这个模型的有趣之处在于:自律可以培养,且个人一生中变化显著。若决心本质是意志与自律的乘积,那么通过提升自律就能增强决心。[1] 瓜子模型的另一推论是:意志越强,缺乏自律越危险。现实中不乏例证。某些精力充沛者的人生呈现"机翼震颤"现象,在卓越工作与彻底懈怠间摇摆,外部观察极似躁郁症。 但瓜子模型至少有一处不准确:它是静态的。实际上,诱惑越强,放纵的危害越大。这意味着决心会自我侵蚀——若你足够坚定去成就伟业,周围诱惑必然增多。除非自律同步提升,否则意志终将失控,成就回归平庸。 这正是莎士比亚笔下凯撒认为瘦子危险的原因:他们不受权力小恩惠的诱惑。 瓜子模型暗示过度自律可能适得其反。确有其人:被严苛自律压抑意志者,若稍减自我苛责或能成就更多。年轻人有时成功而长者失败,正因他们未察觉自身无能。这让他们能进行某种"赤字运营":初涉领域时高估成就,却因此获得持续动力直至真正提升。而清醒者可能被初始无能劝退。 决心还有另一关键要素:野心。如果说意志力与自律是引擎,野心就是导航仪。 将野心归为决心组成部分或许不够严谨,但二者绝非正交关系。若有人声称坚决要做微不足道之事,这种决心显然名不副实。 所幸野心极具可塑性。多数人不知该怀抱多大野心,尤其在年轻时。他们既不了解事情难度,也不清楚自身潜力。当缺乏同类参照时,这个问题更严重——野心家本就稀少,若早期随机混居,便难遇同道中人。将这类人聚集时,他们如久旱逢霖般焕发生机。任何年龄的野心家,都渴望来自同类的激励。[2] 成就能滋养野心。每一步突破都拓展下一次尝试的勇气。 综上所述,决心的运作机制是:以野心为导向,意志与自律动态平衡。幸运的是,这三者中至少两项可培养——意志力或能增强,自律绝对可习得,而绝大多数人正遭受野心的"营养不良"。 现在我似乎稍懂决心了。但只是稍懂:意志力、自律和野心本身都是与决心同样复杂的概念。[3] 需注意决心与天赋并非全部。成就还有第三要素:对工作的热爱。若真正热爱某事,你不需要决心驱动——这本就是你的生命冲动。但多数工作包含为他人服务的成分,需求强加的任务很难完全契合个人意愿。 事实上,若要创造最大财富,就该更关注他人需求而非个人兴趣,用决心填补其间的鸿沟。 注释 [1] 粗略而言。瓜子模型更精确的表达应是:决心正比于wd^m - k|w - d|^n,其中w代表意志,d代表自律。 [2] 这意味着提升社会整体水平的最佳方式之一,是创建汇聚野心家的活动与机构。这如同抽出核反应堆的控制棒:他们释放的能量将激励其他野心家,而非被周遭普通人吸收。 反观某些欧洲国家试图拉平大学差距的政策,恐怕是种谬误。 [3] 例如意志力明显包含固执与活力两个子项。仅有前者造就顽固的惰性,仅有后者形成浮躁的性格。当意志坚定者年老力衰时,往往退化为单纯固执。 致谢 Sam Altman、Jessica Livingston和Robert Morris对本文初稿的审阅。
September 2009 When meeting people you don't know very well, the convention is to seem extra friendly. You smile and say "pleased to meet you," whether you are or not. There's nothing dishonest about this. Everyone knows that these little social lies aren't meant to be taken literally, just as everyone knows that "Can you pass the salt?" is only grammatically a question. I'm perfectly willing to smile and say "pleased to meet you" when meeting new people. But there is another set of customs for being ingratiating in print that are not so harmless. The reason there's a convention of being ingratiating in print is that most essays are written to persuade. And as any politician could tell you, the way to persuade people is not just to baldly state the facts. You have to add a spoonful of sugar to make the medicine go down. For example, a politician announcing the cancellation of a government program will not merely say "The program is canceled." That would seem offensively curt. Instead he'll spend most of his time talking about the noble effort made by the people who worked on it. The reason these conventions are more dangerous is that they interact with the ideas. Saying "pleased to meet you" is just something you prepend to a conversation, but the sort of spin added by politicians is woven through it. We're starting to move from social lies to real lies. Here's an example of a paragraph from an essay I wrote about labor unions. As written, it tends to offend people who like unions. > People who think the labor movement was the creation of heroic union organizers have a problem to explain: why are unions shrinking now? The best they can do is fall back on the default explanation of people living in fallen civilizations. Our ancestors were giants. The workers of the early twentieth century must have had a moral courage that's lacking today.
2009年9月 初次见面时,人们通常会表现得格外友好。无论是否真心,你都会微笑着说"很高兴认识你"。这并非虚伪——就像"能把盐递过来吗?"在语法上是疑问句,但实际是请求一样,这些社交辞令本就不该按字面理解。
面对陌生人时,我完全愿意微笑致意。但书面文字中那些曲意逢迎的惯例,危害性就大得多。
这种惯例源于多数文章旨在说服。正如政客所知,说服不能只靠平铺直叙,必须像苦药裹糖衣般加工。例如宣布取消政府项目时,政客绝不会只说"项目终止",那显得粗鲁无礼。他会用大部分篇幅歌颂项目人员的辛勤付出。
Now here's the same paragraph rewritten to please instead of offending them:
这类惯例更危险之处在于会扭曲观点。"很高兴认识你"只是对话开场白,但政客式话术会渗透全文实质。我们正从社交谎言滑向真实谎言。
以我讨论工会运动的段落为例,原文容易激怒工会支持者:
> 认为劳工运动全靠工会组织者英雄壮举的人需要解释:为何如今工会日渐式微?他们最多只能搬出文明衰落的陈词——先辈都是巨人,二十世纪初的工人必有今人缺乏的道德勇气。
以下是讨好而非冒犯的改写版:
> Early union organizers made heroic sacrifices to improve conditions for workers. But though labor unions are shrinking now, it's not because present union leaders are any less courageous. An employer couldn't get away with hiring thugs to beat up union leaders today, but if they did, I see no reason to believe today's union leaders would shrink from the challenge. So I think it would be a mistake to attribute the decline of unions to some kind of decline in the people who run them. Early union leaders were heroic, certainly, but we should not suppose that if unions have declined, it's because present union leaders are somehow inferior. The cause must be external. [1]
> 早期工会组织者确曾为改善工人境遇英勇奋斗。但如今工会萎缩,并非现任领导者缺乏勇气。现今雇主若雇暴徒殴打工会领袖必遭严惩,即便如此,我相信当代工会领袖同样不会退缩。因此将工会衰落归咎于领导者素质下降有失公允。早期工会领袖固然英勇,但若认为工会衰落源于现任者能力不足,这种推断并不合理。根源必在外部。[1]
这同样说明了一个观点:早期工会组织者的个人品质并非工会成功的关键,必然存在某种外部因素,否则当今的工会领袖就只能是能力低下之辈。但以这种方式表述时,它更像是对当今工会组织者的辩护,而非对早期工会领袖的抨击。这种写法对工会支持者更具说服力,因为它显得对其事业抱有同情。
我完全相信第二版写的内容。早期工会领袖确实做出了英勇牺牲。而当今工会领袖在必要时很可能也会挺身而出——人性本就如此,我对所谓"最伟大的一代"的说法持怀疑态度。
既然我认同第二版的所有观点,为何不采用那种写法?何必无谓地冒犯他人?
It makes the same point: that it can't have been the personal qualities of early union organizers that made unions successful, but must have been some external factor, or otherwise present-day union leaders would have to be inferior people. But written this way it seems like a defense of present-day union organizers rather than an attack on early ones. That makes it more persuasive to people who like unions, because it seems sympathetic to their cause. I believe everything I wrote in the second version. Early union leaders did make heroic sacrifices. And present union leaders probably would rise to the occasion if necessary. People tend to; I'm skeptical about the idea of "the greatest generation." [2] If I believe everything I said in the second version, why didn't I write it that way? Why offend people needlessly? Because I'd rather offend people than pander to them, and if you write about controversial topics you have to choose one or the other. The degree of courage of past or present union leaders is beside the point; all that matters for the argument is that they're the same. But if you want to please people who are mistaken, you can't simply tell the truth. You're always going to have to add some sort of padding to protect their misconceptions from bumping against reality. Most writers do. Most writers write to persuade, if only out of habit or politeness. But I don't write to persuade; I write to figure out. I write to persuade a hypothetical perfectly unbiased reader. Since the custom is to write to persuade the actual reader, someone who doesn't will seem arrogant. In fact, worse than arrogant: since readers are used to essays that try to please someone, an essay that displeases one side in a dispute reads as an attempt to pander to the other. To a lot of pro-union readers, the first paragraph sounds like the sort of thing a right-wing radio talk show host would say to stir up his followers. But it's not.
因为我宁愿冒犯读者也不愿曲意逢迎,撰写争议性话题时你必须二选一。历代工会领袖的勇气程度并非重点,论证的核心只在于他们本质相同。但若想取悦认知错误的人群,你就无法直陈真相——必须添加缓冲剂来保护他们的谬见免受现实冲击。
多数作家确实如此。多数写作旨在说服,哪怕只是出于习惯或礼貌。但我的写作不为说服,而为探索。我为假想中绝对公正的读者而写。
当惯例是取悦实际读者时,反其道者就显得傲慢。事实上比傲慢更糟:由于读者习惯了讨好性的文章,当某篇文字触怒争议一方时,就会被解读成是在谄媚另一方。对许多工会支持者而言,第一段听起来就像右翼电台主持人煽动听众的言论。但事实并非如此——直截了当否定信念的论述,往往难以与党派攻击区分,尽管二者效果相似,根源却不同。
多加几句安抚性话语真有那么糟糕吗?或许未必。可能我过分执着于简洁。我写代码与写文章如出一辙,反复删削直至无可删减。但这有正当理由:唯有精简到极致,你才能真正把握思想内核。
Something that curtly contradicts one's beliefs can be hard to distinguish from a partisan attack on them, but though they can end up in the same place they come from different sources. Would it be so bad to add a few extra words, to make people feel better? Maybe not. Maybe I'm excessively attached to conciseness. I write code the same way I write essays, making pass after pass looking for anything I can cut. But I have a legitimate reason for doing this. You don't know what the ideas are until you get them down to the fewest words. [3] The danger of the second paragraph is not merely that it's longer. It's that you start to lie to yourself. The ideas start to get mixed together with the spin you've added to get them past the readers' misconceptions. I think the goal of an essay should be to discover surprising things. That's my goal, at least. And most surprising means most different from what people currently believe. So writing to persuade and writing to discover are diametrically opposed. The more your conclusions disagree with readers' present beliefs, the more effort you'll have to expend on selling your ideas rather than having them. As you accelerate, this drag increases, till eventually you reach a point where 100% of your energy is devoted to overcoming it and you can't go any faster. It's hard enough to overcome one's own misconceptions without having to think about how to get the resulting ideas past other people's. I worry that if I wrote to persuade, I'd start to shy away unconsciously from ideas I knew would be hard to sell. When I notice something surprising, it's usually very faint at first. There's nothing more than a slight stirring of discomfort. I don't want anything to get in the way of noticing it consciously. Notes [1] I had a strange feeling of being back in high school writing this.
第二段的危险不仅在于冗长,更在于你会开始自我欺骗。思想开始与你为绕过读者偏见而添加的粉饰纠缠不清。
我认为文章的目标应是发现令人惊奇的洞见。至少这是我的追求。而最惊人的洞见往往与主流认知截然相反。因此说服性写作与探索性写作根本对立。你的结论与读者现有信念分歧越大,耗费在推销观点而非形成观点上的精力就越多。如同加速时的空气阻力,这种消耗持续增加,直至你全部精力都用于克服阻力而无法继续前进。
克服自身谬见已属不易,更遑论还要考虑如何让他人接受由此产生的思想。我担心若为说服而写作,会不自觉地回避那些难以推销的洞见。当我察觉惊人之处时,最初往往只是隐约的不适感。我不愿有任何事物阻碍这种意识的觉醒。
[1] 写作时有种重回高中的怪异感。要拿高分就必须既写出符合期待的陈词滥调,又要显得深信不疑。解决方法是一种方法派表演。重新陷入这种状态令人作呕地熟悉。
To get a good grade you had to both write the sort of pious crap you were expected to, but also seem to be writing with conviction. The solution was a kind of method acting. It was revoltingly familiar to slip back into it. [2] Exercise for the reader: rephrase that thought to please the same people the first version would offend. [3] Come to think of it, there is one way in which I deliberately pander to readers, because it doesn't change the number of words: I switch person. This flattering distinction seems so natural to the average reader that they probably don't notice even when I switch in mid-sentence, though you tend to notice when it's done as conspicuously as this. Thanks to Jessica Livingston and Robert Morris for reading drafts of this. Note: An earlier version of this essay began by talking about why people dislike Michael Arrington. I now believe that was mistaken, and that most people don't dislike him for the same reason I did when I first met him, but simply because he writes about controversial things..
[2] 读者练习:用取悦第一版冒犯对象的方式重述这个观点。
[3] 细想之下,我确实会刻意迎合读者一处,因其不增减字数:人称转换。这种讨巧的区分对普通读者如此自然,甚至当我句中切换时他们都难以察觉,尽管像这样明显转换时你们总会注意到。
致谢 Jessica Livingston和Robert Morris审阅了本文草稿。
附记 本文早期版本开篇探讨人们为何不喜欢Michael Arrington。现在我意识到那是个错误——多数人不像我初次见他时那样反感他,单纯只因他常写争议性话题。
August 2009 Kate Courteau is the architect who designed Y Combinator's office. Recently we managed to recruit her to help us run YC when she's not busy with architectural projects. Though she'd heard a lot about YC since the beginning, the last 9 months have been a total immersion. I've been around the startup world for so long that it seems normal to me, so I was curious to hear what had surprised her most about it. This was her list: 1\. How many startups fail. Kate knew in principle that startups were very risky, but she was surprised to see how constant the threat of failure was — not just for the minnows, but even for the famous startups whose founders came to speak at YC dinners. 2\. How much startups' ideas change. As usual, by Demo Day about half the startups were doing something significantly different than they started with. We encourage that. Starting a startup is like science in that you have to follow the truth wherever it leads. In the rest of the world, people don't start things till they're sure what they want to do, and once started they tend to continue on their initial path even if it's mistaken. 3\. How little money it can take to start a startup. In Kate's world, everything is still physical and expensive. You can barely renovate a bathroom for the cost of starting a startup. 4\. How scrappy founders are. That was her actual word. I agree with her, but till she mentioned this it never occurred to me how little this quality is appreciated in most of the rest of the world. It wouldn't be a compliment in most organizations to call someone scrappy. What does it mean, exactly? It's basically the diminutive form of belligerent. Someone who's scrappy manages to be both threatening and undignified at the same time. Which seems to me exactly what one would want to be, in any kind of work.
If you're not threatening, you're probably not doing anything new, and dignity is merely a sort of plaque. 5\. How tech-saturated Silicon Valley is. "It seems like everybody here is in the industry." That isn't literally true, but there is a qualitative difference between Silicon Valley and other places. You tend to keep your voice down, because there's a good chance the person at the next table would know some of the people you're talking about. I never felt that in Boston. The good news is, there's also a good chance the person at the next table could help you in some way. 6\. That the speakers at YC were so consistent in their advice. Actually, I've noticed this too. I always worry the speakers will put us in an embarrassing position by contradicting what we tell the startups, but it happens surprisingly rarely. When I asked her what specific things she remembered speakers always saying, she mentioned: that the way to succeed was to launch something fast, listen to users, and then iterate; that startups required resilience because they were always an emotional rollercoaster; and that most VCs were sheep. I've been impressed by how consistently the speakers advocate launching fast and iterating. That was contrarian advice 10 years ago, but it's clearly now the established practice. 7\. How casual successful startup founders are. Most of the famous founders in Silicon Valley are people you'd overlook on the street. It's not merely that they don't dress up. They don't project any kind of aura of power either. "They're not trying to impress anyone." Interestingly, while Kate said that she could never pick out successful founders, she could recognize VCs, both by the way they dressed and the way they carried themselves. 8\.
How important it is for founders to have people to ask for advice. (I swear I didn't prompt this one.) Without advice "they'd just be sort of lost." Fortunately, there are a lot of people to help them. There's a strong tradition within YC of helping other YC-funded startups. But we didn't invent that idea: it's just a slightly more concentrated form of existing Valley culture. 9\. What a solitary task startups are. Architects are constantly interacting face to face with other people, whereas doing a technology startup, at least, tends to require long stretches of uninterrupted time to work. "You could do it in a box." By inverting this list, we can get a portrait of the "normal" world. It's populated by people who talk a lot with one another as they work slowly but harmoniously on conservative, expensive projects whose destinations are decided in advance, and who carefully adjust their manner to reflect their position in the hierarchy. That's also a fairly accurate description of the past. So startup culture may not merely be different in the way you'd expect any subculture to be, but a leading indicator.
2009年8月 凯特·库尔托是Y Combinator办公室的设计师。最近我们成功招募她在不忙建筑项目时协助运营YC。虽然她从一开始就听过许多关于YC的事,但过去9个月才是真正的沉浸式体验。 我在创业世界待得太久,早已习以为常,所以很好奇她最惊讶的是什么。以下是她的观察清单: 1. 创业失败率之高 凯特理论上知道创业风险很大,但令她震惊的是失败威胁如影随形——不仅对小公司如此,就连那些创始人受邀来YC晚宴演讲的知名初创企业也不例外。 2. 创业方向的剧烈变化 到Demo Day时,约半数团队做的项目与最初设想已大相径庭。我们鼓励这种转变。创业如同科学探索,必须追随真相指引。在其他领域,人们总要万事俱备才行动,而一旦开始即便发现错误也倾向于坚持原路。 3. 创业所需的资金之少 在凯特的建筑领域,所有事物都涉及实体且造价高昂。改造一个浴室的费用就抵得上创办一家初创企业。 4. 创始人的草根韧性 这是她的原话。我完全赞同,但此前从未意识到这种特质在其他领域多么不被赏识。在多数机构里,形容某人"草根"可不算恭维。 具体指什么?本质上是"好斗"的温和版。草根创业者能同时兼具威胁性与不修边幅的特质——在我看来这正是任何工作中都该追求的。若不具备威胁性,可能意味着缺乏创新;而所谓体面不过是层枷锁。 5. 硅谷的技术浓度 "这里好像人人都在科技行业。"虽非字面事实,但硅谷与其他地区存在质的不同。你会不自觉压低声音,因为邻桌很可能认识你谈论的对象。在波士顿从未有此感受。好消息是,邻桌也很有可能为你提供帮助。 6. YC演讲者的建议高度一致 其实我也注意到这点。总担心演讲者会与我们的指导相左而引发尴尬,但这种情况极少发生。 被问及具体有哪些反复出现的建议时,她提到:成功之道在于快速发布产品→倾听用户→迭代优化;创业需要韧性因为情绪常如过山车;以及大多数风投都是跟风者。 演讲者始终强调快速迭代令我印象深刻。这在十年前还是反主流建议,如今显然已成行业准则。 7. 成功创始人的随性程度 硅谷多数知名创始人走在街上毫不起眼。他们不仅衣着随意,也不刻意彰显权力气场。"他们不需要取悦任何人。" 有趣的是,凯特说她虽无法辨别成功创始人,却能认出风投人士——通过他们的着装和举止。 8. 创始人获取建议的重要性 (我发誓没暗示这点)没有建议"他们就像迷途羔羊"。幸运的是,这里有大量愿意帮忙的人。YC内部有互相帮助的深厚传统,但这并非我们的发明,只是对硅谷现有文化的浓缩强化。 9. 创业是何等孤独的事业 建筑师需要持续面对面协作,而科技创业至少需要大块不间断工作时间。"你在封闭盒子裡也能完成。" 将此清单反向解读,便能勾勒出"常规"世界的画像:那里的人们缓慢而和谐地推进着预算高昂、目标既定的保守项目,工作中频繁交谈,并精心调整举止以匹配自身阶层定位。 这也是对过去的准确描述。因此创业文化可能不仅是亚文化的差异体现,更是一种前沿指标。
July 2009 The Segway hasn't delivered on its initial promise, to put it mildly. There are several reasons why, but one is that people don't want to be seen riding them. Someone riding a Segway looks like a dork. My friend Trevor Blackwell built his own Segway, which we called the Segwell. He also built a one-wheeled version, the Eunicycle, which looks exactly like a regular unicycle till you realize the rider isn't pedaling. He has ridden them both to downtown Mountain View to get coffee. When he rides the Eunicycle, people smile at him. But when he rides the Segwell, they shout abuse from their cars: "Too lazy to walk, ya fuckin homo?" Why do Segways provoke this reaction? The reason you look like a dork riding a Segway is that you look _smug_. You don't seem to be working hard enough. Someone riding a motorcycle isn't working any harder. But because he's sitting astride it, he seems to be making an effort. When you're riding a Segway you're just standing there. And someone who's being whisked along while seeming to do no work — someone in a sedan chair, for example — can't help but look smug. Try this thought experiment and it becomes clear: imagine something that worked like the Segway, but that you rode with one foot in front of the other, like a skateboard. That wouldn't seem nearly as uncool. So there may be a way to capture more of the market Segway hoped to reach: make a version that doesn't look so easy for the rider. It would also be helpful if the styling was in the tradition of skateboards or bicycles rather than medical devices. Curiously enough, what got Segway into this problem was that the company was itself a kind of Segway. It was too easy for them; they were too successful raising money.
2009年7月 委婉地说,赛格威(Segway)并未兑现其最初的承诺。原因有多方面,其中之一是人们不愿意被人看到骑它。骑赛格威的人看起来像个呆子。
我的朋友特雷弗·布莱克韦尔(Trevor Blackwell)自制了一台赛格威,我们称之为“赛格威尔”(Segwell)。他还造了一个单轮版本——“优尼赛克”(Eunicycle),乍看和普通独轮车无异,直到你发现骑手并没有踩踏板。他曾骑着这两样东西去山景城(Mountain View)市中心买咖啡。骑优尼赛克时,路人会对他微笑;但骑赛格威尔时,车里的人会冲他辱骂:“懒得走路吗,你这该死的基佬?”
为什么赛格威会引发这种反应?骑它显得呆板,是因为你看上去很得意。你似乎不够卖力。
If they'd had to grow the company gradually, by iterating through several versions they sold to real users, they'd have learned pretty quickly that people looked stupid riding them. Instead they had enough to work in secret. They had focus groups aplenty, I'm sure, but they didn't have the people yelling insults out of cars. So they never realized they were zooming confidently down a blind alley..
骑摩托车的人也没多费劲。但因为他跨坐在车上,就显得在用力。而骑赛格威时,你只是站着。一个看似毫不费力就被带着走的人——比如坐轿子的——难免显得得意。
做个思维实验就明白了:想象一种功能类似赛格威,但需要像滑板那样前后脚站立的交通工具。那样就不会显得那么不酷了。
所以,或许有一种方法能赢得更多赛格威原本希望占领的市场:做一个让骑手看起来不那么轻松的版本。如果设计风格能延续滑板或自行车的传统,而非医疗设备,也会有所帮助。
耐人寻味的是,赛格威公司陷入这一困境的原因在于,它本身就像一台赛格威。对他们来说太容易了;他们融资太顺利了。如果不得不逐步发展公司,通过向真实用户迭代多个版本,他们本会很快发现人们骑起来显得愚蠢。但他们有足够的资本秘密研发。他们肯定做过大量焦点小组测试,但没遇到过从车里骂街的人。因此,他们从未意识到自己正信心十足地冲进死胡同。
Want to start a startup? Get funded by Y Combinator.
July 2009 Now that the term "ramen profitable" has become widespread, I ought to explain precisely what the idea entails. Ramen profitable means a startup makes just enough to pay the founders' living expenses. This is a different form of profitability than startups have traditionally aimed for. Traditional profitability means a big bet is finally paying off, whereas the main importance of ramen profitability is that it buys you time. [1] In the past, a startup would usually become profitable only after raising and spending quite a lot of money. A company making computer hardware might not become profitable for 5 years, during which they spent $50 million. But when they did they might have revenues of $50 million a year. This kind of profitability means the startup has succeeded. Ramen profitability is the other extreme: a startup that becomes profitable after 2 months, even though its revenues are only $3000 a month, because the only employees are a couple 25 year old founders who can live on practically nothing. Revenues of $3000 a month do not mean the company has succeeded. But it does share something with the one that's profitable in the traditional way: they don't need to raise money to survive. Ramen profitability is an unfamiliar idea to most people because it only recently became feasible. It's still not feasible for a lot of startups; it would not be for most biotech startups, for example; but it is for many software startups because they're now so cheap. For many, the only real cost is the founders' living expenses. The main significance of this type of profitability is that you're no longer at the mercy of investors. If you're still losing money, then eventually you'll either have to raise more or shut down. Once you're ramen profitable this painful choice goes away.
想创办一家初创公司? 获得 Y Combinator 的资助。
2009年7月 既然“拉面盈利”这个概念已经广为流传,我有必要准确解释其含义。 拉面盈利指的是初创公司的收入仅够支付创始人的基本生活开支。这与传统初创公司追求的盈利模式不同。传统盈利意味着巨额投入终获回报,而拉面盈利的核心价值在于为你争取时间。[1] 过去,初创公司通常需要筹集并消耗大量资金后才能实现盈利。一家硬件公司可能五年内烧掉5000万美元才实现年收入5000万美元的盈利。这种盈利标志着公司的成功。 拉面盈利则是另一个极端:初创公司仅用两个月就实现每月3000美元的盈利,因为创始人只是两个生活成本极低的25岁年轻人。虽然月入3000美元不算成功,但它与传统盈利公司有个共同点:不再需要依赖融资生存。 这个概念对多数人很陌生,因为它最近才成为可能。许多领域(如生物科技)仍无法实现,但对软件初创公司而言,如今极低的成本使其可行——往往唯一的成本就是创始人的生活费。 这种盈利模式的最大意义在于摆脱对投资人的依赖。持续亏损终将迫使你融资或倒闭,而拉面盈利能消除这种痛苦抉择。你仍可融资,但不必迫在眉睫。
最直接的优势是能获得更有利的融资条款。当投资人知道你需要钱时,可能会趁机压价,甚至故意拖延——因为他们清楚资金枯竭会让你妥协。 拉面盈利还有三个隐性优势: 1. 增强投资吸引力:微薄盈利证明你(a)能让用户付费(b)专注解决真实需求(c)具备控制成本的能力。这消除了投资人最担心的三个问题:产品无人买单、解决伪需求、资金耗尽前未能盈利。 2. 提振团队士气:初创初期公司如同纸上概念。当收入覆盖生活费时,未来状态瞬间切换——生存成为默认选项。这种信心加持至关重要,因为创业最大的障碍正是责任重压。 3. 保持专注:最不显眼却最关键的优势是无需中断工作去融资。融资会严重分散精力——效率往往降至三分之一,且持续数月。我曾亲历此过程:即便顺利融资,处理细节期间几乎无法推进实际工作。若能自主选择融资时机,就能避开关键产品周期。
需澄清两点误解: 1. 拉面盈利≠完全拒绝融资。事实上,多数成功初创都接受过投资。 2. 不同于Joe Kraus主张的"产品测试期同步测试商业模式",拉面盈利不要求立即验证终极商业模式。例如谷歌早期通过向雅虎授权搜索技术盈利。 潜在风险是可能沦为咨询公司。咨询业务虽易达月入3000美元,但违背了初创公司通过标准化产品快速扩张的本质。初期可承接少量定制项目,但要牢记:拉面盈利只是避免中途死亡的手段,真正目标是实现规模增长。 注释 [1] "拉面"指廉价速食面,但请勿字面理解——长期食用并不健康。建议选择米豆为主食,配方如下(2人份): 橄榄油或黄油 n个黄洋葱 时令蔬菜(自由搭配) 3n瓣大蒜 n罐白芸豆/腰豆/黑豆(每罐12盎司) n块Knorr牛肉/蔬菜汤块 n茶匙现磨黑胡椒 3n茶匙孜然粉 n杯干米(推荐糙米)
You can still raise money, but you don't have to do it now.
The most obvious advantage of not needing money is that you can get better terms. If investors know you need money, they'll sometimes take advantage of you. Some may even deliberately stall, because they know that as you run out of money you'll become increasingly pliable. But there are also three less obvious advantages of ramen profitability. One is that it makes you more attractive to investors. If you're already profitable, on however small a scale, it shows that (a) you can get at least someone to pay you, (b) you're serious about building things people want, and (c) you're disciplined enough to keep expenses low. This is reassuring to investors, because you've addressed three of their biggest worries. It's common for them to fund companies that have smart founders and a big market, and yet still fail. When these companies fail, it's usually because (a) people wouldn't pay for what they made, e.g. because it was too hard to sell to them, or the market wasn't ready yet, (b) the founders solved the wrong problem, instead of paying attention to what users needed, or (c) the company spent too much and burned through their funding before they started to make money. If you're ramen profitable, you're already avoiding these mistakes. Another advantage of ramen profitability is that it's good for morale. A company tends to feel rather theoretical when you first start it. It's legally a company, but you feel like you're lying when you call it one. When people start to pay you significant amounts, the company starts to feel real. And your own living expenses are the milestone you feel most, because at that point the future flips state. Now survival is the default, instead of dying. A morale boost on that scale is very valuable in a startup, because the moral weight of running a startup is what makes it hard. Startups are still very rare.
(译文说明:保留原文超链接与注释标记;食谱采用归化处理;技术术语如"ramen profitable"统一译为"拉面盈利";长句按中文习惯拆分;文化负载词如"rice cooker"译为"电饭煲"但原文未出现故未添加)
将米放入电饭煲。按米包装上的说明加水。(默认比例:每杯米加两杯水。)启动电饭煲后无需再管。
Why don't more people do it? The financial risk? Plenty of 25 year olds save nothing anyway. The long hours? Plenty of people work just as long hours in regular jobs. What keeps people from starting startups is the fear of having so much responsibility. And this is not an irrational fear: it really is hard to bear. Anything that takes some of that weight off you will greatly increase your chances of surviving. A startup that reaches ramen profitability may be more likely to succeed than not. Which is pretty exciting, considering the bimodal distribution of outcomes in startups: you either fail or make a lot of money. The fourth advantage of ramen profitability is the least obvious but may be the most important. If you don't need to raise money, you don't have to interrupt working on the company to do it. Raising money is terribly distracting. You're lucky if your productivity is a third of what it was before. And it can last for months. I didn't understand (or rather, remember) precisely why raising money was so distracting till earlier this year. I'd noticed that startups we funded would usually grind to a halt when they switched to raising money, but I didn't remember exactly why till YC raised money itself. We had a comparatively easy time of it; the first people I asked said yes; but it took months to work out the details, and during that time I got hardly any real work done. Why? Because I thought about it all the time. At any given time there tends to be one problem that's the most urgent for a startup. This is what you think about as you fall asleep at night and when you take a shower in the morning. And when you start raising money, that becomes the problem you think about. You only take one shower in the morning, and if you're thinking about investors during it, then you're not thinking about the product.
将洋葱和其他蔬菜切碎,用油以较低火候翻炒至洋葱呈透明状。加入切碎的大蒜、胡椒、孜然和少量油脂,翻炒均匀。保持小火,继续烹饪2到3分钟,然后倒入豆子(无需沥干豆汁),搅拌。投入高汤块,盖上锅盖,以中小火至少再炖煮10分钟。需频繁搅拌以防粘锅。
若想节省开支,可去折扣店购买大罐装豆子。香料批量购买也更划算。若附近有印度杂货店,能以超市小瓶装的价格买到整袋孜然。
Whereas if you can choose when you raise money, you can pick a time when you're not in the middle of something else, and you can probably also insist that the round close fast. You may even be able to avoid having the round occupy your thoughts, if you don't care whether it closes.
Ramen profitable means no more than the definition implies. It does not, for example, imply that you're "bootstrapping" the startup—that you're never going to take money from investors. Empirically that doesn't seem to work very well. Few startups succeed without taking investment. Maybe as startups get cheaper it will become more common. On the other hand, the money is there, waiting to be invested. If startups need it less, they'll be able to get it on better terms, which will make them more inclined to take it. That will tend to produce an equilibrium. [2] Another thing ramen profitability doesn't imply is Joe Kraus's idea that you should put your business model in beta when you put your product in beta. He believes you should get people to pay you from the beginning. I think that's too constraining. Facebook didn't, and they've done better than most startups. Making money right away was not only unnecessary for them, but probably would have been harmful. I do think Joe's rule could be useful for many startups, though. When founders seem unfocused, I sometimes suggest they try to get customers to pay them for something, in the hope that this constraint will prod them into action. The difference between Joe's idea and ramen profitability is that a ramen profitable company doesn't have to be making money the way it ultimately will. It just has to be making money. The most famous example is Google, which initially made money by licensing search to sites like Yahoo.
[2] 权力从投资者向创始人的转移很可能反而会扩大风险投资业的规模。我认为当前投资者对创始人过于严苛。若他们被迫停止这种做法,整个风险投资业将运转得更好,或许会出现类似解除限制性法规后常见的贸易增长现象。
Is there a downside to ramen profitability? Probably the biggest danger is that it might turn you into a consulting firm. Startups have to be product companies, in the sense of making a single thing that everyone uses. The defining quality of startups is that they grow fast, and consulting just can't scale the way a product can. [3] But it's pretty easy to make $3000 a month consulting; in fact, that would be a low rate for contract programming. So there could be a temptation to slide into consulting, and telling yourselves you're a ramen profitable startup, when in fact you're not a startup at all. It's ok to do a little consulting-type work at first. Startups usually have to do something weird at first. But remember that ramen profitability is not the destination. A startup's destination is to grow really big; ramen profitability is a trick for not dying en route. Notes [1] The "ramen" in "ramen profitable" refers to instant ramen, which is just about the cheapest food available. Please do not take the term literally. Living on instant ramen would be very unhealthy. Rice and beans are a better source of food. Start by investing in a rice cooker, if you don't have one. Rice and Beans for 2n olive oil or butter n yellow onions other fresh vegetables; experiment 3n cloves garlic n 12-oz cans white, kidney, or black beans n cubes Knorr beef or vegetable bouillon n teaspoons freshly ground black pepper 3n teaspoons ground cumin n cups dry rice, preferably brown.
投资者是创始人最大的痛苦来源之一;若他们不再制造如此多痛苦,成为创始人将更具吸引力;而若成为创始人更有吸引力,便会有更多人投身其中。
[3] 理论上,初创公司可通过将咨询业务转化为可扩展模式实现壮大。但若真能做到这点,本质上他们已成为产品公司。
Put rice in rice cooker. Add water as specified on rice package. (Default: 2 cups water per cup of rice.) Turn on rice cooker and forget about it. Chop onions and other vegetables and fry in oil, over fairly low heat, till onions are glassy. Put in chopped garlic, pepper, cumin, and a little more fat, and stir. Keep heat low. Cook another 2 or 3 minutes, then add beans (don't drain the beans), and stir. Throw in the bouillon cube(s), cover, and cook on lowish heat for at least 10 minutes more. Stir vigilantly to avoid sticking. If you want to save money, buy beans in giant cans from discount stores. Spices are also much cheaper when bought in bulk. If there's an Indian grocery store near you, they'll have big bags of cumin for the same price as the little jars in supermarkets. [2] There's a good chance that a shift in power from investors to founders would actually increase the size of the venture business. I think investors currently err too far on the side of being harsh to founders. If they were forced to stop, the whole venture business would work better, and you might see something like the increase in trade you always see when restrictive laws are removed. Investors are one of the biggest sources of pain for founders; if they stopped causing so much pain, it would be better to be a founder; and if it were better to be a founder, more people would do it. [3] It's conceivable that a startup could grow big by transforming consulting into a form that would scale. But if they did that they'd really be a product company. Thanks to Jessica Livingston for reading drafts of this.
感谢 Jessica Livingston审阅本文草稿。
| 日语译本
| "...the mere consciousness of an engagement will sometimes worry a whole day." � Charles Dickens
July 2009 One reason programmers dislike meetings so much is that they're on a different type of schedule from other people. Meetings cost them more. There are two types of schedule, which I'll call the manager's schedule and the maker's schedule. The manager's schedule is for bosses. It's embodied in the traditional appointment book, with each day cut into one hour intervals. You can block off several hours for a single task if you need to, but by default you change what you're doing every hour. When you use time that way, it's merely a practical problem to meet with someone. Find an open slot in your schedule, book them, and you're done. Most powerful people are on the manager's schedule. It's the schedule of command. But there's another way of using time that's common among people who make things, like programmers and writers. They generally prefer to use time in units of half a day at least. You can't write or program well in units of an hour. That's barely enough time to get started. When you're operating on the maker's schedule, meetings are a disaster. A single meeting can blow a whole afternoon, by breaking it into two pieces each too small to do anything hard in. Plus you have to remember to go to the meeting. That's no problem for someone on the manager's schedule. There's always something coming on the next hour; the only question is what. But when someone on the maker's schedule has a meeting, they have to think about it. For someone on the maker's schedule, having a meeting is like throwing an exception. It doesn't merely cause you to switch from one task to another; it changes the mode in which you work. I find one meeting can sometimes affect a whole day. A meeting commonly blows at least half a day, by breaking up a morning or afternoon. But in addition there's sometimes a cascading effect.
"...仅仅意识到一个约定有时就会让人忧心忡忡一整天。"
程序员如此厌恶会议的一个原因是,他们的时间安排方式与其他人不同。会议对他们造成的损失更大。
我将时间安排分为两种类型:管理者日程和创造者日程。管理者日程是老板们的日程,体现在传统的预约簿中,每天被分割成一小时为单位的时间块。如果需要,你可以为单个任务预留几小时,但默认情况下每小时都会切换任务。
以这种方式使用时间时,与人会面只是个简单的实际问题:在日程表上找个空档,预约完成即可。
大多数掌权者都遵循管理者日程,这是发号施令者的日程。但还有另一种时间使用方式常见于创造者群体,比如程序员和作家。他们通常偏好以至少半天为单位使用时间。你无法在一小时的单位内写出好文章或编出好程序——这时间刚够进入状态。
If I know the afternoon is going to be broken up, I'm slightly less likely to start something ambitious in the morning. I know this may sound oversensitive, but if you're a maker, think of your own case. Don't your spirits rise at the thought of having an entire day free to work, with no appointments at all? Well, that means your spirits are correspondingly depressed when you don't. And ambitious projects are by definition close to the limits of your capacity. A small decrease in morale is enough to kill them off. Each type of schedule works fine by itself. Problems arise when they meet. Since most powerful people operate on the manager's schedule, they're in a position to make everyone resonate at their frequency if they want to. But the smarter ones restrain themselves, if they know that some of the people working for them need long chunks of time to work in. Our case is an unusual one. Nearly all investors, including all VCs I know, operate on the manager's schedule. But Y Combinator runs on the maker's schedule. Rtm and Trevor and I do because we always have, and Jessica does too, mostly, because she's gotten into sync with us. I wouldn't be surprised if there start to be more companies like us. I suspect founders may increasingly be able to resist, or at least postpone, turning into managers, just as a few decades ago they started to be able to resist switching from jeans to suits. How do we manage to advise so many startups on the maker's schedule? By using the classic device for simulating the manager's schedule within the maker's: office hours. Several times a week I set aside a chunk of time to meet founders we've funded. These chunks of time are at the end of my working day, and I wrote a signup program that ensures all the appointments within a given set of office hours are clustered at the end.
当遵循创造者日程时,会议就是灾难。一个会议可能毁掉整个下午,将其分割成两段短得无法处理复杂任务的时间。此外你还得记得去开会。这对管理者日程不是问题——下个小时总有安排,问题只是具体内容。但当创造者日程的人需要开会时,他们必须为此分神。
对创造者日程而言,开会就像抛出异常。不仅需要切换任务,更会改变工作模式。
我发现一个会议有时会影响一整天。会议通常至少毁掉半天,将上午或下午分割得支离破碎。但有时还会产生连锁反应——如果知道下午时间会被切碎,我早上就不太可能开始需要全神贯注的工作。这可能听起来过于敏感,但如果你是创造者,不妨想想自己的情况:想到有整天不受打扰的工作时间,难道不会精神振奋吗?反之亦然。而雄心勃勃的项目本就接近你的能力极限,士气的微小下降就足以将其扼杀。
每种日程本身都运作良好,问题出在两者相遇时。由于多数掌权者遵循管理者日程,他们有能力让他人按自己的频率共振——但更聪明的人会克制这种冲动,如果他们知道下属需要大块连续时间工作的话。
我们的情况比较特殊。几乎所有投资者(包括我认识的所有风投)都遵循管理者日程。但Y Combinator运行在创造者日程上。Rtm、Trevor和我一直如此,Jessica也基本同步——她已与我们形成共振。
Because they come at the end of my day these meetings are never an interruption. (Unless their working day ends at the same time as mine, the meeting presumably interrupts theirs, but since they made the appointment it must be worth it to them.) During busy periods, office hours sometimes get long enough that they compress the day, but they never interrupt it. When we were working on our own startup, back in the 90s, I evolved another trick for partitioning the day. I used to program from dinner till about 3 am every day, because at night no one could interrupt me. Then I'd sleep till about 11 am, and come in and work until dinner on what I called "business stuff." I never thought of it in these terms, but in effect I had two workdays each day, one on the manager's schedule and one on the maker's. When you're operating on the manager's schedule you can do something you'd never want to do on the maker's: you can have speculative meetings. You can meet someone just to get to know one another. If you have an empty slot in your schedule, why not? Maybe it will turn out you can help one another in some way. Business people in Silicon Valley (and the whole world, for that matter) have speculative meetings all the time. They're effectively free if you're on the manager's schedule. They're so common that there's distinctive language for proposing them: saying that you want to "grab coffee," for example. Speculative meetings are terribly costly if you're on the maker's schedule, though. Which puts us in something of a bind. Everyone assumes that, like other investors, we run on the manager's schedule. So they introduce us to someone they think we ought to meet, or send us an email proposing we grab coffee. At this point we have two options, neither of them good: we can meet with them, and lose half a day's work; or we can try to avoid meeting them, and probably offend them.
如果出现更多类似公司,我不会感到惊讶。我怀疑创始人可能越来越有能力抵抗(或至少推迟)转变为管理者,就像几十年前他们开始能够拒绝从牛仔裤改穿西装那样。
我们如何在创造者日程下指导众多初创公司?通过采用在创造者日程中模拟管理者日程的经典方案:办公时间。每周我会预留几段固定时间会见资助的创始人,这些时段都安排在工作日末尾,并编写预约程序确保所有会面集中时段末端。由于处于工作日尾声,这些会议永远不会造成中断(除非对方工作日与我同时结束,此时会议打断的是他们的时间——但既然是他们主动预约,想必值得付出这个代价)。忙碌时期,办公时间可能延长到压缩当天工作时间的程度,但永远不会造成中途打断。
90年代我们经营自己的初创公司时,我发展出另一种分割时间的技巧:每天从晚餐后编程至凌晨3点,因为深夜无人打扰;然后睡到上午11点,处理所谓"商务事务"直至晚餐。虽然当时没这么定义,但实质上我每天有两个工作日:一个管理者日程,一个创造者日程。
遵循管理者日历时,你可以做创造者日程中绝不会做的事:进行探索性会面。你可以单纯为了结识某人而会面——既然日程表有空档,何乐而不为?说不定双方能互相帮助。
硅谷(乃至全球)的商业人士时刻进行着这种探索性会面。在管理者日程下,这类会面实际上零成本,甚至形成了特定邀约话术,比如"一起喝杯咖啡"。
Till recently we weren't clear in our own minds about the source of the problem. We just took it for granted that we had to either blow our schedules or offend people. But now that I've realized what's going on, perhaps there's a third option: to write something explaining the two types of schedule. Maybe eventually, if the conflict between the manager's schedule and the maker's schedule starts to be more widely understood, it will become less of a problem. Those of us on the maker's schedule are willing to compromise. We know we have to have some number of meetings. All we ask from those on the manager's schedule is that they understand the cost. Thanks to Sam Altman, Trevor Blackwell, Paul Buchheit, Jessica Livingston, and Robert Morris for reading drafts of this. Related:
How to Do What You Love | Good and Bad Procrastination Turkish Translation | French Translation Korean Translation | German Translation.
但对创造者日程而言,探索性会面成本极高。这让我们陷入两难:所有人都默认我们像其他投资者一样遵循管理者日程,于是不断引荐他们认为该见的人,或发邮件提议"喝咖啡"。此时我们只有两个糟糕选择:要么接受会面牺牲半天工作,要么拒绝会面可能得罪对方。
直到最近我们才明确问题的根源。我们过去默认只能在打乱日程和得罪人之间二选一。但既然现在明白了问题本质,或许存在第三种选择:撰写文章阐明这两种日程类型。当管理者日程与创造者日程的冲突被更广泛理解时,问题或许能缓解。
我们这些遵循创造者日程的人愿意妥协,知道必须参加某些会议。只希望管理者日程的同行能理解其中的代价。
致谢 Sam Altman、Trevor Blackwell、Paul Buchheit、Jessica Livingston和Robert Morris对本文草稿的审阅。
April 2009 Om Malik is the most recent of many people to ask why Twitter is such a big deal. The reason is that it's a new messaging protocol, where you don't specify the recipients. New protocols are rare. Or more precisely, new protocols that take off are. There are only a handful of commonly used ones: TCP/IP (the Internet), SMTP (email), HTTP (the web), and so on. So any new protocol is a big deal. But Twitter is a protocol owned by a private company. That's even rarer. Curiously, the fact that the founders of Twitter have been slow to monetize it may in the long run prove to be an advantage. Because they haven't tried to control it too much, Twitter feels to everyone like previous protocols. One forgets it's owned by a private company. That must have made it easier for Twitter to spread.
2009年4月 奥姆·马利克是众多追问"Twitter为何如此重要"的最新发声者。 其核心在于:Twitter开创了一种无需指定收件人的新型通信协议。新协议本就罕见,更准确地说,能真正流行起来的新协议凤毛麟角。目前广泛使用的协议屈指可数:TCP/IP(互联网)、SMTP(电子邮件)、HTTP(万维网)等。因此任何新协议都意义重大。但Twitter的特殊性在于——它是一家私营企业拥有的协议,这更为稀有。 有趣的是,Twitter创始人迟迟未将其货币化的做法,长远来看可能反成优势。正因未施加过多控制,大众对Twitter的感知更接近传统协议。人们甚至会忘记它由私营公司所有——这种特性无疑加速了Twitter的普及。
April 2009 _Inc_ recently asked me who I thought were the 5 most interesting startup founders of the last 30 years. How do you decide who's the most interesting? The best test seemed to be influence: who are the 5 who've influenced me most? Who do I use as examples when I'm talking to companies we fund? Who do I find myself quoting? 1\. Steve Jobs I'd guess Steve is the most influential founder not just for me but for most people you could ask. A lot of startup culture is Apple culture. He was the original young founder. And while the concept of "insanely great" already existed in the arts, it was a novel idea to introduce into a company in the 1980s. More remarkable still, he's stayed interesting for 30 years. People await new Apple products the way they'd await new books by a popular novelist. Steve may not literally design them, but they wouldn't happen if he weren't CEO. Steve is clever and driven, but so are a lot of people in the Valley. What makes him unique is his sense of design. Before him, most companies treated design as a frivolous extra. Apple's competitors now know better. 2\. TJ Rodgers TJ Rodgers isn't as famous as Steve Jobs, but he may be the best writer among Silicon Valley CEOs. I've probably learned more from him about the startup way of thinking than from anyone else. Not so much from specific things he's written as by reconstructing the mind that produced them: brutally candid; aggressively garbage-collecting outdated ideas; and yet driven by pragmatism rather than ideology. The first essay of his that I read was so electrifying that I remember exactly where I was at the time. It was High Technology Innovation: Free Markets or Government Subsidies? and I was downstairs in the Harvard Square T Station. It felt as if someone had flipped on a light switch inside my head. 3\.
《Inc》杂志最近邀请我评选过去30年中最有趣的5位创业创始人。如何定义"最有趣"?最合理的标准似乎是影响力:哪五位创始人对我影响最深?我在与投资的公司交流时最常引用谁的案例?谁的言论总是不自觉浮现在我脑海中?
1. 史蒂夫·乔布斯
我认为乔布斯不仅是对我,对大多数人而言都是最具影响力的创始人。初创企业文化的内核很大程度上源自苹果文化。他是青年创业者的原型人物。"极致完美"的理念虽在艺术领域早有先例,但在1980年代将其引入商业领域却是革命性的创举。
更非凡的是,他持续保持影响力长达30年。人们期待苹果新品发布,就像期待畅销小说家的新作。虽然乔布斯未必亲自参与设计,但若没有他执掌公司,这些产品绝不会诞生。
乔布斯的智慧与魄力在硅谷并不罕见,真正使他独树一帜的是他的设计审美。在他之前,大多数企业将设计视为华而不实的装饰。如今苹果的竞争对手们终于明白了其中真谛。
2. T·J·罗杰斯
Larry & Sergey I'm sorry to treat Larry and Sergey as one person. I've always thought that was unfair to them. But it does seem as if Google was a collaboration. Before Google, companies in Silicon Valley already knew it was important to have the best hackers. So they claimed, at least. But Google pushed this idea further than anyone had before. Their hypothesis seems to have been that, in the initial stages at least, _all_ you need is good hackers: if you hire all the smartest people and put them to work on a problem where their success can be measured, you win. All the other stuff—which includes all the stuff that business schools think business consists of—you can figure out along the way. The results won't be perfect, but they'll be optimal. If this was their hypothesis, it's now been verified experimentally. 4\. Paul Buchheit Few know this, but one person, Paul Buchheit, is responsible for three of the best things Google has done. He was the original author of GMail, which is the most impressive thing Google has after search. He also wrote the first prototype of AdSense, and was the author of Google's mantra "Don't be evil." PB made a point in a talk once that I now mention to every startup we fund: that it's better, initially, to make a small number of users really love you than a large number kind of like you. If I could tell startups only ten sentences, this would be one of them. Now he's cofounder of a startup called Friendfeed. It's only a year old, but already everyone in the Valley is watching them. Someone responsible for three of the biggest ideas at Google is going to come up with more. 5\. Sam Altman I was told I shouldn't mention founders of YC-funded companies in this list. But Sam Altman can't be stopped by such flimsy rules. If he wants to be on this list, he's going to be. Honestly, Sam is, along with Steve Jobs, the founder I refer to most when I'm advising startups.
T·J·罗杰斯虽不及乔布斯声名显赫,但可能是硅谷CEO中最优秀的写作者。关于初创企业的思维方式,我从他身上获益最多。这种领悟并非来自其具体言论,而是源于对其思维模式的解构:极度坦诚,主动摒弃过时观念,始终以实用主义而非意识形态为驱动。
我读他的首篇文章时如遭电击,至今记得当时身处哈佛广场地铁站楼下的场景。那篇题为《高科技创新:自由市场还是政府补贴?》的文章,仿佛突然点亮了我脑中的明灯。
3. 拉里与谢尔盖
将两位创始人合并论述实属无奈。谷歌的诞生显然是深度协作的成果。
在谷歌之前,硅谷公司虽标榜重视顶尖黑客,但谷歌将此理念推向极致。他们的核心假设是:至少在初创阶段,优秀黑客就是全部所需——只要聚集最聪明的人,让他们攻克可量化的问题,其他包括商学院推崇的所有商业要素都可在过程中逐步完善。结果或许不完美,但必定最优。这一假设如今已获实践验证。
4. 保罗·布赫海特
On questions of design, I ask "What would Steve do?" but on questions of strategy or ambition I ask "What would Sama do?" What I learned from meeting Sama is that the doctrine of the elect applies to startups. It applies way less than most people think: startup investing does not consist of trying to pick winners the way you might in a horse race. But there are a few people with such force of will that they're going to get whatever they want..
鲜为人知的是,谷歌三大杰作皆出自保罗·布赫海特之手:他开发了谷歌除搜索外最惊艳的产品Gmail,编写了AdSense首个原型,更创造了谷歌信条"不作恶"。
他在演讲中提出的观点,如今成为我对每家初创企业的必赠箴言:初期宁愿让少量用户狂热喜爱,也不要大量用户勉强认可。若只能给创业者十句忠告,此条必列其中。
现在他联合创立的Friendfeed虽成立仅一年,已是硅谷焦点。这位谷歌三大创意的缔造者,必将带来更多惊喜。
5. 山姆·奥尔特曼
按理我不该在此列举YC投资的创始人,但山姆·奥尔特曼从不受规则束缚——只要他想上榜。
事实上,山姆是与乔布斯并列的我最常引用的创业典范。设计问题我常想"乔布斯会怎么做";战略或野心问题则思考"山姆会如何抉择"。
与山姆的接触让我确信:初创领域存在天选之人。当然这种特质远比人们想象的罕见——投资初创企业绝非赌马式的押注。但确实存在少数意志力超群者,他们终将得到想要的一切。
April 2009 Recently I realized I'd been holding two ideas in my head that would explode if combined. The first is that startups may represent a new economic phase, on the scale of the Industrial Revolution. I'm not sure of this, but there seems a decent chance it's true. People are dramatically more productive as founders or early employees of startups—imagine how much less Larry and Sergey would have achieved if they'd gone to work for a big company—and that scale of improvement can change social customs. The second idea is that startups are a type of business that flourishes in certain places that specialize in it—that Silicon Valley specializes in startups in the same way Los Angeles specializes in movies, or New York in finance. [1] What if both are true? What if startups are both a new economic phase and also a type of business that only flourishes in certain centers? If so, this revolution is going to be particularly revolutionary. All previous revolutions have spread. Agriculture, cities, and industrialization all spread widely. If startups end up being like the movie business, with just a handful of centers and one dominant one, that's going to have novel consequences. There are already signs that startups may not spread particularly well. The spread of startups seems to be proceeding slower than the spread of the Industrial Revolution, despite the fact that communication is so much faster now. Within a few decades of the founding of Boulton & Watt there were steam engines scattered over northern Europe and North America. Industrialization didn't spread much beyond those regions for a while. It only spread to places where there was a strong middle class—countries where a private citizen could make a fortune without having it confiscated. Otherwise it wasn't worth investing in factories. But in a country with a strong middle class it was easy for industrial techniques to take root.
An individual mine or factory owner could decide to install a steam engine, and within a few years he could probably find someone local to make him one. So steam engines spread fast. And they spread widely, because the locations of mines and factories were determined by features like rivers, harbors, and sources of raw materials. [2] Startups don't seem to spread so well, partly because they're more a social than a technical phenomenon, and partly because they're not tied to geography. An individual European manufacturer could import industrial techniques and they'd work fine. This doesn't seem to work so well with startups: you need a community of expertise, as you do in the movie business. [3] Plus there aren't the same forces driving startups to spread. Once railroads or electric power grids were invented, every region had to have them. An area without railroads or power was a rich potential market. But this isn't true with startups. There's no need for a Microsoft of France or Google of Germany. Governments may decide they want to encourage startups locally, but government policy can't call them into being the way a genuine need could. How will this all play out? If I had to predict now, I'd say that startups will spread, but very slowly, because their spread will be driven not by government policies (which won't work) or by market need (which doesn't exist) but, to the extent that it happens at all, by the same random factors that have caused startup culture to spread thus far. And such random factors will increasingly be outweighed by the pull of existing startup hubs. Silicon Valley is where it is because William Shockley wanted to move back to Palo Alto, where he grew up, and the experts he lured west to work with him liked it so much they stayed. Seattle owes much of its position as a tech center to the same cause: Gates and Allen wanted to move home. Otherwise Albuquerque might have Seattle's place in the rankings.
Boston is a tech center because it's the intellectual capital of the US and probably the world. And if Battery Ventures hadn't turned down Facebook, Boston would be significantly bigger now on the startup radar screen. But of course it's not a coincidence that Facebook got funded in the Valley and not Boston. There are more and bolder investors in Silicon Valley than in Boston, and even undergrads know it. Boston's case illustrates the difficulty you'd have establishing a new startup hub this late in the game. If you wanted to create a startup hub by reproducing the way existing ones happened, the way to do it would be to establish a first-rate research university in a place so nice that rich people wanted to live there. Then the town would be hospitable to both groups you need: both founders and investors. That's the combination that yielded Silicon Valley. But Silicon Valley didn't have Silicon Valley to compete with. If you tried now to create a startup hub by planting a great university in a nice place, it would have a harder time getting started, because many of the best startups it produced would be sucked away to existing startup hubs. Recently I suggested a potential shortcut: pay startups to move. Once you had enough good startups in one place, it would create a self-sustaining chain reaction. Founders would start to move there without being paid, because that was where their peers were, and investors would appear too, because that was where the deals were. In practice I doubt any government would have the balls to try this, or the brains to do it right. I didn't mean it as a practical suggestion, but more as an exploration of the lower bound of what it would take to create a startup hub deliberately.
The most likely scenario is (1) that no government will successfully establish a startup hub, and (2) that the spread of startup culture will thus be driven by the random factors that have driven it so far, but (3) that these factors will be increasingly outweighed by the pull of existing startup hubs. Result: this revolution, if it is one, will be unusually localized. Notes [1] There are two very different types of startup: one kind that evolves naturally, and one kind that's called into being to "commercialize" a scientific discovery. Most computer/software startups are now the first type, and most pharmaceutical startups the second. When I talk about startups in this essay, I mean type I startups. There is no difficulty making type II startups spread: all you have to do is fund medical research labs; commercializing whatever new discoveries the boffins throw off is as straightforward as building a new airport. Type II startups neither require nor produce startup culture. But that means having type II startups won't get you type I startups. Philadelphia is a case in point: lots of type II startups, but hardly any type I. Incidentally, Google may appear to be an instance of a type II startup, but it wasn't. Google is not pagerank commercialized. They could have used another algorithm and everything would have turned out the same. What made Google Google is that they cared about doing search well at a critical point in the evolution of the web. [2] Watt didn't invent the steam engine. His critical invention was a refinement that made steam engines dramatically more efficient: the separate condenser. But that oversimplifies his role. He had such a different attitude to the problem and approached it with such energy that he transformed the field. Perhaps the most accurate way to put it would be to say that Watt reinvented the steam engine. [3] The biggest counterexample here is Skype.
If you're doing something that would get shut down in the US, it becomes an advantage to be located elsewhere. That's why Kazaa took the place of Napster. And the expertise and connections the founders gained from running Kazaa helped ensure the success of Skype. Thanks to Patrick Collison, Jessica Livingston, and Fred Wilson for reading drafts of this..
2009年4月 最近我意识到自己脑海中并存的两个观点一旦结合就会产生爆炸性结论。 第一个观点是:初创企业可能代表着与工业革命同量级的新经济阶段。虽然无法确定,但确有合理可能性。作为初创企业创始人或早期员工,人们的生产力会呈几何级提升——想象一下如果拉里和佩奇去大公司打工,他们的成就会缩水多少——这种能级的效率变革足以改变社会习俗。 第二个观点是:初创企业属于那种在特定专业化区域才能蓬勃发展的商业模式——硅谷之于初创企业,正如洛杉矶之于电影业,纽约之于金融业。[1] 若两者皆为真呢?若初创企业既是新经济阶段,又只能在特定中心地带繁荣? 倘若如此,这场革命将具有前所未有的颠覆性。历次经济革命都具有扩散性——农业、城市化和工业化都实现了广泛传播。但如果初创企业最终像电影产业那样,仅存少数中心且一家独大,将会引发全新局面。 已有迹象表明初创企业可能不具备强扩散性。尽管现代通信速度远超当年,初创企业的扩散速度仍明显慢于工业革命。 博尔顿-瓦特公司成立后短短几十年,蒸汽机就已遍布北欧和北美。工业化进程曾长期局限于这些区域,仅在中产阶级强大的国家蔓延——即私人财富不会被随意没收的地区。否则建工厂就毫无意义。但在中产阶级稳固的国家,工业技术极易扎根。某个矿主或工厂主决定安装蒸汽机后,不出几年就能在当地找到制造商。因此蒸汽机传播既快且广,因为厂矿选址取决于河流、港口和原料产地等地理因素。[2] 初创企业的扩散性较弱,部分因其本质是社会现象而非技术现象,部分因其不受地理约束。欧洲制造商可以单独引进工业技术并顺利运作,但这招对初创企业不灵——就像电影产业那样,你需要完整的专业生态圈。[3] 更何况推动初创企业扩散的驱动力也不同。铁路和电网问世后,每个地区都必须配备,未覆盖区域就是待开发市场。但初创企业不存在这种需求——法国不需要自己的微软,德国也不需要克隆谷歌。 政府或许会试图扶持本地初创企业,但政策手段永远无法像真实需求那样催生创业生态。 未来将如何演变?若现在预测,我认为初创企业会缓慢扩散,因为驱动力既非政策(无效)也非市场需求(不存在),而是延续至今的随机因素——这些因素正日益被现有创业中心的虹吸效应所抵消。 硅谷的崛起源于威廉·肖克利执意搬回故乡帕洛阿尔托,他吸引来的技术专家们爱上此地便扎根下来。西雅图能成为科技中心同样源于此因——盖茨与艾伦一心返乡,否则阿尔伯克基可能取代其地位。波士顿成为科技重镇因它是美国乃至全球的学术首都。若非Battery Ventures拒绝投资Facebook,波士顿在创业版图上的地位会显著提升。 但Facebook在硅谷而非波士顿获得融资绝非偶然。硅谷拥有更多敢于冒险的投资者,连大学生都深谙此道。 波士顿的案例揭示了当下新建创业中心的困境。若想复制现有中心的形成路径,正确方法是在宜居胜地建立顶尖研究型大学,同时吸引创始人与投资者——这正是硅谷的诞生公式。但当年硅谷没有竞争对手。如今若在风景胜地创办名校来培育创业中心,其成长将更为艰难,因为优质初创企业会被现有中心虹吸。 最近我设想过一条捷径:付费迁移初创企业。只要某地聚集足够多优质初创企业,就能触发链式反应。创始人会自发涌入(无需补贴),因为同行在此;投资者也会闻风而至,因为商机在此。 实际上恐怕没有政府具备尝试的魄力或正确执行的智慧。这并非务实建议,而是探讨人为打造创业中心的最低条件。 最可能的情景是:(1)没有政府能成功建立创业中心;(2)初创文化延续当前的随机扩散模式;(3)这种扩散日益被现有中心的虹吸效应压制。结果就是:这场革命(如果算革命的话)将异常局部化。 注释 [1] 初创企业分两种:自然进化型与科研成果转化型。当前计算机/软件初创企业多属前者,生物制药初创企业多属后者。本文讨论仅限第一类。第二类初创企业的扩散毫无难度——只需资助医学实验室,科研成果转化就像建机场般程序化。这类企业既不依赖也不催生创业文化。但拥有第二类企业并不意味着能培育第一类,费城就是典型案例:第二类众多,第一类罕见。 顺带一提,谷歌看似第二类企业实则不然。谷歌并非PageRank算法的简单商业化——换用其他算法结果依然。其成功关键在于他们在互联网演进的关键期执着于优化搜索体验。 [2] 瓦特并非蒸汽机发明者。他的划时代贡献是分离式冷凝器——这个改良使蒸汽机效率飞跃。但这简化了他的角色。他以全新视角和惊人能量改造了整个领域,或许最准确的说法是:瓦特 reinvented(再造)了蒸汽机。 [3] 最大反例是Skype。当业务可能在美国遭禁时,境外布局反而成为优势。这正是Kazaa取代Napster的原因。而运营Kazaa积累的经验与人脉,恰恰成就了Skype的成功。 致谢 Patrick Collison、Jessica Livingston与Fred Wilson对本文初稿的审阅。.
April 2009 I usually avoid politics, but since we now seem to have an administration that's open to suggestions, I'm going to risk making one. The single biggest thing the government could do to increase the number of startups in this country is a policy that would cost nothing: establish a new class of visa for startup founders. The biggest constraint on the number of new startups that get created in the US is not tax policy or employment law or even Sarbanes-Oxley. It's that we won't let the people who want to start them into the country. Letting just 10,000 startup founders into the country each year could have a visible effect on the economy. If we assume 4 people per startup, which is probably an overestimate, that's 2500 new companies. _Each year._ They wouldn't all grow as big as Google, but out of 2500 some would come close. By definition these 10,000 founders wouldn't be taking jobs from Americans: it could be part of the terms of the visa that they couldn't work for existing companies, only new ones they'd founded. In fact they'd cause there to be more jobs for Americans, because the companies they started would hire more employees as they grew. The tricky part might seem to be how one defined a startup. But that could be solved quite easily: let the market decide. Startup investors work hard to find the best startups. The government could not do better than to piggyback on their expertise, and use investment by recognized startup investors as the test of whether a company was a real startup. How would the government decide who's a startup investor? The same way they decide what counts as a university for student visas. We'll establish our own accreditation procedure. We know who one another are. 10,000 people is a drop in the bucket by immigration standards, but would represent a huge increase in the pool of startup founders.
I think this would have such a visible effect on the economy that it would make the legislator who introduced the bill famous. The only way to know for sure would be to try it, and that would cost practically nothing. Thanks to Trevor Blackwell, Paul Buchheit, Jeff Clavier, David Hornik, Jessica Livingston, Greg Mcadoo, Aydin Senkut, and Fred Wilson for reading drafts of this. Related:
The United States of Entrepreneurs About Half of VC-Backed Company Founders are Immigrants.
2009年4月 我通常回避政治话题,但既然现在这届政府似乎愿意听取建议,我决定冒险提出一个。美国政府若想显著增加本土初创企业数量,最有效的政策其实无需任何财政支出:设立针对创业者的新型签证类别。 当前制约美国初创企业诞生的最大障碍并非税收政策、雇佣法规,甚至不是萨班斯法案。问题在于我们拒绝让那些想要创业的人进入这个国家。 每年仅允许10,000名创业者入境,就足以对经济产生显著影响。假设每家初创企业平均4人(这个数字可能偏高),相当于每年新增2500家企业。它们未必都能成为谷歌那样的巨头,但2500家企业中必然会有接近这个量级的成功案例。 从定义上说,这10,000名创始人不会抢走美国人的工作机会——可以在签证条款中明确规定他们不得受雇于现有企业,只能为自己创立的公司工作。实际上他们会为美国人创造更多就业岗位,因为这些初创企业随着发展必然需要雇佣更多员工。 看似棘手的问题是如何界定"初创企业"。其实解决方法很简单:让市场决定。风险投资者们本就竭尽全力寻找最优质的初创项目。政府只需借助他们的专业判断,将获得知名风投机构投资作为企业资质的认证标准。 如何认定风投机构的资质?参照学生签证中大学的认证方式即可。我们将建立自己的认证体系——这个圈子里的人都清楚彼此的分量。 按照移民标准,10,000人只是沧海一粟,却能让创业者基数获得巨大提升。这项政策带来的经济效应将如此显著,足以让提案议员青史留名。唯一能验证效果的方式就是付诸实践,而试错成本几乎为零。 致谢:感谢Trevor Blackwell、Paul Buchheit、Jeff Clavier、David Hornik、Jessica Livingston、Greg Mcadoo、Aydin Senkut和Fred Wilson审阅本文草稿。 相关阅读:
March 2009 About twenty years ago people noticed computers and TV were on a collision course and started to speculate about what they'd produce when they converged. We now know the answer: computers. It's clear now that even by using the word "convergence" we were giving TV too much credit. This won't be convergence so much as replacement. People may still watch things they call "TV shows," but they'll watch them mostly on computers. What decided the contest for computers? Four forces, three of which one could have predicted, and one that would have been harder to. One predictable cause of victory is that the Internet is an open platform. Anyone can build whatever they want on it, and the market picks the winners. So innovation happens at hacker speeds instead of big company speeds. The second is Moore's Law, which has worked its usual magic on Internet bandwidth. [1] The third reason computers won is piracy. Users prefer it not just because it's free, but because it's more convenient. Bittorrent and YouTube have already trained a new generation of viewers that the place to watch shows is on a computer screen. [2] The somewhat more surprising force was one specific type of innovation: social applications. The average teenage kid has a pretty much infinite capacity for talking to their friends. But they can't physically be with them all the time. When I was in high school the solution was the telephone. Now it's social networks, multiplayer games, and various messaging applications. The way you reach them all is through a computer. [3] Which means every teenage kid (a) wants a computer with an Internet connection, (b) has an incentive to figure out how to use it, and (c) spends countless hours in front of it. This was the most powerful force of all. This was what made everyone want computers. Nerds got computers because they liked them. Then gamers got them to play games on.
But it was connecting to other people that got everyone else: that's what made even grandmas and 14 year old girls want computers. After decades of running an IV drip right into their audience, people in the entertainment business had understandably come to think of them as rather passive. They thought they'd be able to dictate the way shows reached audiences. But they underestimated the force of their desire to connect with one another. Facebook killed TV. That is wildly oversimplified, of course, but probably as close to the truth as you can get in three words. ___ The TV networks already seem, grudgingly, to see where things are going, and have responded by putting their stuff, grudgingly, online. But they're still dragging their heels. They still seem to wish people would watch shows on TV instead, just as newspapers that put their stories online still seem to wish people would wait till the next morning and read them printed on paper. They should both just face the fact that the Internet is the primary medium. They'd be in a better position if they'd done that earlier. When a new medium arises that's powerful enough to make incumbents nervous, then it's probably powerful enough to win, and the best thing they can do is jump in immediately. Whether they like it or not, big changes are coming, because the Internet dissolves the two cornerstones of broadcast media: synchronicity and locality. On the Internet, you don't have to send everyone the same signal, and you don't have to send it to them from a local source. People will watch what they want when they want it, and group themselves according to whatever shared interest they feel most strongly. Maybe their strongest shared interest will be their physical location, but I'm guessing not. Which means local TV is probably dead. It was an artifact of limitations imposed by old technology.
If someone were creating an Internet-based TV company from scratch now, they might have some plan for shows aimed at specific regions, but it wouldn't be a top priority. Synchronicity and locality are tied together. TV network affiliates care what's on at 10 because that delivers viewers for local news at 11. This connection adds more brittleness than strength, however: people don't watch what's on at 10 because they want to watch the news afterward. TV networks will fight these trends, because they don't have sufficient flexibility to adapt to them. They're hemmed in by local affiliates in much the same way car companies are hemmed in by dealers and unions. Inevitably, the people running the networks will take the easy route and try to keep the old model running for a couple more years, just as the record labels have done. A recent article in the _Wall Street Journal_ described how TV networks were trying to add more live shows, partly as a way to make viewers watch TV synchronously instead of watching recorded shows when it suited them. Instead of delivering what viewers want, they're trying to force them to change their habits to suit the networks' obsolete business model. That never works unless you have a monopoly or cartel to enforce it, and even then it only works temporarily. The other reason networks like live shows is that they're cheaper to produce. There they have the right idea, but they haven't followed it to its conclusion. Live content can be way cheaper than networks realize, and the way to take advantage of dramatic decreases in cost is to increase volume. The networks are prevented from seeing this whole line of reasoning because they still think of themselves as being in the broadcast business—as sending one signal to everyone. [4] ___ Now would be a good time to start any company that competes with TV networks.
That's what a lot of Internet startups are, though they may not have had this as an explicit goal. People only have so many leisure hours a day, and TV is premised on such long sessions (unlike Google, which prides itself on sending users on their way quickly) that anything that takes up their time is competing with it. But in addition to such indirect competitors, I think TV companies will increasingly face direct ones. Even in cable TV, the long tail was lopped off prematurely by the threshold you had to get over to start a new channel. It will be longer on the Internet, and there will be more mobility within it. In this new world, the existing players will only have the advantages any big company has in its market. That will change the balance of power between the networks and the people who produce shows. The networks used to be gatekeepers. They distributed your work, and sold advertising on it. Now the people who produce a show can distribute it themselves. The main value networks supply now is ad sales. Which will tend to put them in the position of service providers rather than publishers. Shows will change even more. On the Internet there's no reason to keep their current format, or even the fact that they have a single format. Indeed, the more interesting sort of convergence that's coming is between shows and games. But on the question of what sort of entertainment gets distributed on the Internet in 20 years, I wouldn't dare to make any predictions, except that things will change a lot. We'll get whatever the most imaginative people can cook up. That's why the Internet won. Notes [1] Thanks to Trevor Blackwell for this point. He adds: "I remember the eyes of phone companies gleaming in the early 90s when they talked about convergence. They thought most programming would be on demand, and they would implement it and make a lot of money. It didn't work out.
They assumed that their local network infrastructure would be critical to do video on-demand, because you couldn't possibly stream it from a few data centers over the internet. At the time (1992) the entire cross-country Internet bandwidth wasn't enough for one video stream. But wide-area bandwidth increased more than they expected and they were beaten by iTunes and Hulu." [2] Copyright owners tend to focus on the aspect they see of piracy, which is the lost revenue. They therefore think what drives users to do it is the desire to get something for free. But iTunes shows that people will pay for stuff online, if you make it easy. A significant component of piracy is simply that it offers a better user experience. [3] Or a phone that is actually a computer. I'm not making any predictions about the size of the device that will replace TV, just that it will have a browser and get data via the Internet. [4] Emmett Shear writes: "I'd argue the long tail for sports may be even larger than the long tail for other kinds of content. Anyone can broadcast a high school football game that will be interesting to 10,000 people or so, even if the quality of production is not so good." Thanks to Sam Altman, Trevor Blackwell, Nancy Cook, Michael Seibel, Emmett Shear, and Fred Wilson for reading drafts of this.
2009年3月 大约二十年前,人们注意到计算机和电视即将发生碰撞,并开始猜测两者融合会产生什么。现在我们知道了答案:计算机。如今显而易见的是,使用“融合”这个词已经高估了电视。这与其说是融合,不如说是替代。人们可能仍会观看所谓的“电视节目”,但主要是在计算机上观看。 计算机赢得这场竞争的原因是什么?有四种力量,其中三种可以预见,另一种则较难预测。 一个可预见的胜利原因是互联网是一个开放平台。任何人都可以在其上构建任何东西,市场会选出赢家。因此,创新以黑客的速度而非大公司的速度发生。 第二个原因是摩尔定律,它对互联网带宽产生了惯常的魔力。[1] 计算机获胜的第三个原因是盗版。用户喜欢盗版不仅因为它是免费的,还因为它更方便。BitTorrent和YouTube已经培养了一代新观众,他们认为观看节目的地方是计算机屏幕。[2] 稍微令人惊讶的力量是一种特定类型的创新:社交应用。普通青少年与朋友交流的能力几乎是无限的,但他们无法一直与朋友在一起。我上高中时的解决方案是电话。现在是社交网络、多人游戏和各种消息应用。接触所有这些的方式是通过计算机。[3]这意味着每个青少年(a)想要一台能上网的计算机,(b)有动力学会如何使用它,(c)在它面前花费无数时间。 这是最强大的力量。这是让每个人都想要计算机的原因。极客们因为喜欢计算机而拥有计算机。然后游戏玩家为了玩游戏而拥有计算机。但让其他人拥有计算机的是与他人连接:这让甚至祖母和14岁的女孩都想要计算机。 娱乐行业的人们几十年来一直向观众灌输内容,因此理所当然地认为观众相当被动。他们认为自己能够决定节目如何触达观众。但他们低估了人们彼此连接的欲望。 Facebook杀死了电视。当然,这种说法过于简化,但可能是最接近真相的三个字。 ___ 电视网络似乎已经勉强看到了事情的发展方向,并勉强将内容放到了网上。但他们仍然拖拖拉拉。他们似乎仍然希望人们在电视上观看节目,就像将新闻放到网上的报纸仍然希望人们等到第二天早上阅读纸质版一样。他们应该面对一个事实:互联网是主要媒介。 如果他们早点这样做,情况会更好。当一种新媒介强大到足以让现有企业感到紧张时,它可能强大到足以获胜,他们能做的最好的事情就是立即加入。 无论他们喜欢与否,重大变革即将到来,因为互联网瓦解了广播媒体的两大基石:同步性和地域性。在互联网上,你不必向每个人发送相同的信号,也不必从本地源发送信号。人们会在他们想要的时候观看他们想要的内容,并根据他们最强烈的共同兴趣自行分组。也许他们最强烈的共同兴趣是地理位置,但我猜不是。这意味着地方电视可能已经消亡。它是旧技术限制的产物。如果有人现在从头开始创建一家基于互联网的电视公司,他们可能会制定针对特定地区的节目计划,但这不会是首要任务。 同步性和地域性是相互关联的。电视联播网的分支机构关心10点播出的内容,因为这为11点的本地新闻带来观众。然而,这种联系带来的脆弱性多于力量:人们不是因为想在之后观看新闻才观看10点的节目。 电视网络将抵制这些趋势,因为他们缺乏足够的灵活性来适应这些趋势。他们被地方分支机构束缚,就像汽车公司被经销商和工会束缚一样。不可避免地,运营网络的人会采取简单的方式,试图让旧模式再运行几年,就像唱片公司所做的那样。 《华尔街日报》最近的一篇文章描述了电视网络如何试图增加更多直播节目,部分原因是为了让观众同步观看电视,而不是在他们方便的时候观看录制的节目。他们不是在提供观众想要的内容,而是试图强迫观众改变习惯以适应网络过时的商业模式。除非你有垄断或卡特尔来强制执行,否则这永远不会奏效,即便如此,也只是暂时的。 网络喜欢直播节目的另一个原因是制作成本更低。他们在这方面的想法是正确的,但没有贯彻到底。直播内容可以比网络意识到的便宜得多,利用成本大幅下降的方法是增加数量。网络无法看到这一整套推理,因为他们仍然认为自己处于广播业务中——向每个人发送一个信号。[4] ___ 现在是创办任何与电视网络竞争的公司的好时机。许多互联网初创公司就是如此,尽管他们可能没有将其作为明确目标。人们每天的休闲时间有限,而电视的前提是长时间的观看(与谷歌不同,谷歌以快速送走用户为荣),因此任何占用他们时间的东西都在与电视竞争。但除了这些间接竞争者,我认为电视公司将越来越多地面对直接竞争者。 即使在有线电视中,长尾也因启动新频道必须跨越的门槛而过早被切断。在互联网上,长尾会更长,而且内部会有更多的流动性。在这个新世界中,现有参与者将只拥有任何大公司在市场中拥有的优势。 这将改变网络和节目制作人之间的力量平衡。网络曾经是守门人。他们分发你的作品,并为其销售广告。现在,制作节目的人可以自己分发。网络现在提供的主要价值是广告销售。这将使他们倾向于成为服务提供商而非出版商。 节目会发生更大的变化。在互联网上,没有理由保持它们当前的格式,甚至没有理由保持单一格式。事实上,即将到来的更有趣的融合是节目和游戏之间的融合。但关于20年后互联网上会分发什么样的娱乐内容,我不敢做出任何预测,只能说事情会发生很大变化。我们将得到最有想象力的人能想出的任何东西。这就是互联网获胜的原因。 注释 [1] 感谢Trevor Blackwell提出这一点。他补充道:“我记得90年代初电话公司谈到融合时眼中闪烁的光芒。他们认为大多数节目将按需提供,他们将实现这一点并赚很多钱。结果并非如此。他们假设本地网络基础设施对视频点播至关重要,因为你不可能通过互联网从几个数据中心流式传输视频。当时(1992年)整个跨国的互联网带宽还不够一个视频流。但广域带宽的增长超出了他们的预期,他们被iTunes和Hulu击败了。” [2] 版权所有者倾向于关注他们看到的盗版方面,即收入的损失。因此他们认为驱动用户盗版的原因是希望免费获得东西。但iTunes表明,如果你让事情变得简单,人们会为在线内容付费。盗版的一个重要组成部分是它提供了更好的用户体验。 [3] 或者实际上是计算机的手机。我没有对将取代电视的设备尺寸做出任何预测,只是说它将有一个浏览器并通过互联网获取数据。 [4] Emmett Shear写道:“我认为体育的长尾可能比其他类型的内容的长尾更大。任何人都可以广播一场高中橄榄球比赛,即使制作质量不太好,也会吸引大约10,000人观看。” 感谢 Sam Altman、Trevor Blackwell、Nancy Cook、Michael Seibel、Emmett Shear和Fred Wilson阅读本文草稿。
日文翻译.
Want to start a startup? Get funded by Y Combinator.
March 2009 A couple days ago I finally got being a good startup founder down to two words: relentlessly resourceful. Till then the best I'd managed was to get the opposite quality down to one: hapless. Most dictionaries say hapless means unlucky. But the dictionaries are not doing a very good job. A team that outplays its opponents but loses because of a bad decision by the referee could be called unlucky, but not hapless. Hapless implies passivity. To be hapless is to be battered by circumstances — to let the world have its way with you, instead of having your way with the world. [1] Unfortunately there's no antonym of hapless, which makes it difficult to tell founders what to aim for. "Don't be hapless" is not much of a rallying cry. It's not hard to express the quality we're looking for in metaphors. The best is probably a running back. A good running back is not merely determined, but flexible as well. They want to get downfield, but they adapt their plans on the fly. Unfortunately this is just a metaphor, and not a useful one to most people outside the US. "Be like a running back" is no better than "Don't be hapless." But finally I've figured out how to express this quality directly. I was writing a talk for investors, and I had to explain what to look for in founders. What would someone who was the opposite of hapless be like? They'd be relentlessly resourceful. Not merely relentless. That's not enough to make things go your way except in a few mostly uninteresting domains. In any interesting domain, the difficulties will be novel. Which means you can't simply plow through them, because you don't know initially how hard they are; you don't know whether you're about to plow through a block of foam or granite. So you have to be resourceful. You have to keep trying new things. Be relentlessly resourceful.
That sounds right, but is it simply a description of how to be successful in general? I don't think so. This isn't the recipe for success in writing or painting, for example. In that kind of work the recipe is more to be actively curious. Resourceful implies the obstacles are external, which they generally are in startups. But in writing and painting they're mostly internal; the obstacle is your own obtuseness. [2] There probably are other fields where "relentlessly resourceful" is the recipe for success. But though other fields may share it, I think this is the best short description we'll find of what makes a good startup founder. I doubt it could be made more precise. Now that we know what we're looking for, that leads to other questions. For example, can this quality be taught? After four years of trying to teach it to people, I'd say that yes, surprisingly often it can. Not to everyone, but to many people. [3] Some people are just constitutionally passive, but others have a latent ability to be relentlessly resourceful that only needs to be brought out. This is particularly true of young people who have till now always been under the thumb of some kind of authority. Being relentlessly resourceful is definitely not the recipe for success in big companies, or in most schools. I don't even want to think what the recipe is in big companies, but it is certainly longer and messier, involving some combination of resourcefulness, obedience, and building alliances. Identifying this quality also brings us closer to answering a question people often wonder about: how many startups there could be. There is not, as some people seem to think, any economic upper bound on this number. There's no reason to believe there is any limit on the amount of newly created wealth consumers can absorb, any more than there is a limit on the number of theorems that can be proven.
So probably the limiting factor on the number of startups is the pool of potential founders. Some people would make good founders, and others wouldn't. And now that we can say what makes a good founder, we know how to put an upper bound on the size of the pool. This test is also useful to individuals. If you want to know whether you're the right sort of person to start a startup, ask yourself whether you're relentlessly resourceful. And if you want to know whether to recruit someone as a cofounder, ask if they are. You can even use it tactically. If I were running a startup, this would be the phrase I'd tape to the mirror. "Make something people want" is the destination, but "Be relentlessly resourceful" is how you get there. Notes [1] I think the reason the dictionaries are wrong is that the meaning of the word has shifted. No one writing a dictionary from scratch today would say that hapless meant unlucky. But a couple hundred years ago they might have. People were more at the mercy of circumstances in the past, and as a result a lot of the words we use for good and bad outcomes have origins in words about luck. When I was living in Italy, I was once trying to tell someone that I hadn't had much success in doing something, but I couldn't think of the Italian word for success. I spent some time trying to describe the word I meant. Finally she said "Ah! Fortuna!" [2] There are aspects of startups where the recipe is to be actively curious. There can be times when what you're doing is almost pure discovery. Unfortunately these times are a small proportion of the whole. On the other hand, they are in research too. [3] I'd almost say to most people, but I realize (a) I have no idea what most people are like, and (b) I'm pathologically optimistic about people's ability to change. Thanks to Trevor Blackwell and Jessica Livingston for reading drafts of this..
想创办一家初创公司? 获得 Y Combinator 的资助。
2009年3月 几天前,我终于将优秀初创公司创始人的特质浓缩为两个词:不屈不挠的机智。 在此之前,我最多只能用一个词来描述其反面特质:倒霉。大多数词典将“倒霉”解释为“不幸”。但词典的释义并不准确。一支球队因裁判误判而输掉比赛,可以说是“不幸”,但算不上“倒霉”。“倒霉”暗含被动性——被环境碾压,任由世界摆布,而非主动掌控局面。[1] 遗憾的是,“倒霉”没有反义词,这使得我们难以向创始人指明方向。“别倒霉”显然算不上振奋人心的口号。 用比喻来描述这种特质并不难。最佳喻体或许是美式橄榄球中的跑卫。优秀的跑卫不仅意志坚定,而且灵活应变。他们渴望推进阵地,但会实时调整策略。 可惜这只是个比喻,对美国以外的大多数人并无实际意义。“像跑卫一样”和“别倒霉”一样苍白无力。 但我终于找到了直接表达这种特质的方式。在为投资者撰写演讲时,我需要说明如何甄别创始人。与“倒霉”相反的特质是什么?那就是不屈不挠的机智。仅有“不屈不挠”是不够的——除非在少数乏味的领域,否则单靠蛮力无法成事。在任何有趣的领域,困难都是新颖的。这意味着你无法一味硬闯,因为最初你无法预判障碍的硬度:不知前方是泡沫块还是花岗岩。因此你必须机智,必须不断尝试新方法。 做不屈不挠的机智者。 这听起来正确,但这是否只是对普遍成功法则的描述?我认为并非如此。例如,写作或绘画的成功法则更强调主动保持好奇心。“机智”意味着障碍主要来自外部——这正是初创企业的常态。而写作与绘画的障碍多源于内部:你的愚钝。[2] 或许其他领域也适用“不屈不挠的机智”这一成功法则。但即便存在共性,这仍是对优秀初创企业创始人的最佳简短描述。我怀疑能否找到更精确的定义。 明确这一特质后,新的问题随之而来。例如:这种特质能否后天培养?经过四年的教学尝试,我的答案是肯定的——令人惊讶的是,往往可以。并非对所有人有效,但对许多人有效。[3] 有些人天生被动,但更多人潜藏着“不屈不挠的机智”,只需被激发。 这对长期受权威压制的年轻人尤为适用。在大公司或多数学校中,“不屈不挠的机智”绝非成功之道。大公司的成功法则更为复杂,混杂着机敏、服从与结盟。 明确这一特质也有助于解答常见疑问:初创企业的数量上限。这个数字并不像某些人认为的那样存在经济上限。消费者对新创财富的吸纳能力如同可被证明的定理数量,理论上没有极限。因此,初创企业的数量上限很可能取决于潜在创始人的基数。有些人适合创业,有些则不适合。既然我们已能定义优秀创始人的特质,就能估算这个基数的上限。 这一标准对个人同样实用。若你想知道自己是否适合创业,只需问:我是否具备不屈不挠的机智?若你想评估某人是否适合成为联合创始人,同样以此衡量。 你甚至可以将其作为战术准则。若我运营初创公司,会将这句话贴在镜面上:“创造人们需要的东西”是目标,而“不屈不挠的机智”是实现路径。 注释 [1] 我认为词典释义错误的原因是词义已发生演变。如今重新编撰词典的人不会将“倒霉”等同于“不幸”。但两百年前或许会——过去人们更受制于环境,因此许多描述结果的词汇都源于运气。 在意大利生活时,我曾想表达某事未获成功,却想不起意大利语的“成功”。经过一番描述,对方终于恍然:“啊!Fortuna(运气)!” [2] 初创企业的某些方面确实需要主动好奇心,尤其在纯探索阶段。遗憾的是这类时刻占比很小。不过科研领域同样如此。 [3] 我几乎想说“对多数人有效”,但意识到:(a) 我并不了解大多数人的特性;(b) 我对人的改变能力存在病态乐观。 致谢 感谢Trevor Blackwell和Jessica Livingston审阅本文草稿。
March 2009 _(This essay is derived from a talk atAngelConf.)_ When we sold our startup in 1998 I thought one day I'd do some angel investing. Seven years later I still hadn't started. I put it off because it seemed mysterious and complicated. It turns out to be easier than I expected, and also more interesting. The part I thought was hard, the mechanics of investing, really isn't. You give a startup money and they give you stock. You'll probably get either preferred stock, which means stock with extra rights like getting your money back first in a sale, or convertible debt, which means (on paper) you're lending the company money, and the debt converts to stock at the next sufficiently big funding round. [1] There are sometimes minor tactical advantages to using one or the other. The paperwork for convertible debt is simpler. But really it doesn't matter much which you use. Don't spend much time worrying about the details of deal terms, especially when you first start angel investing. That's not how you win at this game. When you hear people talking about a successful angel investor, they're not saying "He got a 4x liquidation preference." They're saying "He invested in Google." That's how you win: by investing in the right startups. That is so much more important than anything else that I worry I'm misleading you by even talking about other things. Mechanics Angel investors often syndicate deals, which means they join together to invest on the same terms. In a syndicate there is usually a "lead" investor who negotiates the terms with the startup. But not always: sometimes the startup cobbles together a syndicate of investors who approach them independently, and the startup's lawyer supplies the paperwork. The easiest way to get started in angel investing is to find a friend who already does it, and try to get included in his syndicates. Then all you have to do is write checks.
(本文改编自我在AngelConf的演讲。)
1998年我们卖掉创业公司时,我曾想过有一天要做天使投资。七年后我仍未开始。拖延是因为觉得这事神秘又复杂。结果发现比想象中简单,也更有趣。
我以为最难的环节——投资机制——其实不然。你给初创公司钱,他们给你股份。通常你会获得优先股(意味着附带额外权利,比如公司出售时优先拿回本金),或可转换债券(纸面上是借钱给公司,债务会在下一轮大额融资时转为股权)[1]。
两种方式各有微小优势。可转换债券文件更简单。但选哪种其实差别不大。别在交易条款细节上耗费太多时间,尤其是刚起步时。这不是制胜关键。人们谈论成功天使投资人时,不会说"他拿到了4倍清算优先权",而是说"他投了谷歌"。
制胜之道在于:投对初创公司。这远比任何事都重要,以至于我担心讨论其他话题会误导你。
Don't feel like you have to join a syndicate, though. It's not that hard to do it yourself. You can just use the standard series AA documents Wilson Sonsini and Y Combinator published online. You should of course have your lawyer review everything. Both you and the startup should have lawyers. But the lawyers don't have to create the agreement from scratch. [2] When you negotiate terms with a startup, there are two numbers you care about: how much money you're putting in, and the valuation of the company. The valuation determines how much stock you get. If you put $50,000 into a company at a pre-money valuation of $1 million, then the post-money valuation is $1.05 million, and you get .05/1.05, or 4.76% of the company's stock. If the company raises more money later, the new investor will take a chunk of the company away from all the existing shareholders just as you did. If in the next round they sell 10% of the company to a new investor, your 4.76% will be reduced to 4.28%. That's ok. Dilution is normal. What saves you from being mistreated in future rounds, usually, is that you're in the same boat as the founders. They can't dilute you without diluting themselves just as much. And they won't dilute themselves unless they end up net ahead. So in theory, each further round of investment leaves you with a smaller share of an even more valuable company, till after several more rounds you end up with .5% of the company at the point where it IPOs, and you are very happy because your $50,000 has become $5 million. [3] The agreement by which you invest should have provisions that let you contribute to future rounds to maintain your percentage. So it's your choice whether you get diluted. [4] If the company does really well, you eventually will, because eventually the valuations will get so high it's not worth it for you.
天使投资人常采用联合投资模式,即多人按相同条款共同投资。通常由"领投"人与初创公司谈判条款。但有时是初创公司自行整合独立接触的投资人,由公司律师准备文件。
最简单的入门方式是找一位有经验的朋友,加入他的联合投资。这样你只需开支票。
不过不必强求联合投资。独立操作也不难。直接使用Wilson Sonsini和Y Combinator公布的标准AA系列文件即可。当然要让律师审核文件。你和初创公司都应聘请律师,但无需从零起草协议[2]。
谈判时关注两个数字:投资金额和公司估值。估值决定持股比例。若以5万美元投资估值100万的公司,投后估值105万,你将获得4.76%股份。
后续融资时,新投资人会像你一样稀释所有股东股权。如下轮出售10%股份,你的4.76%将降至4.28%。
How much does an angel invest? That varies enormously, from $10,000 to hundreds of thousands or in rare cases even millions. The upper bound is obviously the total amount the founders want to raise. The lower bound is 5-10% of the total or $10,000, whichever is greater. A typical angel round these days might be $150,000 raised from 5 people. Valuations don't vary as much. For angel rounds it's rare to see a valuation lower than half a million or higher than 4 or 5 million. 4 million is starting to be VC territory. How do you decide what valuation to offer? If you're part of a round led by someone else, that problem is solved for you. But what if you're investing by yourself? There's no real answer. There is no rational way to value an early stage startup. The valuation reflects nothing more than the strength of the company's bargaining position. If they really want you, either because they desperately need money, or you're someone who can help them a lot, they'll let you invest at a low valuation. If they don't need you, it will be higher. So guess. The startup may not have any more idea what the number should be than you do. [5] Ultimately it doesn't matter much. When angels make a lot of money from a deal, it's not because they invested at a valuation of $1.5 million instead of $3 million. It's because the company was really successful. I can't emphasize that too much. Don't get hung up on mechanics or deal terms. What you should spend your time thinking about is whether the company is good. (Similarly, founders also should not get hung up on deal terms, but should spend their time thinking about how to make the company good.) There's a second less obvious component of an angel investment: how much you're expected to help the startup. Like the amount you invest, this can vary a lot. You don't have to do anything if you don't want to; you could simply be a source of money. Or you can become a de facto employee of the company.
这很正常。稀释难以避免的保护在于:你和创始人同舟共济。他们稀释你时自身同样受损。除非最终净收益为正,否则不会这么做。理论上每轮融资后,你持有比例减小但公司价值增长,直至IPO时可能持有0.5%股份——此时5万美元已变成500万,皆大欢喜[3]。
投资协议应包含参与后续融资维持股比的条款。因此稀释与否由你决定[4]。若公司表现极佳,最终你仍会被稀释,因为估值高到不值得跟投。
天使投资额差异巨大,从1万到数十万甚至罕见的上百万美元。上限显然是创始人的总需求,下限通常是总额的5-10%或1万美元(取较高者)。如今典型的天使轮可能是5人共投15万美元。
估值区间较集中。天使轮很少低于50万或高于400-500万美元——后者已接近VC领域。
如何确定估值?若参与他人领投的轮次,这个问题已解决。独立投资时?其实没有标准答案。早期初创公司无法理性估值,数字只反映公司议价能力。若他们急需资金或你能提供重大帮助,可能接受低估值;若不需要你,估值就高。所以只能猜测。初创公司可能和你一样迷茫[5]。
最终估值影响有限。天使大赚从来不是因为以150万而非300万估值入场,而是公司最终大获成功。
Just make sure that you and the startup agree in advance about roughly how much you'll do for them. Really hot companies sometimes have high standards for angels. The ones everyone wants to invest in practically audition investors, and only take money from people who are famous and/or will work hard for them. But don't feel like you have to put in a lot of time or you won't get to invest in any good startups. There is a surprising lack of correlation between how hot a deal a startup is and how well it ends up doing. Lots of hot startups will end up failing, and lots of startups no one likes will end up succeeding. And the latter are so desperate for money that they'll take it from anyone at a low valuation. [6] Picking Winners It would be nice to be able to pick those out, wouldn't it? The part of angel investing that has most effect on your returns, picking the right companies, is also the hardest. So you should practically ignore (or more precisely, archive, in the Gmail sense) everything I've told you so far. You may need to refer to it at some point, but it is not the central issue. The central issue is picking the right startups. What "Make something people want" is for startups, "Pick the right startups" is for investors. Combined they yield "Pick the startups that will make something people want." How do you do that? It's not as simple as picking startups that are already making something wildly popular. By then it's too late for angels. VCs will already be onto them. As an angel, you have to pick startups before they've got a hit—either because they've made something great but users don't realize it yet, like Google early on, or because they're still an iteration or two away from the big hit, like Paypal when they were making software for transferring money between PDAs. To be a good angel investor, you have to be a good judge of potential. That's what it comes down to. VCs can be fast followers.
这点再怎么强调都不为过。别纠结机制或条款,该花时间判断公司潜力。
(同理,创始人也该专注公司建设而非条款谈判。)
天使投资的隐性变量是:你需为初创公司提供多少帮助。和投资额一样,这差异很大。你可以只出钱,也可成为实际员工。关键要提前与公司达成共识。
热门公司对天使常有高要求。抢手项目会筛选投资人,只接受知名或愿全力相助者。但别以为必须投入大量时间才能投到好项目。初创公司的热门程度与最终成功率惊人地缺乏相关性。许多热门公司会失败,许多冷门公司会成功。后者往往急需资金,愿以低估值接受任何投资[6]。
若能提前识别后者该多好?天使投资最影响回报的环节——选对公司——也最难。因此你该暂时"归档"前文内容(用Gmail的归档功能理解)。它们虽可能有用,但非核心。
Most of them don't try to predict what will win. They just try to notice quickly when something already is winning. But angels have to be able to predict. [7] One interesting consequence of this fact is that there are a lot of people out there who have never even made an angel investment and yet are already better angel investors than they realize. Someone who doesn't know the first thing about the mechanics of venture funding but knows what a successful startup founder looks like is actually far ahead of someone who knows termsheets inside out, but thinks "hacker" means someone who breaks into computers. If you can recognize good startup founders by empathizing with them—if you both resonate at the same frequency—then you may already be a better startup picker than the median professional VC. [8] Paul Buchheit, for example, started angel investing about a year after me, and he was pretty much immediately as good as me at picking startups. My extra year of experience was rounding error compared to our ability to empathize with founders. What makes a good founder? If there were a word that meant the opposite of hapless, that would be the one. Bad founders seem hapless. They may be smart, or not, but somehow events overwhelm them and they get discouraged and give up. Good founders make things happen the way they want. Which is not to say they force things to happen in a predefined way. Good founders have a healthy respect for reality. But they are relentlessly resourceful. That's the closest I can get to the opposite of hapless. You want to fund people who are relentlessly resourceful. Notice we started out talking about things, and now we're talking about people. There is an ongoing debate between investors which is more important, the people, or the idea—or more precisely, the market. Some, like Ron Conway, say it's the people—that the idea will change, but the people are the foundation of the company.
核心是选对初创公司。对投资人而言,"选对初创公司"如同创始人的"做人们需要的东西"。二者结合即"选择能做出人们需要的东西的初创公司"。
如何做到?并非简单选择已做出爆款产品的公司——那时已太晚,VC早已入场。天使要在公司成功前下注:或因产品卓越但用户尚未察觉(如早期谷歌),或因距爆款还差一两次迭代(如做PDA转账软件时的Paypal)。
优秀天使投资人必须是潜力判断高手。VC可以快速跟随,多数不预测胜负,只快速发现赢家。但天使必须预测[7]。
由此产生有趣现象:许多从未投资的人可能比自以为的更擅长天使投资。完全不懂风投机制但能识别优秀创始人的人,远胜精通条款却认为"黑客"是入侵电脑者的人。若你能通过共鸣识别优秀创始人,可能已比普通职业VC更会挑选项目[8]。
例如Paul Buchheit比我晚一年开始投资,但选项目能力几乎立即与我相当。相比共鸣能力,我多出的一年经验可忽略不计。
Whereas Marc Andreessen says he'd back ok founders in a hot market over great founders in a bad one. [9] These two positions are not so far apart as they seem, because good people find good markets. Bill Gates would probably have ended up pretty rich even if IBM hadn't happened to drop the PC standard in his lap. I've thought a lot about the disagreement between the investors who prefer to bet on people and those who prefer to bet on markets. It's kind of surprising that it even exists. You'd expect opinions to have converged more. But I think I've figured out what's going on. The three most prominent people I know who favor markets are Marc, Jawed Karim, and Joe Kraus. And all three of them, in their own startups, basically flew into a thermal: they hit a market growing so fast that it was all they could do to keep up with it. That kind of experience is hard to ignore. Plus I think they underestimate themselves: they think back to how easy it felt to ride that huge thermal upward, and they think "anyone could have done it." But that isn't true; they are not ordinary people. So as an angel investor I think you want to go with Ron Conway and bet on people. Thermals happen, yes, but no one can predict them—not even the founders, and certainly not you as an investor. And only good people can ride the thermals if they hit them anyway. Deal Flow Of course the question of how to choose startups presumes you have startups to choose between. How do you find them? This is yet another problem that gets solved for you by syndicates. If you tag along on a friend's investments, you don't have to find startups. The problem is not finding startups, exactly, but finding a stream of reasonably high quality ones. The traditional way to do this is through contacts. If you're friends with a lot of investors and founders, they'll send deals your way. The Valley basically runs on referrals.
优秀创始人特质?找个词描述"不走霉运"的反义词就对了。糟糕创始人总显得倒霉——聪明与否,总被变故击垮而放弃。优秀创始人让事情按意愿发展。这不是说强行按预设路径推进,而是对现实保持清醒认知的同时,展现出"永不言弃的机智"——这是我想到最接近反义的表述。你要投资永不言弃的机智者。
注意我们从讨论"事物"转向了"人"。投资人持续争论人与创意(确切说是市场)孰重孰轻。如Ron Conway认为人是根基,创意会变;而Marc Andreessen说宁愿投资普通团队但火热市场,而非优秀团队但糟糕市场[9]。
两种观点差异没表面那么大,因为优秀的人会找到好市场。即使IBM没送上PC标准,比尔·盖茨可能依然很富有。
我深入思考过这种分歧。令人惊讶的是它竟然存在——按理观点该更趋同。
我想通了原因:我认识最推崇市场的三人——Marc、Jawed Karim和Joe Kraus——创业时都遇上爆发式增长的市场,忙到只能勉强跟上。这种经历令人难忘。加之他们低估自己:回想乘势而上的轻松感,觉得"谁都能做到"。但事实并非如此——他们本就不凡。
因此作为天使,我建议跟随Ron Conway押注于人。风口确实存在,但无人能预测——包括创始人和投资人。且只有优秀者才能乘风而起。
And once you start to become known as reliable, useful investor, people will refer lots of deals to you. I certainly will. There's also a newer way to find startups, which is to come to events like Y Combinator's Demo Day, where a batch of newly created startups presents to investors all at once. We have two Demo Days a year, one in March and one in August. These are basically mass referrals. But events like Demo Day only account for a fraction of matches between startups and investors. The personal referral is still the most common route. So if you want to hear about new startups, the best way to do it is to get lots of referrals. The best way to get lots of referrals is to invest in startups. No matter how smart and nice you seem, insiders will be reluctant to send you referrals until you've proven yourself by doing a couple investments. Some smart, nice guys turn out to be flaky, high-maintenance investors. But once you prove yourself as a good investor, the deal flow, as they call it, will increase rapidly in both quality and quantity. At the extreme, for someone like Ron Conway, it is basically identical with the deal flow of the whole Valley. So if you want to invest seriously, the way to get started is to bootstrap yourself off your existing connections, be a good investor in the startups you meet that way, and eventually you'll start a chain reaction. Good investors are rare, even in Silicon Valley. There probably aren't more than a couple hundred serious angels in the whole Valley, and yet they're probably the single most important ingredient in making the Valley what it is. Angels are the limiting reagent in startup formation. If there are only a couple hundred serious angels in the Valley, then by deciding to become one you could single-handedly make the pipeline for startups in Silicon Valley significantly wider.
如何选择初创公司的前提是有可选项目。如何找到它们?联合投资再次解决这个问题——跟随朋友投资就无需自己寻找。
问题不在于找项目,而是找到持续的高质量项目流。传统方式是通过人脉。若你认识大量投资人和创始人,他们会推荐项目。硅谷基本靠推荐运转。一旦你成为可靠、有用的投资人,推荐会纷至沓来。我肯定会推荐。
新方式是参加Y Combinator演示日等活动,一批新创公司集中向投资人展示。我们每年3月和8月各办一次,本质是批量推荐。
但演示日只占匹配的一小部分。个人推荐仍是最常见渠道。因此想接触新项目,最佳方式是获取大量推荐。
获取推荐的最佳方式就是投资。无论你多聪明友善,圈内人在你完成几笔投资前都难放心推荐——有些聪明人最后是难缠的投资人。但一旦证明自己是好投资人,所谓的"项目流"会在质与量上快速提升。极致如Ron Conway,他的项目流基本等同于整个硅谷。
That is kind of mind-blowing. Being Good How do you be a good angel investor? The first thing you need is to be decisive. When we talk to founders about good and bad investors, one of the ways we describe the good ones is to say "he writes checks." That doesn't mean the investor says yes to everyone. Far from it. It means he makes up his mind quickly, and follows through. You may be thinking, how hard could that be? You'll see when you try it. It follows from the nature of angel investing that the decisions are hard. You have to guess early, at the stage when the most promising ideas still seem counterintuitive, because if they were obviously good, VCs would already have funded them. Suppose it's 1998. You come across a startup founded by a couple grad students. They say they're going to work on Internet search. There are already a bunch of big public companies doing search. How can these grad students possibly compete with them? And does search even matter anyway? All the search engines are trying to get people to start calling them "portals" instead. Why would you want to invest in a startup run by a couple of nobodies who are trying to compete with large, aggressive companies in an area they themselves have declared passe? And yet the grad students seem pretty smart. What do you do? There's a hack for being decisive when you're inexperienced: ratchet down the size of your investment till it's an amount you wouldn't care too much about losing. For every rich person (you probably shouldn't try angel investing unless you think of yourself as rich) there's some amount that would be painless, though annoying, to lose. Till you feel comfortable investing, don't invest more than that per startup. For example, if you have $5 million in investable assets, it would probably be painless (though annoying) to lose $15,000. That's less than .3% of your net worth. So start by making 3 or 4 $15,000 investments.
因此想认真投资,就该从现有关系起步,成为优质投资人,最终启动链式反应。优秀投资人即便在硅谷也稀缺——可能不超过两百人,却是硅谷成功的最关键要素。天使是初创公司形成的限制性因素。
若硅谷仅有两百名认真天使,那么你决定成为其中一员,就能单枪匹马拓宽硅谷创业管道——这想法很震撼。
如何做好天使投资?首先需要果断。我们评价投资人好坏时,常说优秀者"会开支票"——这不是说来者不拒,而是快速决策并落实。你或许觉得这有何难?试试就知道。天使投资的决策天然艰难:必须在早期判断,那时最有潜力的想法往往反直觉——若显而易见,VC早出手了。
假设在1998年,遇到两个研究生创建的搜索引擎公司。已有大批上市公司做搜索,研究生如何抗衡?搜索本身重要吗?所有搜索引擎都改称"门户"了。为何要投资无名小卒挑战大公司已宣布过时的领域?但研究生看起来挺聪明。你怎么办?
新手果断的诀窍是:降低单笔投资额到你不太在乎亏损的程度。每个富人(自认不富就别尝试天使投资)都有可承受的损失上限。在适应前,单笔投资别超过这个数。
Nothing will teach you about angel investing like experience. Treat the first few as an educational expense. $60,000 is less than a lot of graduate programs. Plus you get equity. What's really uncool is to be strategically indecisive: to string founders along while trying to gather more information about the startup's trajectory. [10] There's always a temptation to do that, because you just have so little to go on, but you have to consciously resist it. In the long term it's to your advantage to be good. The other component of being a good angel investor is simply to be a good person. Angel investing is not a business where you make money by screwing people over. Startups create wealth, and creating wealth is not a zero sum game. No one has to lose for you to win. In fact, if you mistreat the founders you invest in, they'll just get demoralized and the company will do worse. Plus your referrals will dry up. So I recommend being good. The most successful angel investors I know are all basically good people. Once they invest in a company, all they want to do is help it. And they'll help people they haven't invested in too. When they do favors they don't seem to keep track of them. It's too much overhead. They just try to help everyone, and assume good things will flow back to them somehow. Empirically that seems to work. Notes [1] Convertible debt can be either capped at a particular valuation, or can be done at a discount to whatever the valuation turns out to be when it converts. E.g. convertible debt at a discount of 30% means when it converts you get stock as if you'd invested at a 30% lower valuation. That can be useful in cases where you can't or don't want to figure out what the valuation should be. You leave it to the next investor.
例如你有500万美元可投资产,损失1.5万美元可能无碍(尽管不爽)。这不到净资产的0.3%。因此先做3-4笔1.5万美元投资。实践是最好的老师。把前几笔当作学费——6万美元比许多研究生课程便宜,何况还能获得股权。
真正糟糕的是"战略性犹豫"——拖延创始人以观察公司发展[10]。信息匮乏时总有这种诱惑,但必须克制。长期看,做正确的事对你有利。
另一关键是做个好人。天使投资不是靠坑人赚钱。初创公司创造财富,而财富创造非零和游戏。你的成功不必以他人失败为代价。实际上,若亏待创始人,只会打击士气恶化公司状况,还会断绝推荐来源。所以我建议行善。
我认识最成功的天使投资人都本质善良。投资后他们只想助力公司,甚至帮助未投资的对象。行善不留名——太费神。他们尽力助人,相信善缘终有回报。实证表明这确实有效。
[1] 可转换债券可设估值上限,或按转换时估值打折。例如30%折扣意味着转换时相当于以低30%的估值获得股份。这在无法或不愿确定估值时有用,把问题留给下轮投资人。但许多投资人希望明确所得,因此只接受带上限的可转换债。
[2] 从零起草协议的高成本不在文件本身,而在于每小时数百美元的细节争论。因此AA系列文件取中间路线——直接采用反复协商后的折中方案。
On the other hand, a lot of investors want to know exactly what they're getting, so they will only do convertible debt with a cap. [2] The expensive part of creating an agreement from scratch is not writing the agreement, but bickering at several hundred dollars an hour over the details. That's why the series AA paperwork aims at a middle ground. You can just start from the compromise you'd have reached after lots of back and forth. When you fund a startup, both your lawyers should be specialists in startups. Do not use ordinary corporate lawyers for this. Their inexperience makes them overbuild: they'll create huge, overcomplicated agreements, and spend hours arguing over irrelevant things. In the Valley, the top startup law firms are Wilson Sonsini, Orrick, Fenwick & West, Gunderson Dettmer, and Cooley Godward. In Boston the best are Goodwin Procter, Wilmer Hale, and Foley Hoag. [3] Your mileage may vary. [4] These anti-dilution provisions also protect you against tricks like a later investor trying to steal the company by doing another round that values the company at $1. If you have a competent startup lawyer handle the deal for you, you should be protected against such tricks initially. But it could become a problem later. If a big VC firm wants to invest in the startup after you, they may try to make you take out your anti-dilution protections. And if they do the startup will be pressuring you to agree. They'll tell you that if you don't, you're going to kill their deal with the VC. I recommend you solve this problem by having a gentlemen's agreement with the founders: agree with them in advance that you're not going to give up your anti-dilution protections. Then it's up to them to tell VCs early on. The reason you don't want to give them up is the following scenario. The VCs recapitalize the company, meaning they give it additional funding at a pre-money valuation of zero.
投资初创公司时,双方律师都应是专业 startup 律师。别用普通公司律师——缺乏经验会导致文件冗长复杂,浪费时间争论无关条款。
硅谷顶级 startup 律所:Wilson Sonsini、Orrick、Fenwick & West、Gunderson Dettmer 和 Cooley Godward。波士顿最佳:Goodwin Procter、Wilmer Hale 和 Foley Hoag。
[3] 实际效果因人而异。
[4] 反稀释条款也防止后期投资人用1美元估值轮次窃取公司。专业 startup 律师能初期防范这类把戏。但后期可能出问题——当大VC想投资时,可能要求你放弃反稀释保护,初创公司也会施压,声称拒绝将导致VC交易失败。建议与创始人达成君子协议:事先约定不放弃反稀释保护,由他们提前告知VC。
放弃保护的噩梦场景:VC以零估值注资重组公司,清零现有股东(包括你和创始人),然后给创始人大量期权(因需留任他们),而你一无所获。
This wipes out the existing shareholders, including both you and the founders. They then grant the founders lots of options, because they need them to stay around, but you get nothing. Obviously this is not a nice thing to do. It doesn't happen often. Brand-name VCs wouldn't recapitalize a company just to steal a few percent from an angel. But there's a continuum here. A less upstanding, lower-tier VC might be tempted to do it to steal a big chunk of stock. I'm not saying you should always absolutely refuse to give up your anti-dilution protections. Everything is a negotiation. If you're part of a powerful syndicate, you might be able to give up legal protections and rely on social ones. If you invest in a deal led by a big angel like Ron Conway, for example, you're pretty well protected against being mistreated, because any VC would think twice before crossing him. This kind of protection is one of the reasons angels like to invest in syndicates. [5] Don't invest so much, or at such a low valuation, that you end up with an excessively large share of a startup, unless you're sure your money will be the last they ever need. Later stage investors won't invest in a company if the founders don't have enough equity left to motivate them. I talked to a VC recently who said he'd met with a company he really liked, but he turned them down because investors already owned more than half of it. Those investors probably thought they'd been pretty clever by getting such a large chunk of this desirable company, but in fact they were shooting themselves in the foot. [6] At any given time I know of at least 3 or 4 YC alumni who I believe will be big successes but who are running on vapor, financially, because investors don't yet get what they're doing. (And no, unfortunately, I can't tell you who they are. I can't refer a startup to an investor I don't know.) [7] There are some VCs who can predict instead of reacting.
这种事虽不常见(知名VC不会为窃取天使几个点股份这么做),但存在道德光谱——不够正直的二线VC可能为大量股权动心。
并非绝对不可放弃保护。一切可谈判——若加入强大联合投资(如Ron Conway领投),可放弃法律保护转而依靠社交保护。这种保护正是天使喜欢联合投资的原因之一。
[5] 别投资过多或估值过低导致持股比例过大——除非确定你的钱是他们最后所需。后期投资人不会投资创始人激励不足的公司。最近有位VC说他拒绝了个好项目,只因投资人已持股过半。那些投资人自以为聪明拿到大比例,实则自断后路。
[6] 我总知道3-4个YC校友项目潜力巨大但资金紧张,因为投资人尚未理解其模式。(不,抱歉不能透露是谁。我不会向陌生投资人推荐项目。)
[7] 有些VC能预测而非跟风。不出所料,这些是最成功的。
Not surprisingly, these are the most successful ones. [8] It's somewhat sneaky of me to put it this way, because the median VC loses money. That's one of the most surprising things I've learned about VC while working on Y Combinator. Only a fraction of VCs even have positive returns. The rest exist to satisfy demand among fund managers for venture capital as an asset class. Learning this explained a lot about some of the VCs I encountered when we were working on Viaweb. [9] VCs also generally say they prefer great markets to great people. But what they're really saying is they want both. They're so selective that they only even consider great people. So when they say they care above all about big markets, they mean that's how they choose between great people. [10] Founders rightly dislike the sort of investor who says he's interested in investing but doesn't want to lead. There are circumstances where this is an acceptable excuse, but more often than not what it means is "No, but if you turn out to be a hot deal, I want to be able to claim retroactively I said yes." If you like a startup enough to invest in it, then invest in it. Just use the standard series AA terms and write them a check. Thanks to Sam Altman, Paul Buchheit, Jessica Livingston, Robert Morris, and Fred Wilson for reading drafts of this. Comment on this essay..
[8] 我这么说有点狡猾——普通VC其实亏钱。这是YC工作中关于VC最惊人的发现:仅少数VC有正回报,其余只为满足基金管理者对风投资产类别的需求。这解释了我做Viaweb时遇到的某些VC现象。
[9] VC通常也说更看重市场而非人。但实际是两者都要——他们只考虑优秀团队,因此说最关注大市场,实指如何在优秀团队中做选择。
[10] 创始人厌恶说"有兴趣但不愿领投"的投资人。虽有例外,但通常意思是"不投,但若你变热门,我想事后宣称同意过"。
若真看好就投。用标准AA系列条款开支票即可。
致谢 Sam Altman、Paul Buchheit、Jessica Livingston、Robert Morris和Fred Wilson的审阅。
评论本文。
February 2009 I finally realized today why politics and religion yield such uniquely useless discussions. As a rule, any mention of religion on an online forum degenerates into a religious argument. Why? Why does this happen with religion and not with Javascript or baking or other topics people talk about on forums? What's different about religion is that people don't feel they need to have any particular expertise to have opinions about it. All they need is strongly held beliefs, and anyone can have those. No thread about Javascript will grow as fast as one about religion, because people feel they have to be over some threshold of expertise to post comments about that. But on religion everyone's an expert. Then it struck me: this is the problem with politics too. Politics, like religion, is a topic where there's no threshold of expertise for expressing an opinion. All you need is strong convictions. Do religion and politics have something in common that explains this similarity? One possible explanation is that they deal with questions that have no definite answers, so there's no back pressure on people's opinions. Since no one can be proven wrong, every opinion is equally valid, and sensing this, everyone lets fly with theirs. But this isn't true. There are certainly some political questions that have definite answers, like how much a new government policy will cost. But the more precise political questions suffer the same fate as the vaguer ones. I think what religion and politics have in common is that they become part of people's identity, and people can never have a fruitful argument about something that's part of their identity. By definition they're partisan. Which topics engage people's identity depends on the people, not the topic. For example, a discussion about a battle that included citizens of one or more of the countries involved would probably degenerate into a political argument.
But a discussion today about a battle that took place in the Bronze Age probably wouldn't. No one would know what side to be on. So it's not politics that's the source of the trouble, but identity. When people say a discussion has degenerated into a religious war, what they really mean is that it has started to be driven mostly by people's identities. [1] Because the point at which this happens depends on the people rather than the topic, it's a mistake to conclude that because a question tends to provoke religious wars, it must have no answer. For example, the question of the relative merits of programming languages often degenerates into a religious war, because so many programmers identify as X programmers or Y programmers. This sometimes leads people to conclude the question must be unanswerable—that all languages are equally good. Obviously that's false: anything else people make can be well or badly designed; why should this be uniquely impossible for programming languages? And indeed, you can have a fruitful discussion about the relative merits of programming languages, so long as you exclude people who respond from identity. More generally, you can have a fruitful discussion about a topic only if it doesn't engage the identities of any of the participants. What makes politics and religion such minefields is that they engage so many people's identities. But you could in principle have a useful conversation about them with some people. And there are other topics that might seem harmless, like the relative merits of Ford and Chevy pickup trucks, that you couldn't safely talk about with others. The most intriguing thing about this theory, if it's right, is that it explains not merely which kinds of discussions to avoid, but how to have better ideas.
If people can't think clearly about anything that has become part of their identity, then all other things being equal, the best plan is to let as few things into your identity as possible. [2] Most people reading this will already be fairly tolerant. But there is a step beyond thinking of yourself as x but tolerating y: not even to consider yourself an x. The more labels you have for yourself, the dumber they make you. Notes [1] When that happens, it tends to happen fast, like a core going critical. The threshold for participating goes down to zero, which brings in more people. And they tend to say incendiary things, which draw more and angrier counterarguments. [2] There may be some things it's a net win to include in your identity. For example, being a scientist. But arguably that is more of a placeholder than an actual label—like putting NMI on a form that asks for your middle initial—because it doesn't commit you to believing anything in particular. A scientist isn't committed to believing in natural selection in the same way a biblical literalist is committed to rejecting it. All he's committed to is following the evidence wherever it leads. Considering yourself a scientist is equivalent to putting a sign in a cupboard saying "this cupboard must be kept empty." Yes, strictly speaking, you're putting something in the cupboard, but not in the ordinary sense. Thanks to Sam Altman, Trevor Blackwell, Paul Buchheit, and Robert Morris for reading drafts of this.
Russian Translation Portuguese Translation Romanian Translation.
2009年2月 我终于在今天明白了为什么政治和宗教总会引发特别无意义的讨论。 通常情况下,在线论坛上任何提及宗教的言论都会演变成宗教争论。为什么?为什么这种现象会发生在宗教上,而不是发生在Javascript、烘焙或论坛上人们讨论的其他话题上? 宗教的不同之处在于,人们觉得不需要任何特定的专业知识就可以对它发表意见。他们所需要的只是坚定的信念,而任何人都可以拥有这些信念。没有哪个关于Javascript的帖子会像关于宗教的帖子那样迅速增长,因为人们觉得必须达到一定的专业门槛才能发表评论。但在宗教上,每个人都是专家。 然后我突然意识到:这也是政治的问题。和政治一样,宗教是一个表达意见没有专业门槛的话题。你所需要的只是坚定的信念。 宗教和政治是否有某种共同点可以解释这种相似性?一种可能的解释是,它们处理的问题没有明确的答案,因此人们的意见不会受到反向压力。既然没有人能被证明是错的,那么每一种意见都是同样有效的,意识到这一点后,每个人都会尽情表达自己的观点。 但事实并非如此。当然有一些政治问题是有明确答案的,比如一项新政府政策的成本是多少。但越是精确的政治问题,其命运与那些模糊的问题并无二致。 我认为宗教和政治的共同点是,它们成为了人们身份的一部分,而人们永远无法就身份的一部分进行富有成效的争论。从定义上讲,他们是偏袒的。 哪些话题会涉及人们的身份取决于人,而不是话题。例如,一场涉及一个或多个相关国家公民的关于战役的讨论可能会演变成政治争论。但今天关于青铜时代一场战役的讨论可能就不会。没有人会知道该站在哪一边。因此,问题的根源不是政治,而是身份。当人们说一场讨论已经演变成宗教战争时,他们真正的意思是,这场讨论已经开始主要由人们的身份驱动。[1] 由于这种情况发生的点取决于人而不是话题,因此得出“因为一个问题容易引发宗教战争,所以它一定没有答案”的结论是错误的。例如,关于编程语言相对优点的讨论常常演变成宗教战争,因为许多程序员自认为是X程序员或Y程序员。这有时会让人们得出结论,认为这个问题一定是无法回答的——所有语言都一样好。显然这是错误的:人们制造的任何其他东西都可以设计得好或不好;为什么编程语言就偏偏不可能呢?事实上,你可以就编程语言的相对优点进行富有成效的讨论,只要你排除那些从身份出发回应的人。 更一般地说,只有当话题不涉及任何参与者的身份时,你才能进行富有成效的讨论。政治和宗教之所以成为雷区,是因为它们涉及太多人的身份。但原则上,你可以与某些人就这些问题进行有益的对话。还有一些话题看似无害,比如福特和雪佛兰皮卡的相对优点,但你无法安全地与某些人讨论。 如果这个理论是正确的,那么最引人入胜的地方在于,它不仅解释了应该避免哪些类型的讨论,还解释了如何产生更好的想法。如果人们无法清晰地思考已经成为他们身份一部分的任何事情,那么在同等条件下,最好的计划是尽可能少地让事情成为你的身份。[2] 阅读本文的大多数人已经相当宽容。但有一种超越“认为自己是x但容忍y”的做法:甚至不认为自己是x。你给自己贴的标签越多,它们就会让你变得越愚蠢。 注释 [1] 当这种情况发生时,它往往会迅速发生,就像核心达到临界点一样。参与的门槛降为零,这吸引了更多的人。而他们往往会发表煽动性的言论,从而引发更多、更愤怒的反驳。 [2] 可能有一些事情纳入你的身份是净收益。例如,成为一名科学家。但可以说,这更像是一个占位符,而不是一个实际的标签——就像在表格上填写“NMI”作为中间名首字母一样——因为它并不要求你相信任何特定的东西。科学家并不像圣经字面主义者必须拒绝自然选择那样必须相信自然选择。他所要做的就是遵循证据,无论它指向哪里。 认为自己是科学家,相当于在橱柜里放一个牌子,上面写着“这个橱柜必须保持空置”。是的,严格来说,你是在橱柜里放了东西,但不是通常意义上的。 感谢 Sam Altman、Trevor Blackwell、Paul Buchheit和Robert Morris阅读本文的草稿。
February 2009 A lot of cities look at Silicon Valley and ask "How could we make something like that happen here?" The organic way to do it is to establish a first-rate university in a place where rich people want to live. That's how Silicon Valley happened. But could you shortcut the process by funding startups? Possibly. Let's consider what it would take. The first thing to understand is that encouraging startups is a different problem from encouraging startups in a particular city. The latter is much more expensive. People sometimes think they could improve the startup scene in their town by starting something like Y Combinator there, but in fact it will have near zero effect. I know because Y Combinator itself had near zero effect on Boston when we were based there half the year. The people we funded came from all over the country (indeed, the world) and afterward they went wherever they could get more funding—which generally meant Silicon Valley. The seed funding business is not a regional business, because at that stage startups are mobile. They're just a couple founders with laptops. [1] If you want to encourage startups in a particular city, you have to fund startups that won't leave. There are two ways to do that: have rules preventing them from leaving, or fund them at the point in their life when they naturally take root. The first approach is a mistake, because it becomes a filter for selecting bad startups. If your terms force startups to do things they don't want to, only the desperate ones will take your money. Good startups will move to another city as a condition of funding. What they won't do is agree not to move the next time they need funding.
So the only way to get them to stay is to give them enough that they never need to leave. ___ How much would that take? If you want to keep startups from leaving your town, you have to give them enough that they're not tempted by an offer from Silicon Valley VCs that requires them to move. A startup would be able to refuse such an offer if they had grown to the point where they were (a) rooted in your town and/or (b) so successful that VCs would fund them even if they didn't move. How much would it cost to grow a startup to that point? A minimum of several hundred thousand dollars. Wufoo seem to have rooted themselves in Tampa on $118k, but they're an extreme case. On average it would take at least half a million. So if it seems too good to be true to think you could grow a local silicon valley by giving startups $15-20k each like Y Combinator, that's because it is. To make them stick around you'd have to give them at least 20 times that much. However, even that is an interesting prospect. Suppose to be on the safe side it would cost a million dollars per startup. If you could get startups to stick to your town for a million apiece, then for a billion dollars you could bring in a thousand startups. That probably wouldn't push you past Silicon Valley itself, but it might get you second place. For the price of a football stadium, any town that was decent to live in could make itself one of the biggest startup hubs in the world. What's more, it wouldn't take very long. You could probably do it in five years. During the term of one mayor. And it would get easier over time, because the more startups you had in town, the less it would take to get new ones to move there. By the time you had a thousand startups in town, the VCs wouldn't be trying so hard to get them to move to Silicon Valley; instead they'd be opening local offices. Then you'd really be in good shape.
You'd have started a self-sustaining chain reaction like the one that drives the Valley. ___ But now comes the hard part. You have to pick the startups. How do you do that? Picking startups is a rare and valuable skill, and the handful of people who have it are not readily hireable. And this skill is so hard to measure that if a government did try to hire people with it, they'd almost certainly get the wrong ones. For example, a city could give money to a VC fund to establish a local branch, and let them make the choices. But only a bad VC fund would take that deal. They wouldn't _seem_ bad to the city officials. They'd seem very impressive. But they'd be bad at picking startups. That's the characteristic failure mode of VCs. All VCs look impressive to limited partners. The difference between the good ones and the bad ones only becomes visible in the other half of their jobs: choosing and advising startups. [2] What you really want is a pool of local angel investors—people investing money they made from their own startups. But unfortunately you run into a chicken and egg problem here. If your city isn't already a startup hub, there won't be people there who got rich from startups. And there is no way I can think of that a city could attract angels from outside. By definition they're rich. There's no incentive that would make them move. [3] However, a city could select startups by piggybacking on the expertise of investors who weren't local. It would be pretty straightforward to make a list of the most eminent Silicon Valley angels and from that to generate a list of all the startups they'd invested in. If a city offered these companies a million dollars each to move, a lot of the earlier stage ones would probably take it. Preposterous as this plan sounds, it's probably the most efficient way a city could select good startups. It would hurt the startups somewhat to be separated from their original investors.
On the other hand, the extra million dollars would give them a lot more runway. ___ Would the transplanted startups survive? Quite possibly. The only way to find out would be to try it. It would be a pretty cheap experiment, as civil expenditures go. Pick 30 startups that eminent angels have recently invested in, give them each a million dollars if they'll relocate to your city, and see what happens after a year. If they seem to be thriving, you can try importing startups on a larger scale. Don't be too legalistic about the conditions under which they're allowed to leave. Just have a gentlemen's agreement. Don't try to do it on the cheap and pick only 10 for the initial experiment. If you do this on too small a scale you'll just guarantee failure. Startups need to be around other startups. 30 would be enough to feel like a community. Don't try to make them all work in some renovated warehouse you've made into an "incubator." Real startups prefer to work in their own spaces. In fact, don't impose any restrictions on the startups at all. Startup founders are mostly hackers, and hackers are much more constrained by gentlemen's agreements than regulations. If they shake your hand on a promise, they'll keep it. But show them a lock and their first thought is how to pick it. Interestingly, the 30-startup experiment could be done by any sufficiently rich private citizen. And what pressure it would put on the city if it worked. [4] ___ Should the city take stock in return for the money? In principle they're entitled to, but how would they choose valuations for the startups? You couldn't just give them all the same valuation: that would be too low for some (who'd turn you down) and too high for others (because it might make their next round a "down round"). And since we're assuming we're doing this without being able to pick startups, we also have to assume we can't value them, since that's practically the same thing.
Another reason not to take stock in the startups is that startups are often involved in disreputable things. So are established companies, but they don't get blamed for it. If someone gets murdered by someone they met on Facebook, the press will treat the story as if it were about Facebook. If someone gets murdered by someone they met at a supermarket, the press will just treat it as a story about a murder. So understand that if you invest in startups, they might build things that get used for pornography, or file-sharing, or the expression of unfashionable opinions. You should probably sponsor this project jointly with your political opponents, so they can't use whatever the startups do as a club to beat you with. It would be too much of a political liability just to give the startups the money, though. So the best plan would be to make it convertible debt, but which didn't convert except in a really big round, like $20 million. ___ How well this scheme worked would depend on the city. There are some towns, like Portland, that would be easy to turn into startup hubs, and others, like Detroit, where it would really be an uphill battle. So be honest with yourself about the sort of town you have before you try this. It will be easier in proportion to how much your town resembles San Francisco. Do you have good weather? Do people live downtown, or have they abandoned the center for the suburbs? Would the city be described as "hip" and "tolerant," or as reflecting "traditional values?" Are there good universities nearby? Are there walkable neighborhoods? Would nerds feel at home? If you answered yes to all these questions, you might be able not only to pull off this scheme, but to do it for less than a million per startup. I realize the chance of any city having the political will to carry out this plan is microscopically small. I just wanted to explore what it would take if one did.
How hard would it be to jumpstart a silicon valley? It's fascinating to think this prize might be within the reach of so many cities. So even though they'll all still spend the money on the stadium, at least now someone can ask them: why did you choose to do that instead of becoming a serious rival to Silicon Valley? Notes [1] What people who start these supposedly local seed firms always find is that (a) their applicants come from all over, not just the local area, and (b) the local startups also apply to the other seed firms. So what ends up happening is that the applicant pool gets partitioned by quality rather than geography. [2] Interestingly, the bad VCs fail by choosing startups run by people like them—people who are good presenters, but have no real substance. It's a case of the fake leading the fake. And since everyone involved is so plausible, the LPs who invest in these funds have no idea what's happening till they measure their returns. [3] Not even being a tax haven, I suspect. That makes some rich people move, but not the type who would make good angel investors in startups. [4] Thanks to Michael Keenan for pointing this out. Thanks to Trevor Blackwell, Jessica Livingston, Robert Morris, and Fred Wilson for reading drafts of this..
2009年2月 许多城市看着硅谷问道:"我们怎样才能在这里复制这样的奇迹?"有机的培育方式是在富人愿意定居的地方建立一所顶尖大学——这正是硅谷的诞生之路。但能否通过资助初创企业来走捷径呢? 或许可以。让我们探讨所需条件。 首先要明白,鼓励创业与在特定城市培育创业生态是截然不同的命题。后者成本高昂得多。 有人以为在当地设立类似Y Combinator的机构就能激活本土创业氛围,实则收效甚微。我们在波士顿运营Y Combinator时深有体会:资助的创业者来自全球各地,后期他们只会前往融资更便利的地方——通常就是硅谷。 种子投资本质上是无地域边界的生意,因为初创企业在这个阶段具有高度流动性——不过是几个创始人加笔记本电脑的组合。[1] 若想将初创企业锚定在某座城市,必须投资那些不会离开的团队。有两种实现路径:制定限制搬迁的条款,或在企业自然扎根阶段注资。前者实属下策,因为这将筛选出劣质项目——只有走投无路的团队才会接受违背意愿的条款。 优质初创企业会为融资迁移城市,但绝不会承诺下次融资时不搬迁。因此留住他们的唯一方式,就是提供足以支撑长期发展的资金。 ___ 具体需要多少?要让初创企业拒绝硅谷风投的搬迁要求,必须助其发展到(a)已在当地扎根或(b)足够成功以致无需搬迁也能融资的阶段。 培育至该阶段至少需要数十万美元。Wufoo曾用11.8万美元在坦帕扎根,但这属于极端案例。通常需要至少50万美元。 若以为像Y Combinator那样给每家初创企业1.5-2万美元就能培育出本土硅谷,这幻想未免过于美好。实际所需金额至少要乘以20倍。 不过即便如此也值得探讨。假设保守估计每家需百万美元投资,那么十亿美元就能引入千家初创企业。虽无法超越硅谷,但足以问鼎亚军。 用一座足球场的造价,任何宜居城市都能跻身全球顶级创业中心之列。 更妙的是见效速度——五年内即可实现,正好是一届市长的任期。随着初创企业数量增加,吸引新团队的成本将递减。当数量突破千家时,风投机构自会主动设立本地办公室,这时良性循环便真正形成——就像驱动硅谷的自持链式反应。 ___ 真正的难点在于项目筛选。这需要罕见而珍贵的判断力,且具备该能力的人才往往不受雇于政府。若政府试图招聘这类人才,几乎必定会选错对象。 例如,城市可注资风投基金设立分部并委托其筛选。但只有劣质风投才会接受这种合作——他们在官员面前光鲜亮丽,实则缺乏甄别能力。这正是风投行业的典型陷阱:所有风投在有限合伙人眼中都实力非凡,但其优劣差异只有在项目筛选与辅导环节才会显现。[2] 理想情况是依靠本地天使投资人群体——那些从创业中获利的成功者。但这里存在"鸡生蛋"困境:若非创业中心,自然缺乏这类人群。而吸引外部天使投资人几无可能——他们本就财务自由,没有搬迁动机。[3] 不过城市可以借助非本地投资人的专业眼光:列出硅谷顶尖天使投资人及其投资组合,向这些早期项目提供百万美元搬迁资金,相信不少团队会接受。 尽管这个方案看似荒谬,却可能是城市筛选优质项目的最有效途径。 虽然与原始投资人分离对初创企业不利,但百万美元注资将极大延长其发展周期。 ___ 迁移的初创企业能否存活?很可能。唯有实践才能验证。作为市政支出,这将是个成本低廉的实验:精选30家获知名天使投资的新创企业,提供百万美元搬迁资金,观察一年后的发展。若成效显著,便可扩大规模。 别用繁琐条款限制企业流动,依靠君子协定即可。 初始实验切勿为省钱只选10家——规模过小注定失败。初创企业需要集群效应,30家才能形成社区氛围。 别强迫所有团队入驻政府改造的"孵化器"仓库,真正的初创企业偏爱自主空间。 事实上,不要施加任何限制。创业者多是黑客,他们更受君子协定而非规章约束。握手之诺必会遵守,但若见锁必先思破解。 有趣的是,这个30家企业的实验可由任何足够富有的个人实施。若成功,将对市政当局形成巨大压力。[4] ___ 城市是否应该获取股权?理论上可以,但如何估值?统一估值行不通——对某些企业过低(会拒绝),对另一些则过高(可能导致下轮融资估值下降)。既然假设我们缺乏筛选能力,估值能力自然也不具备。 另一个放弃股权的理由是:初创企业常涉足争议领域。成熟企业也如此但鲜受指责。若凶案与Facebook有关,媒体会归咎平台;若与超市有关,则仅视为普通刑案。投资初创企业意味着可能涉及色情、文件共享或非主流观点表达。最好与政敌联合赞助此项目,避免被对方利用创业公司的行为进行攻击。 但纯粹赠款政治风险过大。最佳方案是可转换债券,且仅在大额融资(如2000万美元)时转换。 ___ 计划成效取决于城市特质。波特兰等城市较易转型为创业中心,底特律等则阻力重重。实施前请客观评估本地条件。 城市与旧金山相似度越高,实施难度越低:气候宜人吗?市中心有人居住还是空心化?城市以"前卫包容"还是"传统保守"著称?附近有好大学吗?有适合步行的社区吗?极客会觉得自在吗?若全答是,不仅计划可行,单家企业成本还可能低于百万美元。 我深知任何城市执行此计划的政治意愿都微乎其微。但探索"打造硅谷需要什么"本身就充满魅力——原来这么多城市都可能触及这个目标。尽管他们仍会选择投资体育场,但至少现在有人能质问:为何不选择成为硅谷的真正竞争者? 注释 [1] 所谓本地种子基金的创办者总会发现:(a)申请者来自全国各地而非本地,(b)本地初创企业也会申请其他基金。最终申请池是按质量而非地域划分的。 [2] 劣质风投的失败在于选择同类创业者——善于演讲但缺乏实质。这是赝品筛选赝品的典型案例。由于所有参与者都极具说服力,有限合伙人直到核算收益时才会发现问题。 [3] 即便成为避税天堂也无济于事。这能吸引部分富人,但非优质天使投资人类型。 [4] 感谢Michael Keenan指出这一点。 致谢 Trevor Blackwell、Jessica Livingston、Robert Morris和Fred Wilson对本文初稿的审阅。.
February 2009 Hacker News was two years old last week. Initially it was supposed to be a side project—an application to sharpen Arc on, and a place for current and future Y Combinator founders to exchange news. It's grown bigger and taken up more time than I expected, but I don't regret that because I've learned so much from working on it. Growth When we launched in February 2007, weekday traffic was around 1600 daily uniques. It's since grown to around 22,000. This growth rate is a bit higher than I'd like. I'd like the site to grow, since a site that isn't growing at least slowly is probably dead. But I wouldn't want it to grow as large as Digg or Reddit—mainly because that would dilute the character of the site, but also because I don't want to spend all my time dealing with scaling. I already have problems enough with that. Remember, the original motivation for HN was to test a new programming language, and moreover one that's focused on experimenting with language design, not performance. Every time the site gets slow, I fortify myself by recalling McIlroy and Bentley's famous quote > The key to performance is elegance, not battalions of special cases.
2009年2月 上周是Hacker News成立两周年。最初它只是一个副业项目——一个用来打磨Arc语言的应用,也是当前及未来Y Combinator创始人交流新闻的场所。它的发展规模和我投入的时间都超出了预期,但我并不后悔,因为运营它让我获益良多。 成长历程 2007年2月上线时,工作日日均独立访客约为1600人。如今已增长至约22,000人。这个增速略高于我的预期。虽然我希望网站保持增长(因为停滞不前的网站无异于消亡),但我不愿它发展成Digg或Reddit那样的规模——主要担心会稀释网站特色,同时也因不愿将所有时间耗费在扩容问题上。 现有问题已足够棘手。请记住,创建HN的初衷是为了测试一门新编程语言,而且这是一门专注于语言设计实验而非性能优化的语言。每当网站运行迟缓时,我就用McIlroy和Bentley的经典名言来激励自己: > 性能的关键在于优雅,而非堆砌特例。
这是Paul Graham的文章《我从Hacker News中学到了什么》的第2部分,共3部分。
寻找能用最少代码消除的瓶颈。到目前为止,我还能勉强跟上,尽管用户量增长了14倍,但性能始终维持在中等水平。我不知道下一步该怎么做,但应该能想出办法。
这是我对待这个网站的基本态度。Hacker News是一个实验,而且是一个非常新兴领域的实验。这类网站的历史只有几年。互联网上的对话总体上也只有几十年历史。因此,我们可能只发现了未来将发现的一小部分。
这就是为什么我对HN如此乐观。当一项技术如此年轻,现有的解决方案通常都很糟糕;这意味着一定有办法做得更好;也意味着许多看似无解的问题其实并非如此。包括——我希望——困扰许多前人的问题:因增长而毁灭。
and look for the bottleneck I can remove with least code. So far I've been able to keep up, in the sense that performance has remained consistently mediocre despite 14x growth. I don't know what I'll do next, but I'll probably think of something. This is my attitude to the site generally. Hacker News is an experiment, and an experiment in a very young field. Sites of this type are only a few years old. Internet conversation generally is only a few decades old. So we've probably only discovered a fraction of what we eventually will. That's why I'm so optimistic about HN. When a technology is this young, the existing solutions are usually terrible; which means it must be possible to do much better; which means many problems that seem insoluble aren't. Including, I hope, the problem that has afflicted so many previous communities: being ruined by growth. Dilution Users have worried about that since the site was a few months old. So far these alarms have been false, but they may not always be. Dilution is a hard problem. But probably soluble; it doesn't mean much that open conversations have "always" been destroyed by growth when "always" equals 20 instances. But it's important to remember we're trying to solve a new problem, because that means we're going to have to try new things, most of which probably won't work. A couple weeks ago I tried displaying the names of users with the highest average comment scores in orange. [1] That was a mistake. Suddenly a culture that had been more or less united was divided into haves and have-nots. I didn't realize how united the culture had been till I saw it divided. It was painful to watch. [2] So orange usernames won't be back. (Sorry about that.) But there will be other equally broken-seeming ideas in the future, and the ones that turn out to work will probably seem just as broken as those that don't.
用户从网站成立几个月起就开始担心这个问题。到目前为止这些警报都是虚惊,但未来未必总是如此。稀释是个难题。但或许有解;当“总是”只等于20个案例时,说开放对话“总是”被增长摧毁并没有太大意义。
但重要的是记住我们在尝试解决一个新问题,这意味着我们必须尝试新方法,而大多数可能行不通。几周前我尝试用橙色显示平均评论得分最高的用户名。[1]这是个错误。原本基本团结的文化突然分裂成“有产者”和“无产者”。直到看到分裂,我才意识到原先的团结有多珍贵。这过程令人痛苦。[2]
所以橙色用户名不会再出现。(对此我很抱歉。)但未来还会有其他看似同样糟糕的主意,而最终成功的那些可能和失败的看起来一样糟糕。
关于稀释,我学到最重要的大概是:衡量标准更多在于行为而非用户。你想阻挡的是不良行为,而非不良用户。用户行为出人意料地具有可塑性。如果人们被期待表现良好,他们往往会做到;反之亦然。
当然,禁止不良行为确实会赶走不良用户,因为他们在一个需要表现良好的地方感到束缚。但这种阻挡方式比显性屏障更温和,可能也更有效。
Probably the most important thing I've learned about dilution is that it's measured more in behavior than users. It's bad behavior you want to keep out more than bad people. User behavior turns out to be surprisingly malleable. If people are expected to behave well, they tend to; and vice versa. Though of course forbidding bad behavior does tend to keep away bad people, because they feel uncomfortably constrained in a place where they have to behave well. But this way of keeping them out is gentler and probably also more effective than overt barriers. It's pretty clear now that the broken windows theory applies to community sites as well. The theory is that minor forms of bad behavior encourage worse ones: that a neighborhood with lots of graffiti and broken windows becomes one where robberies occur. I was living in New York when Giuliani introduced the reforms that made the broken windows theory famous, and the transformation was miraculous. And I was a Reddit user when the opposite happened there, and the transformation was equally dramatic. I'm not criticizing Steve and Alexis. What happened to Reddit didn't happen out of neglect. From the start they had a policy of censoring nothing except spam. Plus Reddit had different goals from Hacker News. Reddit was a startup, not a side project; its goal was to grow as fast as possible. Combine rapid growth and zero censorship, and the result is a free for all. But I don't think they'd do much differently if they were doing it again. Measured by traffic, Reddit is much more successful than Hacker News. But what happened to Reddit won't inevitably happen to HN. There are several local maxima. There can be places that are free for alls and places that are more thoughtful, just as there are in the real world; and people will behave differently depending on which they're in, just as they do in the real world. I've observed this in the wild.
现在很清楚,破窗理论也适用于社区网站。该理论认为轻微的不良行为会助长更严重的:一个满是涂鸦和破窗的社区会变成抢劫案高发地。朱利安尼推行让破窗理论闻名的改革时,我住在纽约,那种转变堪称奇迹。而当相反情况发生在Reddit时,我也是一名用户,其转变同样戏剧性。
我并非批评Steve和Alexis。Reddit的遭遇并非因为疏忽。他们从一开始就奉行只屏蔽垃圾信息的政策。此外Reddit的目标与Hacker News不同。Reddit是创业公司,而非副项目;它的目标是尽可能快速增长。快速增长加零审查,结果就是彻底的自由放任。但我不认为他们重来一次会做出多大改变。以流量衡量,Reddit比Hacker News成功得多。
但Reddit的遭遇不一定会降临HN。存在多个局部最优解。可以有彻底自由的空间,也可以有更深思熟虑的空间,就像现实世界一样;人们会根据所处环境调整行为,正如现实世界那样。
我亲眼见过这种现象。有人在Reddit和Hacker News交叉发帖时,会特意写两个版本:Reddit上煽动,HN上克制。
Hacker News这类网站需要避免两类主要问题:劣质文章和劣质评论。目前劣质文章的风险似乎较小。首页展示的内容仍大致符合HN创立时的标准。
我曾以为需要通过加权投票来屏蔽垃圾内容,但至今尚未实施。我没想到首页能保持得这么好,也不完全明白原因。或许只有更深思熟虑的用户才愿意提交和投票,因此每增加一个随机新用户的边际成本接近零。又或许首页通过展示内容标准实现了自我保护。
I've seen people cross-posting on Reddit and Hacker News who actually took the trouble to write two versions, a flame for Reddit and a more subdued version for HN. Submissions There are two major types of problems a site like Hacker News needs to avoid: bad stories and bad comments. So far the danger of bad stories seems smaller. The stories on the frontpage now are still roughly the ones that would have been there when HN started. I once thought I'd have to weight votes to keep crap off the frontpage, but I haven't had to yet. I wouldn't have predicted the frontpage would hold up so well, and I'm not sure why it has. Perhaps only the more thoughtful users care enough to submit and upvote links, so the marginal cost of one random new user approaches zero. Or perhaps the frontpage protects itself, by advertising what type of submission is expected. The most dangerous thing for the frontpage is stuff that's too easy to upvote. If someone proves a new theorem, it takes some work by the reader to decide whether or not to upvote it. An amusing cartoon takes less. A rant with a rallying cry as the title takes zero, because people vote it up without even reading it. Hence what I call the Fluff Principle: on a user-voted news site, the links that are easiest to judge will take over unless you take specific measures to prevent it. Hacker News has two kinds of protections against fluff. The most common types of fluff links are banned as off-topic. Pictures of kittens, political diatribes, and so on are explicitly banned. This keeps out most fluff, but not all of it. Some links are both fluff, in the sense of being very short, and also on topic. There's no single solution to that. If a link is just an empty rant, editors will sometimes kill it even if it's on topic in the sense of being about hacking, because it's not on topic by the real standard, which is to engage one's intellectual curiosity.
首页最危险的莫过于太容易获得投票的内容。如果有人证明新定理,读者需要花些功夫决定是否投票。有趣漫画需要的思考较少。而标题煽动的 rant 则完全不需要,因为人们不读内容就会投票。
因此我提出“泡沫原则”:在用户投票的新闻网站,除非采取特定措施,否则最易评判的链接将占据主导。
HN有两道防线抵御泡沫。最常见的泡沫链接被归类为无关内容禁止发布。小猫图片、政治抨击等被明确禁止。这阻挡了大部分泡沫,但非全部。有些链接既短小(泡沫特征)又主题相关。
对此没有单一解决方案。如果链接只是空洞的 rant,管理员有时会删除,即使它 technically 关于黑客——因为真正标准是激发求知欲。若某网站内容多属此类,我可能封禁其域名,来自该网址的新内容会自动删除。若帖子标题诱导点击,管理员会改为平实表述。这对标题是 rallying cry 的链接尤其必要,否则它们会变成隐形的“认同就点赞”帖子——泡沫的终极形态。
处理链接的技术必须进化,因为链接在进化。聚合器的存在已影响被聚合内容。作者开始为吸引聚合器流量刻意写作——有时甚至针对特定平台。(不,这句话的反讽我没忽略。)还有更恶意的变体,如 linkjacking——转述他人文章后提交 paraphrase 而非原文。这些能获得大量点赞,因为文章精华常被保留;事实上,paraphrase 越接近抄袭,保留越多。[3]
If the posts on a site are characteristically of this type I sometimes ban it, which means new stuff at that url is auto-killed. If a post has a linkbait title, editors sometimes rephrase it to be more matter-of-fact. This is especially necessary with links whose titles are rallying cries, because otherwise they become implicit "vote up if you believe such-and-such" posts, which are the most extreme form of fluff. The techniques for dealing with links have to evolve, because the links do. The existence of aggregators has already affected what they aggregate. Writers now deliberately write things to draw traffic from aggregators—sometimes even specific ones. (No, the irony of this statement is not lost on me.) Then there are the more sinister mutations, like linkjacking—posting a paraphrase of someone else's article and submitting that instead of the original. These can get a lot of upvotes, because a lot of what's good in an article often survives; indeed, the closer the paraphrase is to plagiarism, the more survives. [3] I think it's important that a site that kills submissions provide a way for users to see what got killed if they want to. That keeps editors honest, and just as importantly, makes users confident they'd know if the editors stopped being honest. HN users can do this by flipping a switch called showdead in their profile. [4] Comments Bad comments seem to be a harder problem than bad submissions. While the quality of links on the frontpage of HN hasn't changed much, the quality of the median comment may have decreased somewhat. There are two main kinds of badness in comments: meanness and stupidity. There is a lot of overlap between the two—mean comments are disproportionately likely also to be dumb—but the strategies for dealing with them are different. Meanness is easier to control. You can have rules saying one shouldn't be mean, and if you enforce them it seems possible to keep a lid on meanness.
我认为,删除提交的网站必须提供查看被删内容的途径。这既监督管理员,也确保用户相信能察觉管理员的不公。HN用户可通过个人资料中的showdead开关实现。[4]
劣质评论似乎比劣质文章更难解决。虽然HN首页链接质量变化不大,但评论的中位数质量可能有所下降。
劣质评论主要有两种:刻薄与愚蠢。两者常重叠——刻薄评论往往也愚蠢——但应对策略不同。刻薄更容易控制。制定禁止刻薄的规则并执行,似乎能有效抑制。
抑制愚蠢更难,或许因愚蠢更难辨别。刻薄者比愚蠢者更容易意识到自己的刻薄。
最危险的愚蠢评论不是长篇大论但错误的观点,而是无聊玩笑。长篇错误观点其实很罕见。评论质量与长度高度相关;若要比较社区网站评论质量,平均长度是良好指标。原因可能在于人性而非评论线程特性。或许愚蠢更多表现为缺乏观点,而非观点错误。
无论原因为何,愚蠢评论往往短小。由于短评难以靠信息量出众,人们转而追求幽默。愚蠢评论最诱人的形式是所谓机智挖苦,可能因挖苦是最简单的幽默。[5]因此禁止刻薄的附带好处是减少这类内容。
Keeping a lid on stupidity is harder, perhaps because stupidity is not so easily distinguishable. Mean people are more likely to know they're being mean than stupid people are to know they're being stupid. The most dangerous form of stupid comment is not the long but mistaken argument, but the dumb joke. Long but mistaken arguments are actually quite rare. There is a strong correlation between comment quality and length; if you wanted to compare the quality of comments on community sites, average length would be a good predictor. Probably the cause is human nature rather than anything specific to comment threads. Probably it's simply that stupidity more often takes the form of having few ideas than wrong ones. Whatever the cause, stupid comments tend to be short. And since it's hard to write a short comment that's distinguished for the amount of information it conveys, people try to distinguish them instead by being funny. The most tempting format for stupid comments is the supposedly witty put-down, probably because put-downs are the easiest form of humor. [5] So one advantage of forbidding meanness is that it also cuts down on these. Bad comments are like kudzu: they take over rapidly. Comments have much more effect on new comments than submissions have on new submissions. If someone submits a lame article, the other submissions don't all become lame. But if someone posts a stupid comment on a thread, that sets the tone for the region around it. People reply to dumb jokes with dumb jokes. Maybe the solution is to add a delay before people can respond to a comment, and make the length of the delay inversely proportional to some prediction of its quality. Then dumb threads would grow slower. [6] People I notice most of the techniques I've described are conservative: they're aimed at preserving the character of the site rather than enhancing it. I don't think that's a bias of mine. It's due to the shape of the problem.
劣质评论如同葛藤:会迅速蔓延。评论对新评论的影响远大于文章对新文章的影响。若有人提交低劣文章,其他提交不会集体变差。但若某条评论愚蠢,它会设定周围讨论的基调。人们用无聊玩笑回应无聊玩笑。
或许解决方案是在回复评论前增加延迟,延迟长度与评论质量预测值成反比。这样愚蠢讨论会生长更慢。[6]
我注意到所述方法大多保守:旨在保持而非提升网站特质。我不认为这是个人偏见,而是问题本质使然。HN有幸始于良好状态,因此这确实是保存问题。但我认为该原则也适用于不同起源的网站。
社区网站的优质内容更多来自人而非技术;技术主要在预防劣质内容时发挥作用。技术当然能促进讨论。例如嵌套评论。但我宁愿使用功能原始但用户聪明友善的网站,而非功能先进但用户愚蠢或引战的平台。
因此社区网站最重要的任务是吸引目标用户。追求最大规模的网站希望吸引所有人。但瞄准特定用户群的网站必须精准吸引——同样重要的是,排斥其他人群。我在HN有意识地这样做。设计尽可能朴素,网站规则反对夸张标题。目标是让首次访问者唯一感兴趣的只能是那里表达的思想。
Hacker News had the good fortune to start out good, so in this case it's literally a matter of preservation. But I think this principle would also apply to sites with different origins. The good things in a community site come from people more than technology; it's mainly in the prevention of bad things that technology comes into play. Technology certainly can enhance discussion. Nested comments do, for example. But I'd rather use a site with primitive features and smart, nice users than a more advanced one whose users were idiots or trolls. So the most important thing a community site can do is attract the kind of people it wants. A site trying to be as big as possible wants to attract everyone. But a site aiming at a particular subset of users has to attract just those—and just as importantly, repel everyone else. I've made a conscious effort to do this on HN. The graphic design is as plain as possible, and the site rules discourage dramatic link titles. The goal is that the only thing to interest someone arriving at HN for the first time should be the ideas expressed there. The downside of tuning a site to attract certain people is that, to those people, it can be too attractive. I'm all too aware how addictive Hacker News can be. For me, as for many users, it's a kind of virtual town square. When I want to take a break from working, I walk into the square, just as I might into Harvard Square or University Ave in the physical world. [7] But an online square is more dangerous than a physical one. If I spent half the day loitering on University Ave, I'd notice. I have to walk a mile to get there, and sitting in a cafe feels different from working. But visiting an online forum takes just a click, and feels superficially very much like working. You may be wasting your time, but you're not idle. Someone is wrong on the Internet, and you're fixing the problem. Hacker News is definitely useful.
针对特定人群调整网站的缺点是:对目标人群可能过于吸引。我深知Hacker News有多令人上瘾。对我和许多用户而言,它是虚拟的城镇广场。想休息时,我就走进广场,就像走进现实中的哈佛广场或大学路。[7]但线上广场比实体更危险。若在大学路闲逛半天,我会察觉。去那里要步行一英里,坐在咖啡馆与工作感觉不同。但访问在线论坛只需点击,表面与工作极为相似。你可能在浪费时间,但并非无所事事。网上有人犯错,而你正在纠正。
Hacker News无疑有用。我从HN阅读的内容中学到很多。有几篇文章最初是那里的评论。因此我不希望它消失。但我想确认它没有净消耗生产力。若吸引成千上万聪明人到导致他们浪费时间的网站,将是场灾难。我希望能百分百确定这不是HN的写照。
我认为游戏和社交应用的成瘾性仍是未解难题。现状如同1980年代的可卡因:我们发明了极易上瘾的新事物,却尚未进化出自我保护机制。我们终将做到,这是我接下来希望关注的问题之一。
[1] 我尝试过按评论得分的平均值和中位数排名,剔除最高分后的平均值对高质量预测更准确。但中位数可能对低质量预测更准。
[2] 这个实验还让我明白:若要对人区分,必须确保方法正确。这是快速原型法不适用的问题。
事实上,反对区别对待的诚实理由是:并非人人相同,而是容易做错且难以做对。
I've learned a lot from things I've read on HN. I've written several essays that began as comments there. So I wouldn't want the site to go away. But I would like to be sure it's not a net drag on productivity. What a disaster that would be, to attract thousands of smart people to a site that caused them to waste lots of time. I wish I could be 100% sure that's not a description of HN. I feel like the addictiveness of games and social applications is still a mostly unsolved problem. The situation now is like it was with crack in the 1980s: we've invented terribly addictive new things, and we haven't yet evolved ways to protect ourselves from them. We will eventually, and that's one of the problems I hope to focus on next. Notes [1] I tried ranking users by both average and median comment score, and average (with the high score thrown out) seemed the more accurate predictor of high quality. Median may be the more accurate predictor of low quality though. [2] Another thing I learned from this experiment is that if you're going to distinguish between people, you better be sure you do it right. This is one problem where rapid prototyping doesn't work. Indeed, that's the intellectually honest argument for not discriminating between various types of people. The reason not to do it is not that everyone's the same, but that it's bad to do wrong and hard to do right. [3] When I catch egregiously linkjacked posts I replace the url with that of whatever they copied. Sites that habitually linkjack get banned. [4] Digg is notorious for its lack of transparency. The root of the problem is not that the guys running Digg are especially sneaky, but that they use the wrong algorithm for generating their frontpage. Instead of bubbling up from the bottom as they get more votes, as on Reddit, stories start at the top and get pushed down by new arrivals.
[3] 发现严重 linkjacking 时,我会将网址替换为被抄袭的原链接。惯犯网站会被封禁。
[4] Digg因缺乏透明度声名狼藉。根源并非运营者特别狡猾,而是采用了错误的前页生成算法。与Reddit不同,Digg的故事从顶部开始,被新内容向下推挤。
差异源于Digg继承Slashdot,Reddit继承Delicious/popular。Digg是用投票代替编辑的Slashdot,Reddit是用投票代替书签的Delicious/popular。(从界面设计仍能看出渊源。)
Digg算法极易被操纵,因为任何登上首页的故事都会成为新头条。这迫使Digg采取极端对策。许多初创公司都有早期不得已的秘密手段,我怀疑Digg的是:头条实际由人工编辑选定。
[5] 《瘪四与大头蛋》的对话多属此类,当我在糟糕网站读评论时,能听到他们的声音。
The reason for the difference is that Digg is derived from Slashdot, while Reddit is derived from Delicious/popular. Digg is Slashdot with voting instead of editors, and Reddit is Delicious/popular with voting instead of bookmarking. (You can still see fossils of their origins in their graphic design.) Digg's algorithm is very vulnerable to gaming, because any story that makes it onto the frontpage is the new top story. Which in turn forces Digg to respond with extreme countermeasures. A lot of startups have some kind of secret about the subterfuges they had to resort to in the early days, and I suspect Digg's is the extent to which the top stories were de facto chosen by human editors. [5] The dialog on Beavis and Butthead was composed largely of these, and when I read comments on really bad sites I can hear them in their voices. [6] I suspect most of the techniques for discouraging stupid comments have yet to be discovered. Xkcd implemented a particularly clever one in its IRC channel: don't allow the same thing twice. Once someone has said "fail," no one can ever say it again. This would penalize short comments especially, because they have less room to avoid collisions in. Another promising idea is the stupid filter, which is just like a probabilistic spam filter, but trained on corpora of stupid and non-stupid comments instead. You may not have to kill bad comments to solve the problem. Comments at the bottom of a long thread are rarely seen, so it may be enough to incorporate a prediction of quality in the comment sorting algorithm. [7] What makes most suburbs so demoralizing is that there's no center to walk to. Thanks to Justin Kan, Jessica Livingston, Robert Morris, Alexis Ohanian, Emmet Shear, and Fred Wilson for reading drafts of this. Comment on this essay..
[6] 我认为抑制愚蠢评论的大多数方法尚未被发现。Xkcd在IRC频道实施了特别聪明的一招:禁止重复。一旦有人说“失败”,再无人能说。这会特别惩罚短评,因其更难避免重复。
另一个有前景的主意是愚蠢过滤器,原理类似概率性垃圾过滤器,但训练数据是愚蠢与非愚蠢评论语料。
或许无需删除劣质评论也能解决问题。长线程底部的评论很少被看到,因此在排序算法中加入质量预测可能足够。
[7] 多数郊区令人沮丧的原因在于没有可步行前往的中心。
致谢 Justin Kan、Jessica Livingston、Robert Morris、Alexis Ohanian、Emmet Shear和Fred Wilson阅读了本文草稿。
评论本文。
Want to start a startup? Get funded by Y Combinator.
Watch how this essay was written.
February 2009 One of the things I always tell startups is a principle I learned from Paul Buchheit: it's better to make a few people really happy than to make a lot of people semi-happy. I was saying recently to a reporter that if I could only tell startups 10 things, this would be one of them. Then I thought: what would the other 9 be? When I made the list there turned out to be 13:
想创办一家创业公司? 获得 Y Combinator 的资助。
观看这篇文章是如何写成的。
2009年2月 我经常告诉创业公司的一个原则是从保罗·布赫海特那里学来的:让少数人真正快乐,比让很多人半快乐要好。我最近对一位记者说,如果我只能告诉创业公司10件事,这会是其中之一。然后我想:另外9件会是什么? 当我列出清单时,结果有13条:
1. 选择优秀的联合创始人。
联合创始人对于初创企业,就像地段对于房地产一样重要。你可以改变房子的任何部分,唯独无法改变它的位置。在创业中,你可以轻易调整想法,但更换联合创始人却极为困难。[1] 而初创企业的成功几乎总是取决于创始人的素质。
2. 快速发布。
快速发布的关键原因并不完全是为了尽早将产品推向市场,而是因为只有发布后你才算真正开始工作。发布过程会告诉你本该构建什么。在此之前,你的努力可能是徒劳的。因此,初期产品的核心价值在于它是接触用户的契机。
1\. Pick good cofounders. Cofounders are for a startup what location is for real estate. You can change anything about a house except where it is. In a startup you can change your idea easily, but changing your cofounders is hard. [1] And the success of a startup is almost always a function of its founders. 2\. Launch fast. The reason to launch fast is not so much that it's critical to get your product to market early, but that you haven't really started working on it till you've launched. Launching teaches you what you should have been building. Till you know that you're wasting your time. So the main value of whatever you launch with is as a pretext for engaging users. 3\. Let your idea evolve. This is the second half of launching fast. Launch fast and iterate. It's a big mistake to treat a startup as if it were merely a matter of implementing some brilliant initial idea. As in an essay, most of the ideas appear in the implementing. 4\. Understand your users. You can envision the wealth created by a startup as a rectangle, where one side is the number of users and the other is how much you improve their lives. [2] The second dimension is the one you have most control over. And indeed, the growth in the first will be driven by how well you do in the second. As in science, the hard part is not answering questions but asking them: the hard part is seeing something new that users lack. The better you understand them the better the odds of doing that. That's why so many successful startups make something the founders needed. 5\. Better to make a few users love you than a lot ambivalent. Ideally you want to make large numbers of users love you, but you can't expect to hit that right away. Initially you have to choose between satisfying all the needs of a subset of potential users, or satisfying a subset of the needs of all potential users. Take the first.
3. 让想法自然进化。
这是“快速发布”的另一面。快速发布并持续迭代。将初创企业视为单纯执行某个绝妙初始想法的工具是大错特错的。就像写作一样,大多数灵感会在实施过程中涌现。
4. 理解你的用户。
你可以将初创企业创造的财富想象成一个矩形:一边是用户数量,另一边是你改善用户生活的程度。[2] 后者是你能掌控更多的维度。事实上,前者的增长恰恰取决于后者做得如何。如同科学研究,难点不在于回答问题,而在于提出问题——关键在于发现用户未被满足的新需求。越了解用户,成功概率越高。这就是为什么许多成功企业创造的产品正是创始人自己所需的。
5. 宁可让少数用户狂热,也别让多数用户无感。
理想状态下你希望赢得海量用户的喜爱,但初期必须做出选择:要么满足一小部分用户的全部需求,要么满足所有用户的部分需求。选择前者。横向扩展用户群比纵向提升满意度更容易。更重要的是,数据不会欺骗你——如果自认为产品完成了85%,实际可能是70%或10%?而用户数量一目了然。
It's easier to expand userwise than satisfactionwise. And perhaps more importantly, it's harder to lie to yourself. If you think you're 85% of the way to a great product, how do you know it's not 70%? Or 10%? Whereas it's easy to know how many users you have. 6\. Offer surprisingly good customer service. Customers are used to being maltreated. Most of the companies they deal with are quasi-monopolies that get away with atrocious customer service. Your own ideas about what's possible have been unconsciously lowered by such experiences. Try making your customer service not merely good, but surprisingly good. Go out of your way to make people happy. They'll be overwhelmed; you'll see. In the earliest stages of a startup, it pays to offer customer service on a level that wouldn't scale, because it's a way of learning about your users. 7\. You make what you measure. I learned this one from Joe Kraus. [3] Merely measuring something has an uncanny tendency to improve it. If you want to make your user numbers go up, put a big piece of paper on your wall and every day plot the number of users. You'll be delighted when it goes up and disappointed when it goes down. Pretty soon you'll start noticing what makes the number go up, and you'll start to do more of that. Corollary: be careful what you measure. 8\. Spend little. I can't emphasize enough how important it is for a startup to be cheap. Most startups fail before they make something people want, and the most common form of failure is running out of money. So being cheap is (almost) interchangeable with iterating rapidly. [4] But it's more than that. A culture of cheapness keeps companies young in something like the way exercise keeps people young. 9\. Get ramen profitable. "Ramen profitable" means a startup makes just enough to pay the founders' living expenses.
6. 提供超预期的客户服务。
用户早已习惯被糟糕对待。他们接触的大多是垄断企业,这些公司即便服务恶劣也能存活。这种经历无形中拉低了你的期望值。试着让客服不仅达标,更要惊艳。主动创造惊喜,用户的反响会让你震撼。初创早期,提供无法规模化的极致服务是值得的,因为这是了解用户的绝佳途径。
7. 测量驱动改进。
这个观点来自Joe Kraus。[3] 测量本身就有催生改进的神奇力量。如果想提升用户数,就在墙上贴张大纸每天记录数字。数字增长你会欣喜,下降则会沮丧。很快你将洞察增长动因并加以强化。但切记:谨慎选择测量指标。
8. 保持节俭。
初创企业必须极度节俭,这点怎么强调都不为过。多数失败源于资金耗尽而非产品未达标。因此节俭几乎等同于快速迭代。[4] 但意义不止于此:节俭文化能让公司保持年轻活力,如同锻炼之于人体。
It's not rapid prototyping for business models (though it can be), but more a way of hacking the investment process. Once you cross over into ramen profitable, it completely changes your relationship with investors. It's also great for morale. 10\. Avoid distractions. Nothing kills startups like distractions. The worst type are those that pay money: day jobs, consulting, profitable side-projects. The startup may have more long-term potential, but you'll always interrupt working on it to answer calls from people paying you now. Paradoxically, fundraising is this type of distraction, so try to minimize that too. 11\. Don't get demoralized. Though the immediate cause of death in a startup tends to be running out of money, the underlying cause is usually lack of focus. Either the company is run by stupid people (which can't be fixed with advice) or the people are smart but got demoralized. Starting a startup is a huge moral weight. Understand this and make a conscious effort not to be ground down by it, just as you'd be careful to bend at the knees when picking up a heavy box. 12\. Don't give up. Even if you get demoralized, don't give up. You can get surprisingly far by just not giving up. This isn't true in all fields. There are a lot of people who couldn't become good mathematicians no matter how long they persisted. But startups aren't like that. Sheer effort is usually enough, so long as you keep morphing your idea. 13\. Deals fall through. One of the most useful skills we learned from Viaweb was not getting our hopes up. We probably had 20 deals of various types fall through. After the first 10 or so we learned to treat deals as background processes that we should ignore till they terminated. It's very dangerous to morale to start to depend on deals closing, not just because they so often don't, but because it makes them less likely to..
9. 实现"泡面盈利"。
"泡面盈利"指收入刚够覆盖创始人的生活开支。这并非商业模式的快速验证(尽管可以是),更是对融资流程的巧妙破解。一旦达到这个状态,你与投资人的关系将彻底改变,团队士气也会大振。
10. 拒绝分心。
没有什么比分心更能扼杀初创企业。最危险的是那些能赚钱的干扰:全职工作、咨询业务、盈利副业。尽管创业项目潜力更大,但付费客户的来电总会让你暂停工作。讽刺的是,融资同样属于此类干扰,也应尽量减少。
11. 保持士气。
Having gotten it down to 13 sentences, I asked myself which I'd choose if I could only keep one. Understand your users. That's the key. The essential task in a startup is to create wealth; the dimension of wealth you have most control over is how much you improve users' lives; and the hardest part of that is knowing what to make for them. Once you know what to make, it's mere effort to make it, and most decent hackers are capable of that. Understanding your users is part of half the principles in this list. That's the reason to launch early, to understand your users. Evolving your idea is the embodiment of understanding your users. Understanding your users well will tend to push you toward making something that makes a few people deeply happy. The most important reason for having surprisingly good customer service is that it helps you understand your users. And understanding your users will even ensure your morale, because when everything else is collapsing around you, having just ten users who love you will keep you going. Notes [1] Strictly speaking it's impossible without a time machine. [2] In practice it's more like a ragged comb. [3] Joe thinks one of the founders of Hewlett Packard said it first, but he doesn't remember which. [4] They'd be interchangeable if markets stood still.
虽然资金链断裂是初创企业猝死的直接原因,但深层症结往往是专注力丧失——要么管理层无能(这无法通过建议解决),要么团队因士气低落而迷失。创业背负着巨大的心理重压,要有意识避免被压垮,就像搬重物时要记得屈膝。
12. 坚持到底。
即使士气低迷,也绝不放弃。仅凭坚持就足以带你走得很远。这在其他领域未必适用(比如数学天赋与坚持时长无关),但创业不同。只要持续进化创意,努力终将见效。
13. 交易总会流产。
Viaweb教会我们最实用的技能之一就是避免过早乐观。我们经历过约20次交易告吹,前10次后就学会将其视为后台进程——除非确认完成,否则不予理会。依赖交易成约会严重打击士气,不仅因为失败率高,更可怕的是这种心态本身就会降低成功率。
将文章浓缩为13句话后,我自问:若只能保留一句,该选哪句?
Since they don't, working twice as fast is better than having twice as much time.
Turkish Translation | Spanish Translation Bulgarian Translation | Japanese Translation Persian Translation.
理解你的用户。这才是关键。创业的核心在于创造财富;而你能掌控的最大财富维度,就是改善用户生活的程度;其中最困难的部分,正是明白该为他们创造什么。一旦确定方向,剩下的不过是执行——大多数合格的黑客都能胜任。
这份清单里半数原则都关乎理解用户。这就是为什么要尽早发布产品——为了理解用户。迭代创意的本质就是理解用户的过程。深度理解用户会推动你打造令少数人狂热喜爱的产品。提供超预期客服的根本意义,也在于它助你理解用户。甚至团队士气的维系也源于此:当周遭一切崩塌时,十个深爱你的用户就足以支撑你继续前进。
备注 [1] 严格来说没有时间机器就不可能实现 [2] 实际情况更接近参差不齐的梳齿 [3] 乔认为惠普某位创始人最早说过这话,但记不清具体是谁 [4] 若市场静止不动两者本可互换。但市场瞬息万变,速度翻倍永远优于时间翻倍
[](https://s.turbifycdn.com/aah/paulgraham/after-credentials-11.gif) December 2008 A few months ago I read a _New York Times_ article on South Korean cram schools that said > Admission to the right university can make or break an ambitious young South Korean.
[](https://s.turbifycdn.com/aah/paulgraham/after-credentials-11.gif) 2008年12月 几个月前,我读到《纽约时报》一篇关于韩国补习学校的文章,其中提到 > 对胸怀大志的韩国年轻人而言,进入合适的大学可能成就也可能毁掉他们的人生。
> "在我国,大学入学考试决定了一个人70%到80%的未来。"
这段论述听起来是如此过时,令人惊讶。然而在我高中时代,它作为对美国社会的描述还不算太离谱。这意味着过去25年间,美国社会必然发生了深刻变革。
A parent added:
如今在美国,决定人生轨迹的要素已从学历证书转向实际能力。名校背景依然重要,但其影响力已大不如前。
以学术资历评判人才曾是社会进步的标志。这一传统可追溯至公元587年的中国科举制度——选拔官员需通过儒家经典考试[1]。这本质上也是财富测试,因为应试所需的专业知识必须通过长期昂贵训练获得。尽管财富是及第的必要条件,却非充分条件。以公元587年的世界标准来看,中国科举制度堪称开明。欧洲直到19世纪才建立文官考试制度,且明显借鉴了中国经验。
在文凭制度之前,官职获取主要依靠家族势力甚至公然行贿。通过考试选拔人才是巨大进步,但绝非完美方案。这种选拔方式必然催生应试教育——无论是明朝中国、维多利亚时代的英国,还是当代韩国,补习机构都如影随形。
补习机构实质上是制度防线的漏洞。文凭制度本意是阻断代际权力的直接传递,而补习班则代表着财富找到了制度缺口。它们将上一代的财富转化为下一代的文凭资质。
> "In our country, college entrance exams determine 70 to 80 percent of a person's future."
这种现象难以根除,因为教育机构会不断适应考核标准。当考试范围狭窄且模式固定时,就会出现传统补习班——比如英国桑赫斯特军校的备考课程,或是如今美国学生提升SAT分数的培训班。随着考试范围扩大,补习机构也随之进化。如同现代预科学校,中国古代科举备考同样需要数年光阴。但这些机构的本质始终如一:突破体制限制[2]。
历史表明,在其他条件相同时,社会繁荣程度与其阻断家长直接影响子女成就的能力成正比。父母通过间接方式(如培养子女智慧或自律品格)助力子女成长值得赞赏,问题在于直接手段——用自身财富权力替代子女能力。
只要有机会,父母就会这么做。父母愿为子女牺牲生命,自然也会为其突破道德底线——尤其在"别人都这么做"时。
It was striking how old fashioned this sounded. And yet when I was in high school it wouldn't have seemed too far off as a description of the US. Which means things must have been changing here. The course of people's lives in the US now seems to be determined less by credentials and more by performance than it was 25 years ago. Where you go to college still matters, but not like it used to. What happened? _____ Judging people by their academic credentials was in its time an advance. The practice seems to have begun in China, where starting in 587 candidates for the imperial civil service had to take an exam on classical literature. [1] It was also a test of wealth, because the knowledge it tested was so specialized that passing required years of expensive training. But though wealth was a necessary condition for passing, it was not a sufficient one. By the standards of the rest of the world in 587, the Chinese system was very enlightened. Europeans didn't introduce formal civil service exams till the nineteenth century, and even then they seem to have been influenced by the Chinese example. Before credentials, government positions were obtained mainly by family influence, if not outright bribery. It was a great step forward to judge people by their performance on a test. But by no means a perfect solution. When you judge people that way, you tend to get cram schools—which they did in Ming China and nineteenth century England just as much as in present day South Korea. What cram schools are, in effect, is leaks in a seal. The use of credentials was an attempt to seal off the direct transmission of power between generations, and cram schools represent that power finding holes in the seal. Cram schools turn wealth in one generation into credentials in the next. It's hard to beat this phenomenon, because the schools adjust to suit whatever the tests measure.
阻断这种直接干预具有双重效益:社会不仅能实现"人尽其才",更能将父母野心引导至培养子女实际能力的正道。
但我们必须认识到,遏制父母为子女谋取不正当优势极为困难。这是人性中最强大的力量之一,任何简单解决方案都如同监狱禁毒般难以奏效。
最直接的解决方案是完善文凭制度。当现有考核体系存在漏洞时,我们可以研究作弊手法并修补缺陷。补习机构恰恰揭示了制度漏洞所在,其衰落也标志着改革成效。
更根本的解决之道是推动关键社会节点(如大学招生)的透明度。美国大学招生仍存在诸多腐败迹象,例如传承录取制度。官方说辞是校友子女仅在同分情况下享有优先权——申请人按能力分组,传承身份只影响临界线附近的取舍。但这意味着大学可通过调整临界区间大小,任意操控传承因素权重。
When the tests are narrow and predictable, you get cram schools on the classic model, like those that prepared candidates for Sandhurst (the British West Point) or the classes American students take now to improve their SAT scores. But as the tests get broader, the schools do too. Preparing a candidate for the Chinese imperial civil service exams took years, as prep school does today. But the raison d'etre of all these institutions has been the same: to beat the system. [2] _____ History suggests that, all other things being equal, a society prospers in proportion to its ability to prevent parents from influencing their children's success directly. It's a fine thing for parents to help their children indirectly—for example, by helping them to become smarter or more disciplined, which then makes them more successful. The problem comes when parents use direct methods: when they are able to use their own wealth or power as a substitute for their children's qualities. Parents will tend to do this when they can. Parents will die for their kids, so it's not surprising to find they'll also push their scruples to the limits for them. Especially if other parents are doing it. Sealing off this force has a double advantage. Not only does a society get "the best man for the job," but parents' ambitions are diverted from direct methods to indirect ones—to actually trying to raise their kids well. But we should expect it to be very hard to contain parents' efforts to obtain an unfair advantage for their kids. We're dealing with one of the most powerful forces in human nature. We shouldn't expect naive solutions to work, any more than we'd expect naive solutions for keeping heroin out of a prison to work. _____ The obvious way to solve the problem is to make credentials better. If the tests a society uses are currently hackable, we can study the way people beat them and try to plug the holes.
通过持续遏制文凭滥用,或许能构建更严密的制度。但这注定是场持久战——尤其当主考机构本身缺乏改革动力时。
幸运的是,我们还有更好的解决方案:与其强化文凭防伪,不如降低文凭本身的重要性。
让我们思考文凭的本质功能:它本质上是能力预测工具。若能直接评估实际能力,文凭便毫无必要。
为何文凭制度会产生?为何不直接考核实际能力?观察文凭主义的起源场域就能明白——大型组织的选才机制。在庞大机构中,个人绩效难以量化,而越难评估绩效,预测就越重要。若组织能即时低成本评估新人表现,就无需考察文凭——大可以广纳人才,优胜劣汰。
You can use the cram schools to show you where most of the holes are. They also tell you when you're succeeding in fixing them: when cram schools become less popular. A more general solution would be to push for increased transparency, especially at critical social bottlenecks like college admissions. In the US this process still shows many outward signs of corruption. For example, legacy admissions. The official story is that legacy status doesn't carry much weight, because all it does is break ties: applicants are bucketed by ability, and legacy status is only used to decide between the applicants in the bucket that straddles the cutoff. But what this means is that a university can make legacy status have as much or as little weight as they want, by adjusting the size of the bucket that straddles the cutoff. By gradually chipping away at the abuse of credentials, you could probably make them more airtight. But what a long fight it would be. Especially when the institutions administering the tests don't really want them to be airtight. _____ Fortunately there's a better way to prevent the direct transmission of power between generations. Instead of trying to make credentials harder to hack, we can also make them matter less. Let's think about what credentials are for. What they are, functionally, is a way of predicting performance. If you could measure actual performance, you wouldn't need them. So why did they even evolve? Why haven't we just been measuring actual performance? Think about where credentialism first appeared: in selecting candidates for large organizations. Individual performance is hard to measure in large organizations, and the harder performance is to measure, the more important it is to predict it. If an organization could immediately and cheaply measure the performance of recruits, they wouldn't need to examine their credentials. They could take everyone and keep just the good ones.
大型组织无力实施这种机制,但市场中的小型组织集群可以接近这个理想状态。市场对所有组织进行筛选,保留优质者。当组织规模足够小时,这就近似于对个人的直接筛选。因此在其他条件相同时,由更多小型组织构成的社会会更不重视文凭。
这正是美国正在发生的变革。那些韩国引文听起来如此陈旧,因为它们描述的是几十年前由大企业主导的美国经济图景。在那样的环境中,野心家的路径是加入大公司并攀登阶梯——此时文凭至关重要。在大组织文化里,精英学历会成为自我实现的预言。
这套逻辑在小公司行不通。即便同事因你的名校背景刮目相看,若表现不佳,你们很快会分道扬镳——因为公司可能倒闭,团队必然解散。
Large organizations can't do this. But a bunch of small organizations in a market can come close. A market takes every organization and keeps just the good ones. As organizations get smaller, this approaches taking every person and keeping just the good ones. So all other things being equal, a society consisting of more, smaller organizations will care less about credentials. _____ That's what's been happening in the US. That's why those quotes from Korea sound so old fashioned. They're talking about an economy like America's a few decades ago, dominated by a few big companies. The route for the ambitious in that sort of environment is to join one and climb to the top. Credentials matter a lot then. In the culture of a large organization, an elite pedigree becomes a self-fulfilling prophecy. This doesn't work in small companies. Even if your colleagues were impressed by your credentials, they'd soon be parted from you if your performance didn't match, because the company would go out of business and the people would be dispersed. In a world of small companies, performance is all anyone cares about. People hiring for a startup don't care whether you've even graduated from college, let alone which one. All they care about is what you can do. Which is in fact all that should matter, even in a large organization. The reason credentials have such prestige is that for so long the large organizations in a society tended to be the most powerful. But in the US at least they don't have the monopoly on power they once did, precisely because they can't measure (and thus reward) individual performance. Why spend twenty years climbing the corporate ladder when you can get rewarded directly by the market? I realize I see a more exaggerated version of the change than most other people. As a partner at an early stage venture funding firm, I'm like a jumpmaster shoving people out of the old world of credentials and into the new one of performance.
在小公司主导的世界里,实力才是唯一通行证。初创企业招聘时不在乎你是否大学毕业,更遑论毕业院校。他们只关注你能创造什么价值——这本该是所有组织的用人标准。文凭之所以长期享有崇高地位,是因为大型组织曾垄断社会权力。但至少在美国,这种垄断已被打破——正因为大机构无力准确评估(因而无法合理回报)个人绩效。当市场能直接给予回报时,谁还愿花二十年爬 corporate ladder?
我承认自己可能比常人更强烈地感知这种变革。作为早期风投机构合伙人,我就像跳伞教练,将人们从文凭旧世界推入能力新天地。我是这场变革的推动者,但绝非幻想者。25年前,有志之士很难选择直接接受市场检验——你必须经过老板筛选,而他们深受你毕业院校的影响。
是什么让小型组织在美国取得成功?我尚未完全确定答案,但初创企业无疑是重要因素。小组织能更快孕育新创意,而创新价值正与日俱增。
但我不认为初创企业能完全解释从文凭到能力的转变。我朋友Julian Weber告诉我,1950年代纽约律所给助理律师的薪酬远低于现今水平。当时的律所毫不掩饰按资历而非贡献付酬的规则——年轻员工正在"缴纳会费",回报将在未来兑现。
I'm an agent of the change I'm seeing. But I don't think I'm imagining it. It was not so easy 25 years ago for an ambitious person to choose to be judged directly by the market. You had to go through bosses, and they were influenced by where you'd been to college. _____ What made it possible for small organizations to succeed in America? I'm still not entirely sure. Startups are certainly a large part of it. Small organizations can develop new ideas faster than large ones, and new ideas are increasingly valuable. But I don't think startups account for all the shift from credentials to measurement. My friend Julian Weber told me that when he went to work for a New York law firm in the 1950s they paid associates far less than firms do today. Law firms then made no pretense of paying people according to the value of the work they'd done. Pay was based on seniority. The younger employees were paying their dues. They'd be rewarded later. The same principle prevailed at industrial companies. When my father was working at Westinghouse in the 1970s, he had people working for him who made more than he did, because they'd been there longer. Now companies increasingly have to pay employees market price for the work they do. One reason is that employees no longer trust companies to deliver deferred rewards: why work to accumulate deferred rewards at a company that might go bankrupt, or be taken over and have all its implicit obligations wiped out? The other is that some companies broke ranks and started to pay young employees large amounts. This was particularly true in consulting, law, and finance, where it led to the phenomenon of yuppies. The word is rarely used today because it's no longer surprising to see a 25 year old with money, but in 1985 the sight of a 25 year old _professional_ able to afford a new BMW was so novel that it called forth a new word. The classic yuppie worked for a small organization.
工业企业同样奉行此道。1970年代我父亲在西屋电气工作时,某些下属薪水比他更高,只因资历更深。
如今企业不得不按市场价支付报酬。部分原因是员工不再相信企业会兑现[延迟回报]:为何要在可能破产或被收购(导致所有隐性承诺作废)的公司积累未来收益?另一原因是部分公司率先打破陈规,开始高薪聘用年轻人——这在咨询、法律和金融领域尤为突出,由此催生了"雅皮士"现象。这个词如今已不常用,因为25岁的有钱人不再令人惊讶。但在1985年,能买得起全新宝马的年轻专业人士足以催生新词汇。
典型雅皮士就职于小型机构——不是通用部件公司,而是处理其收购案的法律事务所,或承销其债券的投资银行。
"初创企业"与"雅皮士"几乎同时于1970年代末80年代初进入美国话语体系。我认为二者没有因果关系:初创企业兴起源于技术变革加速打破了大公司的压制;雅皮士现象则似乎源于大公司运作规则的社会惯例(或许还有法律)变化。但这两股力量迅速融合,催生出如今看来显而易见的准则:按市场价支付年轻人才报酬,并获得相应的高绩效。
He didn't work for General Widget, but for the law firm that handled General Widget's acquisitions or the investment bank that floated their bond issues. Startups and yuppies entered the American conceptual vocabulary roughly simultaneously in the late 1970s and early 1980s. I don't think there was a causal connection. Startups happened because technology started to change so fast that big companies could no longer keep a lid on the smaller ones. I don't think the rise of yuppies was inspired by it; it seems more as if there was a change in the social conventions (and perhaps the laws) governing the way big companies worked. But the two phenomena rapidly fused to produce a principle that now seems obvious: paying energetic young people market rates, and getting correspondingly high performance from them. At about the same time the US economy rocketed out of the doldrums that had afflicted it for most of the 1970s. Was there a connection? I don't know enough to say, but it felt like it at the time. There was a lot of energy released. _____ Countries worried about their competitiveness are right to be concerned about the number of startups started within them. But they would do even better to examine the underlying principle. Do they let energetic young people get paid market rate for the work they do? The young are the test, because when people aren't rewarded according to performance, they're invariably rewarded according to seniority instead. All it takes is a few beachheads in your economy that pay for performance. Measurement spreads like heat. If one part of a society is better at measurement than others, it tends to push the others to do better. If people who are young but smart and driven can make more by starting their own companies than by working for existing ones, the existing companies are forced to pay more to keep them.
几乎同时,美国经济摆脱了1970年代的长期低迷。两者是否存在关联?我学识有限难下定论,但当时确实能感受到蓬勃迸发的能量。
关注国际竞争力的国家重视初创企业数量是正确的,但更应探究深层原则:是否允许有为青年按其贡献获取市场报酬?年轻人是最佳试金石——当社会不按绩效回报时,资历就会成为替代标准。
只需在经济体中建立几个按绩效付酬的桥头堡,这种机制就会如热力般扩散。当某社会群体更善评估绩效时,就会推动其他群体效仿。当聪明勤奋的年轻人创业比打工更赚钱时,现有企业就不得不提高待遇留人。于是市场定价逐渐渗透每个组织——甚至政府机构[3]。
So market rates gradually permeate every organization, even the government. [3] The measurement of performance will tend to push even the organizations issuing credentials into line. When we were kids I used to annoy my sister by ordering her to do things I knew she was about to do anyway. As credentials are superseded by performance, a similar role is the best former gatekeepers can hope for. Once credential granting institutions are no longer in the self-fullfilling prophecy business, they'll have to work harder to predict the future. _____ Credentials are a step beyond bribery and influence. But they're not the final step. There's an even better way to block the transmission of power between generations: to encourage the trend toward an economy made of more, smaller units. Then you can measure what credentials merely predict. No one likes the transmission of power between generations—not the left or the right. But the market forces favored by the right turn out to be a better way of preventing it than the credentials the left are forced to fall back on. The era of credentials began to end when the power of large organizations peaked in the late twentieth century. Now we seem to be entering a new era based on measurement. The reason the new model has advanced so rapidly is that it works so much better. It shows no sign of slowing. Notes [1] Miyazaki, Ichisada (Conrad Schirokauer trans.), _China's Examination Hell: The Civil Service Examinations of Imperial China,_ Yale University Press, 1981. Scribes in ancient Egypt took exams, but they were more the type of proficiency test any apprentice might have to pass. [2] When I say the raison d'etre of prep schools is to get kids into better colleges, I mean this in the narrowest sense.
绩效评估的趋势甚至会影响文凭颁发机构。就像我小时候常故意命令妹妹做她本就打算做的事来惹恼她,当绩效取代文凭后,昔日的守门人最多只能扮演类似角色。一旦文凭机构无法继续自我实现的预言游戏,他们就不得不更努力地预测未来。
文凭制度超越了贿赂与裙带关系,但并非终极形态。阻断代际权力传递还有更优解:推动经济向更多小型单元转型。这样我们就能直接测量文凭试图预测的内容。
没有人喜欢代际权力传递——无论左派右派。但右派推崇的市场力量,实际上比左派依赖的文凭制度更能有效阻止这种现象。
当大型组织权力在20世纪末[登顶]后,文凭时代便开始落幕。如今我们似乎正迈入以绩效评估为基础的新纪元。新范式迅猛发展的根本原因在于:它确实更高效,且毫无减速迹象。
I'm not saying that's all prep schools do, just that if they had zero effect on college admissions there would be far less demand for them. [3] Progressive tax rates will tend to damp this effect, however, by decreasing the difference between good and bad measurers. Thanks to Trevor Blackwell, Sarah Harlin, Jessica Livingston, and David Sloo for reading drafts of this..
注释 [1] 宫崎市定(康拉德·希罗考尔译),《中国的考试地狱:中华帝国的科举制度》,耶鲁大学出版社,1981年。 古埃及书吏虽需考试,但更接近学徒制的技能测试。
[2] 我说预科学校的本质是提升大学录取率,这是最狭义的定义。并非否定其教育功能,而是指若对升学毫无助益,其需求将大幅减少。
[3] 累进税率会削弱这种效应,因其缩小了优劣评估者之间的报酬差距。
致谢 特雷弗·布莱克韦尔、莎拉·哈林、杰西卡·利文斯顿和大卫·斯洛对本文草稿提出宝贵意见。
December 2008 For nearly all of history the success of a society was proportionate to its ability to assemble large and disciplined organizations. Those who bet on economies of scale generally won, which meant the largest organizations were the most successful ones. Things have already changed so much that this is hard for us to believe, but till just a few decades ago the largest organizations tended to be the most progressive. An ambitious kid graduating from college in 1960 wanted to work in the huge, gleaming offices of Ford, or General Electric, or NASA. Small meant small-time. Small in 1960 didn't mean a cool little startup. It meant uncle Sid's shoe store. When I grew up in the 1970s, the idea of the "corporate ladder" was still very much alive. The standard plan was to try to get into a good college, from which one would be drafted into some organization and then rise to positions of gradually increasing responsibility. The more ambitious merely hoped to climb the same ladder faster. [1] But in the late twentieth century something changed. It turned out that economies of scale were not the only force at work. Particularly in technology, the increase in speed one could get from smaller groups started to trump the advantages of size. The future turned out to be different from the one we were expecting in 1970. The domed cities and flying cars we expected have failed to materialize. But fortunately so have the jumpsuits with badges indicating our specialty and rank. Instead of being dominated by a few, giant tree-structured organizations, it's now looking like the economy of the future will be a fluid network of smaller, independent units. It's not so much that large organizations stopped working. There's no evidence that famously successful organizations like the Roman army or the British East India Company were any less afflicted by protocol and politics than organizations of the same size today.
But they were competing against opponents who couldn't change the rules on the fly by discovering new technology. Now it turns out the rule "large and disciplined organizations win" needs to have a qualification appended: "at games that change slowly." No one knew till change reached a sufficient speed. Large organizations _will_ start to do worse now, though, because for the first time in history they're no longer getting the best people. An ambitious kid graduating from college now doesn't want to work for a big company. They want to work for the hot startup that's rapidly growing into one. If they're really ambitious, they want to start it. [2] This doesn't mean big companies will disappear. To say that startups will succeed implies that big companies will exist, because startups that succeed either become big companies or are acquired by them. [3] But large organizations will probably never again play the leading role they did up till the last quarter of the twentieth century. It's kind of surprising that a trend that lasted so long would ever run out. How often does it happen that a rule works for thousands of years, then switches polarity? The millennia-long run of bigger-is-better left us with a lot of traditions that are now obsolete, but extremely deeply rooted. Which means the ambitious can now do arbitrage on them. It will be very valuable to understand precisely which ideas to keep and which can now be discarded. The place to look is where the spread of smallness began: in the world of startups. There have always been occasional cases, particularly in the US, of ambitious people who grew the ladder under them instead of climbing it. But till recently this was an anomalous route that tended to be followed only by outsiders. It was no coincidence that the great industrialists of the nineteenth century had so little formal education.
As huge as their companies eventually became, they were all essentially mechanics and shopkeepers at first. That was a social step no one with a college education would take if they could avoid it. Till the rise of technology startups, and in particular, Internet startups, it was very unusual for educated people to start their own businesses. The eight men who left Shockley Semiconductor to found Fairchild Semiconductor, the original Silicon Valley startup, weren't even trying to start a company at first. They were just looking for a company willing to hire them as a group. Then one of their parents introduced them to a small investment bank that offered to find funding for them to start their own, so they did. But starting a company was an alien idea to them; it was something they backed into. [4] Now I would guess that practically every Stanford or Berkeley undergrad who knows how to program has at least considered the idea of starting a startup. East Coast universities are not far behind, and British universities only a little behind them. This pattern suggests that attitudes at Stanford and Berkeley are not an anomaly, but a leading indicator. This is the way the world is going. Of course, Internet startups are still only a fraction of the world's economy. Could a trend based on them be that powerful? I think so. There's no reason to suppose there's any limit to the amount of work that could be done in this area. Like science, wealth seems to expand fractally. Steam power was a sliver of the British economy when Watt started working on it. But his work led to more work till that sliver had expanded into something bigger than the whole economy of which it had initially been a part. The same thing could happen with the Internet. If Internet startups offer the best opportunity for ambitious people, then a lot of ambitious people will start them, and this bit of the economy will balloon in the usual fractal way.
Even if Internet-related applications only become a tenth of the world's economy, this component will set the tone for the rest. The most dynamic part of the economy always does, in everything from salaries to standards of dress. Not just because of its prestige, but because the principles underlying the most dynamic part of the economy tend to be ones that work. For the future, the trend to bet on seems to be networks of small, autonomous groups whose performance is measured individually. And the societies that win will be the ones with the least impedance. As with the original industrial revolution, some societies are going to be better at this than others. Within a generation of its birth in England, the Industrial Revolution had spread to continental Europe and North America. But it didn't spread everywhere. This new way of doing things could only take root in places that were prepared for it. It could only spread to places that already had a vigorous middle class. There is a similar social component to the transformation that began in Silicon Valley in the 1960s. Two new kinds of techniques were developed there: techniques for building integrated circuits, and techniques for building a new type of company designed to grow fast by creating new technology. The techniques for building integrated circuits spread rapidly to other countries. But the techniques for building startups didn't. Fifty years later, startups are ubiquitous in Silicon Valley and common in a handful of other US cities, but they're still an anomaly in most of the world. Part of the reason—possibly the main reason—that startups have not spread as broadly as the Industrial Revolution did is their social disruptiveness. Though it brought many social changes, the Industrial Revolution was not fighting the principle that bigger is better. Quite the opposite: the two dovetailed beautifully.
The new industrial companies adapted the customs of existing large organizations like the military and the civil service, and the resulting hybrid worked well. "Captains of industry" issued orders to "armies of workers," and everyone knew what they were supposed to do. Startups seem to go more against the grain, socially. It's hard for them to flourish in societies that value hierarchy and stability, just as it was hard for industrialization to flourish in societies ruled by people who stole at will from the merchant class. But there were already a handful of countries past that stage when the Industrial Revolution happened. There do not seem to be that many ready this time. Notes [1] One of the bizarre consequences of this model was that the usual way to make more money was to become a manager. This is one of the things startups fix. [2] There are a lot of reasons American car companies have been doing so much worse than Japanese car companies, but at least one of them is a cause for optimism: American graduates have more options. [3] It's possible that companies will one day be able to grow big in revenues without growing big in people, but we are not very far along that trend yet. [4] Lecuyer, Christophe, _Making Silicon Valley_ , MIT Press, 2006. Thanks to Trevor Blackwell, Paul Buchheit, Jessica Livingston, and Robert Morris for reading drafts of this..
2008年12月 在几乎整个历史长河中,一个社会的成功程度与其组建大规模纪律性组织的能力成正比。押注规模经济的人通常能获胜,这意味着最大的组织往往是最成功的。 如今情况已发生巨变,以至于我们很难相信——但就在几十年前,最大型的组织往往代表着最先进的水平。1960年大学毕业的雄心勃勃的年轻人渴望进入福特、通用电气或NASA那些庞大闪亮的办公室工作。"小"在当时意味着不入流。1960年的"小"可不是指酷炫的小型创业公司,而是指西德叔叔的鞋店。 我在1970年代成长时,"公司阶梯"的概念仍然深入人心。标准的人生规划是:考入好大学,被某个组织录用,然后逐步晋升到责任更大的职位。更有野心的人只不过希望更快地攀爬同样的阶梯。[1] 但在二十世纪末,某些事情发生了变化。事实证明规模经济并非唯一的主导力量。尤其在科技领域,小团队所能获得的效率提升开始超越规模优势。 未来与我们1970年预期的截然不同。我们曾期待的穹顶城市和飞行汽车并未实现。但幸运的是,标明专业与等级的连体制服也未成为现实。未来的经济格局不再是少数巨型树状组织主导,而将演变为由小型独立单元组成的流动网络。 并非大型组织突然失灵。没有证据表明罗马军队或英国东印度公司等著名成功组织,会比当今同等规模的组织更少受繁文缛节和政治斗争困扰。但它们当时的竞争对手无法通过新技术即时改变游戏规则。现在我们发现"大型纪律性组织获胜"这条规则需要附加条件:"在规则变化缓慢的领域"。直到变革速度达到临界点,人们才意识到这点。 不过大型组织确实将开始衰落,因为这是历史上首次它们无法获得最优秀的人才。如今大学毕业的雄心勃勃的年轻人不愿去大公司工作,他们想加入快速成长的热门初创企业。如果野心足够大,他们更想自己创立公司。[2] 这并不意味着大公司会消失。初创企业的成功恰恰意味着大公司的存在,因为成功的初创要么成长为巨头,要么被巨头收购。[3]但大型组织可能永远无法重现其在二十世纪最后二十五年的主导地位。 一个持续千年的趋势竟会逆转,这着实令人惊讶。有多少规律能运行数千年后突然反转? "越大越好"的千年传统给我们留下了大量过时却根深蒂固的惯例。这意味着野心家现在可以进行套利。准确辨别哪些观念需要保留、哪些可以抛弃将极具价值。 观察的起点就在小型化趋势的发源地:初创企业的世界。 美国历史上总有特立独行者选择自己搭建阶梯而非攀爬现成的。但直到最近,这仍是局外人才会选择的非常规路径。十九世纪工业巨头普遍缺乏正规教育绝非巧合。尽管他们的公司最终规模惊人,但最初本质上都是机械师或店主——这是任何受过大学教育的人都会避免的社会阶层跃迁。在科技初创(尤其是互联网初创)兴起前,受过高等教育者自主创业极为罕见。 离开肖克利半导体创立仙童半导体的八位先驱(硅谷初创企业的雏形),最初甚至没打算创业。他们只是寻找愿意集体雇佣他们的公司。后来其中一位的父母引荐了愿意提供启动资金的小投行,这才偶然踏入创业之路。对他们而言,创立公司本是个陌生概念,纯属机缘巧合。[4] 如今我推测斯坦福或伯克利几乎所有会编程的本科生都至少考虑过创业。东海岸大学紧随其后,英国高校也不遑多让。这种模式表明斯坦福和伯克利的态度并非特例,而是领先指标。这就是世界发展的方向。 当然,互联网初创企业仍只是全球经济的一小部分。基于它们的趋势能具有如此影响力吗? 我认为可以。这个领域的发展空间没有理论上限。如同科学,财富似乎呈分形扩张。瓦特开始研究蒸汽机时,它在英国经济中的占比微不足道。但他的工作引发连锁反应,最终这个微小领域扩张到比当初的整个经济体系还要庞大。 互联网可能重演这种模式。如果互联网初创为野心家提供最佳机会,大量人才就会涌入,这个经济板块将以典型的分形方式膨胀。 即便互联网相关应用仅占全球经济十分之一,这个组成部分也将为其他领域定调。从薪资水平到着装标准,经济中最活跃的部分总是引领潮流。这不仅源于其声望,更因为支撑最活跃经济板块的原则往往具有普适性。 未来的趋势押注点在于:以独立绩效衡量的小型自治群体网络。而胜出的社会将是阻抗最小的那些。 如同最初的工业革命,不同社会对此的适应能力将存在差异。工业革命诞生于英格兰后,仅用一代人时间就蔓延至欧洲大陆和北美,但并未普及全球。这种新模式只能在准备好的土壤生根——必须已有活跃中产阶级的地方才能接纳它。 1960年代始于硅谷的变革同样具有社会属性。那里发展出两类新技术:集成电路制造技术,以及通过技术创新实现快速成长的新型企业构建技术。集成电路技术迅速传播至其他国家,但初创企业技术没有。五十年后的今天,初创企业在硅谷无处不在,在美国其他少数城市也很常见,但在世界大部分地区仍是异类。 初创企业未能像工业革命那样广泛传播的部分原因(可能是主因)在于其社会颠覆性。尽管带来诸多社会变革,工业革命并未挑战"越大越好"的原则,反而与之完美契合。新兴工业企业借鉴了军队和公务员体系等现有大型组织的惯例,形成的混合体运作良好。"工业领袖"向"工人大军"发号施令,每个人都清楚自己的职责。 相比之下,初创企业似乎更违背社会常规。在重视等级和稳定的社会难以蓬勃发展,就像工业化难以在统治者随意掠夺商人阶层的社会中生根。但工业革命发生时已有少数国家跨越了那个阶段。而这次,似乎没那么多社会做好了准备。 注释 [1] 这种模式的怪异后果之一是:通常加薪途径是成为管理者。这是初创企业修正的问题之一。 [2] 美国汽车公司表现远逊日本同行有诸多原因,但至少有一个令人乐观:美国毕业生有更多选择。 [3] 未来可能出现人员规模不增但收入增长的大公司,但这个趋势尚在萌芽。 [4] 克里斯托夫·勒库耶,《打造硅谷》,麻省理工出版社,2006年。 致谢 特雷弗·布莱克韦尔、保罗·布赫海特、杰西卡·利文斯顿和罗伯特·莫里斯审阅了本文草稿。.
December 2008 _(I originally wrote this at the request of a company producing a report about entrepreneurship. Unfortunately after reading it they decided it was too controversial to include.)_ VC funding will probably dry up somewhat during the present recession, like it usually does in bad times. But this time the result may be different. This time the number of new startups may not decrease. And that could be dangerous for VCs. When VC funding dried up after the Internet Bubble, startups dried up too. There were not a lot of new startups being founded in 2003\. But startups aren't tied to VC the way they were 10 years ago. It's now possible for VCs and startups to diverge. And if they do, they may not reconverge once the economy gets better. The reason startups no longer depend so much on VCs is one that everyone in the startup business knows by now: it has gotten much cheaper to start a startup. There are four main reasons: Moore's law has made hardware cheap; open source has made software free; the web has made marketing and distribution free; and more powerful programming languages mean development teams can be smaller. These changes have pushed the cost of starting a startup down into the noise. In a lot of startups—probaby most startups funded by Y Combinator—the biggest expense is simply the founders' living expenses. We've had startups that were profitable on revenues of $3000 a month. $3000 is insignificant as revenues go. Why should anyone care about a startup making $3000 a month? Because, although insignificant as _revenue_ , this amount of money can change a startup's _funding_ situation completely. Someone running a startup is always calculating in the back of their mind how much "runway" they have—how long they have till the money in the bank runs out and they either have to be profitable, raise more money, or go out of business. Once you cross the threshold of profitability, however low, your runway becomes infinite.
(本文应某创业研究报告机构邀约撰写,但对方审阅后认为观点过于争议而未予采纳。)
当前经济衰退期间,风险投资可能会像往常萧条期那样有所萎缩。但这次结果或许不同——新兴初创企业的数量未必减少,而这可能对风投机构构成威胁。
互联网泡沫破裂后,风投资金枯竭时初创企业也随之凋零。2003年新创企业寥寥无几。但如今的初创企业已不再像十年前那样与风投紧密绑定。风投与初创企业可能出现分化,且经济复苏后二者未必重新融合。
It's a qualitative change, like the stars turning into lines and disappearing when the Enterprise accelerates to warp speed. Once you're profitable you don't need investors' money. And because Internet startups have become so cheap to run, the threshold of profitability can be trivially low. Which means many Internet startups don't need VC-scale investments anymore. For many startups, VC funding has, in the language of VCs, gone from a must-have to a nice-to-have. This change happened while no one was looking, and its effects have been largely masked so far. It was during the trough after the Internet Bubble that it became trivially cheap to start a startup, but few realized it because startups were so out of fashion. When startups came back into fashion, around 2005, investors were starting to write checks again. And while founders may not have needed VC money the way they used to, they were willing to take it if offered—partly because there was a tradition of startups taking VC money, and partly because startups, like dogs, tend to eat when given the opportunity. As long as VCs were writing checks, founders were never forced to explore the limits of how little they needed them. There were a few startups who hit these limits accidentally because of their unusual circumstances—most famously 37signals, which hit the limit because they crossed into startup land from the other direction: they started as a consulting firm, so they had revenue before they had a product. VCs and founders are like two components that used to be bolted together. Around 2000 the bolt was removed. Because the components have so far been subjected to the same forces, they still seem to be joined together, but really one is just resting on the other. A sharp impact would make them fly apart. And the present recession could be that impact.
初创企业降低对风投依赖的原因已是业内共识:创业成本已大幅降低。四大关键因素:摩尔定律使硬件成本骤降;开源软件实现零成本;网络让营销与分发免费;强大编程语言使小型团队成为可能。这些变化将创业成本压缩至可忽略水平。对多数Y Combinator资助的企业而言,最大开支仅是创始人的生活费。我们甚至有月入3000美元即实现盈利的案例。
3000美元营收看似微不足道,但这点资金能彻底改变初创企业的融资处境。创业者始终在计算"跑道"长度——银行资金耗尽前实现盈利、再融资或倒闭的时限。一旦跨越盈利门槛(无论多低),跑道便无限延长。这种质变如同企业号加速至曲速时星辰化作流光消失。盈利意味着不再需要投资,而网络创业的低成本使盈利门槛极低,许多企业已不再需要风投级资金。用风投术语说,对众多初创企业而言,融资已从"必需品"降级为"加分项"。
这一变革在无人察觉时发生,其影响至今仍被掩盖。互联网泡沫后的低谷期恰是创业成本骤降时,但因创业热潮退却而鲜被关注。2005年创业回潮时,投资者重启支票簿。尽管创始人不再如昔日般依赖风投,他们仍乐于接受资金——部分因传统惯性,部分如犬类见食必啖的本能。只要风投持续注资,创始人就无需探索最低依赖限度。极少数企业因特殊情境触及底线,最著名的是37signals——他们从咨询业务跨界创业,产品未出已有收入。
Because of Y Combinator's position at the extreme end of the spectrum, we'd be the first to see signs of a separation between founders and investors, and we are in fact seeing it. For example, though the stock market crash does seem to have made investors more cautious, it doesn't seem to have had any effect on the number of people who want to start startups. We take applications for funding every 6 months. Applications for the current funding cycle closed on October 17, well after the markets tanked, and even so we got a record number, up 40% from the same cycle a year before. Maybe things will be different a year from now, if the economy continues to get worse, but so far there is zero slackening of interest among potential founders. That's different from the way things felt in 2001. Then there was a widespread feeling among potential founders that startups were over, and that one should just go to grad school. That isn't happening this time, and part of the reason is that even in a bad economy it's not that hard to build something that makes $3000 a month. If investors stop writing checks, who cares? We also see signs of a divergence between founders and investors in the attitudes of existing startups we've funded. I was talking to one recently that had a round fall through at the last minute over the sort of trifle that breaks deals when investors feel they have the upper hand—over an uncertainty about whether the founders had correctly filed their 83(b) forms, if you can believe that. And yet this startup is obviously going to succeed: their traffic and revenue graphs look like a jet taking off. So I asked them if they wanted me to introduce them to more investors. To my surprise, they said no—that they'd just spent four months dealing with investors, and they were actually a lot happier now that they didn't have to. There was a friend they wanted to hire with the investor money, and now they'd have to postpone that.
风投与创始人如同曾经螺栓紧固的两个部件。2000年前后螺栓拆除,因受力相同仍看似一体,实则仅靠惯性维持。剧烈冲击便会使其分离,而当前衰退可能就是那记冲击。
作为行业最前沿观察者,Y Combinator最先察觉创始人与投资者的分化迹象。例如:股市崩盘虽令投资者更谨慎,却未削弱创业热情。我们每半年受理融资申请,本轮截止日(10月17日)虽处市场低谷,申请量仍同比激增40%创纪录。
若经济持续恶化,明年情况或生变。但与2001年不同,当前潜在创始人毫无退缩之意,部分原因在于:即便经济寒冬,月入3000美元的产品也非难事。投资者停开支票又何妨?
已投企业的态度也显示分化迹象。某家被投企业最近因琐事(创始人83(b)表格填报疑云这类投资者强势时才会计较的细节)导致临门一脚的融资流产。但其流量与营收曲线如战机腾空般飙升,当我提出引荐其他投资者时,他们竟拒绝——为摆脱耗时四个月的融资纠缠而如释重负。虽需推迟用融资款招聘某位朋友,但现有资金足以支撑至盈利。为保险起见,他们正搬往更廉价的公寓(当前市场想必能谈个好价钱)。
But otherwise they felt they had enough in the bank to make it to profitability. To make sure, they were moving to a cheaper apartment. And in this economy I bet they got a good deal on it. I've detected this "investors aren't worth the trouble" vibe from several YC founders I've talked to recently. At least one startup from the most recent (summer) cycle may not even raise angel money, let alone VC. Ticketstumbler made it to profitability on Y Combinator's $15,000 investment and they hope not to need more. This surprised even us. Although YC is based on the idea of it being cheap to start a startup, we never anticipated that founders would grow successful startups on nothing more than YC funding. If founders decide VCs aren't worth the trouble, that could be bad for VCs. When the economy bounces back in a few years and they're ready to write checks again, they may find that founders have moved on. There is a founder community just as there's a VC community. They all know one another, and techniques spread rapidly between them. If one tries a new programming language or a new hosting provider and gets good results, 6 months later half of them are using it. And the same is true for funding. The current generation of founders want to raise money from VCs, and Sequoia specifically, because Larry and Sergey took money from VCs, and Sequoia specifically. Imagine what it would do to the VC business if the next hot company didn't take VC at all. VCs think they're playing a zero sum game. In fact, it's not even that. If you lose a deal to Benchmark, you lose that deal, but VC as an industry still wins. If you lose a deal to None, all VCs lose. This recession may be different from the one after the Internet Bubble. This time founders may keep starting startups.
近期与多位YC创始人交流时,我多次捕捉到"融资得不偿失"的情绪。最新一期(夏季)甚至有企业连天使轮都不打算融。Ticketstumbler仅凭YC的1.5万美元投资即实现盈利,希望不再募资。这超出我们预期——尽管YC基于低成本创业理念,但未料创始人能仅靠我们的资金培育成功企业。
若创始人判定风投不值费心,后者将处境艰难。待经济复苏风投重启投资时,或发现创业者已另辟蹊径。
创业者社区与风投圈同样存在人际网络。新编程语言或主机服务商的好口碑半年内能覆盖半数成员,融资模式亦如此。当下创始人效仿佩奇与布林接受风投(尤其是红杉资本)的模式。设想若下一个明星企业完全拒绝风投,将对行业产生何种冲击?
And if they do, VCs will have to keep writing checks, or they could become irrelevant. Thanks to Sam Altman, Trevor Blackwell, David Hornik, Jessica Livingston, Robert Morris, and Fred Wilson for reading drafts of this.
风投机构自以为参与零和博弈,实则不然。输给Benchmark只是单局失利,行业整体仍胜;若败给"零融资"模式,则全体风投皆输。
本次衰退或异于互联网泡沫后那次。若创业者持续涌现,风投机构必须持续投资,否则恐将边缘化。
致谢:萨姆·奥尔特曼、特雷弗·布莱克韦尔、大卫·霍尼克、杰西卡·利文斯顿、罗伯特·莫里斯、弗雷德·威尔逊审阅本文草稿。
November 2008 One of the differences between big companies and startups is that big companies tend to have developed procedures to protect themselves against mistakes. A startup walks like a toddler, bashing into things and falling over all the time. A big company is more deliberate. The gradual accumulation of checks in an organization is a kind of learning, based on disasters that have happened to it or others like it. After giving a contract to a supplier who goes bankrupt and fails to deliver, for example, a company might require all suppliers to prove they're solvent before submitting bids. As companies grow they invariably get more such checks, either in response to disasters they've suffered, or (probably more often) by hiring people from bigger companies who bring with them customs for protecting against new types of disasters. It's natural for organizations to learn from mistakes. The problem is, people who propose new checks almost never consider that the check itself has a cost. _Every check has a cost._ For example, consider the case of making suppliers verify their solvency. Surely that's mere prudence? But in fact it could have substantial costs. There's obviously the direct cost in time of the people on both sides who supply and check proofs of the supplier's solvency. But the real costs are the ones you never hear about: the company that would be the best supplier, but doesn't bid because they can't spare the effort to get verified. Or the company that would be the best supplier, but falls just short of the threshold for solvency—which will of course have been set on the high side, since there is no apparent cost of increasing it. Whenever someone in an organization proposes to add a new check, they should have to explain not just the benefit but the cost. No matter how bad a job they did of analyzing it, this meta-check would at least remind everyone there had to _be_ a cost, and send them looking for it.
大公司与初创企业的一个区别在于,大公司往往建立了防止错误的流程体系。初创企业像蹒跚学步的幼儿,总是跌跌撞撞;而大公司行事更为审慎。
企业逐步建立的审查机制是一种经验积累,源自自身或同类机构遭遇的灾难。例如,某公司与破产失约的供应商签约后,可能要求所有投标供应商必须证明其偿付能力。
随着公司规模扩大,这类审查必然增多——或是应对经历过的灾难,或是(更常见地)聘用来自更大公司的人员,这些人带来了防范新型灾难的惯例。
组织从错误中学习是自然规律。问题在于,提出新增审查的人几乎从不考虑审查本身也有成本。
每项审查都有代价。以要求供应商验证偿付能力为例,这难道不是基本谨慎?但实际代价可能巨大。双方人员为准备和核查偿付证明所耗费的时间是直接成本,而真正的成本却隐而不显:那些本应是最佳供应商的企业,或因无力应付验证流程而放弃投标;或是某家本应最优的企业,仅因偿付能力略低于被刻意抬高(因抬高标准看似无成本)的门槛而落选。
If companies started doing that, they'd find some surprises. Joel Spolsky recently spoke at Y Combinator about selling software to corporate customers. He said that in most companies software costing up to about $1000 could be bought by individual managers without any additional approvals. Above that threshold, software purchases generally had to be approved by a committee. But babysitting this process was so expensive for software vendors that it didn't make sense to charge less than $50,000. Which means if you're making something you might otherwise have charged $5000 for, you have to sell it for $50,000 instead. The purpose of the committee is presumably to ensure that the company doesn't waste money. And yet the result is that the company pays 10 times as much. Checks on purchases will always be expensive, because the harder it is to sell something to you, the more it has to cost. And not merely linearly, either. If you're hard enough to sell to, the people who are best at making things don't want to bother. The only people who will sell to you are companies that specialize in selling to you. Then you've sunk to a whole new level of inefficiency. Market mechanisms no longer protect you, because the good suppliers are no longer in the market. Such things happen constantly to the biggest organizations of all, governments. But checks instituted by governments can cause much worse problems than merely overpaying. Checks instituted by governments can cripple a country's whole economy. Up till about 1400, China was richer and more technologically advanced than Europe. One reason Europe pulled ahead was that the Chinese government restricted long trading voyages. So it was left to the Europeans to explore and eventually to dominate the rest of the world, including China. In more recent times, Sarbanes-Oxley has practically destroyed the US IPO market. That wasn't the intention of the legislators who wrote it.
每当组织内有人提议新增审查,必须同时说明其收益与成本。即便分析粗糙,这种"元审查"至少能提醒众人成本必然存在,促使他们主动寻找。
若企业践行此法,将会发现惊人事实。Joel Spolsky最近在Y Combinator谈到向企业客户销售软件时指出:多数公司里,1000美元以下的软件可由经理直接购买,超过此阈值则需委员会审批。但对软件商而言,配合审批流程的成本过高,导致定价低于5万美元便无利可图。这意味着本该标价5000美元的产品被迫提价至5万美元。
委员会的本意是防止资金浪费,结果却导致企业支付十倍价格。
采购审查永远昂贵,因为销售难度与成本呈非线性增长。当销售门槛过高,最优秀的制造者会选择退出,只剩下专攻官僚采购体系的供应商。此时你已陷入效率黑洞——市场机制失效,因为优质供应商早已离场。
这种情形在最大型的组织(政府)中不断上演。但政府设立的审查造成的恶果远不止超额支付。约1400年前,中国比欧洲更富裕且技术先进。欧洲后来居上的原因之一,是中国政府限制远洋贸易,最终让欧洲人探索并主宰了包括中国在内的世界。
They just wanted to add a few more checks on public companies. But they forgot to consider the cost. They forgot that companies about to go public are usually rather stretched, and that the weight of a few extra checks that might be easy for General Electric to bear are enough to prevent younger companies from being public at all. Once you start to think about the cost of checks, you can start to ask other interesting questions. Is the cost increasing or decreasing? Is it higher in some areas than others? Where does it increase discontinuously? If large organizations started to ask questions like that, they'd learn some frightening things. I think the cost of checks may actually be increasing. The reason is that software plays an increasingly important role in companies, and the people who write software are particularly harmed by checks. Programmers are unlike many types of workers in that the best ones actually prefer to work hard. This doesn't seem to be the case in most types of work. When I worked in fast food, we didn't prefer the busy times. And when I used to mow lawns, I definitely didn't prefer it when the grass was long after a week of rain. Programmers, though, like it better when they write more code. Or more precisely, when they release more code. Programmers like to make a difference. Good ones, anyway. For good programmers, one of the best things about working for a startup is that there are few checks on releases. In true startups, there are no external checks at all. If you have an idea for a new feature in the morning, you can write it and push it to the production servers before lunch. And when you can do that, you have more ideas. At big companies, software has to go through various approvals before it can be launched. And the cost of doing this can be enormous—in fact, discontinuous. I was talking recently to a group of three programmers whose startup had been acquired a few years before by a big company.
近例则是《萨班斯法案》几乎摧毁了美国IPO市场。立法者本意只是加强对上市公司的审查,却忽略了成本——准备上市的企业通常资源紧张,这些对通用电气轻而易举的额外审查,足以扼杀年轻公司的上市可能。
一旦开始思考审查成本,就能提出更多关键问题:成本在上升还是下降?某些领域成本是否更高?何处存在成本断层?大型组织若追问这些问题,将会发现骇人真相。
我认为审查成本实际在增长,因为软件在企业中的作用日益重要,而审查对软件开发者的伤害尤为深重。
程序员不同于多数劳动者——最优秀的群体其实渴望高强度工作。这在其他行业很少见:我在快餐店打工时不欢迎客流高峰,修剪草坪时更厌恶雨后疯长的草丛。
但程序员乐于编写更多代码,更准确说是发布更多代码。他们渴望创造价值,至少优秀者如此。
When they'd been independent, they could release changes instantly. Now, they said, the absolute fastest they could get code released on the production servers was two weeks. This didn't merely make them less productive. It made them hate working for the acquirer. Here's a sign of how much programmers like to be able to work hard: these guys would have _paid_ to be able to release code immediately, the way they used to. I asked them if they'd trade 10% of the acquisition price for the ability to release code immediately, and all three instantly said yes. Then I asked what was the maximum percentage of the acquisition price they'd trade for it. They said they didn't want to think about it, because they didn't want to know how high they'd go, but I got the impression it might be as much as half. They'd have sacrificed hundreds of thousands of dollars, perhaps millions, just to be able to deliver more software to users. And you know what? It would have been perfectly safe to let them. In fact, the acquirer would have been better off; not only wouldn't these guys have broken anything, they'd have gotten a lot more done. So the acquirer is in fact getting worse performance at greater cost. Just like the committee approving software purchases. And just as the greatest danger of being hard to sell to is not that you overpay but that the best suppliers won't even sell to you, the greatest danger of applying too many checks to your programmers is not that you'll make them unproductive, but that good programmers won't even want to work for you. Steve Jobs's famous maxim "artists ship" works both ways. Artists aren't merely capable of shipping. They insist on it. So if you don't let people ship, you won't have any artists..
对优秀程序员而言,初创企业最吸引人之处正是极少的发布限制。真正的初创企业完全没有外部审查:早晨构思的新功能,午餐前就能部署上线。这种自由会激发更多创意。
大公司的软件发布需经层层审批,其代价巨大且存在断层。我曾与三位程序员交谈,他们的初创公司被大企业收购后,代码从即时发布变成最快两周才能上线。这不仅降低效率,更让他们痛恨为收购方工作。
程序员对高效工作的渴望强烈到何种程度?这三人愿意付费换取曾经的即时发布权限。当我问是否愿用收购价的10%换取该权限时,三人立即同意。追问最高愿付比例时,他们拒绝深想,但我感觉可能高达半数。
他们愿牺牲数十万乃至数百万美元,只为能向用户交付更多软件。而真相是:允许他们这么做完全安全。收购方本可获益——这些程序员不仅不会搞砸系统,反而会创造更多价值。就像软件采购委员会那样,收购方实际以更高成本获得了更差产出。
正如销售门槛过高的最大风险不是多付钱,而是失去最佳供应商;对程序员施加过多审查的最大危险不是降低其效率,而是让优秀程序员拒绝为你效力。
史蒂夫·乔布斯的名言"艺术家总要发布作品"具有双重含义:艺术家不仅能够发布,更坚持发布。若不允许人们发布,你就留不住任何艺术家。
Want to start a startup? Get funded by Y Combinator.
October 2008 The economic situation is apparently so grim that some experts fear we may be in for a stretch as bad as the mid seventies. When Microsoft and Apple were founded. As those examples suggest, a recession may not be such a bad time to start a startup. I'm not claiming it's a particularly good time either. The truth is more boring: the state of the economy doesn't matter much either way. If we've learned one thing from funding so many startups, it's that they succeed or fail based on the qualities of the founders. The economy has some effect, certainly, but as a predictor of success it's rounding error compared to the founders. Which means that what matters is who you are, not when you do it. If you're the right sort of person, you'll win even in a bad economy. And if you're not, a good economy won't save you. Someone who thinks "I better not start a startup now, because the economy is so bad" is making the same mistake as the people who thought during the Bubble "all I have to do is start a startup, and I'll be rich." So if you want to improve your chances, you should think far more about who you can recruit as a cofounder than the state of the economy. And if you're worried about threats to the survival of your company, don't look for them in the news. Look in the mirror. But for any given team of founders, would it not pay to wait till the economy is better before taking the leap? If you're starting a restaurant, maybe, but not if you're working on technology. Technology progresses more or less independently of the stock market. So for any given idea, the payoff for acting fast in a bad economy will be higher than for waiting. Microsoft's first product was a Basic interpreter for the Altair.
That was exactly what the world needed in 1975, but if Gates and Allen had decided to wait a few years, it would have been too late. Of course, the idea you have now won't be the last you have. There are always new ideas. But if you have a specific idea you want to act on, act now. That doesn't mean you can ignore the economy. Both customers and investors will be feeling pinched. It's not necessarily a problem if customers feel pinched: you may even be able to benefit from it, by making things that save money. Startups often make things cheaper, so in that respect they're better positioned to prosper in a recession than big companies. Investors are more of a problem. Startups generally need to raise some amount of external funding, and investors tend to be less willing to invest in bad times. They shouldn't be. Everyone knows you're supposed to buy when times are bad and sell when times are good. But of course what makes investing so counterintuitive is that in equity markets, good times are defined as everyone thinking it's time to buy. You have to be a contrarian to be correct, and by definition only a minority of investors can be. So just as investors in 1999 were tripping over one another trying to buy into lousy startups, investors in 2009 will presumably be reluctant to invest even in good ones. You'll have to adapt to this. But that's nothing new: startups always have to adapt to the whims of investors. Ask any founder in any economy if they'd describe investors as fickle, and watch the face they make. Last year you had to be prepared to explain how your startup was viral. Next year you'll have to explain how it's recession-proof. (Those are both good things to be.
The mistake investors make is not the criteria they use but that they always tend to focus on one to the exclusion of the rest.) Fortunately the way to make a startup recession-proof is to do exactly what you should do anyway: run it as cheaply as possible. For years I've been telling founders that the surest route to success is to be the cockroaches of the corporate world. The immediate cause of death in a startup is always running out of money. So the cheaper your company is to operate, the harder it is to kill. And fortunately it has gotten very cheap to run a startup. A recession will if anything make it cheaper still. If nuclear winter really is here, it may be safer to be a cockroach even than to keep your job. Customers may drop off individually if they can no longer afford you, but you're not going to lose them all at once; markets don't "reduce headcount." What if you quit your job to start a startup that fails, and you can't find another? That could be a problem if you work in sales or marketing. In those fields it can take months to find a new job in a bad economy. But hackers seem to be more liquid. Good hackers can always get some kind of job. It might not be your dream job, but you're not going to starve. Another advantage of bad times is that there's less competition. Technology trains leave the station at regular intervals. If everyone else is cowering in a corner, you may have a whole car to yourself. You're an investor too. As a founder, you're buying stock with work: the reason Larry and Sergey are so rich is not so much that they've done work worth tens of billions of dollars, but that they were the first investors in Google. And like any investor you should buy when times are bad.
Were you nodding in agreement, thinking "stupid investors" a few paragraphs ago when I was talking about how investors are reluctant to put money into startups in bad markets, even though that's the time they should rationally be most willing to buy? Well, founders aren't much better. When times get bad, hackers go to grad school. And no doubt that will happen this time too. In fact, what makes the preceding paragraph true is that most readers won't believe it—at least to the extent of acting on it. So maybe a recession is a good time to start a startup. It's hard to say whether advantages like lack of competition outweigh disadvantages like reluctant investors. But it doesn't matter much either way. It's the people that matter. And for a given set of people working on a given technology, the time to act is always now.
Russian Translation | Chinese Translation Japanese Translation.
想创业? 获得 Y Combinator 的资助。
2008年10月 经济形势显然非常严峻,以至于一些专家担心我们可能会遭遇类似70年代中期那样的糟糕时期。 而微软和苹果正是在那时创立的。 这些例子表明,经济衰退可能并不是创业的糟糕时机。我也并非声称这是一个特别好的时机。真相其实更乏味:经济状况无论好坏,影响都不大。 如果我们从资助众多初创企业中学到了一件事,那就是它们的成败取决于创始人的素质。经济当然有一定影响,但作为成功的预测因素,与创始人相比,它只是四舍五入的误差。 这意味着重要的是你是谁,而不是你何时行动。如果你是合适的人选,即使在糟糕的经济中也能成功。而如果你不是,再好的经济也救不了你。那些认为“我现在最好不要创业,因为经济太糟糕”的人,与泡沫时期认为“我只要创业就能致富”的人犯的是同样的错误。 因此,如果你想提高成功几率,应该更多地考虑你能招募谁作为联合创始人,而不是经济状况。如果你担心公司生存的威胁,不要从新闻中寻找答案,而是照照镜子。 但对于任何给定的创始团队来说,是否应该等到经济好转后再行动呢?如果你开的是餐厅,也许可以,但如果是技术领域就不行。技术的进步或多或少与股市无关。因此,对于任何给定的想法,在经济不好时快速行动的回报会高于等待。微软的第一个产品是为Altair开发的Basic解释器。这正是1975年世界需要的,但如果盖茨和艾伦决定再等几年,那就太晚了。 当然,你现在有的想法不会是最后一个。总会有新的想法。但如果你有一个具体的想法想要实施,现在就行动。 这并不意味着你可以忽视经济。客户和投资者都会感到拮据。客户感到拮据不一定是问题:你甚至可以通过开发省钱的产品从中受益。初创企业通常能让东西更便宜,因此在这方面,它们比大公司更有能力在经济衰退中蓬勃发展。 投资者的问题更大。初创企业通常需要筹集一定数量的外部资金,而投资者在经济不好时往往不太愿意投资。他们不应该这样。大家都知道应该在行情不好时买入,行情好时卖出。但当然,投资之所以如此反直觉,是因为在股票市场中,好行情被定义为每个人都认为是买入的时候。你必须逆势而行才能正确,而根据定义,只有少数投资者能做到。 因此,就像1999年投资者争先恐后地投资糟糕的初创企业一样,2009年的投资者可能会连好的初创企业也不愿意投资。 你必须适应这一点。但这并不新鲜:初创企业总是需要适应投资者的反复无常。在任何经济环境下问任何创始人是否认为投资者善变,看看他们的表情就知道了。去年你必须准备好解释你的初创企业如何具有病毒式传播性。明年你必须解释它如何抗衰退。 (这两者都是好事。投资者的错误不在于他们使用的标准,而在于他们总是倾向于关注一个而忽视其他。) 幸运的是,让初创企业抗衰退的方法正是你应该做的:尽可能低成本运营。多年来我一直告诉创始人,最可靠的成功的途径是成为企业界的蟑螂。初创企业死亡的直接原因总是资金耗尽。因此,公司运营成本越低,就越难被杀死。幸运的是,现在运营初创企业的成本已经非常低了。经济衰退只会让它更便宜。 如果核冬天真的来了,做一只蟑螂可能比保住工作更安全。如果客户负担不起,他们可能会一个个离开,但你不会一下子失去所有客户;市场不会“裁员”。 如果你辞去工作创业失败,又找不到另一份工作怎么办?如果你从事销售或市场营销,这可能是个问题。在这些领域,经济不好时可能需要几个月才能找到新工作。但黑客似乎流动性更强。优秀的黑客总能找到某种工作。可能不是理想的工作,但不会饿死。 经济不好的另一个优势是竞争更少。技术列车每隔一段时间就会发车。如果其他人都蜷缩在角落里,你可能独占一整节车厢。 你也是投资者。作为创始人,你是在用工作购买股票:拉里和谢尔盖之所以如此富有,不是因为他们做了价值数百亿美元的工作,而是因为他们是谷歌的第一批投资者。和任何投资者一样,你应该在行情不好时买入。 几段前当我谈到投资者不愿在经济不好时投资初创企业时,你是否点头同意,心想“愚蠢的投资者”?尽管从理性上讲,这正是他们最应该愿意买入的时候。好吧,创始人也好不到哪去。经济不好时,黑客会去读研。毫无疑问,这次也会如此。事实上,前一段之所以成立,正是因为大多数读者不会相信——至少不会付诸行动。 因此,经济衰退可能是创业的好时机。很难说缺乏竞争这样的优势是否超过了投资者不愿投资这样的劣势。但无论如何,这都不太重要。重要的是人。对于一组特定的人在开发一项特定技术时,行动的时间永远是现在。
Want to start a startup? Get funded by Y Combinator.
August 2008 Raising money is the second hardest part of starting a startup. The hardest part is making something people want: most startups that die, die because they didn't do that. But the second biggest cause of death is probably the difficulty of raising money. Fundraising is brutal. One reason it's so brutal is simply the brutality of markets. People who've spent most of their lives in schools or big companies may not have been exposed to that. Professors and bosses usually feel some sense of responsibility toward you; if you make a valiant effort and fail, they'll cut you a break. Markets are less forgiving. Customers don't care how hard you worked, only whether you solved their problems. Investors evaluate startups the way customers evaluate products, not the way bosses evaluate employees. If you're making a valiant effort and failing, maybe they'll invest in your next startup, but not this one. But raising money from investors is harder than selling to customers, because there are so few of them. There's nothing like an efficient market. You're unlikely to have more than 10 who are interested; it's difficult to talk to more. So the randomness of any one investor's behavior can really affect you. Problem number 3: investors are very random. All investors, including us, are by ordinary standards incompetent. We constantly have to make decisions about things we don't understand, and more often than not we're wrong. And yet a lot is at stake. The amounts invested by different types of investors vary from five thousand dollars to fifty million, but the amount usually seems large for whatever type of investor it is. Investment decisions are big decisions. That combination—making big decisions about things they don't understand—tends to make investors very skittish. VCs are notorious for leading founders on.
想创立一家初创公司? 获得Y Combinator的资助。
2008年8月 融资是创立初创公司过程中第二困难的部分。最困难的是创造出人们真正需要的东西:大多数失败的初创公司都死于此因。而第二大死因很可能就是融资的艰难。融资过程极其残酷。 这种残酷部分源于市场本身的冷酷无情。那些大部分时间生活在学校或大公司里的人可能从未体验过这一点。教授和上司通常对你怀有某种责任感;如果你付出了巨大努力却失败了,他们会给你喘息的机会。市场则不会如此宽容。客户不在乎你付出了多少汗水,只在乎你是否解决了他们的问题。 投资者评估初创公司的方式与客户评估产品如出一辙,而非上司评价员工那般。如果你正在拼命努力却遭遇失败,他们或许会投资你的下一家初创公司,但绝不会是眼下这个。 然而,从投资者那里融资比向客户销售产品更为艰难,因为投资者数量稀少。这里不存在所谓的有效市场。你很难找到超过10位对你感兴趣的投资者;接触更多人更是难上加难。因此,任何一位投资者的随机行为都可能对你产生实质性影响。 第三个问题:投资者的行为极度不可预测。包括我们在内的所有投资者,在常规标准下都称不上称职。我们经常要对一无所知的事物做出决策,而大多数时候我们都错了。 然而这背后牵涉重大利益。不同类型投资者的投资金额从五千美元到五千万美元不等,但无论哪种类型,这笔钱对他们而言通常都显得数额庞大。投资决策是重大决策。 这种组合——对他们不了解的事物做出重大决策——往往使投资者变得极度反复无常。风险投资家以吊创始人胃口而臭名昭著。其中一些更无原则的人会故意为之。但即便是最善意的投资者,其行为在日常生活中也会显得荒诞不经。某天他们热情高涨,似乎随时准备当场签支票;次日却连你的电话都不接。他们并非在戏耍你。他们只是无法下定决心。[1] 如果这还不够糟糕,这些剧烈波动的节点还全都相互关联。初创企业的投资者彼此熟识,而且(尽管他们不愿承认)他们对你的看法最大程度上取决于其他投资者的意见。[2] 这简直就是制造不稳定的完美配方。你得到的是恐惧/贪婪平衡通常在市场中产生的阻尼效应的反面。没有人会对一家被其他所有人嫌弃的"便宜货"初创公司感兴趣。 因此,参与者稀少的低效市场,又因他们无法完全独立行动而雪上加霜。结果形成了一种系统,就像某种原始的多细胞海洋生物,当你刺激它的一处肢体时,整个生物体会剧烈收缩。 Y Combinator正在努力改变这种状况。我们正试图增加投资者的数量,就像我们增加初创企业的数量一样。我们希望随着双方数量的增长,我们能获得更接近有效市场的状态。当t趋近于无穷大时,演示日就趋近于一场拍卖会。 不幸的是,t距离无穷大仍然非常遥远。在当前这个不完美的世界里,初创公司该如何应对?最重要的是不要让融资打击你的士气。初创公司的生死取决于士气。如果你让融资的困难摧毁了你的士气,这将成为一种自我实现的预言。 自力更生(=咨询业务) 一些准创始人此时可能会想,为什么要与投资者打交道?如果融资如此痛苦,为何还要进行? 一个显而易见的答案是:因为你需要钱来维持生活。原则上,用公司自身的收入来资助初创公司是个好主意,但你无法凭空变出客户。无论你创造什么产品,都需要卖出一定数量才能收支平衡。将销售额增长到那个水平需要时间,而在尝试之前很难预测需要多长时间。 例如,我们无法自力更生Viaweb。我们的软件收费相当高——每月每用户约140美元——但至少需要一年时间,我们的收入才能覆盖我们微薄的成本。我们没有足够的积蓄来维持一年的生活。 如果将那些实际上是通过创始人储蓄或日常工作收入来资助的"自力更生"公司排除在外,剩下的公司要么(a)极其幸运(这很难按需实现),要么(b)最初是咨询公司,逐渐转型为产品公司。 咨询是你唯一可以依赖的选择。但咨询绝非免费资金。它可能不像从投资者那里融资那么痛苦,但这种痛苦会分散在更长的时间里。很可能是数年。而对许多类型的初创公司来说,这种延迟可能是致命的。如果你正在开发的东西非常独特,其他人不太可能想到,你可以慢慢来。约书亚·沙克特在华尔街工作期间,逐步建立了Delicious。他之所以能成功,是因为其他人没有意识到这是个好主意。但如果你在Viaweb大约同一时期开发像在线商店软件这样明显必需的产品,并且大部分时间都在做客户工作,只在业余时间开发它,你的处境就不妙了。 自力更生在原则上听起来很棒,但在这片看似繁茂的土地上,很少有初创公司能活着走出来。仅仅因为自力更生的初创公司往往因此而出名这一事实,就应该敲响警钟。如果它真的那么有效,它就会成为常态。[3] 自力更生可能会变得更容易,因为创办公司的成本正在降低。但我认为我们永远不会达到大多数初创公司不需要外部资金的地步。技术成本往往会大幅下降,但生活费用不会。 结果是,你可以选择你的痛苦:要么是融资的短暂而剧烈的痛苦,要么是咨询业务的长期慢性痛苦。对于相同总量的痛苦,融资是更好的选择,因为新技术通常现在比以后更有价值。 尽管对大多数初创公司来说,融资是两害相权取其轻,但它仍然是一个相当大的祸害——大到足以轻易杀死你。不仅仅是在明显的意义上,如果你未能筹集资金,你可能不得不关闭公司,还因为融资过程本身就可能杀死你。 要生存下来,你需要一套与说服投资者所用的技巧基本正交的技术,就像登山者需要知道的生存技巧与物理上上下山所用的技巧基本正交一样。 1. 保持低期望。 融资摧毁众多初创公司士气的原因不仅在于它很难,而且在于它比他们预期的要难得多。杀死你的是失望。而你的期望越低,就越难感到失望。 初创公司的创始人往往乐观。这在技术上可能很有效,至少在某些时候是这样,但这是应对融资的错误方式。最好假设投资者总会让你失望。顺便说一句,收购方也是如此。在YC,我们的次要口头禅之一是"交易会失败"。无论你正在进行什么交易,都假设它会失败。这条简单规则的预测能力令人惊讶。 随着交易的进展,会有一种倾向,开始相信它会成功,然后依赖它的成功。你必须抵制这一点。把自己绑在桅杆上。这才是杀死你的东西。交易不像大多数其他人类互动那样具有轨迹,即共同的计划随着时间的推移线性固化。交易往往在最后一刻失败。通常对方直到最后一刻才真正考虑他们想要什么。因此,你不能用你对共同计划的日常直觉作为指导。在交易方面,你必须有意识地关闭这些直觉,变得病态地多疑。 这比听起来更难做到。当著名的投资者似乎对资助你感兴趣时,这非常令人受宠若惊。很容易开始相信融资会快速而直接。但这几乎从未发生过。 2. 继续推进你的初创公司。 说你应该在融资的同时继续推进你的初创公司听起来很明显。实际上这很难做到。大多数初创公司都做不到。 融资有一种神秘的能力,能吸走你所有的注意力。即使你每天只与投资者开一次会,不知何故,那一次会议就会耗尽你一整天的时间。它不仅花费了实际会议的时间,还包括往返的时间,以及事先准备和事后思考的时间。 应对与投资者会面分散注意力的最佳方法可能是对公司进行分工:挑选一位创始人负责与投资者打交道,而其他人则继续推进公司业务。这在初创公司有3位创始人时比2位时效果更好,当公司领导者不是主要开发人员时效果也更好。在最好的情况下,公司能以大约一半的速度继续前进。 不过,那是最好的情况。更多情况下,公司在融资期间会陷入停滞。这出于多种原因都非常危险。融资总是比你预期的时间长。看似两周的中断会变成四个月的停滞。这可能非常打击士气。更糟糕的是,这可能让你对投资者失去吸引力。他们希望投资于充满活力的公司。一家四个月内没有任何新进展的公司看起来并不活跃,因此他们开始失去兴趣。投资者很少意识到这一点,但当他们对一家初创公司失去兴趣时,他们很大程度上是在回应自己优柔寡断所造成的损害。 解决方案:将初创公司放在首位。将投资者会议安排在你开发日程的零碎时间,而不是在投资者会议间隙进行开发。如果你能让公司不断前进——发布新功能、增加流量、达成交易、获得媒体报道——那些投资者会议更有可能富有成效。不仅因为你的初创公司看起来更有活力,还因为这更有利于你自己的士气,而士气是投资者评判你的主要标准之一。 3. 保持保守。 随着情况恶化,最优策略会变得更加保守。当事情进展顺利时,你可以冒险;当情况糟糕时,你希望稳妥行事。 我建议以融资总是进展不顺的态度来对待融资。原因在于,在你自我欺骗的能力和你所处理的系统极度不稳定的性质之间,事情很可能已经或很容易变得比看起来糟糕得多。 我对我们资助的大多数初创公司的建议是,如果有信誉良好的投资者以合理条件提供资金,就接受它。有些初创公司忽视这一建议并侥幸成功——它们拒绝了一个好报价,希望获得更好的报价,并且确实做到了。但在同样的情况下,我仍会给出同样的建议。谁知道他们玩俄罗斯轮盘赌时枪里装了几颗子弹? 推论:如果一位投资者表现出兴趣,不要让他们干坐着。你不能假设一位有兴趣投资的投资者会保持兴趣。事实上,在你试图将这种兴趣转化为资金之前,你甚至无法判断(他们自己甚至也无法判断)他们是否真的有兴趣。因此,如果你有一个热门目标,要么现在就搞定他们,要么放弃他们。除非你已经获得足够的资金,否则这归结为:现在就搞定他们。 初创公司不是通过获得巨额融资轮次而获胜,而是通过创造出伟大的产品。因此,完成融资并回到工作中去。 4. 保持灵活。 风险投资家会问两个你不应该回答的问题:"你还在和谁谈?"和"你想筹集多少钱?" 风险投资家并不指望你回答第一个问题。他们只是以防万一才问。[4] 他们似乎确实期望你回答第二个问题。但我认为你不应该直接告诉他们一个数字。这不是为了和他们玩游戏,而是因为你本就不应该有一个固定的融资数额。 初创公司需要固定金额融资的习俗是一个过时的遗留物,源自初创公司成本更高的时代。一家需要建工厂或雇佣50人的公司显然需要筹集一定的最低金额。但如今很少有科技初创公司处于这种境地。 我们建议初创公司告诉投资者,根据筹集金额的不同,他们可以采取几种不同的路径。少至5万美元就能支付创始人一年的食物和房租。几十万美元可以让他们租办公室并雇佣一些从学校认识的聪明人。几百万美元可以让他们真正大展拳脚。传达的信息(不仅是信息,而且是事实)应该是:无论如何我们都会成功。筹集更多资金只是让我们更快实现目标。 如果你正在进行天使轮融资,融资规模甚至可以随时调整。事实上,最好一开始将融资规模定得较小,然后根据需要扩大,而不是试图筹集一大笔钱,冒着因无法筹集全额而失去已有投资者的风险。你甚至可能希望进行"滚动交割",即融资没有预定规模,而是当投资者同意时,你逐个向他们出售股票。这有助于打破僵局,因为你可以在第一位投资者准备好购买时就开始。[5] 5. 保持独立。 一家由二十出头的几位创始人组成的初创公司,其开支可能低至每月2000美元就能盈利。就公司收入而言,这微不足道,但它对你的士气和谈判地位的影响却绝非如此。在YC,我们用"拉面盈利"来形容你赚的钱刚好够支付生活开支的情况。一旦你进入拉面盈利状态,一切都会改变。你可能仍然需要投资来扩大规模,但这个月你不需要它。 在创办初创公司时,你无法计划需要多长时间才能盈利。但如果你发现自己处于只需在销售上稍加努力就能跨越拉面盈利门槛的位置,那就去做。 投资者喜欢你处于拉面盈利状态。这表明你考虑过赚钱,而不仅仅是研究有趣的技术问题;这表明你有纪律保持低开支;但最重要的是,这意味着你不需要他们。 投资者最喜欢的是看起来即使没有他们也能成功的初创公司。投资者喜欢他们能帮助初创公司,但他们不喜欢没有这种帮助就会死亡的初创公司。 在YC,我们花了很多时间试图预测我们资助的初创公司会如何发展,因为我们试图学习如何挑选赢家。我们现在已经观察了如此多初创公司的发展轨迹,以至于我们越来越擅长预测它们。当我们谈论我们认为可能成功的初创公司时,我们发现自己在说"哦,那些人能照顾好自己。他们会没事的"之类的话,而不是"那些人真的很聪明"或"那些人正在研究一个伟大的想法"。[6] 当我们预测初创公司的好结果时,支持论据中出现的品质是坚韧、适应力和决心。这意味着,就我们正确而言,这些就是你获胜所需的品质。 投资者知道这一点,至少是无意识地。他们喜欢你不.
我最终的数据大概是收到并阅读了500到800份商业计划书,进行了大约50到100次初始的1小时会议,对其中约20家公司产生了兴趣,认真考虑并投入大量工作的有5家左右,一年内达成1到2笔交易。所以形势对你并不利。你可能是一位出色的创业者,正在做有趣的项目等等,但即便如此,获得投资的可能性依然微乎其微。
Some of the more unscrupulous do it deliberately. But even the most well-intentioned investors can behave in a way that would seem crazy in everyday life. One day they're full of enthusiasm and seem ready to write you a check on the spot; the next they won't return your phone calls. They're not playing games with you. They just can't make up their minds. [1] If that weren't bad enough, these wildly fluctuating nodes are all linked together. Startup investors all know one another, and (though they hate to admit it) the biggest factor in their opinion of you is the opinion of other investors. [2] Talk about a recipe for an unstable system. You get the opposite of the damping that the fear/greed balance usually produces in markets. No one is interested in a startup that's a "bargain" because everyone else hates it. So the inefficient market you get because there are so few players is exacerbated by the fact that they act less than independently. The result is a system like some kind of primitive, multi-celled sea creature, where you irritate one extremity and the whole thing contracts violently. Y Combinator is working to fix this. We're trying to increase the number of investors just as we're increasing the number of startups. We hope that as the number of both increases we'll get something more like an efficient market. As t approaches infinity, Demo Day approaches an auction. Unfortunately, t is still very far from infinity. What does a startup do now, in the imperfect world we currently inhabit? The most important thing is not to let fundraising get you down. Startups live or die on morale. If you let the difficulty of raising money destroy your morale, it will become a self-fulfilling prophecy. Bootstrapping (= Consulting) Some would-be founders may by now be thinking, why deal with investors at all? If raising money is so painful, why do it? One answer to that is obvious: because you need money to live on.
天使投资人在这方面稍好一些,但风险投资机构几乎会拒绝所有人。他们的业务结构决定了每位合伙人每年最多只能进行两笔新投资,无论有多少优秀初创企业找上门来。
除了成功概率极低之外,正如我提到的,普通投资者对初创企业的判断力往往很差。评估初创企业比其他大多数事情都困难,因为绝佳的创业点子往往看起来像是错的。一个好的创业想法不仅要优秀,还必须新颖。而要做到既优秀又新颖,这个想法对大多数人来说很可能显得糟糕——否则早就有人在做,它也就不新颖了。
It's a fine idea in principle to finance your startup with its own revenues, but you can't create instant customers. Whatever you make, you have to sell a certain amount to break even. It will take time to grow your sales to that point, and it's hard to predict, till you try, how long it will take. We could not have bootstrapped Viaweb, for example. We charged quite a lot for our software—about $140 per user per month—but it was at least a year before our revenues would have covered even our paltry costs. We didn't have enough saved to live on for a year. If you factor out the "bootstrapped" companies that were actually funded by their founders through savings or a day job, the remainder either (a) got really lucky, which is hard to do on demand, or (b) began life as consulting companies and gradually transformed themselves into product companies. Consulting is the only option you can count on. But consulting is far from free money. It's not as painful as raising money from investors, perhaps, but the pain is spread over a longer period. Years, probably. And for many types of startup, that delay could be fatal. If you're working on something so unusual that no one else is likely to think of it, you can take your time. Joshua Schachter gradually built Delicious on the side while working on Wall Street. He got away with it because no one else realized it was a good idea. But if you were building something as obviously necessary as online store software at about the same time as Viaweb, and you were working on it on the side while spending most of your time on client work, you were not in a good position. Bootstrapping sounds great in principle, but this apparently verdant territory is one from which few startups emerge alive. The mere fact that bootstrapped startups tend to be famous on that account should set off alarm bells.
这使得评判初创企业比其他大多数判断都更难。要成为优秀的初创企业投资者,你必须是个智力上的逆向思考者。这对风投机构是个问题,因为他们大多缺乏想象力。风投人士本质上是金融从业者,而非产品创造者[7]。天使投资人更擅长欣赏新颖想法,因为他们大多自己创过业。
所以当你被拒绝时,要利用其中包含的信息,而非凭空臆测。如果投资者给出了具体的拒绝理由,审视你的公司并思考这些批评是否成立。如果确实是问题所在,就解决它们。但不要盲目采信——你才是领域专家,必须自己做出判断。
If it worked so well, it would be the norm. [3] Bootstrapping may get easier, because starting a company is getting cheaper. But I don't think we'll ever reach the point where most startups can do without outside funding. Technology tends to get dramatically cheaper, but living expenses don't. The upshot is, you can choose your pain: either the short, sharp pain of raising money, or the chronic ache of consulting. For a given total amount of pain, raising money is the better choice, because new technology is usually more valuable now than later. But although for most startups raising money will be the lesser evil, it's still a pretty big evil—so big that it can easily kill you. Not merely in the obvious sense that if you fail to raise money you might have to shut the company down, but because the _process_ of raising money itself can kill you. To survive it you need a set of techniques mostly orthogonal to the ones used in convincing investors, just as mountain climbers need to know survival techniques that are mostly orthogonal to those used in physically getting up and down mountains. 1\. Have low expectations. The reason raising money destroys so many startups' morale is not simply that it's hard, but that it's so much harder than they expected. What kills you is the disappointment. And the lower your expectations, the harder it is to be disappointed. Startup founders tend to be optimistic. This can work well in technology, at least some of the time, but it's the wrong way to approach raising money. Better to assume investors will always let you down. Acquirers too, while we're at it. At YC one of our secondary mantras is "Deals fall through." No matter what deal you have going on, assume it will fall through. The predictive power of this simple rule is amazing. There will be a tendency, as a deal progresses, to start to believe it will happen, and then to depend on it happening. You must resist this.
虽然拒绝未必能说明你的初创企业存在问题,但它确实暗示你的推介方式有待改进。找出问题所在并调整策略,别简单归咎于"投资人太蠢"。虽然他们经常如此,但要准确定位你在哪个环节失去了他们的兴趣。
别让拒绝堆积成令人沮丧的无差别废料堆。对它们进行分类分析,这样你就能从"没人看好我们"的挫败感,转变为准确认知问题严重性及解决方案。
7. 必要时能转向咨询业务
Tie yourself to the mast. This is what kills you. Deals do not have a trajectory like most other human interactions, where shared plans solidify linearly over time. Deals often fall through at the last moment. Often the other party doesn't really think about what they want till the last moment. So you can't use your everyday intuitions about shared plans as a guide. When it comes to deals, you have to consciously turn them off and become pathologically cynical. This is harder to do than it sounds. It's very flattering when eminent investors seem interested in funding you. It's easy to start to believe that raising money will be quick and straightforward. But it hardly ever is. 2\. Keep working on your startup. It sounds obvious to say that you should keep working on your startup while raising money. Actually this is hard to do. Most startups don't manage to. Raising money has a mysterious capacity to suck up all your attention. Even if you only have one meeting a day with investors, somehow that one meeting will burn up your whole day. It costs not just the time of the actual meeting, but the time getting there and back, and the time preparing for it beforehand and thinking about it afterward. The best way to survive the distraction of meeting with investors is probably to partition the company: to pick one founder to deal with investors while the others keep the company going. This works better when a startup has 3 founders than 2, and better when the leader of the company is not also the lead developer. In the best case, the company keeps moving forward at about half speed. That's the best case, though. More often than not the company comes to a standstill while raising money. And that is dangerous for so many reasons. Raising money always takes longer than you expect. What seems like it's going to be a 2 week interruption turns into a 4 month interruption. That can be very demoralizing.
正如前文所述,通过咨询业务为初创企业输血存在风险。但总比倒闭强。这有点像无氧呼吸:虽非长期最优解,却能化解燃眉之急。如果融资完全受阻,转型咨询或许能挽救公司。
这种模式更适合某些类型的初创企业。比如对谷歌就不适用,但如果你是做网站建设软件的,通过为客户建站来过渡就相对自然。
And worse still, it can make you less attractive to investors. They want to invest in companies that are dynamic. A company that hasn't done anything new in 4 months doesn't seem dynamic, so they start to lose interest. Investors rarely grasp this, but much of what they're responding to when they lose interest in a startup is the damage done by their own indecision. The solution: put the startup first. Fit meetings with investors into the spare moments in your development schedule, rather than doing development in the spare moments between meetings with investors. If you keep the company moving forward—releasing new features, increasing traffic, doing deals, getting written about—those investor meetings are more likely to be productive. Not just because your startup will seem more alive, but also because it will be better for your own morale, which is one of the main ways investors judge you. 3\. Be conservative. As conditions get worse, the optimal strategy becomes more conservative. When things go well you can take risks; when things are bad you want to play it safe. I advise approaching fundraising as if it were always going badly. The reason is that between your ability to delude yourself and the wildly unstable nature of the system you're dealing with, things probably either already are or could easily become much worse than they seem. What I tell most startups we fund is that if someone reputable offers you funding on reasonable terms, take it. There have been startups that ignored this advice and got away with it—startups that ignored a good offer in the hope of getting a better one, and actually did. But in the same position I'd give the same advice again. Who knows how many bullets were in the gun they were playing Russian roulette with? Corollary: if an investor seems interested, don't just let them sit. You can't assume someone interested in investing will stay interested.
只要注意不被咨询业务永久绑架,这种模式甚至能带来好处。通过亲自为客户使用自家软件,你能更深入理解用户需求。此外作为服务商,你或许能让某些知名客户使用你的软件——这些客户可能根本不会考虑采购你的产品。
Viaweb早期就不得不以咨询公司模式运作,因为我们极度渴望用户,甚至承诺为签约商户免费建站。但我们从不收费,避免被当成真正的服务商——否则客户会为每个网站改动来电求助。我们清楚必须保持产品公司的本质,因为只有这样才能实现规模扩张。
In fact, you can't even tell ( _they_ can't even tell) if they're really interested till you try to convert that interest into money. So if you have hot prospect, either close them now or write them off. And unless you already have enough funding, that reduces to: close them now. Startups don't win by getting great funding rounds, but by making great products. So finish raising money and get back to work. 4\. Be flexible. There are two questions VCs ask that you shouldn't answer: "Who else are you talking to?" and "How much are you trying to raise?" VCs don't expect you to answer the first question. They ask it just in case. [4] They do seem to expect an answer to the second. But I don't think you should just tell them a number. Not as a way to play games with them, but because you shouldn't _have_ a fixed amount you need to raise. The custom of a startup needing a fixed amount of funding is an obsolete one left over from the days when startups were more expensive. A company that needed to build a factory or hire 50 people obviously needed to raise a certain minimum amount. But few technology startups are in that position today. We advise startups to tell investors there are several different routes they could take depending on how much they raised. As little as $50k could pay for food and rent for the founders for a year. A couple hundred thousand would let them get office space and hire some smart people they know from school. A couple million would let them really blow this thing out. The message (and not just the message, but the fact) should be: we're going to succeed no matter what. Raising more money just lets us do it faster. If you're raising an angel round, the size of the round can even change on the fly. In fact, it's just as well to make the round small initially, then expand as needed, rather than trying to raise a large round and risk losing the investors you already have if you can't raise the full amount.
8. 警惕投资新手
新手投资者看似无害,实则可能最危险,因为他们过度紧张——尤其相对于其投资金额而言。从初次试水的天使投资人那里融资2万美元耗费的精力,可能堪比从风投基金融资200万。
他们的律师通常也缺乏经验。但区别在于:投资人可以承认自己不懂行,律师却不行。某YC初创公司与天使投资人谈妥小额融资条款后,竟收到其律师起草的70页协议。由于律师不可能在客户面前承认失误,他坚持保留所有严苛条款,最终导致交易流产。
You may even want to do a "rolling close," where the round has no predetermined size, but instead you sell stock to investors one at a time as they say yes. That helps break deadlocks, because you can start as soon as the first one is ready to buy. [5] 5\. Be independent. A startup with a couple founders in their early twenties can have expenses so low that they could be profitable on as little as $2000 per month. That's negligible as corporate revenues go, but the effect on your morale and your bargaining position is anything but. At YC we use the phrase "ramen profitable" to describe the situation where you're making just enough to pay your living expenses. Once you cross into ramen profitable, everything changes. You may still need investment to make it big, but you don't need it this month. You can't plan when you start a startup how long it will take to become profitable. But if you find yourself in a position where a little more effort expended on sales would carry you over the threshold of ramen profitable, do it. Investors like it when you're ramen profitable. It shows you've thought about making money, instead of just working on amusing technical problems; it shows you have the discipline to keep your expenses low; but above all, it means you don't need them. There is nothing investors like more than a startup that seems like it's going to succeed even without them. Investors like it when they can help a startup, but they don't like startups that would die without that help. At YC we spend a lot of time trying to predict how the startups we've funded will do, because we're trying to learn how to pick winners. We've now watched the trajectories of so many startups that we're getting better at predicting them. And when we're talking about startups we think are likely to succeed, what we find ourselves saying is things like "Oh, those guys can take care of themselves.
当然,总得有人成为新手投资人的"练手对象",否则市场上永远不会出现成熟投资者。但如果你决定接受这类投资,要么(a)全程主导流程(包括提供标准化法律文件),要么(b)仅将其作为某轮大型融资的补充资金。
9. 明确自身处境
They'll be fine." Not "those guys are really smart" or "those guys are working on a great idea." [6] When we predict good outcomes for startups, the qualities that come up in the supporting arguments are toughness, adaptability, determination. Which means to the extent we're correct, those are the qualities you need to win. Investors know this, at least unconsciously. The reason they like it when you don't need them is not simply that they like what they can't have, but because that quality is what makes founders succeed. Sam Altman has it. You could parachute him into an island full of cannibals and come back in 5 years and he'd be the king. If you're Sam Altman, you don't have to be profitable to convey to investors that you'll succeed with or without them. (He wasn't, and he did.) Not everyone has Sam's deal-making ability. I myself don't. But if you don't, you can let the numbers speak for you. 6\. Don't take rejection personally. Getting rejected by investors can make you start to doubt yourself. After all, they're more experienced than you. If they think your startup is lame, aren't they probably right? Maybe, maybe not. The way to handle rejection is with precision. You shouldn't simply ignore rejection. It might mean something. But you shouldn't automatically get demoralized either. To understand what rejection means, you have to understand first of all how common it is. Statistically, the average VC is a rejection machine. David Hornik, a partner at August, told me:.
投资者最危险的特质是优柔寡断。最糟糕的情况是"漫长的拒绝"——经过数月会议后才给出的否定答复。投资人的拒绝就像设计缺陷:无法完全避免,但越早发现代价越小。
因此在与投资人周旋时,要持续评估自身处境:他们出具投资条款书的可能性有多大?还需要说服他们相信什么?不必总是直白提问(可能惹人厌),但要持续收集相关信号。
> The numbers for me ended up being something like 500 to 800 plans received and read, somewhere between 50 and 100 initial 1 hour meetings held, about 20 companies that I got interested in, about 5 that I got serious about and did a bunch of work, 1 to 2 deals done in a year. So the odds are against you. You may be a great entrepreneur, working on interesting stuff, etc. but it is still incredibly unlikely that you get funded.
投资人天然抗拒做出承诺,除非你施加压力。对他们而言,最理想状态是在最小化决策的同时最大化信息收集。当然,制造竞争态势是最佳施压手段。但你也可以通过聚焦讨论来推进:明确他们做出决策需要解决的具体问题,然后逐个击破。如果你连续突破多个障碍后对方仍不断设置新关卡,基本可以判定他们最终会退缩。
评估投资人意向时需要保持理性克制。否则他们"吊着你"的倾向与你"被吊着"的期待相结合,会产生严重失真的判断。
根据数据调整策略。你很可能同时在接触多个投资人,应该优先攻克最可能点头的那个。潜在投资人的价值取决于两个因素:他们投资带来的好处,以及他们实际投资的可能性。要更重视后者——部分因为投资人最重要的品质就是愿意投资,更因为(如前所述)投资人对你评价的最大影响因素,是其他投资人对你的评价。如果你能推动某个投资人突破心理阈值表示同意,其他观望者兴趣会立刻提升。所以专注突破最热切的投资人并非冷落犹豫者——说服前者恰恰是打动后者的最佳方式。
This is less true with angels, but VCs reject practically everyone. The structure of their business means a partner does at most 2 new investments a year, no matter how many good startups approach him. In addition to the odds being terrible, the average investor is, as I mentioned, a pretty bad judge of startups. It's harder to judge startups than most other things, because great startup ideas tend to seem wrong. A good startup idea has to be not just good but novel. And to be both good and novel, an idea probably has to seem bad to most people, or someone would already be doing it and it wouldn't be novel. That makes judging startups harder than most other things one judges. You have to be an intellectual contrarian to be a good startup investor. That's a problem for VCs, most of whom are not particularly imaginative. VCs are mostly money guys, not people who make things. [7] Angels are better at appreciating novel ideas, because most were founders themselves. So when you get a rejection, use the data that's in it, and not what's not. If an investor gives you specific reasons for not investing, look at your startup and ask if they're right. If they're real problems, fix them. But don't just take their word for it. You're supposed to be the domain expert; you have to decide. Though a rejection doesn't necessarily tell you anything about your startup, it does suggest your pitch could be improved. Figure out what's not working and change it. Don't just think "investors are stupid." Often they are, but figure out precisely where you lose them. Don't let rejections pile up as a depressing, undifferentiated heap. Sort them and analyze them, and then instead of thinking "no one likes us," you'll know precisely how big a problem you have, and what to do about it. 7\. Be able to downshift into consulting (if appropriate). Consulting, as I mentioned, is a dangerous way to finance a startup. But it's better than dying.
我期待这种扭曲状态不会永远持续。随着创业成本持续降低和投资者数量增加,融资过程即便不会变得轻松,至少能更加直截了当。
现阶段,融资机制的缺陷中蕴藏着巨大机会。多数投资者根本意识不到自己造成的风险。若听说从他们那里融资竟被视作威胁企业生存的隐患,他们定会愕然——他们自认为只是需要更多信息来做决定。殊不知还有十个投资人也抱着同样想法,而与所有这些人的周旋足以让初创企业停滞数月。
It's a bit like anaerobic respiration: not the optimum solution for the long term, but it can save you from an immediate threat. If you're having trouble raising money from investors at all, it could save you to be able to shift toward consulting. This works better for some startups than others. It wouldn't have been a natural fit for, say, Google, but if your company was making software for building web sites, you could degrade fairly gracefully into consulting by building sites for clients with it. So long as you were careful not to get sucked permanently into consulting, this could even have advantages. You'd understand your users well if you were using the software for them. Plus as a consulting company you might be able to get big-name users using your software that you wouldn't have gotten as a product company. At Viaweb we were forced to operate like a consulting company initially, because we were so desperate for users that we'd offer to build merchants' sites for them if they'd sign up. But we never charged for such work, because we didn't want them to start treating us like actual consultants, and calling us every time they wanted something changed on their site. We knew we had to stay a product company, because only that scales. 8\. Avoid inexperienced investors. Though novice investors seem unthreatening they can be the most dangerous sort, because they're so nervous. Especially in proportion to the amount they invest. Raising $20,000 from a first-time angel investor can be as much work as raising $2 million from a VC fund. Their lawyers are generally inexperienced too. But while the investors can admit they don't know what they're doing, their lawyers can't. One YC startup negotiated terms for a tiny round with an angel, only to receive a 70-page agreement from his lawyer.
由于投资者未能理解创业者对接成本,他们没意识到潜在竞争者有多大空间可以颠覆现有模式。根据YC的实操经验,我们已将决策时间压缩至20分钟(5分钟阅读申请材料+10分钟面谈+5分钟讨论)。当然,大额投资需要更长时间尽调。但既然我们能在20分钟内做决定,其他人真的需要超过几天吗?
即使在风投这样保守的行业,这类机会也不会永远被忽视。要么现有投资者会加速决策,要么更高效的新投资者将涌现。
And since the lawyer could never admit, in front of his client, that he'd screwed up, he instead had to insist on retaining all the draconian terms in it, so the deal fell through. Of course, someone has to take money from novice investors, or there would never be any experienced ones. But if you do, either (a) drive the process yourself, including supplying the paperwork, or (b) use them only to fill up a larger round led by someone else. 9\. Know where you stand. The most dangerous thing about investors is their indecisiveness. The worst case scenario is the long no, the no that comes after months of meetings. Rejections from investors are like design flaws: inevitable, but much less costly if you discover them early. So while you're talking to investors, constantly look for signs of where you stand. How likely are they to offer you a term sheet? What do they have to be convinced of first? You shouldn't necessarily always be asking these questions outright—that could get annoying—but you should always be collecting data about them. Investors tend to resist committing except to the extent you push them to. It's in their interest to collect the maximum amount of information while making the minimum number of decisions. The best way to force them to act is, of course, competing investors. But you can also apply some force by focusing the discussion: by asking what specific questions they need answered to make up their minds, and then answering them. If you get through several obstacles and they keep raising new ones, assume that ultimately they're going to flake. You have to be disciplined when collecting data about investors' intentions. Otherwise their desire to lead you on will combine with your own desire to be led on to produce completely inaccurate impressions. Use the data to weight your strategy. You'll probably be talking to several investors.
在此之前,创始人必须将融资视为高危动作。所幸我可以在此消除最大的风险——认知落差。最危险的情况是初创企业低估融资难度:前期顺风顺水,真正开始融资时却遭遇意外挫折,最终士气崩溃选择放弃。所以我现在明确告知你:融资本就艰难。
[1] 当投资者犹豫不决时,他们常把问题包装成初创企业的属性。比如"你们对我们来说太早期了"。但如果用时光机把这些人带回谷歌创立当天,谁会拒绝以创始人开的任何估值投资呢?如果是合适的项目,成立一小时也不算早。"你们太早期"的真实含义是"我们还无法判断你们能否成功"。
[2] 投资者会通过直接和间接方式相互影响。直接影响表现为热门项目引发的"跟风效应"。但更微妙的是通过创始人产生的间接影响——当众多投资者对你感兴趣时,这种信心加持会让你对投资者更具吸引力。
Focus on the ones that are most likely to say yes. The value of a potential investor is a combination of how good it would be if they said yes, and how likely they are to say it. Put the most weight on the second factor. Partly because the most important quality in an investor is simply investing. But also because, as I mentioned, the biggest factor in investors' opinion of you is other investors' opinion of you. If you're talking to several investors and you manage to get one over the threshold of saying yes, it will make the others much more interested. So you're not sacrificing the lukewarm investors if you focus on the hot ones; convincing the hot investors is the best way to convince the lukewarm ones. Future I'm hopeful things won't always be so awkward. I hope that as startups get cheaper and the number of investors increases, raising money will become, if not easy, at least straightforward. In the meantime, the brokenness of the funding process offers a big opportunity. Most investors have no idea how dangerous they are. They'd be surprised to hear that raising money from them is something that has to be treated as a threat to a company's survival. They just think they need a little more information to make up their minds. They don't get that there are 10 other investors who also want a little more information, and that the process of talking to them all can bring a startup to a standstill for months. Because investors don't understand the cost of dealing with them, they don't realize how much room there is for a potential competitor to undercut them. I know from my own experience how much faster investors could decide, because we've brought our own time down to 20 minutes (5 minutes of reading an application plus a 10 minute interview plus 5 minutes of discussion). If you were investing more money you'd want to take longer, of course.
没有风投会承认受跟风效应影响,有些确实没有。但极少有人敢说不受创业者信心的影响。
[3] 某位阅读本文的风投人士写道:"我们尽量避免投资靠咨询业务起家的公司。这会形成难以消除的不良文化基因。"
But if we can decide in 20 minutes, should it take anyone longer than a couple days? Opportunities like this don't sit unexploited forever, even in an industry as conservative as venture capital. So either existing investors will start to make up their minds faster, or new investors will emerge who do. In the meantime founders have to treat raising money as a dangerous process. Fortunately, I can fix the biggest danger right here. The biggest danger is surprise. It's that startups will underestimate the difficulty of raising money—that they'll cruise through all the initial steps, but when they turn to raising money they'll find it surprisingly hard, get demoralized, and give up. So I'm telling you in advance: raising money is hard. Notes [1] When investors can't make up their minds, they sometimes describe it as if it were a property of the startup. "You're too early for us," they sometimes say. But which of them, if they were taken back in a time machine to the hour Google was founded, wouldn't offer to invest at any valuation the founders chose? An hour old is not too early if it's the right startup. What "you're too early" really means is "we can't figure out yet whether you'll succeed." [2] Investors influence one another both directly and indirectly. They influence one another directly through the "buzz" that surrounds a hot startup. But they also influence one another indirectly _through the founders._ When a lot of investors are interested in you, it increases your confidence in a way that makes you much more attractive to investors. No VC will admit they're influenced by buzz. Some genuinely aren't. But there are few who can say they're not influenced by confidence. [3] One VC who read this essay wrote: "We try to avoid companies that got bootstrapped with consulting.
[4] 回答"还有哪些机构在接触"的最优解是:婉拒透露具体名称,同时暗示多家风投即将给你条款书。如果你深谙此道请自便,否则千万别勉强——没有什么比拙劣的话术更惹风投反感了。
[5] 动态扩大融资轮的缺点是估值已在初期锁定。若突然出现超额认购,你将面临两难:拒绝部分投资者,或出让超出预期的股份。不过这属于甜蜜的烦恼。
It creates very bad behaviors/instincts that are hard to erase from a company's culture." [4] The optimal way to answer the first question is to say that it would be improper to name names, while simultaneously implying that you're talking to a bunch of other VCs who are all about to give you term sheets. If you're the sort of person who understands how to do that, go ahead. If not, don't even try. Nothing annoys VCs more than clumsy efforts to manipulate them. [5] The disadvantage of expanding a round on the fly is that the valuation is fixed at the start, so if you get a sudden rush of interest, you may have to decide between turning some investors away and selling more of the company than you meant to. That's a good problem to have, however. [6] I wouldn't say that intelligence doesn't matter in startups. We're only comparing YC startups, who've already made it over a certain threshold. [7] But not all are. Though most VCs are suits at heart, the most successful ones tend not to be. Oddly enough, the best VCs tend to be the least VC-like. Thanks to Trevor Blackwell, David Hornik, Jessica Livingston, Robert Morris, and Fred Wilson for reading drafts of this.
[6] 我并非认为智力在创业中不重要。这里比较的是已通过YC筛选门槛的初创企业。
[7] 但并非所有风投都如此。虽然多数风投骨子里是金融人士,但最成功者往往例外。有趣的是,最优秀的投资人通常最不像典型风投。
致谢 感谢Trevor Blackwell、David Hornik、Jessica Livingston、Robert Morris和Fred Wilson审阅本文草稿。
July 2008 At this year's startup school, David Heinemeier Hansson gave a talk in which he suggested that startup founders should do things the old fashioned way. Instead of hoping to get rich by building a valuable company and then selling stock in a "liquidity event," founders should start companies that make money and live off the revenues. Sounds like a good plan. Let's think about the optimal way to do this. One disadvantage of living off the revenues of your company is that you have to keep running it. And as anyone who runs their own business can tell you, that requires your complete attention. You can't just start a business and check out once things are going well, or they stop going well surprisingly fast. The main economic motives of startup founders seem to be freedom and security. They want enough money that (a) they don't have to worry about running out of money and (b) they can spend their time how they want. Running your own business offers neither. You certainly don't have freedom: no boss is so demanding. Nor do you have security, because if you stop paying attention to the company, its revenues go away, and with them your income. The best case, for most people, would be if you could hire someone to manage the company for you once you'd grown it to a certain size. Suppose you could find a really good manager. Then you would have both freedom and security. You could pay as little attention to the business as you wanted, knowing that your manager would keep things running smoothly. And that being so, revenues would continue to flow in, so you'd have security as well. There will of course be some founders who wouldn't like that idea: the ones who like running their company so much that there's nothing else they'd rather do. But this group must be small.
在今年创业学院的演讲中,大卫·海涅迈尔·汉森提出一个观点:初创企业创始人应该回归传统模式。与其寄望于打造高估值公司后通过"流动性事件"出售股份致富,创始人更应创立能持续盈利、依靠营收维持生计的企业。
这听起来是个好计划。让我们思考如何最优地实现它。
依靠公司营收生活的弊端在于你必须持续经营。任何创业者都会告诉你,这需要投入全部精力。你无法在业务步入正轨后抽身而退——否则发展势头会以惊人的速度急转直下。
初创创始人核心的经济动机通常是自由与安全。他们渴望获得足够资金以实现:(a) 不必为财务枯竭担忧;(b) 能自主支配时间。而自主经营企业无法提供这两点。你绝无自由可言:没有比企业主更严苛的老板;你也缺乏安全保障,因为一旦疏于管理,营收便会枯竭,收入随之消失。
对大多数人而言,理想情况是在企业发展到一定规模后聘请专业经理人代为管理。假设能找到真正优秀的管理者,你将同时获得自由与安全。你可以随心所欲地减少对业务的关注,确信经理人会维持企业顺畅运转。由此带来的持续收入流也将保障你的财务安全。
The way you succeed in most businesses is to be fanatically attentive to customers' needs. What are the odds that your own desires would coincide exactly with the demands of this powerful, external force? Sure, running your own company can be fairly interesting. Viaweb was more interesting than any job I'd had before. And since I made much more money from it, it offered the highest ratio of income to boringness of anything I'd done, by orders of magnitude. But was it _the_ most interesting work I could imagine doing? No. Whether the number of founders in the same position is asymptotic or merely large, there are certainly a lot of them. For them the right approach would be to hand the company over to a professional manager eventually, if they could find one who was good enough. _____ So far so good. But what if your manager was hit by a bus? What you really want is a management company to run your company for you. Then you don't depend on any one person. If you own rental property, there are companies you can hire to manage it for you. Some will do everything, from finding tenants to fixing leaks. Of course, running companies is a lot more complicated than managing rental property, but let's suppose there were management companies that could do it for you. They'd charge a lot, but wouldn't it be worth it? I'd sacrifice a large percentage of the income for the extra peace of mind. I realize what I'm describing already sounds too good to be true, but I can think of a way to make it even more attractive. If company management companies existed, there would be an additional service they could offer clients: they could let them insure their returns by pooling their risk. After all, even a perfect manager can't save a company when, as sometimes happens, its whole market dies, just as property managers can't save you from the building burning down.
当然,部分创始人会抵触这个想法——那些热爱经营企业胜过一切的创业者。但这类群体必然稀少。大多数企业的成功秘诀在于对客户需求近乎偏执的关注。个人志趣与这种强大外部需求完美契合的概率能有多大?
诚然,经营自有企业颇具趣味。Viaweb比我此前任何工作都更有意思。由于从中获利远超以往,其收入与乏味度的性价比达到前所未有的高度。但这是我能想象到最有意义的工作吗?并非如此。
无论处于相同境遇的创始人是趋近无限还是仅占多数,这个群体必然庞大。对他们而言,若能找到足够优秀的职业经理人,最终移交企业管理权才是正确选择。
至此一切顺利。但若经理人遭遇不测呢?理想方案是委托企业管理公司代为运营,这样你就不必依赖特定个人。
房产租赁领域存在提供全流程托管服务的公司,从招租到维修无所不包。当然企业经营远比物业管理复杂,但假设存在能胜任的托管公司呢?虽然收费高昂,但这笔支出物有所值。为换取内心安宁,我愿牺牲可观比例的收入。
我意识到上述构想美好得近乎虚幻,但还能进一步优化:若企业管理公司存在,它们可提供风险共担服务。毕竟即便最优秀的经理人也无法挽救因市场消亡而衰败的企业,就像物业公司无法阻止大楼焚毁。但管理足够多企业的公司可以向客户承诺:我们将合并所有企业收益,按比例分配。
But a company that managed a large enough number of companies could say to all its clients: we'll combine the revenues from all your companies, and pay you your proportionate share. If such management companies existed, they'd offer the maximum of freedom and security. Someone would run your company for you, and you'd be protected even if it happened to die. Let's think about how such a management company might be organized. The simplest way would be to have a new kind of stock representing the total pool of companies they were managing. When you signed up, you'd trade your company's stock for shares of this pool, in proportion to an estimate of your company's value that you'd both agreed upon. Then you'd automatically get your share of the returns of the whole pool. The catch is that because this kind of trade would be hard to undo, you couldn't switch management companies. But there's a way they could fix that: suppose all the company management companies got together and agreed to allow their clients to exchange shares in all their pools. Then you could, in effect, simultaneously choose all the management companies to run yours for you, in whatever proportion you wanted, and change your mind later as often as you wanted. If such pooled-risk company management companies existed, signing up with one would seem the ideal plan for most people following the route David advocated. Good news: they do exist. What I've just described is an acquisition by a public company. _____ Unfortunately, though public acquirers are structurally identical to pooled-risk company management companies, they don't think of themselves that way. With a property management company, you can just walk in whenever you want and say "manage my rental property for me" and they'll do it. Whereas acquirers are, as of this writing, extremely fickle. Sometimes they're in a buying mood and they'll overpay enormously; other times they're not interested.
这类管理公司将提供最大限度的自由与安全:有人替你经营企业,即使企业倒闭你仍受保护。
设想这类公司的组织架构:最简单的形式是发行代表被管理企业池的新型股票。签约时,双方根据议定估值将你的公司股票转换为资产池份额,之后你自动获得整体收益的分成。
关键在于这种交易难以撤销,你将无法更换管理公司。但解决方案是存在的:假设所有管理公司达成协议,允许客户跨平台交换份额。这样你就能按任意比例同时选择多家管理公司,并随时调整配置。
若这类风险共担型企业管理公司真实存在,对遵循大卫建议的大多数人而言,签约入驻将是理想选择。
好消息是:它们确实存在。我描述的正是上市公司收购行为。
遗憾的是,尽管上市公司在结构上与风险共担型管理公司无异,但二者认知存在偏差。物业公司随时欢迎业主委托管理,而截至目前,收购方的行为却反复无常。它们时而狂热溢价收购,时而兴趣全无,宛如由疯子——更准确说是本杰明·格雷厄姆笔下的"市场先生"——经营的物业公司。
They're like property management companies run by madmen. Or more precisely, by Benjamin Graham's Mr. Market. So while on average public acquirers behave like pooled-risk company managers, you need a window of several years to get average case performance. If you wait long enough (five years, say) you're likely to hit an up cycle where some acquirer is hot to buy you. But you can't choose when it happens. You can't assume investors will carry you for as long as you might have to wait. Your company has to make money. Opinions are divided about how early to focus on that. Joe Kraus says you should try charging customers right away. And yet some of the most successful startups, including Google, ignored revenue at first and concentrated exclusively on development. The answer probably depends on the type of company you're starting. I can imagine some where trying to make sales would be a good heuristic for product design, and others where it would just be a distraction. The test is probably whether it helps you to understand your users. You can choose whichever revenue strategy you think is best for the type of company you're starting, so long as you're profitable. Being profitable ensures you'll get at least the average of the acquisition market—in which public companies do behave as pooled-risk company management companies. David isn't mistaken in saying you should start a company to live off its revenues. The mistake is thinking this is somehow opposed to starting a company and selling it. In fact, for most people the latter is merely the optimal case of the former. Thanks to Trevor Blackwell, Jessica Livingston, Michael Mandel, Robert Morris, and Fred Wilson for reading drafts of this.
虽然长期来看上市公司确实扮演着风险共担管理者的角色,但你需要数年周期才能获得平均收益。若等待足够久(比如五年),很可能遇上收购热潮。但这个时机不可控。
你不能指望投资者会陪你等待。企业必须实现盈利。关于何时聚焦盈利存在分歧:乔·克劳斯主张立即收费,而谷歌等最成功的企业初期却完全专注产品开发。答案可能取决于企业类型——对某些公司,销售尝试能指导产品设计;对另一些则只是干扰。判断标准或许是能否助你理解用户。
只要保持盈利,你可以选择最适合企业类型的营收策略。盈利能确保你至少获得收购市场的平均估值——在这个市场里,上市公司确实发挥着风险共担管理公司的作用。
大卫建议创立依靠营收生存的企业没有错,错在将之与创立后出售对立起来。事实上对多数人而言,后者只是前者的最优形态。
致谢 特雷弗·布莱克韦尔、杰西卡·利文斯顿、迈克尔·曼德尔、罗伯特·莫里斯和弗雷德·威尔逊审阅了本文草稿。
May 2008 Great cities attract ambitious people. You can sense it when you walk around one. In a hundred subtle ways, the city sends you a message: you could do more; you should try harder. The surprising thing is how different these messages can be. New York tells you, above all: you should make more money. There are other messages too, of course. You should be hipper. You should be better looking. But the clearest message is that you should be richer. What I like about Boston (or rather Cambridge) is that the message there is: you should be smarter. You really should get around to reading all those books you've been meaning to. When you ask what message a city sends, you sometimes get surprising answers. As much as they respect brains in Silicon Valley, the message the Valley sends is: you should be more powerful. That's not quite the same message New York sends. Power matters in New York too of course, but New York is pretty impressed by a billion dollars even if you merely inherited it. In Silicon Valley no one would care except a few real estate agents. What matters in Silicon Valley is how much effect you have on the world. The reason people there care about Larry and Sergey is not their wealth but the fact that they control Google, which affects practically everyone. _____ How much does it matter what message a city sends? Empirically, the answer seems to be: a lot. You might think that if you had enough strength of mind to do great things, you'd be able to transcend your environment. Where you live should make at most a couple percent difference. But if you look at the historical evidence, it seems to matter more than that. Most people who did great things were clumped together in a few places where that sort of thing was done at the time. You can see how powerful cities are from something I wrote about earlier: the case of the Milanese Leonardo.
伟大城市吸引有抱负的人。当你漫步其中时,就能感受到这一点。城市通过无数微妙的方式向你传递信息:你可以做得更多;你应该更加努力。
令人惊讶的是,这些信息可以如此不同。纽约告诉你最重要的是:你应该赚更多钱。当然还有其他信息。你应该更时髦。你应该更好看。但最清晰的信息是:你应该更富有。
我喜欢波士顿(或者说剑桥)的原因是,那里传递的信息是:你应该更聪明。你真的应该读完那些你一直想读的书。
当你问一个城市传递什么信息时,有时会得到令人惊讶的答案。尽管硅谷尊重智慧,但硅谷传递的信息是:你应该更有影响力。
Practically every fifteenth century Italian painter you've heard of was from Florence, even though Milan was just as big. People in Florence weren't genetically different, so you have to assume there was someone born in Milan with as much natural ability as Leonardo. What happened to him? If even someone with the same natural ability as Leonardo couldn't beat the force of environment, do you suppose you can? I don't. I'm fairly stubborn, but I wouldn't try to fight this force. I'd rather use it. So I've thought a lot about where to live. I'd always imagined Berkeley would be the ideal place — that it would basically be Cambridge with good weather. But when I finally tried living there a couple years ago, it turned out not to be. The message Berkeley sends is: you should live better. Life in Berkeley is very civilized. It's probably the place in America where someone from Northern Europe would feel most at home. But it's not humming with ambition. In retrospect it shouldn't have been surprising that a place so pleasant would attract people interested above all in quality of life. Cambridge with good weather, it turns out, is not Cambridge. The people you find in Cambridge are not there by accident. You have to make sacrifices to live there. It's expensive and somewhat grubby, and the weather's often bad. So the kind of people you find in Cambridge are the kind of people who want to live where the smartest people are, even if that means living in an expensive, grubby place with bad weather. As of this writing, Cambridge seems to be the intellectual capital of the world. I realize that seems a preposterous claim. What makes it true is that it's more preposterous to claim about anywhere else. American universities currently seem to be the best, judging from the flow of ambitious students. And what US city has a stronger claim? New York? A fair number of smart people, but diluted by a much larger number of neanderthals in suits.
这与纽约传递的信息并不完全相同。当然,权力在纽约也很重要,但纽约对十亿美元印象深刻,即使你只是继承了它。在硅谷,除了少数房地产经纪人,没人会在意。在硅谷重要的是你对世界有多大影响。人们关心拉里和谢尔盖的原因不是他们的财富,而是他们控制着谷歌,这几乎影响着所有人。
一个城市传递的信息有多重要?从经验来看,答案似乎是:非常重要。你可能会认为,如果你有足够的心智力量去做伟大的事情,你就能超越环境。你居住的地方最多应该只有百分之几的影响。但如果你看看历史证据,似乎影响比这更大。大多数做出伟大事情的人都集中在少数几个当时做这种事情的地方。
你可以从我之前写过的东西中看到城市的力量:米兰的达芬奇的例子。几乎所有你听说过的15世纪意大利画家都来自佛罗伦萨,尽管米兰同样大。佛罗伦萨的人在基因上并没有什么不同,所以你不得不假设米兰出生的人中有和达芬奇一样天赋的人。他怎么样了?
如果连和达芬奇有同样天赋的人都无法战胜环境的力量,你认为你能吗?
The Bay Area has a lot of smart people too, but again, diluted; there are two great universities, but they're far apart. Harvard and MIT are practically adjacent by West Coast standards, and they're surrounded by about 20 other colleges and universities. [1] Cambridge as a result feels like a town whose main industry is ideas, while New York's is finance and Silicon Valley's is startups. _____ When you talk about cities in the sense we are, what you're really talking about is collections of people. For a long time cities were the only large collections of people, so you could use the two ideas interchangeably. But we can see how much things are changing from the examples I've mentioned. New York is a classic great city. But Cambridge is just part of a city, and Silicon Valley is not even that. (San Jose is not, as it sometimes claims, the capital of Silicon Valley. It's just 178 square miles at one end of it.) Maybe the Internet will change things further. Maybe one day the most important community you belong to will be a virtual one, and it won't matter where you live physically. But I wouldn't bet on it. The physical world is very high bandwidth, and some of the ways cities send you messages are quite subtle. One of the exhilarating things about coming back to Cambridge every spring is walking through the streets at dusk, when you can see into the houses. When you walk through Palo Alto in the evening, you see nothing but the blue glow of TVs. In Cambridge you see shelves full of promising-looking books. Palo Alto was probably much like Cambridge in 1960, but you'd never guess now that there was a university nearby. Now it's just one of the richer neighborhoods in Silicon Valley. [2] A city speaks to you mostly by accident — in things you see through windows, in conversations you overhear. It's not something you have to seek out, but something you can't turn off.
我不这么认为。我相当固执,但我不想与这种力量对抗。我更愿意利用它。所以我花了很多时间思考住在哪里。
我一直以为伯克利会是理想的地方——基本上是天气好的剑桥。但当我几年前终于尝试住在那里时,发现并非如此。伯克利传递的信息是:你应该生活得更好。伯克利的生活非常文明。这可能是美国最让北欧人感到宾至如归的地方。但它并不充满抱负。
回想起来,一个如此宜人的地方会吸引最关心生活质量的人,这并不奇怪。事实证明,天气好的剑桥并不是剑桥。你在剑桥遇到的人并非偶然在那里。你必须做出牺牲才能住在那里。那里昂贵且有些脏乱,天气也常常不好。所以你在剑桥遇到的人是那种想要住在最聪明的人所在的地方的人,即使这意味着住在一个昂贵、脏乱、天气不好的地方。
截至本文写作时,剑桥似乎是世界的知识之都。我意识到这听起来很荒谬。之所以如此,是因为对其他任何地方的这种说法更加荒谬。从有抱负的学生的流向来看,美国大学目前似乎是最好的。美国哪个城市更有资格?纽约?有不少聪明人,但被更多穿西装的原始人稀释了。湾区也有很多聪明人,但同样被稀释;那里有两所伟大的大学,但它们相距甚远。哈佛和MIT在西海岸的标准下几乎是相邻的,周围还有大约20所其他学院和大学。[1]
One of the occupational hazards of living in Cambridge is overhearing the conversations of people who use interrogative intonation in declarative sentences. But on average I'll take Cambridge conversations over New York or Silicon Valley ones. A friend who moved to Silicon Valley in the late 90s said the worst thing about living there was the low quality of the eavesdropping. At the time I thought she was being deliberately eccentric. Sure, it can be interesting to eavesdrop on people, but is good quality eavesdropping so important that it would affect where you chose to live? Now I understand what she meant. The conversations you overhear tell you what sort of people you're among. _____ No matter how determined you are, it's hard not to be influenced by the people around you. It's not so much that you do whatever a city expects of you, but that you get discouraged when no one around you cares about the same things you do. There's an imbalance between encouragement and discouragement like that between gaining and losing money. Most people overvalue negative amounts of money: they'll work much harder to avoid losing a dollar than to gain one. Similarly, although there are plenty of people strong enough to resist doing something just because that's what one is supposed to do where they happen to be, there are few strong enough to keep working on something no one around them cares about. Because ambitions are to some extent incompatible and admiration is a zero-sum game, each city tends to focus on one type of ambition. The reason Cambridge is the intellectual capital is not just that there's a concentration of smart people there, but that there's nothing _else_ people there care about more. Professors in New York and the Bay area are second class citizens — till they start hedge funds or startups respectively.
因此,剑桥给人的感觉是一个以思想为主要产业的小镇,而纽约的是金融,硅谷的是初创企业。
当我们谈论城市时,实际上是在谈论人群。长期以来,城市是唯一的大型人群聚集地,所以你可以互换使用这两个概念。但从我提到的例子中可以看出,事情正在发生多大的变化。纽约是一个典型的伟大城市。但剑桥只是一个城市的一部分,而硅谷甚至不是。(圣何塞并不像它有时声称的那样是硅谷的首都。它只是硅谷一端的178平方英里。)
也许互联网会进一步改变事情。也许有一天,你所属的最重要的社区将是一个虚拟的,而你实际住在哪里并不重要。但我不会打赌。物理世界的带宽非常高,城市向你传递信息的一些方式非常微妙。
每年春天回到剑桥最令人振奋的事情之一是在黄昏时分穿过街道,那时你可以看到房子里。当你在晚上穿过帕洛阿尔托时,你看到的只是电视的蓝光。在剑桥,你会看到满是看起来很有前途的书的书架。帕洛阿尔托在1960年可能很像剑桥,但现在你根本猜不到附近有一所大学。现在它只是硅谷较富裕的社区之一。[2]
This suggests an answer to a question people in New York have wondered about since the Bubble: whether New York could grow into a startup hub to rival Silicon Valley. One reason that's unlikely is that someone starting a startup in New York would feel like a second class citizen. [3] There's already something else people in New York admire more. In the long term, that could be a bad thing for New York. The power of an important new technology does eventually convert to money. So by caring more about money and less about power than Silicon Valley, New York is recognizing the same thing, but slower. [4] And in fact it has been losing to Silicon Valley at its own game: the ratio of New York to California residents in the Forbes 400 has decreased from 1.45 (81:56) when the list was first published in 1982 to .83 (73:88) in 2007. _____ Not all cities send a message. Only those that are centers for some type of ambition do. And it can be hard to tell exactly what message a city sends without living there. I understand the messages of New York, Cambridge, and Silicon Valley because I've lived for several years in each of them. DC and LA seem to send messages too, but I haven't spent long enough in either to say for sure what they are. The big thing in LA seems to be fame. There's an A List of people who are most in demand right now, and what's most admired is to be on it, or friends with those who are. Beneath that, the message is much like New York's, though perhaps with more emphasis on physical attractiveness. In DC the message seems to be that the most important thing is who you know. You want to be an insider. In practice this seems to work much as in LA. There's an A List and you want to be on it or close to those who are. The only difference is how the A List is selected. And even that is not that different. At the moment, San Francisco's message seems to be the same as Berkeley's: you should live better.
一个城市向你传递信息大多是偶然的——通过你从窗户看到的东西,你无意中听到的对话。这不是你必须去寻找的东西,而是你无法关闭的东西。住在剑桥的职业风险之一是听到人们在陈述句中使用疑问语调的对话。但平均而言,我更喜欢剑桥的对话,而不是纽约或硅谷的。
一位90年代末搬到硅谷的朋友说,住在那里最糟糕的事情是偷听的质量很低。当时我以为她是故意古怪。当然,偷听人们说话可能很有趣,但高质量的偷听如此重要,以至于会影响你选择住在哪里吗?现在我明白她的意思了。你无意中听到的对话告诉你你周围是什么样的人。
无论你多么坚定,都很难不受周围人的影响。与其说你做了城市期望你做的任何事情,不如说当你周围的人都不关心你关心的事情时,你会感到沮丧。
鼓励和沮丧之间的不平衡就像赚钱和亏钱之间的不平衡一样。大多数人高估了负面的金钱:他们会更努力地避免损失一美元,而不是赚一美元。同样,尽管有很多人足够强大,可以抵制仅仅因为那是他们所在的地方应该做的事情而去做某件事,但很少有人足够强大,能够继续做一些周围没有人关心的事情。
But this will change if enough startups choose SF over the Valley. During the Bubble that was a predictor of failure — a self-indulgent choice, like buying expensive office furniture. Even now I'm suspicious when startups choose SF. But if enough good ones do, it stops being a self-indulgent choice, because the center of gravity of Silicon Valley will shift there. I haven't found anything like Cambridge for intellectual ambition. Oxford and Cambridge (England) feel like Ithaca or Hanover: the message is there, but not as strong. Paris was once a great intellectual center. If you went there in 1300, it might have sent the message Cambridge does now. But I tried living there for a bit last year, and the ambitions of the inhabitants are not intellectual ones. The message Paris sends now is: do things with style. I liked that, actually. Paris is the only city I've lived in where people genuinely cared about art. In America only a few rich people buy original art, and even the more sophisticated ones rarely get past judging it by the brand name of the artist. But looking through windows at dusk in Paris you can see that people there actually care what paintings look like. Visually, Paris has the best eavesdropping I know. [5] There's one more message I've heard from cities: in London you can still (barely) hear the message that one should be more aristocratic. If you listen for it you can also hear it in Paris, New York, and Boston. But this message is everywhere very faint. It would have been strong 100 years ago, but now I probably wouldn't have picked it up at all if I hadn't deliberately tuned in to that wavelength to see if there was any signal left. _____ So far the complete list of messages I've picked up from cities is: wealth, style, hipness, physical attractiveness, fame, political power, economic power, intelligence, social class, and quality of life. My immediate reaction to this list is that it makes me slightly queasy.
因为抱负在某种程度上是不相容的,而钦佩是一种零和游戏,所以每个城市往往专注于一种抱负。剑桥成为知识之都的原因不仅是因为那里集中了聪明人,还因为那里的人们没有其他更关心的事情。纽约和湾区的教授是二等公民——直到他们分别开始对冲基金或初创企业。
这为泡沫以来纽约人一直疑惑的问题提供了一个答案:纽约能否发展成为与硅谷匹敌的初创企业中心。不太可能的原因之一是,在纽约创办初创企业的人会觉得自己是二等公民。[3] 纽约人已经有更钦佩的东西了。
从长远来看,这对纽约可能是一件坏事。重要新技术的权力最终会转化为金钱。因此,纽约比硅谷更关心金钱而不是权力,是在承认同样的事情,但更慢。[4] 事实上,纽约在自己的游戏中输给了硅谷:《福布斯》400强中纽约与加州居民的比例从1982年首次发布时的1.45(81:56)下降到2007年的0.83(73:88)。
并非所有城市都传递信息。只有那些作为某种抱负中心的城市才会。而且,不居住在那里,很难准确说出一个城市传递什么信息。我理解纽约、剑桥和硅谷传递的信息,因为我在每个地方都住了几年。华盛顿和洛杉矶似乎也传递信息,但我在任何一个地方都没有待足够长的时间来确切地说出它们是什么。
I'd always considered ambition a good thing, but I realize now that was because I'd always implicitly understood it to mean ambition in the areas I cared about. When you list everything ambitious people are ambitious about, it's not so pretty. On closer examination I see a couple things on the list that are surprising in the light of history. For example, physical attractiveness wouldn't have been there 100 years ago (though it might have been 2400 years ago). It has always mattered for women, but in the late twentieth century it seems to have started to matter for men as well. I'm not sure why — probably some combination of the increasing power of women, the increasing influence of actors as models, and the fact that so many people work in offices now: you can't show off by wearing clothes too fancy to wear in a factory, so you have to show off with your body instead. Hipness is another thing you wouldn't have seen on the list 100 years ago. Or wouldn't you? What it means is to know what's what. So maybe it has simply replaced the component of social class that consisted of being "au fait." That could explain why hipness seems particularly admired in London: it's version 2 of the traditional English delight in obscure codes that only insiders understand. Economic power would have been on the list 100 years ago, but what we mean by it is changing. It used to mean the control of vast human and material resources. But increasingly it means the ability to direct the course of technology, and some of the people in a position to do that are not even rich — leaders of important open source projects, for example. The Captains of Industry of times past had laboratories full of clever people cooking up new technologies for them. The new breed are themselves those people. As this force gets more attention, another is dropping off the list: social class. I think the two changes are related.
洛杉矶的大事似乎是名声。有一个A名单,列出了当下最受欢迎的人,最令人钦佩的是成为其中一员,或与那些人是朋友。除此之外,信息与纽约的非常相似,尽管可能更强调外表吸引力。
在华盛顿,信息似乎是最重要的是你认识谁。你想成为一个内部人士。在实践中,这似乎与洛杉矶非常相似。有一个A名单,你想成为其中一员或接近那些人。唯一的区别是A名单的选择方式。甚至这一点也没有那么不同。
目前,旧金山传递的信息似乎与伯克利相同:你应该生活得更好。但如果足够多的初创企业选择旧金山而不是硅谷,这种情况将会改变。在泡沫时期,这是失败的预兆——一种自我放纵的选择,就像购买昂贵的办公家具。即使现在,我对初创企业选择旧金山持怀疑态度。但如果足够多的优秀企业这样做,它就不再是一种自我放纵的选择,因为硅谷的重心将转移到那里。
我没有找到像剑桥那样对知识抱负的城市。牛津和剑桥(英国)感觉像伊萨卡或汉诺威:信息在那里,但没有那么强烈。
Economic power, wealth, and social class are just names for the same thing at different stages in its life: economic power converts to wealth, and wealth to social class. So the focus of admiration is simply shifting upstream. _____ Does anyone who wants to do great work have to live in a great city? No; all great cities inspire some sort of ambition, but they aren't the only places that do. For some kinds of work, all you need is a handful of talented colleagues. What cities provide is an audience, and a funnel for peers. These aren't so critical in something like math or physics, where no audience matters except your peers, and judging ability is sufficiently straightforward that hiring and admissions committees can do it reliably. In a field like math or physics all you need is a department with the right colleagues in it. It could be anywhere — in Los Alamos, New Mexico, for example. It's in fields like the arts or writing or technology that the larger environment matters. In these the best practitioners aren't conveniently collected in a few top university departments and research labs — partly because talent is harder to judge, and partly because people pay for these things, so one doesn't need to rely on teaching or research funding to support oneself. It's in these more chaotic fields that it helps most to be in a great city: you need the encouragement of feeling that people around you care about the kind of work you do, and since you have to find peers for yourself, you need the much larger intake mechanism of a great city. You don't have to live in a great city your whole life to benefit from it. The critical years seem to be the early and middle ones of your career. Clearly you don't have to grow up in a great city. Nor does it seem to matter if you go to college in one. To most college students a world of a few thousand people seems big enough.
巴黎曾经是一个伟大的知识中心。如果你在1300年去那里,它可能会传递现在剑桥传递的信息。但去年我在那里住了一段时间,居民的抱负并不是知识上的。巴黎现在传递的信息是:做事要有风格。实际上我喜欢这一点。巴黎是我住过的唯一一个人们真正关心艺术的城市。在美国,只有少数富人购买原创艺术,即使更老练的人也往往只根据艺术家的品牌来判断。但在巴黎黄昏时分透过窗户看,你会发现那里的人实际上关心画作的样子。在视觉上,巴黎有我见过的最好的偷听。[5]
我还从城市听到过另一个信息:在伦敦,你仍然(勉强)可以听到一个人应该更有贵族气派的信息。如果你仔细听,在巴黎、纽约和波士顿也能听到。但这个信息在任何地方都非常微弱。100年前它会很强烈,但现在如果我没有特意调到那个波长看看是否还有信号,我可能根本不会注意到它。
到目前为止,我从城市收集到的完整信息列表是:财富、风格、时髦、外表吸引力、名声、政治权力、经济权力、智力、社会阶层和生活质量。
我对这个列表的第一反应是它让我有点不舒服。我一直认为抱负是好事,但现在我意识到,那是因为我一直隐含地理解为在我关心的领域有抱负。当你列出有抱负的人所追求的一切时,就不那么美好了。
Plus in college you don't yet have to face the hardest kind of work — discovering new problems to solve. It's when you move on to the next and much harder step that it helps most to be in a place where you can find peers and encouragement. You seem to be able to leave, if you want, once you've found both. The Impressionists show the typical pattern: they were born all over France (Pissarro was born in the Carribbean) and died all over France, but what defined them were the years they spent together in Paris. _____ Unless you're sure what you want to do and where the leading center for it is, your best bet is probably to try living in several places when you're young. You can never tell what message a city sends till you live there, or even whether it still sends one. Often your information will be wrong: I tried living in Florence when I was 25, thinking it would be an art center, but it turned out I was 450 years too late. Even when a city is still a live center of ambition, you won't know for sure whether its message will resonate with you till you hear it. When I moved to New York, I was very excited at first. It's an exciting place. So it took me quite a while to realize I just wasn't like the people there. I kept searching for the Cambridge of New York. It turned out it was way, way uptown: an hour uptown by air. Some people know at 16 what sort of work they're going to do, but in most ambitious kids, ambition seems to precede anything specific to be ambitious about. They know they want to do something great. They just haven't decided yet whether they're going to be a rock star or a brain surgeon. There's nothing wrong with that. But it means if you have this most common type of ambition, you'll probably have to figure out where to live by trial and error.
仔细观察后,我发现列表中有几件事在历史的背景下令人惊讶。例如,外表吸引力在100年前不会出现在列表中(尽管2400年前可能会)。对女性来说,它一直很重要,但在20世纪末,它似乎也开始对男性重要。我不确定为什么——可能是女性权力的增加、演员作为榜样的影响力增加,以及现在这么多人在办公室工作:你不能通过穿在工厂里太花哨的衣服来炫耀,所以你只能用身体来炫耀。
时髦是100年前你不会在列表中看到的另一件事。或者你会吗?它的意思是知道什么是什么。所以也许它只是取代了社会阶层中“熟悉内情”的部分。这可以解释为什么时髦在伦敦特别受钦佩:它是传统英国人喜欢只有内部人士理解的晦涩代码的2.0版本。
经济权力100年前会在列表中,但我们对它的理解正在改变。它过去意味着控制大量的人力和物质资源。但现在越来越多地意味着指导技术进程的能力,而一些有能力这样做的人甚至并不富有——例如重要开源项目的领导者。过去的工业巨头有实验室,里面满是聪明人为他们研发新技术。新类型的人本身就是那些人。
随着这种力量受到更多关注,另一种力量正在从列表中消失:社会阶层。我认为这两个变化是相关的。经济权力、财富和社会阶层只是同一事物在不同生命阶段的名称:经济权力转化为财富,财富转化为社会阶层。所以钦佩的重点只是在上游转移。
You'll probably have to find the city where you feel at home to know what sort of ambition you have. Notes [1] This is one of the advantages of not having the universities in your country controlled by the government. When governments decide how to allocate resources, political deal-making causes things to be spread out geographically. No central goverment would put its two best universities in the same town, unless it was the capital (which would cause other problems). But scholars seem to like to cluster together as much as people in any other field, and when given the freedom to they derive the same advantages from it. [2] There are still a few old professors in Palo Alto, but one by one they die and their houses are transformed by developers into McMansions and sold to VPs of Bus Dev. [3] How many times have you read about startup founders who continued to live inexpensively as their companies took off? Who continued to dress in jeans and t-shirts, to drive the old car they had in grad school, and so on? If you did that in New York, people would treat you like shit. If you walk into a fancy restaurant in San Francisco wearing a jeans and a t-shirt, they're nice to you; who knows who you might be? Not in New York. One sign of a city's potential as a technology center is the number of restaurants that still require jackets for men. According to Zagat's there are none in San Francisco, LA, Boston, or Seattle, 4 in DC, 6 in Chicago, 8 in London, 13 in New York, and 20 in Paris. (Zagat's lists the Ritz Carlton Dining Room in SF as requiring jackets but I couldn't believe it, so I called to check and in fact they don't.
任何想做伟大工作的人都必须住在伟大的城市吗?不;所有伟大的城市都会激发某种抱负,但它们不是唯一能做到这一点的地方。对于某些工作,你只需要少数有才华的同事。
城市提供的是观众和同行的漏斗。在数学或物理等领域,这些并不那么关键,因为除了同行,没有其他观众重要,判断能力足够直接,招聘和招生委员会可以可靠地做到。在数学或物理等领域,你只需要一个有合适同事的系。它可以在任何地方——例如新墨西哥州的洛斯阿拉莫斯。
在艺术、写作或技术等领域,更大的环境才重要。在这些领域,最好的从业者并没有方便地集中在少数顶尖大学院系和研究实验室——部分原因是才能更难判断,部分原因是人们为这些东西付费,所以不需要依靠教学或研究资金来维持生计。正是在这些更混乱的领域,身处伟大城市最有帮助:你需要感受到周围人关心你所做的工作的鼓励,而且由于你必须自己找到同行,你需要伟大城市更大的吸纳机制。
你不必一生都住在伟大城市中才能从中受益。关键年份似乎是你职业生涯的早期和中期。显然你不必在伟大城市长大。在大学时是否在一个伟大城市似乎也不重要。对大多数大学生来说,一个几千人的世界似乎足够大。此外,在大学时你还不需要面对最困难的工作——发现要解决的新问题。
Apparently there's only one restaurant left on the entire West Coast that still requires jackets: The French Laundry in Napa Valley.) [4] Ideas are one step upstream from economic power, so it's conceivable that intellectual centers like Cambridge will one day have an edge over Silicon Valley like the one the Valley has over New York. This seems unlikely at the moment; if anything Boston is falling further and further behind. The only reason I even mention the possibility is that the path from ideas to startups has recently been getting smoother. It's a lot easier now for a couple of hackers with no business experience to start a startup than it was 10 years ago. If you extrapolate another 20 years, maybe the balance of power will start to shift back. I wouldn't bet on it, but I wouldn't bet against it either. [5] If Paris is where people care most about art, why is New York the center of gravity of the art business? Because in the twentieth century, art as brand split apart from art as stuff. New York is where the richest buyers are, but all they demand from art is brand, and since you can base brand on anything with a sufficiently identifiable style, you may as well use the local stuff. Thanks to Trevor Blackwell, Sarah Harlin, Jessica Livingston, Jackie McDonough, Robert Morris, and David Sloo for reading drafts of this.
Italian Translation | Portuguese Translation Chinese Translation | Korean Translation.
当你进入下一个更困难的步骤时,身处一个可以找到同行和鼓励的地方最有帮助。一旦你找到了这两者,你似乎可以离开,如果你想的话。印象派展示了典型的模式:他们出生在法国各地(毕沙罗出生在加勒比),死在法国各地,但定义他们的是他们在巴黎一起度过的岁月。
除非你确定你想做什么以及它的领先中心在哪里,否则你最好的选择可能是在年轻时尝试住在几个地方。你永远无法知道一个城市传递什么信息,直到你住在那里,甚至不知道它是否还在传递信息。通常你的信息会是错误的:我25岁时尝试住在佛罗伦萨,以为它会是一个艺术中心,但结果我晚了450年。
即使一个城市仍然是一个活跃的抱负中心,你也不会确切知道它的信息是否会引起你的共鸣,直到你听到它。当我搬到纽约时,一开始我非常兴奋。那是一个令人兴奋的地方。所以我花了很长时间才意识到我不像那里的人。我一直在寻找纽约的剑桥。结果它很远,很远的上城:乘飞机一小时的上城。
有些人在16岁时就知道他们要做什么样的工作,但在大多数有抱负的孩子中,抱负似乎先于任何具体的抱负目标。他们知道自己想做些伟大的事情。只是还没有决定是成为摇滚明星还是脑外科医生。这没什么错。但这意味着如果你有这种最常见的抱负类型,你可能需要通过试错来弄清楚住在哪里。你可能需要找到让你感到宾至如归的城市,才能知道你有什么样的抱负。
_Note: The strategy described at the end of this essay didn't work. It would work for a while, and then I'd gradually find myself using the Internet on my work computer. I'm trying other strategies now, but I think this time I'll wait till I'm sure they work before writing about them._ May 2008 Procrastination feeds on distractions. Most people find it uncomfortable just to sit and do nothing; you avoid work by doing something else. So one way to beat procrastination is to starve it of distractions. But that's not as straightforward as it sounds, because there are people working hard to distract you. Distraction is not a static obstacle that you avoid like you might avoid a rock in the road. Distraction seeks you out. Chesterfield described dirt as matter out of place. Distracting is, similarly, desirable at the wrong time. And technology is continually being refined to produce more and more desirable things. Which means that as we learn to avoid one class of distractions, new ones constantly appear, like drug-resistant bacteria. Television, for example, has after 50 years of refinement reached the point where it's like visual crack. I realized when I was 13 that TV was addictive, so I stopped watching it. But I read recently that the average American watches 4 hours of TV a day. A quarter of their life. TV is in decline now, but only because people have found even more addictive ways of wasting time. And what's especially dangerous is that many happen at your computer. This is no accident. An ever larger percentage of office workers sit in front of computers connected to the Internet, and distractions always evolve toward the procrastinators. I remember when computers were, for me at least, exclusively for work. I might occasionally dial up a server to get mail or ftp files, but most of the time I was offline. All I could do was write and program.
Now I feel as if someone snuck a television onto my desk. Terribly addictive things are just a click away. Run into an obstacle in what you're working on? Hmm, I wonder what's new online. Better check. After years of carefully avoiding classic time sinks like TV, games, and Usenet, I still managed to fall prey to distraction, because I didn't realize that it evolves. Something that used to be safe, using the Internet, gradually became more and more dangerous. Some days I'd wake up, get a cup of tea and check the news, then check email, then check the news again, then answer a few emails, then suddenly notice it was almost lunchtime and I hadn't gotten any real work done. And this started to happen more and more often. It took me surprisingly long to realize how distracting the Internet had become, because the problem was intermittent. I ignored it the way you let yourself ignore a bug that only appears intermittently. When I was in the middle of a project, distractions weren't really a problem. It was when I'd finished one project and was deciding what to do next that they always bit me. Another reason it was hard to notice the danger of this new type of distraction was that social customs hadn't yet caught up with it. If I'd spent a whole morning sitting on a sofa watching TV, I'd have noticed very quickly. That's a known danger sign, like drinking alone. But using the Internet still looked and felt a lot like work. Eventually, though, it became clear that the Internet had become so much more distracting that I had to start treating it differently. Basically, I had to add a new application to my list of known time sinks: Firefox.
The problem is a hard one to solve because most people still need the Internet for some things. If you drink too much, you can solve that problem by stopping entirely. But you can't solve the problem of overeating by stopping eating.
I couldn't simply avoid the Internet entirely, as I'd done with previous time sinks. At first I tried rules. For example, I'd tell myself I was only going to use the Internet twice a day. But these schemes never worked for long. Eventually something would come up that required me to use it more than that. And then I'd gradually slip back into my old ways. Addictive things have to be treated as if they were sentient adversaries—as if there were a little man in your head always cooking up the most plausible arguments for doing whatever you're trying to stop doing. If you leave a path to it, he'll find it. The key seems to be visibility. The biggest ingredient in most bad habits is denial. So you have to make it so that you can't merely _slip_ into doing the thing you're trying to avoid. It has to set off alarms. Maybe in the long term the right answer for dealing with Internet distractions will be software that watches and controls them. But in the meantime I've found a more drastic solution that definitely works: to set up a separate computer for using the Internet. I now leave wifi turned off on my main computer except when I need to transfer a file or edit a web page, and I have a separate laptop on the other side of the room that I use to check mail or browse the web. (Irony of ironies, it's the computer Steve Huffman wrote Reddit on. When Steve and Alexis auctioned off their old laptops for charity, I bought them for the Y Combinator museum.) My rule is that I can spend as much time online as I want, as long as I do it on that computer. And this turns out to be enough. When I have to sit on the other side of the room to check email or browse the web, I become much more aware of it. Sufficiently aware, in my case at least, that it's hard to spend more than about an hour a day online. And my main computer is now freed for work.
If you try this trick, you'll probably be struck by how different it feels when your computer is disconnected from the Internet. It was alarming to me how foreign it felt to sit in front of a computer that could only be used for work, because that showed how much time I must have been wasting. _Wow. All I can do at this computer is work. Ok, I better work then._ That's the good part. Your old bad habits now help you to work. You're used to sitting in front of that computer for hours at a time. But you can't browse the web or check email now. What are you going to do? You can't just sit there. So you start working.
Good and Bad Procrastination | Spanish Translation Arabic Translation | Catalan Translation Russian Translation | Spanish Translation.
_注:本文末尾描述的策略并未奏效。它只能暂时起效,之后我会逐渐发现自己又在工作电脑上使用互联网。目前我正在尝试其他策略,但这次我想等确认它们有效后再行文分享。_ 2008年5月 拖延症靠分心事物滋养。大多数人光是坐着无所事事就会感到不适;你通过做其他事来逃避工作。 因此战胜拖延症的一种方法,就是切断分心事物的供给。但这并不像听起来那么简单,因为有人正千方百计地分散你的注意力。分心事物并非像躲避路上石块那样可以绕开的静态障碍,它会主动找上你。 切斯特菲尔德将污垢定义为错位的物质。分心事物同样是在错误时间出现的诱人之物。而科技正在不断精进,制造出越来越多令人渴望的东西。这意味着当我们学会避开一类分心事物时,新的分心物会不断涌现,就像耐药菌株。 例如电视经过50年的进化,已臻至视觉可卡因的境界。我13岁时就意识到电视具有成瘾性,于是戒了它。但最近我读到美国人平均每天看4小时电视——他们生命的四分之一。 如今电视正在式微,但这只是因为人们找到了更让人上瘾的消遣方式。尤其危险的是,许多诱惑就发生在你的电脑上。这并非偶然。越来越多上班族整天坐在联网的电脑前,而分心事物永远朝着拖延者的方向进化。 记得电脑曾是我(至少对我而言)纯粹的工作工具。我偶尔会拨号登录服务器查收邮件或传输文件,但大部分时间处于离线状态。我能做的只有写作和编程。如今我感觉像是有人偷偷在我桌上放了台电视——令人极度上瘾的东西只需点击即得。工作中遇到障碍?嗯,不知道网上有什么新鲜事,得看看。 多年来我小心避开了电视、游戏和新闻组等经典时间陷阱,却仍沦为分心事物的猎物,因为我没意识到它会进化。曾经安全的互联网使用行为,逐渐变得危机四伏。有些日子我醒来后,泡杯茶看新闻,查邮件,再看新闻,回几封邮件,突然发现已近午时,正经工作却毫无进展。这种情况愈发频繁。 我花了惊人长的时间才意识到互联网的干扰性,因为这个问题是间歇性的。就像你会忽略偶尔出现的程序错误那样,我放任自己忽视它。当沉浸于项目时,分心并非真正的问题。总是在完成一个项目、思考下一步时,它们才会咬住我。 这种新型分心危害难以察觉的另一个原因,是社会规范尚未跟上其发展。若我整个上午坐在沙发上看电视,我会立即警觉——那就像独自饮酒一样是危险信号。但使用互联网看起来仍很像工作。 然而最终,互联网的干扰性已明显到必须区别对待。本质上,我不得不在已知时间陷阱清单中添加新条目:火狐浏览器。
这个难题的棘手之处在于,多数人仍需互联网处理某些事务。饮酒过量可以彻底戒除,但无法通过绝食解决暴食问题。我不能像对待其他时间陷阱那样完全避开互联网。 起初我尝试制定规则,比如规定自己每天只上网两次。但这些计划从未长期有效,总会出现需要更多次使用的情况,之后我便逐渐故态复萌。 成瘾物必须被当作有知觉的对手来对待——仿佛你脑中住着个小人,不断为你想戒除的行为编造最合理的借口。只要你留有余地,他就会找到突破口。 关键在于可视化。多数恶习的最大成分是自我欺骗。因此你必须确保自己无法悄然滑向试图避免的行为,必须触发警报。 长远来看,应对网络干扰的答案或许是监控软件。但眼下我找到了绝对有效的更彻底方案:配置专用上网电脑。 如今我的主电脑常闭无线网络,仅在传输文件或编辑网页时开启。房间另一头放着专用笔记本来查邮件和浏览网页(极具讽刺的是,这台电脑正是史蒂夫·霍夫曼编写Reddit时用的。当史蒂夫和亚历克西斯为慈善拍卖旧笔记本时,我买下它们作为Y Combinator博物馆藏品)。 我的规则是:只要在那台电脑上操作,上网时间不限。事实证明这已足够。当必须坐在房间另一端查邮件或浏览时,我会更清醒地意识到自己在做什么。至少对我而言,这种清醒足以将每日上网时间控制在一小时左右。 而我的主电脑现在专用于工作。若你尝试此法,可能会震惊于断网电脑带来的截然不同的感受。面对只能用于工作的电脑时,那种陌生感令我警醒——这说明我此前浪费了多少时间。 _哇,这台电脑只能工作。好吧,那还是工作吧。_ 这就是妙处。你原有的坏习惯现在助推工作。你已习惯在那台电脑前一坐数小时,但现在无法浏览网页或查邮件。你能怎么办?总不能干坐着。于是你开始工作。
May 2008 Adults lie constantly to kids. I'm not saying we should stop, but I think we should at least examine which lies we tell and why. There may also be a benefit to us. We were all lied to as kids, and some of the lies we were told still affect us. So by studying the ways adults lie to kids, we may be able to clear our heads of lies we were told. I'm using the word "lie" in a very general sense: not just overt falsehoods, but also all the more subtle ways we mislead kids. Though "lie" has negative connotations, I don't mean to suggest we should never do this—just that we should pay attention when we do. [1] One of the most remarkable things about the way we lie to kids is how broad the conspiracy is. All adults know what their culture lies to kids about: they're the questions you answer "Ask your parents." If a kid asked who won the World Series in 1982 or what the atomic weight of carbon was, you could just tell him. But if a kid asks you "Is there a God?" or "What's a prostitute?" you'll probably say "Ask your parents." Since we all agree, kids see few cracks in the view of the world presented to them. The biggest disagreements are between parents and schools, but even those are small. Schools are careful what they say about controversial topics, and if they do contradict what parents want their kids to believe, parents either pressure the school into keeping quiet or move their kids to a new school. The conspiracy is so thorough that most kids who discover it do so only by discovering internal contradictions in what they're told. It can be traumatic for the ones who wake up during the operation. Here's what happened to Einstein: > Through the reading of popular scientific books I soon reached the conviction that much in the stories of the Bible could not be true.
2008年5月 成年人总在对孩子说谎。我并非主张停止说谎,但认为至少该审视我们说了哪些谎言及其缘由。 这番审视或许对我们也有裨益。童年时我们都曾被谎言包围,其中某些至今仍在影响我们。通过研究成人欺骗孩子的方式,我们或许能清除那些盘踞在脑海中的谎言。 此处"谎言"取广义:不仅包括赤裸裸的虚假陈述,更涵盖我们误导孩童的所有微妙手段。尽管"谎言"带有负面色彩,但并非全盘否定这种行为——只是强调实施时应当保持清醒。[1] 成人谎言体系最惊人的特征是其共谋的广泛性。所有大人都心照不宣地知晓本文化对孩子的欺瞒内容:那些你回答"去问你父母"的问题。若孩子问"1982年世界大赛谁赢了"或"碳的原子量是多少",你会直接告知。但当他们问"上帝存在吗"或"妓女是什么",你多半会说"去问你父母"。 由于这种默契,孩子很少能窥见成人世界观的裂缝。最大的分歧存在于家庭与学校之间,但即便这些分歧也很有限。学校对争议话题谨言慎行,若其说辞与家长期望相悖,家长要么施压校方保持沉默,要么让孩子转学。 这个共谋体系如此严密,以致多数孩子只有发现被告知的内容自相矛盾时才会察觉其存在。对在"手术"中途醒来的孩子,这种觉醒可能造成创伤。爱因斯坦的经历便是例证: > 通过阅读科普书籍,我很快确信圣经故事多有虚妄。由此产生的狂热自由思想,伴随着"国家正用谎言蓄意欺骗青年"的认知,给我留下了毁灭性的印象。[2]
我记得那种感受。15岁时,我深信整个世界从里到外都腐烂透了。这正是《黑客帝国》这类电影能引发强烈共鸣的原因——每个孩子都成长在一个虚假的世界里。某种程度上,若幕后黑手能像邪恶机器军团那样界限分明,只需吞下一粒药丸就能彻底挣脱,事情反而简单得多。
保护伞 当被问及为何对孩子说谎时,成年人最常给出的理由就是"保护"。孩子确实需要保护。为新生儿营造的环境,本就应该与大都市的街道截然不同。
这个理由如此理所当然,甚至称不上谎言。让婴儿认为世界安静、温暖而安全绝非恶意的欺骗。但若不加审视,这类善意的谎言也可能变质。
The consequence was a positively fanatic freethinking coupled with the impression that youth is intentionally being deceived by the state through lies: it was a crushing impression. [2].
试想若将某人像新生儿般过度保护直至18岁。如此严重地扭曲其对世界的认知,这已非保护而是虐待。当然这是极端案例——现实中若有父母这般行事必成全国新闻。但郊区青少年普遍存在的迷茫情绪,正是同一问题的温和呈现。
郊区存在的核心意义就是为孩子提供受保护的成长环境。对十岁孩童而言,这堪称完美。我十岁时也热爱郊区生活,丝毫察觉不到其 sterilized(消毒过般)的本质。我的整个世界不过是用自行车丈量的几处朋友家宅,以及奔跑嬉戏的小树林。用对数尺度衡量,我正处在婴儿床与地球之间的中点,郊区街道的尺寸恰如其分。但随着年岁增长,郊区开始令人窒息地虚假。
人生在十岁或二十岁都可能很美好,但十五岁往往充满挫败感。这个问题过于庞大难以在此解决,但青春期痛苦的根源之一,正是孩子们被困在为十岁儿童设计的世界里。
父母希望通过郊区生活保护孩子免受什么?一位搬离曼哈顿的朋友只说其三岁女儿"见识太多"。粗略列举可能包括:瘾君子与醉汉、贫困、精神失常、骇人病症、各种怪异性行为,以及暴力怒火。
I remember that feeling. By 15 I was convinced the world was corrupt from end to end. That's why movies like _The Matrix_ have such resonance. Every kid grows up in a fake world. In a way it would be easier if the forces behind it were as clearly differentiated as a bunch of evil machines, and one could make a clean break just by taking a pill. Protection If you ask adults why they lie to kids, the most common reason they give is to protect them. And kids do need protecting. The environment you want to create for a newborn child will be quite unlike the streets of a big city. That seems so obvious it seems wrong to call it a lie. It's certainly not a bad lie to tell, to give a baby the impression the world is quiet and warm and safe. But this harmless type of lie can turn sour if left unexamined. Imagine if you tried to keep someone in as protected an environment as a newborn till age 18. To mislead someone so grossly about the world would seem not protection but abuse. That's an extreme example, of course; when parents do that sort of thing it becomes national news. But you see the same problem on a smaller scale in the malaise teenagers feel in suburbia. The main purpose of suburbia is to provide a protected environment for children to grow up in. And it seems great for 10 year olds. I liked living in suburbia when I was 10. I didn't notice how sterile it was. My whole world was no bigger than a few friends' houses I bicycled to and some woods I ran around in. On a log scale I was midway between crib and globe. A suburban street was just the right size. But as I grew older, suburbia started to feel suffocatingly fake. Life can be pretty good at 10 or 20, but it's often frustrating at 15\. This is too big a problem to solve here, but certainly one reason life sucks at 15 is that kids are trapped in a world designed for 10 year olds.
若我有三岁幼童,最令我忧心的当属街头怒火。我29岁初到纽约时仍感震惊,更不愿幼儿目睹那些激烈冲突。许多成人向幼童隐瞒的真相,并非意图掩盖事实存在,纯粹因其过于骇人——误导只是附带效应。
这似乎是成人对孩子最正当的谎言类型。但因这种欺骗是间接的,我们对其缺乏严格把控。父母清楚自己隐瞒了性知识,多数会在适当时机进行解释。但极少有家长会向孩子剖析真实世界与成长温室的差异。再加上父母竭力灌输的自信,每年都会涌现大批自以为深谙世事的18岁青年。
难道不是所有18岁青年都自认通晓治国之道?其实这是近百年才出现的现象。前工业时代,青少年是成人世界的初级成员,对自身不足有清醒认知——他们能直观感受到自己不如铁匠强壮灵巧。古人在某些方面对孩子撒谎更甚,但人造保护伞式的系统性欺骗却是现代发明。如同许多新事物,权贵最先享用——王侯将相的子女最早体验与世隔绝的成长。郊区化让半数人口都能享受这种"贵族待遇"。
性与毒 若在纽约养育青少年,我的忧虑会有所不同:更担忧其行为而非见闻。我的大学同学中有许多曼哈顿长大的孩子,他们普遍显得世故老成——平均14岁失去童贞,大学时尝试过的毒品比我听过的还多。
What do parents hope to protect their children from by raising them in suburbia? A friend who moved out of Manhattan said merely that her 3 year old daughter "saw too much." Off the top of my head, that might include: people who are high or drunk, poverty, madness, gruesome medical conditions, sexual behavior of various degrees of oddness, and violent anger. I think it's the anger that would worry me most if I had a 3 year old. I was 29 when I moved to New York and I was surprised even then. I wouldn't want a 3 year old to see some of the disputes I saw. It would be too frightening. A lot of the things adults conceal from smaller children, they conceal because they'd be frightening, not because they want to conceal the existence of such things. Misleading the child is just a byproduct. This seems one of the most justifiable types of lying adults do to kids. But because the lies are indirect we don't keep a very strict accounting of them. Parents know they've concealed the facts about sex, and many at some point sit their kids down and explain more. But few tell their kids about the differences between the real world and the cocoon they grew up in. Combine this with the confidence parents try to instill in their kids, and every year you get a new crop of 18 year olds who think they know how to run the world. Don't all 18 year olds think they know how to run the world? Actually this seems to be a recent innovation, no more than about 100 years old. In preindustrial times teenage kids were junior members of the adult world and comparatively well aware of their shortcomings. They could see they weren't as strong or skillful as the village smith. In past times people lied to kids about some things more than we do now, but the lies implicit in an artificial, protected environment are a recent invention. Like a lot of new inventions, the rich got this first. Children of kings and great magnates were the first to grow up out of touch with the world.
父母反对青少年发生性关系的原因很复杂。怀孕与性病是显性风险,但即便零风险,多数14岁少女的父母仍会强烈反对。
孩子能敏锐察觉大人未言明真相——毕竟怀孕与性病对成人同样存在,而成人照样发生关系。
真正令父母不安的是什么?这种厌恶感如此本能,很可能是与生俱来的。但若属先天就该具有普适性,而许多社会对青少年性行为毫不介意——14岁当母亲甚至成为常态。根源何在?对未发育儿童实施性行为确属全球禁忌(进化角度不难理解),我认为工业化社会的父母正是因此反对青少年性行为——他们仍视其为儿童(尽管生理上已非如此),故儿童性禁忌仍在生效。
成人在毒品话题上同样隐瞒了关键事实:它能带来极致快感。正是这点使性与毒品极度危险——对其渴望会蒙蔽判断力,而当判断主体本就是青少年糟糕的决策系统时尤为可怕。
在此父母的期望相互矛盾:传统社会直言孩子缺乏判断力,现代父母却希望子女充满自信。这或许比旧式打压更进步,但副作用是——当孩子真相信我们对其判断力的虚假赞美后,我们又不得不再编织谎言来防止他们惹祸上身。
Suburbia means half the population can live like kings in that respect. Sex (and Drugs) I'd have different worries about raising teenage kids in New York. I'd worry less about what they'd see, and more about what they'd do. I went to college with a lot of kids who grew up in Manhattan, and as a rule they seemed pretty jaded. They seemed to have lost their virginity at an average of about 14 and by college had tried more drugs than I'd even heard of. The reasons parents don't want their teenage kids having sex are complex. There are some obvious dangers: pregnancy and sexually transmitted diseases. But those aren't the only reasons parents don't want their kids having sex. The average parents of a 14 year old girl would hate the idea of her having sex even if there were zero risk of pregnancy or sexually transmitted diseases. Kids can probably sense they aren't being told the whole story. After all, pregnancy and sexually transmitted diseases are just as much a problem for adults, and they have sex. What really bothers parents about their teenage kids having sex? Their dislike of the idea is so visceral it's probably inborn. But if it's inborn it should be universal, and there are plenty of societies where parents don't mind if their teenage kids have sex—indeed, where it's normal for 14 year olds to become mothers. So what's going on? There does seem to be a universal taboo against sex with prepubescent children. One can imagine evolutionary reasons for that. And I think this is the main reason parents in industrialized societies dislike teenage kids having sex. They still think of them as children, even though biologically they're not, so the taboo against child sex still has force. One thing adults conceal about sex they also conceal about drugs: that it can cause great pleasure. That's what makes sex and drugs so dangerous.
若诚实以告,真相应是:"你该远离这些,因为你的判断力太差。即便经验两倍于你的人仍会栽跟头。"但这类真相往往缺乏说服力——因为判断力差的症状之一,正是自认判断力超群。你提不起重物时能明确感知,但冲动决策时却格外自信。
纯真 父母反对青少年性行为的另一动机是保持其纯真。成人对儿童行为有套特殊标准,与其他成年人的期待截然不同。
最显著的差异体现在用语规范。多数成人与同伴交流时会使用自己禁止孩子说的词汇,他们尽可能延长孩子对这些词汇的无知状态。这是场全民共谋的骗局——所有人都知道不该在孩子面前说脏话。
关于禁止说脏话的理由,我听过最多版本的解释。每个家长都禁止孩子说脏话,但他们的理由各不相同。显然多数人先有禁令再编理由。
The desire for them can cloud one's judgement—which is especially frightening when the judgement being clouded is the already wretched judgement of a teenage kid. Here parents' desires conflict. Older societies told kids they had bad judgement, but modern parents want their children to be confident. This may well be a better plan than the old one of putting them in their place, but it has the side effect that after having implicitly lied to kids about how good their judgement is, we then have to lie again about all the things they might get into trouble with if they believed us. If parents told their kids the truth about sex and drugs, it would be: the reason you should avoid these things is that you have lousy judgement. People with twice your experience still get burned by them. But this may be one of those cases where the truth wouldn't be convincing, because one of the symptoms of bad judgement is believing you have good judgement. When you're too weak to lift something, you can tell, but when you're making a decision impetuously, you're all the more sure of it. Innocence Another reason parents don't want their kids having sex is that they want to keep them innocent. Adults have a certain model of how kids are supposed to behave, and it's different from what they expect of other adults. One of the most obvious differences is the words kids are allowed to use. Most parents use words when talking to other adults that they wouldn't want their kids using. They try to hide even the existence of these words for as long as they can. And this is another of those conspiracies everyone participates in: everyone knows you're not supposed to swear in front of kids. I've never heard more different explanations for anything parents tell kids than why they shouldn't swear. Every parent I know forbids their children to swear, and yet no two of them have the same justification.
我的理论是:脏话的功能是标识说话者为成年人。"屎"和"便便"含义无差,为何前者被禁?唯一解释就是人为定义。
为何成人如此介意孩子模仿成人行为?想象一个满嘴脏话、叼着烟卷倚靠路灯的十岁愤世孩童,这画面令人极度不适。但为什么?
保持孩童纯真的动机之一,是我们天生偏爱某种无助感。我多次听母亲们说故意不纠正幼儿的错误发音,只因"太可爱了"。细想便知,可爱本质就是无助——玩具和卡通角色要显得可爱,总配着懵懂表情和短小无用的四肢。
考虑到人类幼崽漫长的脆弱期,我们天生具有保护欲并不奇怪。若孩童失去这种制造可爱的无助感,他们会显得像能力不足的成年人般惹人厌烦。但更深层的原因是:那个假想的世故十岁童令人不安,不仅因其讨厌,更因其过早扼杀了成长可能——要变得世故,必先自认通晓世事,而十岁孩童的世界观注定狭隘。
It's clear most start with not wanting kids to swear, then make up the reason afterward. So my theory about what's going on is that the _function_ of swearwords is to mark the speaker as an adult. There's no difference in the meaning of "shit" and "poopoo." So why should one be ok for kids to say and one forbidden? The only explanation is: by definition. [3] Why does it bother adults so much when kids do things reserved for adults? The idea of a foul-mouthed, cynical 10 year old leaning against a lamppost with a cigarette hanging out of the corner of his mouth is very disconcerting. But why? One reason we want kids to be innocent is that we're programmed to like certain kinds of helplessness. I've several times heard mothers say they deliberately refrained from correcting their young children's mispronunciations because they were so cute. And if you think about it, cuteness is helplessness. Toys and cartoon characters meant to be cute always have clueless expressions and stubby, ineffectual limbs. It's not surprising we'd have an inborn desire to love and protect helpless creatures, considering human offspring are so helpless for so long. Without the helplessness that makes kids cute, they'd be very annoying. They'd merely seem like incompetent adults. But there's more to it than that. The reason our hypothetical jaded 10 year old bothers me so much is not just that he'd be annoying, but that he'd have cut off his prospects for growth so early. To be jaded you have to think you know how the world works, and any theory a 10 year old had about that would probably be a pretty narrow one. Innocence is also open-mindedness. We want kids to be innocent so they can continue to learn. Paradoxical as it sounds, there are some kinds of knowledge that get in the way of other kinds of knowledge. If you're going to learn that the world is a brutal place full of people trying to take advantage of one another, you're better off learning it last.
纯真也意味着开放心态。我们希望孩子保持纯真以便持续学习。有些知识会阻碍其他知识的获取——若你过早知晓世界充满相互倾轧的残酷真相,很可能就此停止探索。
超高智商成人往往显得异常纯真,这非巧合。我认为他们是刻意回避某些认知。至少我是如此——曾以为渴望知晓一切,如今明白并非如此。
死亡 除性之外,成人对儿童最明目张胆的谎言关乎死亡。隐瞒性话题源于深层禁忌,但为何隐瞒死亡?或许因幼儿对此特别恐惧——他们渴望安全感,而死亡是终极威胁。
父母最夸张的谎言是关于我们第一只猫的死亡。多年追问下,他们不断补充细节,最终编织出精密故事:猫咪死于兽医诊所的麻醉事故。为何就诊?绝育手术。常规手术为何致死?先天性心脏缺陷,但事先无从知晓。直到我们二十多岁,真相才浮出水面:当时三岁的妹妹意外踩断猫的脊柱。
他们没觉得需要编造猫咪去了天堂。我父母从不宣称逝者"去了更好的地方"或"将会重逢",这似乎并未对我们造成伤害。
Otherwise you won't bother learning much more. Very smart adults often seem unusually innocent, and I don't think this is a coincidence. I think they've deliberately avoided learning about certain things. Certainly I do. I used to think I wanted to know everything. Now I know I don't. Death After sex, death is the topic adults lie most conspicuously about to kids. Sex I believe they conceal because of deep taboos. But why do we conceal death from kids? Probably because small children are particularly horrified by it. They want to feel safe, and death is the ultimate threat. One of the most spectacular lies our parents told us was about the death of our first cat. Over the years, as we asked for more details, they were compelled to invent more, so the story grew quite elaborate. The cat had died at the vet's office. Of what? Of the anaesthesia itself. Why was the cat at the vet's office? To be fixed. And why had such a routine operation killed it? It wasn't the vet's fault; the cat had a congenitally weak heart; the anaesthesia was too much for it; but there was no way anyone could have known this in advance. It was not till we were in our twenties that the truth came out: my sister, then about three, had accidentally stepped on the cat and broken its back. They didn't feel the need to tell us the cat was now happily in cat heaven. My parents never claimed that people or animals who died had "gone to a better place," or that we'd meet them again. It didn't seem to harm us. My grandmother told us an edited version of the death of my grandfather. She said they'd been sitting reading one day, and when she said something to him, he didn't answer. He seemed to be asleep, but when she tried to rouse him, she couldn't. "He was gone." Having a heart attack sounded like falling asleep. Later I learned it hadn't been so neat, and the heart attack had taken most of a day to kill him.
祖母讲述祖父去世时也经过剪辑:某日共读时,她发现祖父看似入睡却无法唤醒——"他走了"。听起来心脏病发作如同安眠。后来我才知实情没那么平静,他挣扎了近一天才离世。
除直接谎言外,更多是通过转移话题回避死亡。我直到19岁才真正意识到自己终将死亡——如此明显的事实为何迟悟?观察现代父母应对方式便知端倪:关于死亡的提问总被温柔而坚定地回避。
在这个话题上,孩子常是共谋。他们渴望被欺骗,正如父母渴望维持其安全感。
身份认同 某些父母强烈认同特定族群或宗教,并希望子女继承。这通常需要双重谎言:首先告知孩子"你是X",其次是X群体赖以区分的特定虚构。[5]
Along with such outright lies, there must have been a lot of changing the subject when death came up. I can't remember that, of course, but I can infer it from the fact that I didn't really grasp I was going to die till I was about 19. How could I have missed something so obvious for so long? Now that I've seen parents managing the subject, I can see how: questions about death are gently but firmly turned aside. On this topic, especially, they're met half-way by kids. Kids often want to be lied to. They want to believe they're living in a comfortable, safe world as much as their parents want them to believe it. [4] Identity Some parents feel a strong adherence to an ethnic or religious group and want their kids to feel it too. This usually requires two different kinds of lying: the first is to tell the child that he or she is an X, and the second is whatever specific lies Xes differentiate themselves by believing. [5] Telling a child they have a particular ethnic or religious identity is one of the stickiest things you can tell them. Almost anything else you tell a kid, they can change their mind about later when they start to think for themselves. But if you tell a kid they're a member of a certain group, that seems nearly impossible to shake. This despite the fact that it can be one of the most premeditated lies parents tell. When parents are of different religions, they'll often agree between themselves that their children will be "raised as Xes." And it works. The kids obligingly grow up considering themselves as Xes, despite the fact that if their parents had chosen the other way, they'd have grown up considering themselves as Ys. One reason this works so well is the second kind of lie involved. The truth is common property. You can't distinguish your group by doing things that are rational, and believing things that are true.
灌输族群或宗教身份是最难破除的认知植入。孩子长大后能自我修正绝大多数认知,唯独群体身份认同几乎无法摆脱。
尽管这可能是最处心积虑的谎言。当父母信仰不同时,常协商决定"按X方式养育"。结果孩子果然自认X群体成员——即便当初若选择Y方式,他们同样会笃信自己属于Y。
这种机制高效运转的秘诀在于第二重谎言。真相具有普世性——无法通过理性行为或真实信仰来区分群体。要标新立异,必须依靠武断的行为准则和虚假的信条。当孩子终生践行武断习俗、信奉虚妄教条,并因此被"外人"视为异类时,迫使其认同X身份的认知失调必然极其强烈:若非X,为何执着于这些荒诞习俗?若非X,为何所有非X者都如此指认?
这类谎言并非全无价值。可借此植入有益信念使其成为身份核心——比如在"禁止穿黄色""相信世界由巨兔创造""吃鱼前必须打响指"等荒诞戒律之外,加入"X族特别诚实勤勉",X族孩童便会将诚信勤奋视为身份特质。
If you want to set yourself apart from other people, you have to do things that are arbitrary, and believe things that are false. And after having spent their whole lives doing things that are arbitrary and believing things that are false, and being regarded as odd by "outsiders" on that account, the cognitive dissonance pushing children to regard themselves as Xes must be enormous. If they aren't an X, why are they attached to all these arbitrary beliefs and customs? If they aren't an X, why do all the non-Xes call them one? This form of lie is not without its uses. You can use it to carry a payload of beneficial beliefs, and they will also become part of the child's identity. You can tell the child that in addition to never wearing the color yellow, believing the world was created by a giant rabbit, and always snapping their fingers before eating fish, Xes are also particularly honest and industrious. Then X children will grow up feeling it's part of their identity to be honest and industrious. This probably accounts for a lot of the spread of modern religions, and explains why their doctrines are a combination of the useful and the bizarre. The bizarre half is what makes the religion stick, and the useful half is the payload. [6] Authority One of the least excusable reasons adults lie to kids is to maintain power over them. Sometimes these lies are truly sinister, like a child molester telling his victims they'll get in trouble if they tell anyone what happened to them. Others seem more innocent; it depends how badly adults lie to maintain their power, and what they use it for. Most adults make some effort to conceal their flaws from children. Usually their motives are mixed. For example, a father who has an affair generally conceals it from his children.
这很可能是现代宗教传播的重要机制,也解释了为何其教义总混杂实用与怪诞——怪诞部分确保信仰黏性,实用部分才是真正价值。[6]
权威 成人最不可原谅的谎言,是为维持权威而欺骗。有些极其恶毒(如性侵者威胁受害者保密),有些看似无害——其性质取决于谎言程度与动机。
多数成人会向孩子掩饰自身缺陷,通常动机复杂。例如出轨的父亲向子女隐瞒,部分因担忧孩子,部分因回避性话题,更大比例(虽不愿承认)是不想损害自身形象。
想了解成人编织的谎言,只需翻阅任何儿童"教育"读物[7]。彼得·梅尔在《为什么要离婚?》开篇列出三大离婚要点,其中包括:
你不应该把责任归咎于父母中的一方,因为离婚从来不是一个人的错。[8]
His motive is partly that it would worry them, partly that this would introduce the topic of sex, and partly (a larger part than he would admit) that he doesn't want to tarnish himself in their eyes. If you want to learn what lies are told to kids, read almost any book written to teach them about "issues." [7] Peter Mayle wrote one called _Why Are We Getting a Divorce?_ It begins with the three most important things to remember about divorce, one of which is:.
真的吗?当一个男人和他的秘书私奔时,这总是部分归咎于他的妻子吗?但我能理解梅尔为何会这样说。也许对孩子来说,尊重父母比了解父母的真相更重要。
然而,由于成年人隐藏自己的缺点,同时又要求孩子行为端正,许多孩子在成长过程中感到自己永远无法达标。他们会因为说了一句脏话而觉得自己邪恶透顶,而实际上他们周围的成年人大多在做更糟糕的事。
这种情况不仅出现在道德问题上,也出现在智力问题上。越自信的人越愿意回答“我不知道”,而不那么自信的人则觉得必须给出答案,否则会显得无能。我的父母在承认自己不知道的事情上做得不错,但我一定从老师那里听到了许多这类谎言,因为直到上大学,我才很少听到老师说“我不知道”。我记得这一点,因为在全班面前听到有人这样说实在太令人惊讶了。
我第一次意识到老师并非全知全能是在六年级,当时我父亲反驳了我在学校学到的东西。当我抗议说老师说的是相反的,我父亲回答说那家伙根本不知道自己在说什么——毕竟他只是个小学老师。
> You shouldn't put the blame on one parent, because divorce is never only one person's fault. [8]
“只是”个老师?这个短语在语法上几乎显得不合逻辑。难道老师对他们教授的科目不是无所不知吗?如果不是,为什么是他们来教我们?
可悲的事实是,美国公立学校的教师通常对他们所教的内容理解得并不透彻。虽然有一些杰出的例外,但总体而言,打算从事教育行业的人在学术上排名接近大学群体的末尾。因此,我在11岁时仍然认为老师是绝对正确的,这表明这个系统对我的大脑造成了多大的影响。
孩子们在学校学到的东西是谎言与真相的复杂混合体。最可原谅的是那些为了简化概念以便学习的谎言。问题在于,许多宣传以简化的名义悄悄进入了课程。
公立学校的教科书代表了各种强势群体希望孩子们被告知的内容之间的妥协。这些谎言很少是公开的,通常表现为遗漏或过度强调某些主题而牺牲其他主题。我们在小学学到的历史是一种粗糙的圣徒传记,每个强势群体至少有一个代表。
Really? When a man runs off with his secretary, is it always partly his wife's fault? But I can see why Mayle might have said this. Maybe it's more important for kids to respect their parents than to know the truth about them. But because adults conceal their flaws, and at the same time insist on high standards of behavior for kids, a lot of kids grow up feeling they fall hopelessly short. They walk around feeling horribly evil for having used a swearword, while in fact most of the adults around them are doing much worse things. This happens in intellectual as well as moral questions. The more confident people are, the more willing they seem to be to answer a question "I don't know." Less confident people feel they have to have an answer or they'll look bad. My parents were pretty good about admitting when they didn't know things, but I must have been told a lot of lies of this type by teachers, because I rarely heard a teacher say "I don't know" till I got to college. I remember because it was so surprising to hear someone say that in front of a class. The first hint I had that teachers weren't omniscient came in sixth grade, after my father contradicted something I'd learned in school. When I protested that the teacher had said the opposite, my father replied that the guy had no idea what he was talking about—that he was just an elementary school teacher, after all. _Just_ a teacher? The phrase seemed almost grammatically ill-formed. Didn't teachers know everything about the subjects they taught? And if not, why were they the ones teaching us? The sad fact is, US public school teachers don't generally understand the stuff they're teaching very well. There are some sterling exceptions, but as a rule people planning to go into teaching rank academically near the bottom of the college population.
我记得的著名科学家是爱因斯坦、玛丽·居里和乔治·华盛顿·卡弗。爱因斯坦很重要,因为他的工作导致了原子弹的诞生。玛丽·居里与X射线有关。但我对卡弗感到困惑——他似乎只是做了一些关于花生的事情。
现在很明显,他被列入名单是因为他是黑人(玛丽·居里则是因为她是女性),但作为一个孩子,我对他困惑了很多年。我在想,如果直接告诉我们真相会不会更好:当时没有著名的黑人科学家。将乔治·华盛顿·卡弗与爱因斯坦相提并论,不仅误导了我们对科学的理解,也掩盖了黑人在他那个时代面临的障碍。
随着学科的软化,谎言变得更加频繁。到了政治和近代史的部分,我们学到的几乎完全是宣传。例如,我们被教导将政治领袖视为圣人——尤其是最近殉难的肯尼迪和马丁·路德·金。后来得知他们两人都是连环好色之徒,肯尼迪还是个瘾君子,这令人震惊。(当马丁·路德·金的剽窃行为曝光时,我已经对名人的恶行见怪不怪了。)
我怀疑你是否能在不撒谎的情况下教孩子们近代史,因为几乎所有对此有发言权的人都会加入某种倾向。许多近代史本身就是倾向的产物。或许更好的做法是教他们一些元事实,比如这一点。
然而,学校中最大的谎言可能是:成功的方法是遵循“规则”。事实上,大多数这类规则只是为了高效管理大群体的权宜之计。
So the fact that I still thought at age 11 that teachers were infallible shows what a job the system must have done on my brain. School What kids get taught in school is a complex mix of lies. The most excusable are those told to simplify ideas to make them easy to learn. The problem is, a lot of propaganda gets slipped into the curriculum in the name of simplification. Public school textbooks represent a compromise between what various powerful groups want kids to be told. The lies are rarely overt. Usually they consist either of omissions or of over-emphasizing certain topics at the expense of others. The view of history we got in elementary school was a crude hagiography, with at least one representative of each powerful group. The famous scientists I remember were Einstein, Marie Curie, and George Washington Carver. Einstein was a big deal because his work led to the atom bomb. Marie Curie was involved with X-rays. But I was mystified about Carver. He seemed to have done stuff with peanuts. It's obvious now that he was on the list because he was black (and for that matter that Marie Curie was on it because she was a woman), but as a kid I was confused for years about him. I wonder if it wouldn't have been better just to tell us the truth: that there weren't any famous black scientists. Ranking George Washington Carver with Einstein misled us not only about science, but about the obstacles blacks faced in his time. As subjects got softer, the lies got more frequent. By the time you got to politics and recent history, what we were taught was pretty much pure propaganda. For example, we were taught to regard political leaders as saints—especially the recently martyred Kennedy and King.
在我们对孩子撒谎的所有原因中,最强大的可能与他们对我们撒谎的平凡原因相同。
很多时候,我们对别人撒谎并不是出于某种有意识的策略,而是因为他们会对真相反应激烈。孩子几乎从定义上就缺乏自控力。他们对事物的反应会很激烈——因此他们经常被欺骗。[9]
几年前的一个感恩节,我的一位朋友遇到了一个完美体现我们对孩子撒谎的复杂动机的情境。当烤火鸡出现在餐桌上时,他那个异常敏锐的五岁儿子突然问火鸡是否愿意死。预见到灾难,我的朋友和他的妻子迅速编造:是的,火鸡愿意死,事实上它一生的目标就是成为他们的感恩节晚餐。就这样(呼),问题解决了。
每当我们为了保护孩子而撒谎时,通常也是为了维持和平而撒谎。
It was astonishing to learn later that they'd both been serial womanizers, and that Kennedy was a speed freak to boot. (By the time King's plagiarism emerged, I'd lost the ability to be surprised by the misdeeds of famous people.) I doubt you could teach kids recent history without teaching them lies, because practically everyone who has anything to say about it has some kind of spin to put on it. Much recent history _consists_ of spin. It would probably be better just to teach them metafacts like that. Probably the biggest lie told in schools, though, is that the way to succeed is through following "the rules." In fact most such rules are just hacks to manage large groups efficiently. Peace Of all the reasons we lie to kids, the most powerful is probably the same mundane reason they lie to us. Often when we lie to people it's not part of any conscious strategy, but because they'd react violently to the truth. Kids, almost by definition, lack self-control. They react violently to things—and so they get lied to a lot. [9] A few Thanksgivings ago, a friend of mine found himself in a situation that perfectly illustrates the complex motives we have when we lie to kids. As the roast turkey appeared on the table, his alarmingly perceptive 5 year old son suddenly asked if the turkey had wanted to die. Foreseeing disaster, my friend and his wife rapidly improvised: yes, the turkey had wanted to die, and in fact had lived its whole life with the aim of being their Thanksgiving dinner. And that (phew) was the end of that. Whenever we lie to kids to protect them, we're usually also lying to keep the peace. One consequence of this sort of calming lie is that we grow up thinking horrible things are normal. It's hard for us to feel a sense of urgency as adults over something we've literally been trained not to worry about. When I was about 10 I saw a documentary on pollution that put me into a panic.
这种安抚性谎言的一个后果是,我们长大后认为可怕的事情是正常的。作为成年人,我们很难对某些事情产生紧迫感,因为我们从小就被训练不要担心这些事。大约10岁时,我看了一部关于污染的纪录片,感到非常恐慌。地球似乎正在被不可挽回地破坏。之后我去问母亲这是否属实。我不记得她说了什么,但她让我感觉好多了,所以我就不再担心了。
这可能是应对一个受惊的10岁孩子的最佳方式。但我们应该明白代价。这种谎言是坏事持续存在的主要原因之一:我们都被训练去忽视它们。
短跑运动员在比赛中几乎立即进入一种称为“氧债”的状态。他的身体切换到一种比常规有氧呼吸更快的紧急能量来源。但这一过程会积累废物,最终需要额外的氧气来分解,因此在比赛结束时,他必须停下来喘口气才能恢复。
我们成年时带着一种“真相债务”。为了让我们(和我们的父母)度过童年,我们被告知了许多谎言。有些可能是必要的,有些可能不是。但我们成年时,头脑中充满了谎言。
It seemed the planet was being irretrievably ruined. I went to my mother afterward to ask if this was so. I don't remember what she said, but she made me feel better, so I stopped worrying about it. That was probably the best way to handle a frightened 10 year old. But we should understand the price. This sort of lie is one of the main reasons bad things persist: we're all trained to ignore them. Detox A sprinter in a race almost immediately enters a state called "oxygen debt." His body switches to an emergency source of energy that's faster than regular aerobic respiration. But this process builds up waste products that ultimately require extra oxygen to break down, so at the end of the race he has to stop and pant for a while to recover. We arrive at adulthood with a kind of truth debt. We were told a lot of lies to get us (and our parents) through our childhood. Some may have been necessary. Some probably weren't. But we all arrive at adulthood with heads full of lies. There's never a point where the adults sit you down and explain all the lies they told you. They've forgotten most of them. So if you're going to clear these lies out of your head, you're going to have to do it yourself. Few do. Most people go through life with bits of packing material adhering to their minds and never know it. You probably never can completely undo the effects of lies you were told as a kid, but it's worth trying. I've found that whenever I've been able to undo a lie I was told, a lot of other things fell into place. Fortunately, once you arrive at adulthood you get a valuable new resource you can use to figure out what lies you were told. You're now one of the liars. You get to watch behind the scenes as adults spin the world for the next generation of kids. The first step in clearing your head is to realize how far you are from a neutral observer. When I left high school I was, I thought, a complete skeptic.
从来没有一个时刻,成年人会坐下来向你解释他们对你撒过的所有谎言。他们自己已经忘记了大部分。因此,如果你想清除这些谎言,你必须自己动手。
很少有人这样做。大多数人一生都带着一些附着在思想上的包装材料,却从未意识到。你可能永远无法完全消除小时候被灌输的谎言的影响,但值得一试。我发现,每当我能够揭穿一个谎言时,许多其他事情就会变得清晰。
幸运的是,一旦你成年,你会获得一种宝贵的新资源,可以用来弄清楚你被灌输了哪些谎言。你现在也是撒谎者之一。你可以亲眼目睹成年人是如何为下一代孩子编织世界的。
清理头脑的第一步是意识到你离一个中立的观察者有多远。高中毕业时,我以为自己是一个彻底的怀疑论者。我已经意识到高中是一堆垃圾。我以为我已经准备好质疑我所知道的一切。但我当时不知道的是,我的头脑中已经有多少垃圾。仅仅把你的头脑视为一块白板是不够的,你必须主动擦除它。
[1] 我坚持使用如此简单粗暴的词语的一个原因是,我们对孩子撒的谎可能并不像我们想象的那么无害。如果你看看过去成年人对孩子说的话,你会震惊于他们撒了多少谎。和我们一样,他们是出于最好的意图。因此,如果我们认为自己已经尽可能对孩子坦诚,我们可能是在自欺欺人。一百年后的人很可能会对我们今天撒的某些谎感到震惊,就像我们对一百年前的人撒的某些谎感到震惊一样。
I'd realized high school was crap. I thought I was ready to question everything I knew. But among the many other things I was ignorant of was how much debris there already was in my head. It's not enough to consider your mind a blank slate. You have to consciously erase it. Notes [1] One reason I stuck with such a brutally simple word is that the lies we tell kids are probably not quite as harmless as we think. If you look at what adults told children in the past, it's shocking how much they lied to them. Like us, they did it with the best intentions. So if we think we're as open as one could reasonably be with children, we're probably fooling ourselves. Odds are people in 100 years will be as shocked at some of the lies we tell as we are at some of the lies people told 100 years ago. I can't predict which these will be, and I don't want to write an essay that will seem dumb in 100 years. So instead of using special euphemisms for lies that seem excusable according to present fashions, I'm just going to call all our lies lies. (I have omitted one type: lies told to play games with kids' credulity. These range from "make-believe," which is not really a lie because it's told with a wink, to the frightening lies told by older siblings. There's not much to say about these: I wouldn't want the first type to go away, and wouldn't expect the second type to.) [2] Calaprice, Alice (ed.), _The Quotable Einstein_ , Princeton University Press, 1996. [3] If you ask parents why kids shouldn't swear, the less educated ones usually reply with some question-begging answer like "it's inappropriate," while the more educated ones come up with elaborate rationalizations. In fact the less educated parents seem closer to the truth. [4] As a friend with small children pointed out, it's easy for small children to consider themselves immortal, because time seems to pass so slowly for them.
我无法预测哪些谎言会如此,也不想写一篇一百年后看起来愚蠢的文章。因此,我不会根据当前的时尚为看似情有可原的谎言使用特殊的委婉说法,而是直接称它们为谎言。
(我忽略了一种类型:为了戏弄孩子的轻信而撒的谎。这些从“假装游戏”——严格来说不算撒谎,因为它是带着眨眼说的——到兄弟姐妹之间可怕的谎言。关于这些没什么好说的:我不希望第一种消失,也不指望第二种会消失。)
[2] Calaprice, Alice (ed.), 《爱因斯坦语录》, 普林斯顿大学出版社, 1996.
[3] 如果你问父母为什么孩子不应该说脏话,受教育程度较低的人通常会给出一些循环论证的答案,比如“这不合适”,而受教育程度较高的人则会编造复杂的合理化解释。事实上,受教育程度较低的父母似乎更接近真相。
To a 3 year old, a day feels like a month might to an adult. So 80 years sounds to him like 2400 years would to us. [5] I realize I'm going to get endless grief for classifying religion as a type of lie. Usually people skirt that issue with some equivocation implying that lies believed for a sufficiently long time by sufficiently large numbers of people are immune to the usual standards for truth. But because I can't predict which lies future generations will consider inexcusable, I can't safely omit any type we tell. Yes, it seems unlikely that religion will be out of fashion in 100 years, but no more unlikely than it would have seemed to someone in 1880 that schoolchildren in 1980 would be taught that masturbation was perfectly normal and not to feel guilty about it. [6] Unfortunately the payload can consist of bad customs as well as good ones. For example, there are certain qualities that some groups in America consider "acting white." In fact most of them could as accurately be called "acting Japanese." There's nothing specifically white about such customs. They're common to all cultures with long traditions of living in cities. So it is probably a losing bet for a group to consider behaving the opposite way as part of its identity. [7] In this context, "issues" basically means "things we're going to lie to them about." That's why there's a special name for these topics. [8] Mayle, Peter, _Why Are We Getting a Divorce?_ , Harmony, 1988. [9] The ironic thing is, this is also the main reason kids lie to adults. If you freak out when people tell you alarming things, they won't tell you them. Teenagers don't tell their parents what happened that night they were supposed to be staying at a friend's house for the same reason parents don't tell 5 year olds the truth about the Thanksgiving turkey.
[4] 一位有小孩的朋友指出,小孩子很容易认为自己是不朽的,因为时间对他们来说过得很慢。对三岁的孩子来说,一天的感觉就像成年人眼中的一个月。因此,80年对他来说就像2400年对我们一样。
[5] 我知道我会因为将宗教归类为一种谎言而遭到无尽的指责。通常人们会用一些模棱两可的说法回避这个问题,暗示被足够多的人相信足够长时间的谎言可以免受通常的真相标准约束。但由于我无法预测未来几代人会认为哪些谎言不可原谅,我不能安全地省略我们撒的任何一种谎言。是的,宗教似乎不太可能在一百年后过时,但这并不比1880年的人认为1980年的学生会被告知自慰是完全正常的、不必为此感到内疚更不可能。
[6] 不幸的是,这种“有效载荷”可能包括坏习惯和好习惯。例如,美国某些群体认为某些品质是“像白人一样”。事实上,它们中的大多数也可以准确地称为“像日本人一样”。这些习惯并没有什么特别白人的地方。它们是所有有悠久城市生活传统的文化共有的。因此,一个群体将相反的行为视为其身份的一部分可能是一个失败的赌注。
[7] 在这种情况下,“问题”基本上意味着“我们要对他们撒谎的事情”。这就是为什么这些话题有特殊的名称。
They'd freak if they knew. Thanks to Sam Altman, Marc Andreessen, Trevor Blackwell, Patrick Collison, Jessica Livingston, Jackie McDonough, Robert Morris, and David Sloo for reading drafts of this. And since there are some controversial ideas here, I should add that none of them agreed with everything in it.
German Translation | French Translation Russian Translation.
[8] Mayle, Peter, 《我们为什么要离婚?》, Harmony, 1988.
[9] 讽刺的是,这也是孩子对成年人撒谎的主要原因。如果你对令人不安的事情反应过激,人们就不会告诉你这些事。青少年不会告诉父母他们本应在朋友家过夜的那晚发生了什么,就像父母不会告诉五岁的孩子感恩节火鸡的真相一样。如果他们知道了,他们会抓狂。
致谢 感谢Sam Altman、Marc Andreessen、Trevor Blackwell、Patrick Collison、Jessica Livingston、Jackie McDonough、Robert Morris和David Sloo阅读本文草稿。由于文中包含一些有争议的观点,我应该补充说明,他们并不完全同意其中的所有内容。
April 2008 There are some topics I save up because they'll be so much fun to write about. This is one of them: a list of my heroes. I'm not claiming this is a list of the _n_ most admirable people. Who could make such a list, even if they wanted to? Einstein isn't on the list, for example, even though he probably deserves to be on any shortlist of admirable people. I once asked a physicist friend if Einstein was really as smart as his fame implies, and she said that yes, he was. So why isn't he on the list? Because I had to ask. This is a list of people who've influenced me, not people who would have if I understood their work. My test was to think of someone and ask "is this person my hero?" It often returned surprising answers. For example, it returned false for Montaigne, who was arguably the inventor of the essay. Why? When I thought about what it meant to call someone a hero, it meant I'd decide what to do by asking what they'd do in the same situation. That's a stricter standard than admiration. After I made the list, I looked to see if there was a pattern, and there was, a very clear one. Everyone on the list had two qualities: they cared almost excessively about their work, and they were absolutely honest. By honest I don't mean trustworthy so much as that they never pander: they never say or do something because that's what the audience wants. They are all fundamentally subversive for this reason, though they conceal it to varying degrees. Jack Lambert I grew up in Pittsburgh in the 1970s. Unless you were there it's hard to imagine how that town felt about the Steelers. Locally, all the news was bad. The steel industry was dying. But the Steelers were the best team in football — and moreover, in a way that seemed to reflect the personality of the city. They didn't do anything fancy. They just got the job done. Other players were more famous: Terry Bradshaw, Franco Harris, Lynn Swann.
有些话题我珍藏许久,因为写起来会特别有趣。这就是其中之一:一份关于我心目中的英雄的清单。
我并非宣称这是“最值得钦佩的_n_人”榜单。即便有人想列,谁又能做到呢?
比如爱因斯坦不在名单上,尽管他理应出现在任何值得钦佩的短名单中。我曾问一位物理学家朋友,爱因斯坦是否真如他的名声所暗示的那样聪明,她给出了肯定的回答。那么为何他不在我的名单上?因为我是通过询问才确认的。这份名单记录的是影响我的人,而非那些如果我理解其工作就会影响我的人。
我的筛选标准是:想到一个人时自问“此人是否是我的英雄?”答案常常出人意料。例如,蒙田——可说是随笔的发明者——得到的答案是否定的。为什么?当我思考“英雄”一词的含义时,它意味着我会通过设想他们在相同情境下的选择来决定自己的行动。这比单纯的钦佩严格得多。
列完名单后,我试图寻找其中的共性,结果发现了一个极其清晰的模式:名单上的每个人都具备两种品质——他们几乎过度专注于自己的工作,且绝对诚实。这里的诚实并非指值得信赖,而是指他们从不迎合:他们从不因观众想要而说某些话或做某些事。正因如此,他们本质上都具有颠覆性,尽管表现程度各异。
But they played offense, and you always get more attention for that. It seemed to me as a twelve year old football expert that the best of them all was Jack Lambert). And what made him so good was that he was utterly relentless. He didn't just care about playing well; he cared almost too much. He seemed to regard it as a personal insult when someone from the other team had possession of the ball on his side of the line of scrimmage. The suburbs of Pittsburgh in the 1970s were a pretty dull place. School was boring. All the adults around were bored with their jobs working for big companies. Everything that came to us through the mass media was (a) blandly uniform and (b) produced elsewhere. Jack Lambert was the exception. He was like nothing else I'd seen. Kenneth Clark Kenneth Clark is the best nonfiction writer I know of, on any subject. Most people who write about art history don't really like art; you can tell from a thousand little signs. But Clark did, and not just intellectually, but the way one anticipates a delicious dinner. What really makes him stand out, though, is the quality of his ideas. His style is deceptively casual, but there is more in his books than in a library of art monographs. Reading _The Nude_ is like a ride in a Ferrari. Just as you're getting settled, you're slammed back in your seat by the acceleration. Before you can adjust, you're thrown sideways as the car screeches into the first turn. His brain throws off ideas almost too fast to grasp them. Finally at the end of the chapter you come to a halt, with your eyes wide and a big smile on your face. Kenneth Clark was a star in his day, thanks to the documentary series _Civilisation_.
1970年代我在匹兹堡长大。除非亲历,否则很难想象当时那座城市对钢人队的情感。当地新闻总是坏消息——钢铁业正在消亡。但钢人队是橄榄球界最棒的队伍,更重要的是,他们的风格仿佛映射着这座城市的个性:不搞花哨动作,只是完成任务。
其他球员更有名:特里·布拉德肖、弗兰科·哈里斯、林恩·斯旺。但他们打的是进攻位置,自然更受关注。在我这个十二岁橄榄球专家眼中,最出色的却是杰克·兰伯特)。他的卓越源于极致的顽强。他不仅在乎打好比赛,甚至在乎得过了头。当对方球员在他防守的区域持球时,他仿佛将其视为个人侮辱。
1970年代的匹兹堡郊区沉闷至极:学校无聊,周围的大人们厌倦着为大公司打工的生活,大众媒体传递的内容(a)千篇一律且(b)产自他乡。杰克·兰伯特是个例外,他与我见过的任何事物都不同。
肯尼斯·克拉克
肯尼斯·克拉克是我所知所有领域中最优秀的非虚构作家。多数艺术史作者并不真正热爱艺术——你能从无数细节看出这点。但克拉克不同,他的热爱不仅是智性的,更如同期待一顿美餐般真切。
让他真正脱颖而出的是其思想的质量。他的文风看似随意,但其著作蕴含的内容胜过一整库艺术专著。阅读《裸体》如同乘坐法拉利:刚坐稳就被加速度按在椅背上,未及适应又随轮胎尖啸甩入第一个弯道。他的大脑迸发思想的速度快得让人难以捕捉。章节结束时,你双目圆睁,嘴角挂着微笑。
And if you read only one book about art history, _Civilisation_ is the one I'd recommend. It's much better than the drab Sears Catalogs of art that undergraduates are forced to buy for Art History 101. Larry Mihalko A lot of people have a great teacher at some point in their childhood. Larry Mihalko was mine. When I look back it's like there's a line drawn between third and fourth grade. After Mr. Mihalko, everything was different. Why? First of all, he was intellectually curious. I had a few other teachers who were smart, but I wouldn't describe them as intellectually curious. In retrospect, he was out of place as an elementary school teacher, and I think he knew it. That must have been hard for him, but it was wonderful for us, his students. His class was a constant adventure. I used to like going to school every day. The other thing that made him different was that he liked us. Kids are good at telling that. The other teachers were at best benevolently indifferent. But Mr. Mihalko seemed like he actually wanted to be our friend. On the last day of fourth grade, he got out one of the heavy school record players and played James Taylor's "You've Got a Friend" to us. Just call out my name, and you know wherever I am, I'll come running. He died at 59 of lung cancer. I've never cried like I cried at his funeral. Leonardo One of the things I've learned about making things that I didn't realize when I was a kid is that much of the best stuff isn't made for audiences, but for oneself. You see paintings and drawings in museums and imagine they were made for you to look at. Actually a lot of the best ones were made as a way of exploring the world, not as a way to please other people. The best of these explorations are sometimes more pleasing than stuff made explicitly to please. Leonardo did a lot of things.
得益于纪录片系列《文明》,克拉克曾是时代的明星。若你只读一本艺术史书籍,我推荐《文明》。它远胜于艺术史入门课要求购买的那些枯燥目录。
拉里·米哈尔科
许多人在童年遇到过一位伟大教师。拉里·米哈尔科就是我的那位。回首往事,三年级与四年级之间仿佛划着分界线。米哈尔科先生之后,一切都不同了。
为何?首先,他拥有智识上的好奇心。我遇到过其他聪明的老师,但难以用“好奇”形容他们。如今想来,他本不该是小学教师,我想他自己也明白。这对他或许是煎熬,但对学生却是幸运。他的课堂充满冒险,我曾每天都期待上学。
另一不同之处在于他喜欢我们。孩子对此格外敏感。其他老师至多是善意的漠然,而米哈尔科先生似乎真心想成为我们的朋友。四年级最后一天,他搬出笨重的校用留声机,为我们播放詹姆斯·泰勒的《你有个朋友》。“只需呼唤我的名字,无论身在何处,我都会奔向你。”他59岁因肺癌去世。在他的葬礼上,我哭得前所未有。
关于创作,我成年后才明白的一点是:最杰出的作品往往不为观众,而为己作。你在博物馆看到的画作,可能以为是为你而绘,实则许多杰作是探索世界的产物,而非取悦他人。这类探索中最出色的,有时比刻意讨好的作品更动人。
One of his most admirable qualities was that he did so many different things that were admirable. What people know of him now is his paintings and his more flamboyant inventions, like flying machines. That makes him seem like some kind of dreamer who sketched artists' conceptions of rocket ships on the side. In fact he made a large number of far more practical technical discoveries. He was as good an engineer as a painter. His most impressive work, to me, is his drawings. They're clearly made more as a way of studying the world than producing something beautiful. And yet they can hold their own with any work of art ever made. No one else, before or since, was that good when no one was looking. Robert Morris Robert Morris has a very unusual quality: he's never wrong. It might seem this would require you to be omniscient, but actually it's surprisingly easy. Don't say anything unless you're fairly sure of it. If you're not omniscient, you just don't end up saying much. More precisely, the trick is to pay careful attention to how you qualify what you say. By using this trick, Robert has, as far as I know, managed to be mistaken only once, and that was when he was an undergrad. When the Mac came out, he said that little desktop computers would never be suitable for real hacking. It's wrong to call it a trick in his case, though. If it were a conscious trick, he would have slipped in a moment of excitement. With Robert this quality is wired-in. He has an almost superhuman integrity. He's not just generally correct, but also correct about how correct he is. You'd think it would be such a great thing never to be wrong that everyone would do this. It doesn't seem like that much extra work to pay as much attention to the error on an idea as to the idea itself. And yet practically no one does.
达芬奇涉猎广泛。他最令人钦佩的特质是,在众多领域都成就斐然。如今人们熟知他的绘画和飞行器等张扬发明,这让他像个在火箭草图旁做梦的空想家。事实上,他还有大量更实用的技术发现,既是杰出画家,也是卓越工程师。
对我而言,他最震撼的作品是素描。这些显然是为研究世界而非创造美而作,却能与任何艺术品比肩。古今中外,无人能在无人注视时达到如此高度。
罗伯特·莫里斯
罗伯特·莫里斯有种罕见特质:从不出错。这看似需要全知,实则出奇简单——只说你确信的事。若非全知,你自然话少。
更准确地说,诀窍在于谨慎限定所言。据我所知,罗伯特仅失误过一次——大学时评价麦金塔电脑,认为小型台式机永远不适合真正的黑客。
但这对他并非刻意为之的“诀窍”。若是刻意,兴奋时便会失言。这种特质已内化为他的一部分,他具备近乎超人的正直——不仅正确,而且对自身正确性的判断也准确。
I know how hard it is, because since meeting Robert I've tried to do in software what he seems to do in hardware. P. G. Wodehouse People are finally starting to admit that Wodehouse was a great writer. If you want to be thought a great novelist in your own time, you have to sound intellectual. If what you write is popular, or entertaining, or funny, you're ipso facto suspect. That makes Wodehouse doubly impressive, because it meant that to write as he wanted to, he had to commit to being despised in his own lifetime. Evelyn Waugh called him a great writer, but to most people at the time that would have read as a chivalrous or deliberately perverse gesture. At the time any random autobiographical novel by a recent college grad could count on more respectful treatment from the literary establishment. Wodehouse may have begun with simple atoms, but the way he composed them into molecules was near faultless. His rhythm in particular. It makes me self-conscious to write about it. I can think of only two other writers who came near him for style: Evelyn Waugh and Nancy Mitford. Those three used the English language like they owned it. But Wodehouse has something neither of them did. He's at ease. Evelyn Waugh and Nancy Mitford cared what other people thought of them: he wanted to seem aristocratic; she was afraid she wasn't smart enough. But Wodehouse didn't give a damn what anyone thought of him. He wrote exactly what he wanted. Alexander Calder Calder's on this list because he makes me happy. Can his work stand up to Leonardo's? Probably not. There might not be anything from the 20th Century that can. But what was good about Modernism, Calder had, and had in a way that he made seem effortless. What was good about Modernism was its freshness. Art became stuffy in the nineteenth century. The paintings that were popular at the time were mostly the art equivalent of McMansions—big, pretentious, and fake.
你会以为“永不出错”如此美好,人人都会效仿。关注想法本身的同时关注其误差似乎不需额外努力。然而几乎无人做到。我深知其难,因为遇见罗伯特后,我尝试在软件领域做到他在硬件领域的境界。
P·G·沃德豪斯
人们终于开始承认沃德豪斯是伟大作家。若想当代就被视为伟大小说家,你必须显得智性。如果你的作品受欢迎、有趣或好笑,你就天然可疑。这让沃德豪斯加倍令人钦佩——为按自己意愿写作,他甘愿承受生前被轻视。
伊夫林·沃称他为伟大作家,但当时多数人视此为骑士精神或故意唱反调。那时随便一个大学毕业生的自传体小说,都能比沃德豪斯获得文坛更郑重的对待。
沃德豪斯或许始于简单的原子,但他将其组合成近乎完美的分子。尤其是他的节奏——谈论这点让我自觉惭愧。我认为仅两位作家在风格上接近他:伊夫林·沃和南希·米特福德。这三人运用英语如臂使指。
Modernism meant starting over, making things with the same earnest motives that children might. The artists who benefited most from this were the ones who had preserved a child's confidence, like Klee and Calder. Klee was impressive because he could work in so many different styles. But between the two I like Calder better, because his work seemed happier. Ultimately the point of art is to engage the viewer. It's hard to predict what will; often something that seems interesting at first will bore you after a month. Calder's sculptures never get boring. They just sit there quietly radiating optimism, like a battery that never runs out. As far as I can tell from books and photographs, the happiness of Calder's work is his own happiness showing through. Jane Austen Everyone admires Jane Austen. Add my name to the list. To me she seems the best novelist of all time. I'm interested in how things work. When I read most novels, I pay as much attention to the author's choices as to the story. But in her novels I can't see the gears at work. Though I'd really like to know how she does what she does, I can't figure it out, because she's so good that her stories don't seem made up. I feel like I'm reading a description of something that actually happened. I used to read a lot of novels when I was younger. I can't read most anymore, because they don't have enough information in them. Novels seem so impoverished compared to history and biography. But reading Austen is like reading nonfiction. She writes so well you don't even notice her. John McCarthy John McCarthy invented Lisp, the field of (or at least the term) artificial intelligence, and was an early member of both of the top two computer science departments, MIT and Stanford. No one would dispute that he's one of the greats, but he's an especial hero to me because of Lisp.
但沃德豪斯拥有他们缺乏的特质:从容。伊夫林·沃在意他人眼光——他想显得贵族;南希担心自己不够聪明。沃德豪斯则毫不在乎他人评价,他只写自己想写的。
亚历山大·考尔德
考尔德上榜因为他让我快乐。他的作品能与达芬奇比肩吗?或许不能——二十世纪可能无此等作品。但他拥有现代主义的精华,且举重若轻。
现代主义的可贵在于新鲜感。十九世纪艺术变得陈腐,当时流行的绘画如同艺术界的“豪宅”——庞大、浮夸而虚假。现代主义意味着重启,像孩子般真诚地创作。受益最多的是保有童真自信的艺术家,如克利和考尔德。
克利因多变的风格令人印象深刻,但我更偏爱考尔德——他的作品更快乐。艺术的终极目标是触动观者。这难以预测:初看有趣的作品可能一月后就索然无味。考尔德的雕塑永不乏味,它们静默散发着永不枯竭的乐观。据书籍和照片判断,这快乐正是考尔德自身快乐的映照。
人人都钦佩简·奥斯汀,我也如此。对我而言,她是有史以来最伟大小说家。
It's hard for us now to understand what a conceptual leap that was at the time. Paradoxically, one of the reasons his achievement is hard to appreciate is that it was so successful. Practically every programming language invented in the last 20 years includes ideas from Lisp, and each year the median language gets more Lisplike. In 1958 these ideas were anything but obvious. In 1958 there seem to have been two ways of thinking about programming. Some people thought of it as math, and proved things about Turing Machines. Others thought of it as a way to get things done, and designed languages all too influenced by the technology of the day. McCarthy alone bridged the gap. He designed a language that was math. But designed is not really the word; discovered is more like it. The Spitfire As I was making this list I found myself thinking of people like Douglas Bader and R.J. Mitchell and Jeffrey Quill and I realized that though all of them had done many things in their lives, there was one factor above all that connected them: the Spitfire. This is supposed to be a list of heroes. How can a machine be on it? Because that machine was not just a machine. It was a lens of heroes. Extraordinary devotion went into it, and extraordinary courage came out. It's a cliche to call World War II a contest between good and evil, but between fighter designs, it really was. The Spitfire's original nemesis, the ME 109, was a brutally practical plane. It was a killing machine. The Spitfire was optimism embodied. And not just in its beautiful lines: it was at the edge of what could be manufactured. But taking the high road worked.
我着迷于事物的运作机制。读多数小说时,我会像关注故事一样关注作者的选择。但她的作品中我看不见齿轮转动。尽管极想了解她如何做到,我却无法参透——因她过于出色,故事真实得不似虚构,仿佛在阅读真实事件的记录。
年轻时我读大量小说,如今多数已无法卒读——相比历史和传记,小说信息太过贫乏。但读奥斯汀如同读非虚构。她的文字让你忘记她的存在。
约翰·麦卡锡发明了Lisp,开创了人工智能领域(或至少命名了它),并先后任职于MIT和斯坦福两大顶尖计算机系。无人质疑他的伟大,但Lisp使他成为我特别的英雄。
如今我们难以体会当时这一概念飞跃的意义。吊诡的是,其成就难以被充分欣赏的原因之一正是它太过成功——过去20年几乎所有新编程语言都包含Lisp的思想,且每年主流语言都更接近Lisp。
1958年这些思想绝非显而易见。当时编程有两种认知路径:一些人视其为数学,研究图灵机;另一些人视其为完成任务的手段,设计深受当时技术影响的语言。唯有麦卡锡弥合鸿沟——他设计的语言本身就是数学。“设计”一词并不准确,更贴切的说法是“发现”。
In the air, beauty had the edge, just. Steve Jobs People alive when Kennedy was killed usually remember exactly where they were when they heard about it. I remember exactly where I was when a friend asked if I'd heard Steve Jobs had cancer. It was like the floor dropped out. A few seconds later she told me that it was a rare operable type, and that he'd be ok. But those seconds seemed long. I wasn't sure whether to include Jobs on this list. A lot of people at Apple seem to be afraid of him, which is a bad sign. But he compels admiration. There's no name for what Steve Jobs is, because there hasn't been anyone quite like him before. He doesn't design Apple's products himself. Historically the closest analogy to what he does are the great Renaissance patrons of the arts. As the CEO of a company, that makes him unique. Most CEOs delegate taste to a subordinate. The design paradox means they're choosing more or less at random. But Steve Jobs actually has taste himself — such good taste that he's shown the world how much more important taste is than they realized. Isaac Newton Newton has a strange role in my pantheon of heroes: he's the one I reproach myself with. He worked on big things, at least for part of his life. It's so easy to get distracted working on small stuff. The questions you're answering are pleasantly familiar. You get immediate rewards — in fact, you get bigger rewards in your time if you work on matters of passing importance. But I'm uncomfortably aware that this is the route to well-deserved obscurity. To do really great things, you have to seek out questions people didn't even realize were questions. There have probably been other people who did this as well as Newton, for their time, but Newton is my model of this kind of thought. I can just begin to understand what it must have felt like for him. You only get one life.
这是英雄榜,为何列入机器?因这不仅是机器,更是英雄的棱镜——倾注非凡热忱,焕发非凡勇气。
称二战为善恶对决虽是陈词,但在战斗机设计上确实如此。喷火的原初对手ME 109是架残酷务实的杀人机器,而喷火是乐观的化身——不仅因优美线条,更因它处于制造工艺的极限。但这条高尚之路成功了:在空中,美以毫厘之差占了上风。
史蒂夫·乔布斯
肯尼迪遇刺时在世的人常清楚记得听闻消息时的位置。我同样清晰记得朋友问我是否听说乔布斯患癌时身处何处——仿佛地板突然消失。几秒后她补充说是可手术的罕见类型,他会没事。但那几秒无比漫长。
我曾犹豫是否将乔布斯列入名单。苹果许多员工似乎惧怕他,这不是好迹象。但他令人不得不钦佩。
尚无词汇能定义乔布斯,因为前无古人。他并不亲自设计苹果产品,历史上最接近的类比是文艺复兴时期的伟大艺术赞助人。作为公司CEO,这使他独一无二。
Why not do something huge? The phrase "paradigm shift" is overused now, but Kuhn was onto something. And you know more are out there, separated from us by what will later seem a surprisingly thin wall of laziness and stupidity. If we work like Newton. Thanks to Trevor Blackwell, Jessica Livingston, and Jackie McDonough for reading drafts of this.
多数CEO将品味委托下属。设计悖论意味着他们近乎随机选择。但乔布斯本人拥有品味——如此卓越的品味,他向世界证明了品味比人们想象的更重要。
牛顿在我的英雄殿堂中扮演奇特角色:他是用以自我鞭策的典范。至少部分人生中,他专注于宏大问题。人们太容易纠缠于琐事——那些问题熟悉亲切,能带来即时回报。事实上,研究转瞬即逝的问题能获得时代更大的奖赏。但我清醒意识到,这是通往应得 obscurity 之路。
要成就真正伟大的事业,必须寻找人们尚未意识到的问题。或许历史上有人如牛顿般在其时代做到这点,但牛顿是这种思维的标杆。我仅能初窥他当年的感受。
生命只有一次,为何不做些惊天之事?“范式转换”一词如今被滥用,但库恩确有洞见。而我们知道还有更多范式等着被发现,与我们仅隔着一堵后来看来薄得惊人的懒惰与愚蠢之墙——只要像牛顿那样工作。
致谢 感谢特雷弗·布莱克韦尔、杰西卡·利文斯顿和杰基·麦克多诺阅读本文草稿。
[](https://s.turbifycdn.com/aah/paulgraham/be-good-11.gif) April 2008 _(This essay is derived from a talk at the 2008 Startup School.)_ About a month after we started Y Combinator we came up with the phrase that became our motto: Make something people want. We've learned a lot since then, but if I were choosing now that's still the one I'd pick. Another thing we tell founders is not to worry too much about the business model, at least at first. Not because making money is unimportant, but because it's so much easier than building something great. A couple weeks ago I realized that if you put those two ideas together, you get something surprising. Make something people want. Don't worry too much about making money. What you've got is a description of a charity. When you get an unexpected result like this, it could either be a bug or a new discovery. Either businesses aren't supposed to be like charities, and we've proven by reductio ad absurdum that one or both of the principles we began with is false. Or we have a new idea. I suspect it's the latter, because as soon as this thought occurred to me, a whole bunch of other things fell into place. Examples For example, Craigslist. It's not a charity, but they run it like one. And they're astoundingly successful. When you scan down the list of most popular web sites, the number of employees at Craigslist looks like a misprint. Their revenues aren't as high as they could be, but most startups would be happy to trade places with them. In Patrick O'Brian's novels, his captains always try to get upwind of their opponents. If you're upwind, you decide when and if to engage the other ship. Craigslist is effectively upwind of enormous revenues.
[](https://s.turbifycdn.com/aah/paulgraham/be-good-11.gif)
(本文源自2008年创业学校的一次演讲。)
我们创立Y Combinator约一个月后,提出了后来成为座右铭的口号:做人们想要的东西。此后我们学到了很多,但如果现在让我选择,我依然会选这句话。
我们告诉创始人的另一件事是,至少在初期不必过分担心商业模式。不是因为赚钱不重要,而是因为比起打造伟大的产品,赚钱要容易得多。
几周前我突然意识到,如果将这两个观点结合起来,会得出一个令人惊讶的结论:做人们想要的东西,不必过分担心赚钱。这听起来就像在描述一家慈善机构。
They'd face some challenges if they wanted to make more, but not the sort you face when you're tacking upwind, trying to force a crappy product on ambivalent users by spending ten times as much on sales as on development. [1] I'm not saying startups should aim to end up like Craigslist. They're a product of unusual circumstances. But they're a good model for the early phases. Google looked a lot like a charity in the beginning. They didn't have ads for over a year. At year 1, Google was indistinguishable from a nonprofit. If a nonprofit or government organization had started a project to index the web, Google at year 1 is the limit of what they'd have produced. Back when I was working on spam filters I thought it would be a good idea to have a web-based email service with good spam filtering. I wasn't thinking of it as a company. I just wanted to keep people from getting spammed. But as I thought more about this project, I realized it would probably have to be a company. It would cost something to run, and it would be a pain to fund with grants and donations. That was a surprising realization. Companies often claim to be benevolent, but it was surprising to realize there were purely benevolent projects that had to be embodied as companies to work. I didn't want to start another company, so I didn't do it. But if someone had, they'd probably be quite rich now. There was a window of about two years when spam was increasing rapidly but all the big email services had terrible filters. If someone had launched a new, spam-free mail service, users would have flocked to it. Notice the pattern here? From either direction we get to the same spot. If you start from successful startups, you find they often behaved like nonprofits. And if you start from ideas for nonprofits, you find they'd often make good startups. Power How wide is this territory? Would all good nonprofits be good companies? Possibly not.
当得到这种意外结论时,它可能是个错误,也可能是个新发现。要么企业本就不该像慈善机构,我们通过归谬法证明了初始原则中至少有一条是错误的;要么我们有了一个新观点。
我倾向于后者,因为一旦这个想法浮现,许多其他事情也随之豁然开朗。
以Craigslist为例。它并非慈善机构,但运营方式却如出一辙。他们的成功令人惊叹。浏览最受欢迎的网站列表时,Craigslist的员工数量少得像印刷错误。他们的收入本可以更高,但大多数初创公司都愿意与他们交换位置。
在帕特里克·奥布莱恩的小说中,船长们总是设法占据上风位置。处于上风意味着你能决定何时与敌舰交锋。Craigslist本质上占据了巨大收入的上风位置。若想赚更多钱,他们确实会面临挑战,但绝非那种逆风挣扎的困境——比如将劣质产品强塞给摇摆不定的用户,并在销售上投入十倍于开发的成本。[1]
我并非建议初创公司都以Craigslist为终极目标。他们是特殊环境的产物。但他们是早期阶段的优秀范例。
What makes Google so valuable is that their users have money. If you make people with money love you, you can probably get some of it. But could you also base a successful startup on behaving like a nonprofit to people who don't have money? Could you, for example, grow a successful startup out of curing an unfashionable but deadly disease like malaria? I'm not sure, but I suspect that if you pushed this idea, you'd be surprised how far it would go. For example, people who apply to Y Combinator don't generally have much money, and yet we can profit by helping them, because with our help they could make money. Maybe the situation is similar with malaria. Maybe an organization that helped lift its weight off a country could benefit from the resulting growth. I'm not proposing this is a serious idea. I don't know anything about malaria. But I've been kicking ideas around long enough to know when I come across a powerful one. One way to guess how far an idea extends is to ask yourself at what point you'd bet against it. The thought of betting against benevolence is alarming in the same way as saying that something is technically impossible. You're just asking to be made a fool of, because these are such powerful forces. [2] For example, initially I thought maybe this principle only applied to Internet startups. Obviously it worked for Google, but what about Microsoft? Surely Microsoft isn't benevolent? But when I think back to the beginning, they were. Compared to IBM they were like Robin Hood. When IBM introduced the PC, they thought they were going to make money selling hardware at high prices. But by gaining control of the PC standard, Microsoft opened up the market to any manufacturer. Hardware prices plummeted, and lots of people got to have computers who couldn't otherwise have afforded them. It's the sort of thing you'd expect Google to do. Microsoft isn't so benevolent now.
谷歌最初也极像慈善机构。他们一年多没有广告。成立第一年的谷歌与非营利组织毫无二致。如果某个非营利组织或政府机构启动了一个网络索引项目,谷歌第一年的状态就是他们所能达到的极限。
当年我研究垃圾邮件过滤器时,曾认为建立一个具备优秀过滤功能的网络邮件服务会是个好主意。我并未将其视为公司项目,只是想保护人们免受垃圾邮件困扰。但随着思考深入,我意识到这必须通过公司形式实现——运营需要成本,而依靠资助和捐款将难以为继。
这个发现令人意外。企业常标榜自己心怀善意,但意识到某些纯粹善意的项目必须通过公司形式才能实现,仍让人惊讶。
由于不想再开公司,我放弃了。但如果有人做了,现在可能已相当富有。当时有约两年窗口期:垃圾邮件激增,而各大邮件服务的过滤器都很糟糕。若有人推出全新的无垃圾邮件服务,用户必将蜂拥而至。
注意到这个模式了吗?无论从哪端出发,我们都抵达了同一位置。观察成功的初创公司,你会发现他们常表现得像非营利组织;而审视非营利组织的创意时,你会发现它们往往能成为优秀的初创公司。
Now when one thinks of what Microsoft does to users, all the verbs that come to mind begin with F. [3] And yet it doesn't seem to pay. Their stock price has been flat for years. Back when they were Robin Hood, their stock price rose like Google's. Could there be a connection? You can see how there would be. When you're small, you can't bully customers, so you have to charm them. Whereas when you're big you can maltreat them at will, and you tend to, because it's easier than satisfying them. You grow big by being nice, but you can stay big by being mean. You get away with it till the underlying conditions change, and then all your victims escape. So "Don't be evil" may be the most valuable thing Paul Buchheit made for Google, because it may turn out to be an elixir of corporate youth. I'm sure they find it constraining, but think how valuable it will be if it saves them from lapsing into the fatal laziness that afflicted Microsoft and IBM. The curious thing is, this elixir is freely available to any other company. Anyone can adopt "Don't be evil." The catch is that people will hold you to it. So I don't think you're going to see record labels or tobacco companies using this discovery. Morale There's a lot of external evidence that benevolence works. But how does it work? One advantage of investing in a large number of startups is that you get a lot of data about how they work. From what we've seen, being good seems to help startups in three ways: it improves their morale, it makes other people want to help them, and above all, it helps them be decisive. Morale is tremendously important to a startup—so important that morale alone is almost enough to determine success. Startups are often described as emotional roller-coasters. One minute you're going to take over the world, and the next you're doomed. The problem with feeling you're doomed is not just that it makes you unhappy, but that it makes you _stop working_.
这一领域的边界有多广?所有优秀的非营利组织都能成为好公司吗?未必。谷歌的价值在于其用户拥有消费能力。若能让有钱人喜欢你,你就能从中获利。但能否基于对无消费能力人群的慈善行为建立成功企业?例如,能否通过攻克疟疾这类不时尚但致命的疾病来发展初创公司?
我不确定,但推测若深挖这一思路,其潜力会令人惊讶。例如,Y Combinator的申请者通常并不富裕,但我们通过帮助他们获利,因为他们能借此创造财富。疟疾或许同理——帮助国家摆脱疟疾负担的组织,可能从随后的经济增长中受益。
我并非严肃提议此观点(我对疟疾一无所知),但多年构思经验让我能识别强大理念的苗头。
评估理念潜力的方法之一,是自问会在何时否定它。就像断言某事在技术上不可能一样,否定善意的力量同样危险——你只会自取其辱,因为这些力量过于强大。[2]
例如,起初我以为该原则仅适用于互联网初创公司。显然它对谷歌有效,但微软呢?微软肯定不怀善意吧?但回溯其初创时期,他们确实如此。相比IBM,他们就像罗宾汉。IBM推出个人电脑时,企图通过高价硬件获利。而微软通过掌控PC标准,向所有制造商开放市场。硬件价格暴跌,让原本无力负担的人群用上了电脑——这正是你会期待谷歌做的事。
So the downhills of the roller-coaster are more of a self fulfilling prophecy than the uphills. If feeling you're going to succeed makes you work harder, that probably improves your chances of succeeding, but if feeling you're going to fail makes you stop working, that practically guarantees you'll fail. Here's where benevolence comes in. If you feel you're really helping people, you'll keep working even when it seems like your startup is doomed. Most of us have some amount of natural benevolence. The mere fact that someone needs you makes you want to help them. So if you start the kind of startup where users come back each day, you've basically built yourself a giant tamagotchi. You've made something you need to take care of. Blogger is a famous example of a startup that went through really low lows and survived. At one point they ran out of money and everyone left. Evan Williams came in to work the next day, and there was no one but him. What kept him going? Partly that users needed him. He was hosting thousands of people's blogs. He couldn't just let the site die. There are many advantages of launching quickly, but the most important may be that once you have users, the tamagotchi effect kicks in. Once you have users to take care of, you're forced to figure out what will make them happy, and that's actually very valuable information. The added confidence that comes from trying to help people can also help you with investors. One of the founders of Chatterous told me recently that he and his cofounder had decided that this service was something the world needed, so they were going to keep working on it no matter what, even if they had to move back to Canada and live in their parents' basements. Once they realized this, they stopped caring so much what investors thought about them. They still met with them, but they weren't going to die if they didn't get their money.
如今的微软不再如此友善。提起他们对用户的所作所为,人们脑海中浮现的动词都以F开头[3]。但这似乎并未带来回报:其股价多年停滞。而在罗宾汉时期,股价如谷歌般飙升。二者有关联吗?
不难理解其中关联。弱小时你无法欺凌用户,只能取悦他们;强大后你便能肆意妄为,且往往如此——因为满足用户比压榨更费心力。企业因友善而壮大,却因傲慢而苟存。
这种状态能维持至环境剧变,届时所有受害者都将逃离。因此保罗·布赫海特为谷歌制定的"不作恶"准则或许是其最宝贵的贡献——它可能是企业青春的灵药。尽管谷歌觉得受约束,但若能避免重蹈微软和IBM的致命惰性,其价值不可估量。
奇妙的是,任何公司都能免费获取这剂灵药。谁都可以采纳"不作恶"原则。但关键在于人们会以此要求你——因此唱片公司或烟草企业绝不会运用这一发现。
大量外部证据表明善意行之有效。其机制如何?投资大量初创公司的优势在于能获取丰富运营数据。根据观察,善意主要通过三种方式助力初创公司:提升士气、吸引外部帮助,以及最重要的——增强决策力。
士气对初创公司至关重要,其影响力几乎能单独决定成败。初创公司常被形容为情绪过山车:这一刻觉得即将征服世界,下一刻又感到濒临绝境。陷入绝望的问题不仅在于情绪低落,更在于它会让人停止工作——因此低谷比高峰更具自我实现性。若成功信念能激励工作,它确实可能提升成功概率;但若失败预期导致停工,则几乎注定失败。
And you know what? The investors got a lot more interested. They could sense that the Chatterouses were going to do this startup with or without them. If you're really committed and your startup is cheap to run, you become very hard to kill. And practically all startups, even the most successful, come close to death at some point. So if doing good for people gives you a sense of mission that makes you harder to kill, that alone more than compensates for whatever you lose by not choosing a more selfish project. Help Another advantage of being good is that it makes other people want to help you. This too seems to be an inborn trait in humans. One of the startups we've funded, Octopart, is currently locked in a classic battle of good versus evil. They're a search site for industrial components. A lot of people need to search for components, and before Octopart there was no good way to do it. That, it turned out, was no coincidence. Octopart built the right way to search for components. Users like it and they've been growing rapidly. And yet for most of Octopart's life, the biggest distributor, Digi-Key, has been trying to force them take their prices off the site. Octopart is sending them customers for free, and yet Digi-Key is trying to make that traffic stop. Why? Because their current business model depends on overcharging people who have incomplete information about prices. They don't want search to work. The Octoparts are the nicest guys in the world. They dropped out of the PhD program in physics at Berkeley to do this. They just wanted to fix a problem they encountered in their research. Imagine how much time you could save the world's engineers if they could do searches online. So when I hear that a big, evil company is trying to stop them in order to keep search broken, it makes me really want to help them.
此时善意开始发挥作用。若确信自己在真正帮助他人,即便公司看似濒临绝境,你也会坚持工作。多数人天生具备善意——仅仅被需要就会激发助人欲望。因此若创建的用户产品需要每日维护,你本质上建造了一个巨型电子宠物——一个你必须照料的事物。
Blogger是经历低谷又幸存下来的著名案例。他们曾资金耗尽、团队解散。次日埃文·威廉姆斯独自上班时,空荡的办公室只剩他一人。是什么支撑着他?部分原因在于用户需要他——他托管着成千上万的博客,不能让网站消亡。
快速发布有许多优点,但最重要的或许是触发"电子宠物效应"——拥有用户后,你被迫思考如何取悦他们,这实际上是非常宝贵的信息。
来自助人事业的额外信心也能助力融资。Chatterous的创始人曾告诉我,他们认定这项服务是世界所需,因此无论如何都会继续开发,哪怕搬回加拿大住父母地下室。当他们不再在意投资人看法后,投资人反而更感兴趣了——因为他们能感受到这份坚定。
若怀抱真正信念且运营成本低廉,你的公司将极难被摧毁。几乎所有初创公司(包括最成功的)都曾濒临死亡。因此若善念能赋予你使命感的铠甲,其价值已远超选择自私项目可能带来的收益。
It makes me spend more time on the Octoparts than I do with most of the other startups we've funded. It just made me spend several minutes telling you how great they are. Why? Because they're good guys and they're trying to help the world. If you're benevolent, people will rally around you: investors, customers, other companies, and potential employees. In the long term the most important may be the potential employees. I think everyone knows now that good hackers are much better than mediocre ones. If you can attract the best hackers to work for you, as Google has, you have a big advantage. And the very best hackers tend to be idealistic. They're not desperate for a job. They can work wherever they want. So most want to work on things that will make the world better. Compass But the most important advantage of being good is that it acts as a compass. One of the hardest parts of doing a startup is that you have so many choices. There are just two or three of you, and a thousand things you could do. How do you decide? Here's the answer: Do whatever's best for your users. You can hold onto this like a rope in a hurricane, and it will save you if anything can. Follow it and it will take you through everything you need to do. It's even the answer to questions that seem unrelated, like how to convince investors to give you money. If you're a good salesman, you could try to just talk them into it. But the more reliable route is to convince them through your users: if you make something users love enough to tell their friends, you grow exponentially, and that will convince any investor. Being good is a particularly useful strategy for making decisions in complex situations because it's stateless. It's like telling the truth. The trouble with lying is that you have to remember everything you've said in the past to make sure you don't contradict yourself.
行善的另一优势是能吸引他人相助。这似乎也是人类的天性。
我们投资的Octopart正深陷一场典型的善恶之战。作为工业零件搜索引擎,用户迫切需要此类服务,而此前解决方案的缺失并非偶然。
Octopart构建了理想的搜索方式,用户喜爱且增长迅速。然而其发展过程中,最大分销商Digi-Key一直施压要求撤下价格信息。Octopart免费为其导流,对方却试图阻断——因为现有商业模式依赖于信息不对称的高价销售。他们不希望搜索生效。
Octopart团队是世界上最善良的人。他们从伯克利物理博士项目退学,只为解决研究中遭遇的问题。想象一下,若能实现在线搜索,能为全球工程师节省多少时间?因此当我听说邪恶巨头为维持搜索瘫痪而打压他们时,助人之心油然而生。这使我投入给Octopart的时间远超其他被投公司,此刻更不惜笔墨为其发声——因为他们正在努力让世界变得更好。
若你心怀善意,投资者、客户、合作伙伴及潜在员工都会聚集而来。长期来看,潜在员工最为关键。如今人尽皆知优秀黑客远胜平庸之辈。若能如谷歌般吸引顶尖黑客,你将获得巨大优势。而顶尖黑客往往理想主义——他们并非求职无门,可以自由选择工作。因此多数人希望从事改善世界的事业。
If you tell the truth you don't have to remember anything, and that's a really useful property in domains where things happen fast. For example, Y Combinator has now invested in 80 startups, 57 of which are still alive. (The rest have died or merged or been acquired.) When you're trying to advise 57 startups, it turns out you have to have a stateless algorithm. You can't have ulterior motives when you have 57 things going on at once, because you can't remember them. So our rule is just to do whatever's best for the founders. Not because we're particularly benevolent, but because it's the only algorithm that works on that scale. When you write something telling people to be good, you seem to be claiming to be good yourself. So I want to say explicitly that I am not a particularly good person. When I was a kid I was firmly in the camp of bad. The way adults used the word good, it seemed to be synonymous with quiet, so I grew up very suspicious of it. You know how there are some people whose names come up in conversation and everyone says "He's _such_ a great guy?" People never say that about me. The best I get is "he means well." I am not claiming to be good. At best I speak good as a second language. So I'm not suggesting you be good in the usual sanctimonious way. I'm suggesting it because it works. It will work not just as a statement of "values," but as a guide to strategy, and even a design spec for software. Don't just not be evil. Be good. Notes [1] Fifty years ago it would have seemed shocking for a public company not to pay dividends. Now many tech companies don't. The markets seem to have figured out how to value potential dividends. Maybe that isn't the last step in this evolution.
但行善最重要的优势在于它能充当指南针。创业最困难之处在于选择泛滥——两三人团队面对千头万绪,如何抉择?
答案很简单:做对用户最有利的事。这如同飓风中的绳索,是拯救你的唯一依凭。遵循它,你将穿越所有必经之路。
它甚至能解答看似无关的问题,比如如何说服投资者。若擅长销售,你或许能靠话术达成。但更可靠的途径是通过用户说服他们——若产品让用户爱到主动推荐,指数增长自会打动任何投资人。
在复杂情境中,善意作为无状态策略尤为有效。它如同说真话——谎言的麻烦在于必须记忆所有过往陈述以避免矛盾,而真相无需记忆。这在快速变化的领域极为珍贵。
例如,Y Combinator已投资80家初创公司(57家存活)。当需要为57家公司提供建议时,无状态算法成为唯一选择——你无法同时记住57个隐藏动机。因此我们的准则很简单:做对创始人最有利的事。并非因我们特别高尚,而是因为这是唯一可行的规模化策略。
Maybe markets will eventually get comfortable with potential earnings. (VCs already are, and at least some of them consistently make money.) I realize this sounds like the stuff one used to hear about the "new economy" during the Bubble. Believe me, I was not drinking that kool-aid at the time. But I'm convinced there were some good ideas buried in Bubble thinking. For example, it's ok to focus on growth instead of profits—but only if the growth is genuine. You can't be buying users; that's a pyramid scheme. But a company with rapid, genuine growth is valuable, and eventually markets learn how to value valuable things. [2] The idea of starting a company with benevolent aims is currently undervalued, because the kind of people who currently make that their explicit goal don't usually do a very good job. It's one of the standard career paths of trustafarians to start some vaguely benevolent business. The problem with most of them is that they either have a bogus political agenda or are feebly executed. The trustafarians' ancestors didn't get rich by preserving their traditional culture; maybe people in Bolivia don't want to either. And starting an organic farm, though it's at least straightforwardly benevolent, doesn't help people on the scale that Google does. Most explicitly benevolent projects don't hold themselves sufficiently accountable. They act as if having good intentions were enough to guarantee good effects. [3] Users dislike their new operating system so much that they're starting petitions to save the old one. And the old one was nothing special.
撰文劝人行善时,似乎暗示作者本身为善。因此我要明确声明:我并非特别善良的人。童年时我坚定站在"坏孩子"阵营——成人语境中的"好"总与"安静"同义,这让我始终对其保持警惕。
你知道有些人被提及时,众人会赞叹"他真是个好人"吗?从无人如此评价我。最多说我"本意不坏"。我并非以善者自居——至多算是将善良作为第二语言。
因此我并非以常见的道貌岸然姿态劝善,而是因为它切实有效。它不仅是"价值观"宣言,更是战略指南,甚至是软件设计规范。不要仅仅"不作恶",要主动"行善"。
注释 [1] 五十年前,上市公司不派息会令人震惊。如今许多科技公司都如此。市场似乎已学会估值潜在股息。或许这并非演化的终点——市场终将适应估值潜在收益。(风投已做到这点,且至少部分机构持续盈利。)
这听起来像泡沫时期"新经济"的论调。相信我,当时我并未被洗脑。但我确信泡沫思维中埋藏着好点子。例如,专注增长而非利润可行——但仅限于真实增长。购买用户是庞氏骗局,而真实快速增长的公司终将获得市场合理估值。
The hackers within Microsoft must know in their hearts that if the company really cared about users they'd just advise them to switch to OSX. Thanks to Trevor Blackwell, Paul Buchheit, Jessica Livingston, and Robert Morris for reading drafts of this.
Want to start a startup? Get funded by Y Combinator.
April 2008 Umair Haque wrote recently that the reason there aren't more Googles is that most startups get bought before they can change the world.
想创办一家初创公司? 获得 Y Combinator 的资金支持。
2008年4月 乌迈尔·哈克最近写道,世界上没有出现更多谷歌的原因在于,大多数初创公司在改变世界之前就被收购了。
> 尽管微软和雅虎曾对谷歌表现出浓厚兴趣——当时看来这可能是极具诱惑力的机会——谷歌并未选择出售。否则,今天的谷歌或许只会沦为雅虎或MSN的一个搜索框。 > > 为什么没有发生这种情况?因为谷歌怀有深植内心的使命感:坚信要让世界变得更美好。
这听起来很美好,但并非事实。谷歌的创始人早期是愿意出售公司的,只是他们的要价超出了收购方的心理预期。
Facebook的情况如出一辙。他们本可以成交,但雅虎因出价过低错失良机。
> Google, despite serious interest from Microsoft and Yahoo—what must have seemed like lucrative interest at the time—didn't sell out. Google might simply have been nothing but Yahoo's or MSN's search box. > > Why isn't it? Because Google had a deeply felt sense of purpose: a conviction to change the world for the better.
给收购方的小贴士:当初创企业拒绝你时,不妨提高报价——因为他们此刻看似离谱的要价,日后很可能会显得像捡了便宜。[1]
根据我目前观察到的证据,拒绝收购要约的初创企业通常会有更好的发展。虽然并非绝对,但往往会有更高报价接踵而至,甚至可能迎来IPO。
当然,初创企业拒绝收购后表现更好,未必是因为所有报价都低估了其价值。更可能的原因是:敢于拒绝巨额收购的创始人类型,往往正是能取得巨大成功的那类人。这种精神正是初创企业最需要的特质。
尽管我确信拉里和佩奇确实想改变世界(至少现在如此),但谷歌能存活并成长为独立巨头的原因,与Facebook至今保持独立的原因相同:收购方低估了他们。
This has a nice sound to it, but it isn't true. Google's founders were willing to sell early on. They just wanted more than acquirers were willing to pay. It was the same with Facebook. They would have sold, but Yahoo blew it by offering too little. Tip for acquirers: when a startup turns you down, consider raising your offer, because there's a good chance the outrageous price they want will later seem a bargain. [1] From the evidence I've seen so far, startups that turn down acquisition offers usually end up doing better. Not always, but usually there's a bigger offer coming, or perhaps even an IPO. Of course, the reason startups do better when they turn down acquisition offers is not necessarily that all such offers undervalue startups. More likely the reason is that the kind of founders who have the balls to turn down a big offer also tend to be very successful. That spirit is exactly what you want in a startup. While I'm sure Larry and Sergey do want to change the world, at least now, the reason Google survived to become a big, independent company is the same reason Facebook has so far remained independent: acquirers underestimated them. Corporate M&A is a strange business in that respect. They consistently lose the best deals, because turning down reasonable offers is the most reliable test you could invent for whether a startup will make it big. VCs So what's the real reason there aren't more Googles? Curiously enough, it's the same reason Google and Facebook have remained independent: money guys undervalue the most innovative startups. The reason there aren't more Googles is not that investors encourage innovative startups to sell out, but that they won't even fund them. I've learned a lot about VCs during the 3 years we've been doing Y Combinator, because we often have to work quite closely with them. The most surprising thing I've learned is how conservative they are.
企业并购在这方面是个奇特的领域。他们总是错失最优质的交易,因为"拒绝合理报价"堪称检验初创企业能否成就伟业的最可靠试金石。
那么为何再难孕育更多谷歌?耐人寻味的是,答案与谷歌、Facebook保持独立的原因如出一辙:资本方低估了最具创新力的初创企业。
症结不在于投资者鼓励创新型企业出售,而在于他们根本不愿投资这类企业。通过YC三年来的运作(我们常需与风投密切合作),我对VC有了全新认知。最令我惊讶的是他们惊人的保守程度。尽管VC机构总以"大胆鼓励创新"的形象示人,但真正践行者凤毛麟角——即便这些少数派,其实际作风也比官网宣传的保守得多。
我曾将VC视作海盗:胆大妄为但毫无原则。深入了解后才发现他们更像官僚。他们比我预想的更正直(至少优秀机构如此),但远不够勇敢。或许VC行业已今非昔比,又或许初创企业的世界发生了巨变。如今创业成本骤降意味着优质标的往往风险更高,但多数VC仍固守1985年投资硬件创业公司的思维定式。
VC firms present an image of boldly encouraging innovation. Only a handful actually do, and even they are more conservative in reality than you'd guess from reading their sites. I used to think of VCs as piratical: bold but unscrupulous. On closer acquaintance they turn out to be more like bureaucrats. They're more upstanding than I used to think (the good ones, at least), but less bold. Maybe the VC industry has changed. Maybe they used to be bolder. But I suspect it's the startup world that has changed, not them. The low cost of starting a startup means the average good bet is a riskier one, but most existing VC firms still operate as if they were investing in hardware startups in 1985. Howard Aiken said "Don't worry about people stealing your ideas. If your ideas are any good, you'll have to ram them down people's throats." I have a similar feeling when I'm trying to convince VCs to invest in startups Y Combinator has funded. They're terrified of really novel ideas, unless the founders are good enough salesmen to compensate. But it's the bold ideas that generate the biggest returns. Any really good new idea will seem bad to most people; otherwise someone would already be doing it. And yet most VCs are driven by consensus, not just within their firms, but within the VC community. The biggest factor determining how a VC will feel about your startup is how other VCs feel about it. I doubt they realize it, but this algorithm guarantees they'll miss all the very best ideas. The more people who have to like a new idea, the more outliers you lose. Whoever the next Google is, they're probably being told right now by VCs to come back when they have more "traction." Why are VCs so conservative? It's probably a combination of factors. The large size of their investments makes them conservative. Plus they're investing other people's money, which makes them worry they'll get in trouble if they do something risky and it fails.
霍华德·艾肯曾说:"别担心别人窃取你的创意。若想法真够出色,你得硬塞进别人喉咙才行。"当我试图说服VC投资YC孵化的项目时深有同感。他们对真正新颖的创意充满恐惧——除非创始人具备超强说服力。
但最大回报恰恰来自最大胆的构想。任何绝妙的新点子对多数人来说都像坏主意(否则早有人实施了)。可悲的是,多数VC的决策受制于共识——不仅限于机构内部,更蔓延至整个投资圈。VC对项目的评判标准,很大程度上取决于同行态度。这种机制注定会让他们错过所有最卓越的创意,尽管他们未必意识到。需要取悦的人越多,离经叛道的天才就越容易被埋没。
此刻,某个可能成为"下一个谷歌"的团队,大概率正被VC建议"等有了更多市场验证再来"。
VC为何如此保守?多重因素交织:大额投资天然催生保守心态;管理他人资金带来的问责压力;更关键的是,他们多数是金融背景而非技术专家,根本看不懂所投项目的技术内核。
Plus most of them are money guys rather than technical guys, so they don't understand what the startups they're investing in do. What's Next The exciting thing about market economies is that stupidity equals opportunity. And so it is in this case. There is a huge, unexploited opportunity in startup investing. Y Combinator funds startups at the very beginning. VCs will fund them once they're already starting to succeed. But between the two there is a substantial gap. There are companies that will give $20k to a startup that has nothing more than the founders, and there are companies that will give $2 million to a startup that's already taking off, but there aren't enough investors who will give $200k to a startup that seems very promising but still has some things to figure out. This territory is occupied mostly by individual angel investors—people like Andy Bechtolsheim, who gave Google $100k when they seemed promising but still had some things to figure out. I like angels, but there just aren't enough of them, and investing is for most of them a part time job. And yet as it gets cheaper to start startups, this sparsely occupied territory is becoming more and more valuable. Nowadays a lot of startups don't want to raise multi-million dollar series A rounds. They don't need that much money, and they don't want the hassles that come with it. The median startup coming out of Y Combinator wants to raise $250-500k. When they go to VC firms they have to ask for more because they know VCs aren't interested in such small deals. VCs are money managers. They're looking for ways to put large sums to work. But the startup world is evolving away from their current model. Startups have gotten cheaper. That means they want less money, but also that there are more of them. So you can still get large returns on large amounts of money; you just have to spread it more broadly. I've tried to explain this to VC firms.
市场经济最激动人心之处在于:愚蠢即机遇。当前创投领域正存在巨大空白。YC专注种子轮,VC青睐初显成功迹象的项目,但两者间存在断层地带。
现有格局是:既有机构愿给"光杆司令团队"投20万美元,也有机构敢对起飞项目砸200万美元,但鲜有投资者愿为"前景光明但尚存不确定性"的项目提供20万美元级支持。这个领域目前主要依靠像安迪·贝托尔斯海姆这样的天使投资人(他曾给未成形的谷歌10万美元)。天使虽好但数量有限,且多数只是兼职投资。
随着创业成本持续降低,这片投资蓝海正愈发珍贵。如今许多初创企业根本不需要千万美元级的A轮融资——既无此需求,更不愿承受随之而来的麻烦。YC毕业项目的融资中位数是25-50万美元。当他们接触VC时不得不提高额度,因为深知后者对小额交易兴趣缺缺。
VC本质是资金管理者,追求大额资金配置。但创业生态正与其现行模式背道而驰:创业成本降低既意味着单项目需求减少,也预示着项目数量激增。要获取巨额回报,只需将资金更分散地配置。
Instead of making one $2 million investment, make five $400k investments. Would that mean sitting on too many boards? Don't sit on their boards. Would that mean too much due diligence? Do less. If you're investing at a tenth the valuation, you only have to be a tenth as sure. It seems obvious. But I've proposed to several VC firms that they set aside some money and designate one partner to make more, smaller bets, and they react as if I'd proposed the partners all get nose rings. It's remarkable how wedded they are to their standard m.o. But there is a big opportunity here, and one way or the other it's going to get filled. Either VCs will evolve down into this gap or, more likely, new investors will appear to fill it. That will be a good thing when it happens, because these new investors will be compelled by the structure of the investments they make to be ten times bolder than present day VCs. And that will get us a lot more Googles. At least, as long as acquirers remain stupid. Notes [1] Another tip: If you want to get all that value, don't destroy the startup after you buy it. Give the founders enough autonomy that they can grow the acquisition into what it would have become. Thanks to Sam Altman, Paul Buchheit, David Hornik, Jessica Livingston, Robert Morris, and Fred Wilson for reading drafts of this.
我曾向多家VC提议:与其押注单笔200万美元,不如分散成5笔40万美元投资。他们担心董事会席位过多?大可不必入驻。顾虑尽调负担过重?降低标准即可——若估值仅为十分之一,把握性达十分之一便足矣。
道理如此浅显,但当我建议VC机构划拨专项资金、指定合伙人进行小额多投时,他们的反应仿佛我在提议全体合伙人穿鼻环。他们对标准化操作流程的执着令人叹为观止。
但历史机遇不会等人。要么VC主动下沉填补空白,更可能的情形是——新兴投资者将抢占这片沃土。这将是创业生态的福音,因为这类投资的结构特性将倒逼他们比现行VC勇敢十倍。届时,我们终将迎来更多谷歌般的传奇——至少,在收购方持续犯蠢的前提下。
注释 [1] 另一条建议:若想兑现全部价值,收购后别毁了初创企业。赋予创始人足够自主权,让他们把收购标的培育成本该成为的模样。
致谢 萨姆·奥尔特曼、保罗·布赫海特、大卫·霍尼克、杰西卡·利文斯顿、罗伯特·莫里斯和弗雷德·威尔逊对本文初稿的审阅。
March 2008 The web is turning writing into a conversation. Twenty years ago, writers wrote and readers read. The web lets readers respond, and increasingly they do—in comment threads, on forums, and in their own blog posts. Many who respond to something disagree with it. That's to be expected. Agreeing tends to motivate people less than disagreeing. And when you agree there's less to say. You could expand on something the author said, but he has probably already explored the most interesting implications. When you disagree you're entering territory he may not have explored. The result is there's a lot more disagreeing going on, especially measured by the word. That doesn't mean people are getting angrier. The structural change in the way we communicate is enough to account for it. But though it's not anger that's driving the increase in disagreement, there's a danger that the increase in disagreement will make people angrier. Particularly online, where it's easy to say things you'd never say face to face. If we're all going to be disagreeing more, we should be careful to do it well. What does it mean to disagree well? Most readers can tell the difference between mere name-calling and a carefully reasoned refutation, but I think it would help to put names on the intermediate stages. So here's an attempt at a disagreement hierarchy: DH0. Name-calling. This is the lowest form of disagreement, and probably also the most common. We've all seen comments like this: > u r a fag!!!!!!!!!!
互联网正在将写作转变为对话。二十年前,作者写作,读者阅读。而网络让读者能够回应,而且越来越多的人确实这样做了——在评论线程中、在论坛上、在他们自己的博客文章里。
许多回应表达了不同意见。这在意料之中。赞同往往比反对更难激发人们的表达欲。当你赞同时,可说的内容也更少。你可以对作者的观点进行扩展,但他可能已经探讨了最有趣的引申含义。而当你反对时,你进入的可能是他未曾探索的领域。
结果就是,现在发生的争论要多得多,尤其是以字数衡量。这并不意味着人们变得更愤怒了。我们交流方式的结构性变化足以解释这一点。但尽管愤怒并非争论增多的驱动力,争论的增多却有可能让人们变得更愤怒,尤其是在网络上,因为在这里人们很容易说出面对面时绝不会讲的话。
But it's important to realize that more articulate name-calling has just as little weight. A comment like
如果我们将要更多地争论,我们就应该注意好好争论。什么是好的争论?大多数读者都能分辨单纯的辱骂和经过仔细推敲的反驳之间的区别,但我认为给中间的阶段命名会有所帮助。因此,这里尝试提出一个争论层级:
DH0. 辱骂。
这是最低级的争论形式,可能也是最常见的。我们都见过这样的评论:
> 你是个白痴!!!!!!
> The author is a self-important dilettante.
但重要的是要意识到,更“文雅”的辱骂同样没有分量。像这样的评论:
> 作者是个自命不凡的半吊子。
其实不过是“你是个白痴”的装腔作势版。
DH1. 人身攻击。
is really nothing more than a pretentious version of "u r a fag." DH1. Ad Hominem. An ad hominem attack is not quite as weak as mere name-calling. It might actually carry some weight. For example, if a senator wrote an article saying senators' salaries should be increased, one could respond:
人身攻击并不像单纯的辱骂那样无力。它可能确实有一些分量。例如,如果一位参议员写了一篇文章说参议员的薪水应该提高,有人可能会回应:
> 他当然会这么说。他是个参议员。
这并不能反驳作者的论点,但至少可能与情况相关。不过,这仍然是一种非常弱的争论形式。如果参议员的论点有问题,你应该指出问题所在;如果没有问题,他是参议员又有什么关系呢?
> Of course he would say that. He's a senator.
声称作者缺乏讨论某个话题的资格是人身攻击的一种变体——而且是特别无用的那种,因为好的想法往往来自局外人。问题在于作者是否正确。如果他因为缺乏资格而犯了错误,那就指出这些错误。如果没有,那就不是问题。
DH2. 回应语气。
再往上一级,我们开始看到对文章而非作者的回应。其中最低级的形式是反对作者的语气。例如:
> 我无法相信作者竟以如此轻率的态度驳斥智能设计论。
This wouldn't refute the author's argument, but it may at least be relevant to the case. It's still a very weak form of disagreement, though. If there's something wrong with the senator's argument, you should say what it is; and if there isn't, what difference does it make that he's a senator? Saying that an author lacks the authority to write about a topic is a variant of ad hominem—and a particularly useless sort, because good ideas often come from outsiders. The question is whether the author is correct or not. If his lack of authority caused him to make mistakes, point those out. And if it didn't, it's not a problem. DH2. Responding to Tone. The next level up we start to see responses to the writing, rather than the writer. The lowest form of these is to disagree with the author's tone. E.g.
虽然比人身攻击要好,这仍是一种薄弱的反驳方式。作者观点的对错远比其语气重要——何况语气本身难以判断。某个对特定话题心存芥蒂的人,可能会被其他读者认为中立的语气所冒犯。
因此,若你对某观点最严厉的批评仅停留在语气层面,那你的反驳是苍白的。即便作者态度轻浮但观点正确呢?这总比严肃庄重却错误百出要好。若你认为作者有误,请明确指出错在何处。
DH3. 反驳
至此我们终于进入针对观点的回应,而非纠缠表达方式或发言者。对论点最低阶的回应,是仅提出对立主张却几乎不提供证据支撑。
> I can't believe the author dismisses intelligent design in such a cavalier fashion.
此类反驳常与DH2句式结合,例如:
> 我无法相信作者竟以如此轻率的态度驳斥智能设计论。智能设计论是合理的科学理论。
反驳有时可能有一定分量。有时仅仅看到对方观点被明确陈述,就足以意识到它是正确的。但通常证据会更有帮助。
DH4. 反驳论点。
Though better than attacking the author, this is still a weak form of disagreement. It matters much more whether the author is wrong or right than what his tone is. Especially since tone is so hard to judge. Someone who has a chip on their shoulder about some topic might be offended by a tone that to other readers seemed neutral. So if the worst thing you can say about something is to criticize its tone, you're not saying much. Is the author flippant, but correct? Better that than grave and wrong. And if the author is incorrect somewhere, say where. DH3. Contradiction. In this stage we finally get responses to what was said, rather than how or by whom. The lowest form of response to an argument is simply to state the opposing case, with little or no supporting evidence. This is often combined with DH2 statements, as in:
在第四层级,我们首次遇到具有说服力的反对形式:反驳论点。此前层级的反对通常可以忽略,因为它们无法证明什么。而反驳论点或许能证明某些东西。问题在于,很难确切说清它证明了什么。
反驳论点是反驳加上推理和/或证据。当它精准针对原论点时,可能具有说服力。但不幸的是,反驳论点常常针对的是略有不同的东西。很多时候,两个人激烈争论的其实是两件不同的事。有时他们甚至彼此认同,却因陷入争吵而未能察觉。
针对与原作者所言略有不同的内容进行反驳可能存在合理理由:比如你认为对方未触及问题核心。但这样做时,你应当明确声明这一点。
> I can't believe the author dismisses intelligent design in such a cavalier fashion. Intelligent design is a legitimate scientific theory.
DH5. 驳斥。
最具说服力的反对形式是驳斥。这也是最罕见的,因为它最费功夫。事实上,反对层级构成了一种金字塔——越往上层,实例越少。
要驳斥某人,你可能需要引用他们的话。你必须找到"确凿证据",即在你反对的内容中发现你认为错误的段落,然后解释为何它是错的。如果找不到可反对的具体引文,你可能是在攻击稻草人。
虽然驳斥通常需要引用,但引用并不必然意味着驳斥。有些作者会引用他们反对的内容片段,制造合理驳斥的假象,随后却给出低至DH3甚至DH0层级的回应。
Contradiction can sometimes have some weight. Sometimes merely seeing the opposing case stated explicitly is enough to see that it's right. But usually evidence will help. DH4. Counterargument. At level 4 we reach the first form of convincing disagreement: counterargument. Forms up to this point can usually be ignored as proving nothing. Counterargument might prove something. The problem is, it's hard to say exactly what. Counterargument is contradiction plus reasoning and/or evidence. When aimed squarely at the original argument, it can be convincing. But unfortunately it's common for counterarguments to be aimed at something slightly different. More often than not, two people arguing passionately about something are actually arguing about two different things. Sometimes they even agree with one another, but are so caught up in their squabble they don't realize it. There could be a legitimate reason for arguing against something slightly different from what the original author said: when you feel they missed the heart of the matter. But when you do that, you should say explicitly you're doing it. DH5. Refutation. The most convincing form of disagreement is refutation. It's also the rarest, because it's the most work. Indeed, the disagreement hierarchy forms a kind of pyramid, in the sense that the higher you go the fewer instances you find. To refute someone you probably have to quote them. You have to find a "smoking gun," a passage in whatever you disagree with that you feel is mistaken, and then explain why it's mistaken. If you can't find an actual quote to disagree with, you may be arguing with a straw man. While refutation generally entails quoting, quoting doesn't necessarily imply refutation. Some writers quote parts of things they disagree with to give the appearance of legitimate refutation, then follow with a response as low as DH3 or even DH0. DH6.
DH6. 驳斥核心论点。
驳斥的力度取决于你驳斥的内容。最有力的反对形式是驳斥对方的核心论点。
即便在DH5这样的高层级,我们仍会看到蓄意的不诚实行为,比如有人挑出论点的次要部分进行驳斥。有时这种行为的精神实质更像是一种复杂的人身攻击,而非真正的驳斥。例如,纠正对方的语法,或纠缠于名字、数字等小错误。除非对方论点确实依赖这些细节,否则纠正它们的唯一目的就是贬低对手。
真正的驳斥需要针对核心论点,或至少其中一个核心论点。这意味着必须明确承诺什么是核心论点。因此,真正有效的驳斥应当是这样的:
Refuting the Central Point. The force of a refutation depends on what you refute. The most powerful form of disagreement is to refute someone's central point. Even as high as DH5 we still sometimes see deliberate dishonesty, as when someone picks out minor points of an argument and refutes those. Sometimes the spirit in which this is done makes it more of a sophisticated form of ad hominem than actual refutation. For example, correcting someone's grammar, or harping on minor mistakes in names or numbers. Unless the opposing argument actually depends on such things, the only purpose of correcting them is to discredit one's opponent. Truly refuting something requires one to refute its central point, or at least one of them. And that means one has to commit explicitly to what the central point is. So a truly effective refutation would look like:.
> 作者的主要观点似乎是x。正如他所说: > >> > > 但这出于以下原因是错误的...
你指出的错误引述不必是作者核心观点的实际表述,只要能驳倒其依赖的前提就足够了。
现在我们有了分歧形式的分类标准。这有什么用?分歧金字塔_无法_直接判定胜负——它仅描述论述形式,而非正确性。即便第六层反驳也可能完全错误。
> The author's main point seems to be x. As he says: > >> > > But this is wrong for the following reasons...
但分歧层级虽不能决定说服力的下限,却能划定上限。第六层回应或许不够有力,但第二层及以下的争论永远缺乏说服力。
分类最显著的益处是帮助读者鉴别内容,尤其能识破知识欺诈。雄辩者仅凭强势措辞就能制造击败对手的假象,这恰是煽动家的本质特征。通过为分歧形式命名,我们为批判性读者提供了刺破虚妄的利器。
这种分类对写作者同样有益。多数知识欺诈实属无心之举——当某人抨击反对观点的语气时,或许真心认为自己在有效反驳。若能跳出局部看清所处层级,或许能激励他迈向真正的驳论或反驳。
但高质量分歧的最大价值不止于提升对话质量,更在于让对话者更快乐。观察对话可知,第一层的刻薄远多于第六层。当持有真知灼见时,你根本无需刻薄——事实上那只会适得其反。
The quotation you point out as mistaken need not be the actual statement of the author's main point. It's enough to refute something it depends upon. What It Means Now we have a way of classifying forms of disagreement. What good is it? One thing the disagreement hierarchy _doesn't_ give us is a way of picking a winner. DH levels merely describe the form of a statement, not whether it's correct. A DH6 response could still be completely mistaken. But while DH levels don't set a lower bound on the convincingness of a reply, they do set an upper bound. A DH6 response might be unconvincing, but a DH2 or lower response is always unconvincing. The most obvious advantage of classifying the forms of disagreement is that it will help people to evaluate what they read. In particular, it will help them to see through intellectually dishonest arguments. An eloquent speaker or writer can give the impression of vanquishing an opponent merely by using forceful words. In fact that is probably the defining quality of a demagogue. By giving names to the different forms of disagreement, we give critical readers a pin for popping such balloons. Such labels may help writers too. Most intellectual dishonesty is unintentional. Someone arguing against the tone of something he disagrees with may believe he's really saying something. Zooming out and seeing his current position on the disagreement hierarchy may inspire him to try moving up to counterargument or refutation. But the greatest benefit of disagreeing well is not just that it will make conversations better, but that it will make the people who have them happier. If you study conversations, you find there is a lot more meanness down in DH1 than up in DH6. You don't have to be mean when you have a real point to make. In fact, you don't want to. If you have something real to say, being mean just gets in the way.
If moving up the disagreement hierarchy makes people less mean, that will make most of them happier. Most people don't really enjoy being mean; they do it because they can't help it. Thanks to Trevor Blackwell and Jessica Livingston for reading drafts of this. Related:
What You Can't Say | The Age of the Essay Italian Translation | Russian Translation Swedish Translation | Spanish Translation German Translation | French Translation Arabic Translation | Finnish Translation Italian Translation | Turkish Translation.
[](https://s.turbifycdn.com/aah/paulgraham/a-new-venture-animal-11.gif) March 2008, rev May 2013 _(This essay grew out of something I wrote for myself to figure out what we do. Even though Y Combinator is now 3 years old, we're still trying to understand its implications.)_ I was annoyed recently to read a description of Y Combinator that said "Y Combinator does seed funding for startups." What was especially annoying about it was that I wrote it. This doesn't really convey what we do. And the reason it's inaccurate is that, paradoxically, funding very early stage startups is not mainly about funding. Saying YC does seed funding for startups is a description in terms of earlier models. It's like calling a car a horseless carriage. When you scale animals you can't just keep everything in proportion. For example, volume grows as the cube of linear dimension, but surface area only as the square. So as animals get bigger they have trouble radiating heat. That's why mice and rabbits are furry and elephants and hippos aren't. You can't make a mouse by scaling down an elephant. YC represents a new, smaller kind of animal—so much smaller that all the rules are different. Before us, most companies in the startup funding business were venture capital funds. VCs generally fund later stage companies than we do. And they supply so much money that, even though the other things they do may be very valuable, it's not that inaccurate to regard VCs as sources of money. Good VCs are "smart money," but they're still money. All good investors supply a combination of money and help. But these scale differently, just as volume and surface area do. Late stage investors supply huge amounts of money and comparatively little help: when a company about to go public gets a mezzanine round of $50 million, the deal tends to be almost entirely about money.
As you move earlier in the venture funding process, the ratio of help to money increases, because earlier stage companies have different needs. Early stage companies need less money because they're smaller and cheaper to run, but they need more help because life is so precarious for them. So when VCs do a series A round for, say, $2 million, they generally expect to offer a significant amount of help along with the money. Y Combinator occupies the earliest end of the spectrum. We're at least one and generally two steps before VC funding. (Though some startups go straight from YC to VC, the most common trajectory is to do an angel round first.) And what happens at Y Combinator is as different from what happens in a series A round as a series A round is from a mezzanine financing. At our end, money is almost a negligible factor. The startup usually consists of just the founders. Their living expenses are the company's main expense, and since most founders are under 30, their living expenses are low. But at this early stage companies need a lot of help. Practically every question is still unanswered. Some companies we've funded have been working on their software for a year or more, but others haven't decided what to work on, or even who the founders should be. When PR people and journalists recount the histories of startups after they've become big, they always underestimate how uncertain things were at first. They're not being deliberately misleading. When you look at a company like Google, it's hard to imagine they could once have been small and helpless. Sure, at one point they were a just a couple guys in a garage—but even then their greatness was assured, and all they had to do was roll forward along the railroad tracks of destiny. Far from it. A lot of startups with just as promising beginnings end up failing. Google has such momentum now that it would be hard for anyone to stop them.
But all it would have taken in the beginning would have been for two Google employees to focus on the wrong things for six months, and the company could have died. We know, because we've been there, just how vulnerable startups are in the earliest phases. Curiously enough, that's why founders tend to get so rich from them. Reward is always proportionate to risk, and very early stage startups are insanely risky. What we really do at Y Combinator is get startups launched straight. One of many metaphors you could use for YC is a steam catapult on an aircraft carrier. We get startups airborne. Barely airborne, but enough that they can accelerate fast. When you're launching planes they have to be set up properly or you're just launching projectiles. They have to be pointed straight down the deck; the wings have to be trimmed properly; the engines have to be at full power; the pilot has to be ready. These are the kind of problems we deal with. After we fund startups we work closely with them for three months—so closely in fact that we insist they move to where we are. And what we do in those three months is make sure everything is set up for launch. If there are tensions between cofounders we help sort them out. We get all the paperwork set up properly so there are no nasty surprises later. If the founders aren't sure what to focus on first, we try to figure that out. If there is some obstacle right in front of them, we either try to remove it, or shift the startup sideways. The goal is to get every distraction out of the way so the founders can use that time to build (or finish building) something impressive. And then near the end of the three months we push the button on the steam catapult in the form of Demo Day, where the current group of startups present to pretty much every investor in Silicon Valley. Launching companies isn't identical with launching products.
Though we do spend a lot of time on launch strategies for products, there are some things that take too long to build for a startup to launch them before raising their next round of funding. Several of the most promising startups we've funded haven't launched their products yet, but are definitely launched as companies. In the earliest stage, startups not only have more questions to answer, but they tend to be different kinds of questions. In later stage startups the questions are about deals, or hiring, or organization. In the earliest phase they tend to be about technology and design. What do you make? That's the first problem to solve. That's why our motto is "Make something people want." This is always a good thing for companies to do, but it's even more important early on, because it sets the bounds for every other question. Who you hire, how much money you raise, how you market yourself—they all depend on what you're making. Because the early problems are so much about technology and design, you probably need to be hackers to do what we do. While some VCs have technical backgrounds, I don't know any who still write code. Their expertise is mostly in business—as it should be, because that's the kind of expertise you need in the phase between series A and (if you're lucky) IPO. We're so different from VCs that we're really a different kind of animal. Can we claim founders are better off as a result of this new type of venture firm? I'm pretty sure the answer is yes, because YC is an improved version of what happened to our startup, and our case was not atypical. We started Viaweb with $10,000 in seed money from our friend Julian. He was a lawyer and arranged all our paperwork, so we could just code. We spent three months building a version 1, which we then presented to investors to raise more money. Sounds familiar, doesn't it? But YC improves on that significantly.
Julian knew a lot about law and business, but his advice ended there; he was not a startup guy. So we made some basic mistakes early on. And when we presented to investors, we presented to only 2, because that was all we knew. If we'd had our later selves to encourage and advise us, and Demo Day to present at, we would have been in much better shape. We probably could have raised money at 3 to 5 times the valuation we did. If we take 7% of a company we fund, the founders only have to do 7.5% better in their next round of funding to end up net ahead. We certainly manage that. So who is our 7% coming out of? If the founders end up net ahead it's not coming out of them. So is it coming out of later stage investors? Well, they do end up paying more. But I think they pay more because the company is actually more valuable. And later stage investors have no problem with that. The returns of a VC fund depend on the quality of the companies they invest in, not how cheaply they can buy stock in them. If what we do is useful, why wasn't anyone doing it before? There are two answers to that. One is that people were doing it before, just haphazardly on a smaller scale. Before us, seed funding came primarily from individual angel investors. Larry and Sergey, for example, got their seed funding from Andy Bechtolsheim, one of the founders of Sun. And because he was a startup guy he probably gave them useful advice. But raising money from angel investors is a hit or miss thing. It's a sideline for most of them, so they only do a handful of deals a year and they don't spend a lot of time on the startups they invest in. And they're hard to reach, because they don't want random startups pestering them with business plans. The Google guys were lucky because they knew someone who knew Bechtolsheim. It generally takes a personal introduction with angels.
The other reason no one was doing quite what we do is that till recently it was a lot more expensive to start a startup. You'll notice we haven't funded any biotech startups. That's still expensive. But advancing technology has made web startups so cheap that you really can get a company airborne for $15,000. If you understand how to operate a steam catapult, at least. So in effect what's happened is that a new ecological niche has opened up, and Y Combinator is the new kind of animal that has moved into it. We're not a replacement for venture capital funds. We occupy a new, adjacent niche. And conditions in our niche are really quite different. It's not just that the problems we face are different; the whole structure of the business is different. VCs are playing a zero-sum game. They're all competing for a slice of a fixed amount of "deal flow," and that explains a lot of their behavior. Whereas our m.o. is to create new deal flow, by encouraging hackers who would have gotten jobs to start their own startups instead. We compete more with employers than VCs. It's not surprising something like this would happen. Most fields become more specialized—more articulated—as they develop, and startups are certainly an area in which there has been a lot of development over the past couple decades. The venture business in its present form is only about forty years old. It stands to reason it would evolve. And it's natural that the new niche would at first be described, even by its inhabitants, in terms of the old one. But really Y Combinator is not in the startup funding business. Really we're more of a small, furry steam catapult. Thanks to Trevor Blackwell, Jessica Livingston, and Robert Morris for reading drafts of this. Comment on this essay..
[](https://s.turbifycdn.com/aah/paulgraham/a-new-venture-animal-11.gif) 2008年3月,2013年5月修订 _(本文源于我为厘清自身工作所写的笔记。尽管Y Combinator已成立三年,我们仍在探索其深层意义。)_ 最近读到一篇将Y Combinator描述为"为初创企业提供种子资金"的文章令我颇为不快——尤其这句话出自我本人之手。这远未传达我们的实质。吊诡的是,这种表述失准的原因在于:对极早期初创企业而言,资金恰恰是最不重要的环节。 用"种子资金"定义YC,就像将汽车称为"无马马车",是用旧范式描述新物种。 生物按比例缩放时并非简单等比。例如体积随尺寸立方增长,而表面积仅平方增长。因此大型动物面临散热难题,这解释了为何鼠兔被毛而象河马无毛——你无法通过缩小大象来制造老鼠。 YC代表一种更微小、更基础的新型生物——其规则体系已全然不同。 在我们之前,创投领域主导者是风险投资基金。风投通常投资更成熟的企业,其巨额注资使得"资金提供者"的定位虽不精确却勉强成立。优秀风投确是"聪明钱",但终究仍是钱。 所有优秀投资者都提供资金与帮助的组合。但二者缩放比例不同,正如体积与表面积。后期投资者提供海量资金与有限帮助:当准上市公司进行5000万美元夹层融资时,交易本质就是金钱游戏。越是早期项目,帮助与资金的比值越高,因其需求本质不同。早期企业运营成本低而生存脆弱,需要更多指导。因此当风投进行200万美元A轮融资时,通常承诺提供实质性帮扶。 YC处于光谱最左端。我们比风投至少早一至两个阶段(尽管部分项目会从YC直达风投,但更常见路径是先进行天使轮)。YC阶段与A轮的差异,堪比A轮与夹层融资之别。 在我们这一端,资金近乎可忽略。初创团队往往只有创始人,个人生活费即公司主要开支——而30岁以下的创始人生活成本极低。但此刻企业亟需全方位指导:几乎所有问题都悬而未决。有些被投团队已开发软件逾年,另一些却连创业方向或创始团队都未确定。 当公关人员与记者追溯成功企业的发家史时,总会低估早期的混沌状态。这并非刻意误导——面对谷歌这样的巨头,人们很难想象其曾弱小无助的模样。当然,他们确实始于车库创业,但仿佛天生就注定伟大,只需沿着命运轨道前行。 事实远非如此。无数起点同样闪耀的初创企业最终陨落。如今谷歌势不可挡,但初创期只需两名员工半年错配精力,就可能万劫不复。 我们深知初创企业在萌芽期的脆弱——奇妙的是,这也正是创始人能获取巨额财富的原因。回报永远与风险成正比,而极早期创业堪称疯狂赌博。 YC的本质工作是确保初创企业正确启航。可用航空母舰的蒸汽弹射器作喻:我们让企业勉强升空,获得加速空间。 弹射战机需精密调试,否则只是发射炮弹:必须对准甲板中线、精确调整机翼、引擎全速运转、飞行员准备就绪——这正是我们处理的课题。投资后的三个月里,我们要求团队搬迁至我们所在地进行深度协作,核心目标就是完成发射准备:调解创始人矛盾、规范法律文件、明确优先事项、清除前进障碍。最终在"演示日"按下弹射按钮——当天硅谷几乎所有投资者都将目睹这批企业的亮相。 企业发射不同于产品发布。虽然我们花费大量精力设计产品发布策略,但某些产品需要更长时间打磨。部分最具潜力的被投企业尚未发布产品,却已完成企业层面的起飞。 极早期阶段的问题不仅数量庞大,其性质也截然不同。后期企业关注交易、招聘或组织架构,而早期问题集中于技术与设计。"创造什么"是首要命题,因此我们的格言是"创造人们想要的东西"。这永远是企业真理,但对早期团队尤为关键——它划定所有后续问题的边界。招聘策略、融资规模、营销方案,皆取决于产品形态。 由于早期问题高度技术化,执行我们的工作必须懂编程。虽然部分风投具备技术背景,但我未见仍在写代码的从业者——这合情合理,因为A轮到IPO阶段更需要商业专长。 我们与风投差异如此之大,实属不同物种。这种新型创投机构真能让创始人获益吗?我确信如此,因为YC正是我们自身创业经历的升级版——当年我们用朋友朱利安提供的1万美元种子资金创立Viaweb。这位律师帮我们处理全部法律文件,让我们专注编程。三个月后带着初版产品向两位认识的投资者融资——听起来很熟悉吧?但YC显著优化了这个过程:朱利安虽精通法律商业,却非创业老手,导致我们犯下基础错误;若当时有"演示日"平台和过来人指导,估值可能提升3-5倍。 当我们收取7%股权时,创始人只需在下轮融资中表现优于基准7.5%即可净获益——这完全可实现。 那么7%的成本由谁承担?既然创始人净获益,显然非其负担。是后期投资者吗?他们确实支付更高价格,但源于企业真实价值提升——而这正是风投所求,其回报取决于企业质量而非持股成本。 若模式有效,为何前人未涉足?答案有二:其一,天使投资早有实践,但呈碎片化。谷歌双雄从Sun联合创始人安迪·贝托尔斯海姆处获得种子资金,这位创业前辈可能提供了宝贵建议。但天使投资充满随机性:作为副业,他们每年只投少数项目,投入时间有限且难以接触——通常需要私人引荐。 其二,直到最近创业成本才大幅降低。注意到我们从未投资生物技术领域了吗?因其仍属重资产。但技术进步使网络创业成本降至1.5万美元即可起飞——前提是你懂得操作蒸汽弹射器。 本质上,一个新生态位已然出现,YC正是入驻的新物种。我们非风投替代品,而是占据毗邻的新生态位——这里的游戏规则彻底改变。风投玩的是零和游戏,争夺固定"项目流"的份额;而我们通过激励程序员创业来创造新项目流,主要竞争对手实为雇主而非风投。 这种演变实属必然。多数领域都会随发展日趋专业化——过去二十年突飞猛进的创投行业(现代风投仅四十年历史)自然不例外。 新兴生态位最初被旧范式描述(即便由从业者自己)也在情理之中。但YC本质上不属于创业融资业——我们更像一台毛茸茸的小型蒸汽弹射器。 致谢 特雷弗·布莱克韦尔、杰西卡·利文斯顿和罗伯特·莫里斯审阅本文草稿。 评论本文。.
[](https://s.turbifycdn.com/aah/paulgraham/you-weren-t-meant-to-have-a-boss-11.gif) Want to start a startup? Get funded by Y Combinator.
March 2008, rev. June 2008 Technology tends to separate normal from natural. Our bodies weren't designed to eat the foods that people in rich countries eat, or to get so little exercise. There may be a similar problem with the way we work: a normal job may be as bad for us intellectually as white flour or sugar is for us physically. I began to suspect this after spending several years working with startup founders. I've now worked with over 200 of them, and I've noticed a definite difference between programmers working on their own startups and those working for large organizations. I wouldn't say founders seem happier, necessarily; starting a startup can be very stressful. Maybe the best way to put it is to say that they're happier in the sense that your body is happier during a long run than sitting on a sofa eating doughnuts. Though they're statistically abnormal, startup founders seem to be working in a way that's more natural for humans. I was in Africa last year and saw a lot of animals in the wild that I'd only seen in zoos before. It was remarkable how different they seemed. Particularly lions. Lions in the wild seem about ten times more alive. They're like different animals. I suspect that working for oneself feels better to humans in much the same way that living in the wild must feel better to a wide-ranging predator like a lion. Life in a zoo is easier, but it isn't the life they were designed for. Trees What's so unnatural about working for a big company? The root of the problem is that humans weren't meant to work in such large groups. Another thing you notice when you see animals in the wild is that each species thrives in groups of a certain size.
A herd of impalas might have 100 adults; baboons maybe 20; lions rarely 10. Humans also seem designed to work in groups, and what I've read about hunter-gatherers accords with research on organizations and my own experience to suggest roughly what the ideal size is: groups of 8 work well; by 20 they're getting hard to manage; and a group of 50 is really unwieldy. [1] Whatever the upper limit is, we are clearly not meant to work in groups of several hundred. And yet—for reasons having more to do with technology than human nature—a great many people work for companies with hundreds or thousands of employees. Companies know groups that large wouldn't work, so they divide themselves into units small enough to work together. But to coordinate these they have to introduce something new: bosses. These smaller groups are always arranged in a tree structure. Your boss is the point where your group attaches to the tree. But when you use this trick for dividing a large group into smaller ones, something strange happens that I've never heard anyone mention explicitly. In the group one level up from yours, your boss represents your entire group. A group of 10 managers is not merely a group of 10 people working together in the usual way. It's really a group of groups. Which means for a group of 10 managers to work together as if they were simply a group of 10 individuals, the group working for each manager would have to work as if they were a single person—the workers and manager would each share only one person's worth of freedom between them. In practice a group of people are never able to act as if they were one person. But in a large organization divided into groups in this way, the pressure is always in that direction. Each group tries its best to work as if it were the small group of individuals that humans were designed to work in. That was the point of creating it.
And when you propagate that constraint, the result is that each person gets freedom of action in inverse proportion to the size of the entire tree. [2] Anyone who's worked for a large organization has felt this. You can feel the difference between working for a company with 100 employees and one with 10,000, even if your group has only 10 people. Corn Syrup A group of 10 people within a large organization is a kind of fake tribe. The number of people you interact with is about right. But something is missing: individual initiative. Tribes of hunter-gatherers have much more freedom. The leaders have a little more power than other members of the tribe, but they don't generally tell them what to do and when the way a boss can. It's not your boss's fault. The real problem is that in the group above you in the hierarchy, your entire group is one virtual person. Your boss is just the way that constraint is imparted to you. So working in a group of 10 people within a large organization feels both right and wrong at the same time. On the surface it feels like the kind of group you're meant to work in, but something major is missing. A job at a big company is like high fructose corn syrup: it has some of the qualities of things you're meant to like, but is disastrously lacking in others. Indeed, food is an excellent metaphor to explain what's wrong with the usual sort of job. For example, working for a big company is the default thing to do, at least for programmers. How bad could it be? Well, food shows that pretty clearly. If you were dropped at a random point in America today, nearly all the food around you would be bad for you. Humans were not designed to eat white flour, refined sugar, high fructose corn syrup, and hydrogenated vegetable oil. And yet if you analyzed the contents of the average grocery store you'd probably find these four ingredients accounted for most of the calories. "Normal" food is terribly bad for you.
The only people who eat what humans were actually designed to eat are a few Birkenstock-wearing weirdos in Berkeley. If "normal" food is so bad for us, why is it so common? There are two main reasons. One is that it has more immediate appeal. You may feel lousy an hour after eating that pizza, but eating the first couple bites feels great. The other is economies of scale. Producing junk food scales; producing fresh vegetables doesn't. Which means (a) junk food can be very cheap, and (b) it's worth spending a lot to market it. If people have to choose between something that's cheap, heavily marketed, and appealing in the short term, and something that's expensive, obscure, and appealing in the long term, which do you think most will choose? It's the same with work. The average MIT graduate wants to work at Google or Microsoft, because it's a recognized brand, it's safe, and they'll get paid a good salary right away. It's the job equivalent of the pizza they had for lunch. The drawbacks will only become apparent later, and then only in a vague sense of malaise. And founders and early employees of startups, meanwhile, are like the Birkenstock-wearing weirdos of Berkeley: though a tiny minority of the population, they're the ones living as humans are meant to. In an artificial world, only extremists live naturally. Programmers The restrictiveness of big company jobs is particularly hard on programmers, because the essence of programming is to build new things. Sales people make much the same pitches every day; support people answer much the same questions; but once you've written a piece of code you don't need to write it again. So a programmer working as programmers are meant to is always making new things. And when you're part of an organization whose structure gives each person freedom in inverse proportion to the size of the tree, you're going to face resistance when you do something new.
This seems an inevitable consequence of bigness. It's true even in the smartest companies. I was talking recently to a founder who considered starting a startup right out of college, but went to work for Google instead because he thought he'd learn more there. He didn't learn as much as he expected. Programmers learn by doing, and most of the things he wanted to do, he couldn't—sometimes because the company wouldn't let him, but often because the company's code wouldn't let him. Between the drag of legacy code, the overhead of doing development in such a large organization, and the restrictions imposed by interfaces owned by other groups, he could only try a fraction of the things he would have liked to. He said he has learned much more in his own startup, despite the fact that he has to do all the company's errands as well as programming, because at least when he's programming he can do whatever he wants. An obstacle downstream propagates upstream. If you're not allowed to implement new ideas, you stop having them. And vice versa: when you can do whatever you want, you have more ideas about what to do. So working for yourself makes your brain more powerful in the same way a low-restriction exhaust system makes an engine more powerful. Working for yourself doesn't have to mean starting a startup, of course. But a programmer deciding between a regular job at a big company and their own startup is probably going to learn more doing the startup. You can adjust the amount of freedom you get by scaling the size of company you work for. If you start the company, you'll have the most freedom. If you become one of the first 10 employees you'll have almost as much freedom as the founders. Even a company with 100 people will feel different from one with 1000. Working for a small company doesn't ensure freedom. The tree structure of large organizations sets an upper bound on freedom, not a lower bound.
The head of a small company may still choose to be a tyrant. The point is that a large organization is compelled by its structure to be one. Consequences That has real consequences for both organizations and individuals. One is that companies will inevitably slow down as they grow larger, no matter how hard they try to keep their startup mojo. It's a consequence of the tree structure that every large organization is forced to adopt. Or rather, a large organization could only avoid slowing down if they avoided tree structure. And since human nature limits the size of group that can work together, the only way I can imagine for larger groups to avoid tree structure would be to have no structure: to have each group actually be independent, and to work together the way components of a market economy do. That might be worth exploring. I suspect there are already some highly partitionable businesses that lean this way. But I don't know any technology companies that have done it. There is one thing companies can do short of structuring themselves as sponges: they can stay small. If I'm right, then it really pays to keep a company as small as it can be at every stage. Particularly a technology company. Which means it's doubly important to hire the best people. Mediocre hires hurt you twice: they get less done, but they also make you big, because you need more of them to solve a given problem. For individuals the upshot is the same: aim small. It will always suck to work for large organizations, and the larger the organization, the more it will suck. In an essay I wrote a couple years ago I advised graduating seniors to work for a couple years for another company before starting their own. I'd modify that now. Work for another company if you want to, but only for a small one, and if you want to start your own startup, go ahead.
The reason I suggested college graduates not start startups immediately was that I felt most would fail. And they will. But ambitious programmers are better off doing their own thing and failing than going to work at a big company. Certainly they'll learn more. They might even be better off financially. A lot of people in their early twenties get into debt, because their expenses grow even faster than the salary that seemed so high when they left school. At least if you start a startup and fail your net worth will be zero rather than negative. [3] We've now funded so many different types of founders that we have enough data to see patterns, and there seems to be no benefit from working for a big company. The people who've worked for a few years do seem better than the ones straight out of college, but only because they're that much older. The people who come to us from big companies often seem kind of conservative. It's hard to say how much is because big companies made them that way, and how much is the natural conservatism that made them work for the big companies in the first place. But certainly a large part of it is learned. I know because I've seen it burn off. Having seen that happen so many times is one of the things that convinces me that working for oneself, or at least for a small group, is the natural way for programmers to live. Founders arriving at Y Combinator often have the downtrodden air of refugees. Three months later they're transformed: they have so much more confidence that they seem as if they've grown several inches taller. [4] Strange as this sounds, they seem both more worried and happier at the same time. Which is exactly how I'd describe the way lions seem in the wild. Watching employees get transformed into founders makes it clear that the difference between the two is due mostly to environment—and in particular that the environment in big companies is toxic to programmers.
In the first couple weeks of working on their own startup they seem to come to life, because finally they're working the way people are meant to. Notes [1] When I talk about humans being meant or designed to live a certain way, I mean by evolution. [2] It's not only the leaves who suffer. The constraint propagates up as well as down. So managers are constrained too; instead of just doing things, they have to act through subordinates. [3] Do not finance your startup with credit cards. Financing a startup with debt is usually a stupid move, and credit card debt stupidest of all. Credit card debt is a bad idea, period. It is a trap set by evil companies for the desperate and the foolish. [4] The founders we fund used to be younger (initially we encouraged undergrads to apply), and the first couple times I saw this I used to wonder if they were actually getting physically taller. Thanks to Trevor Blackwell, Ross Boucher, Aaron Iba, Abby Kirigin, Ivan Kirigin, Jessica Livingston, and Robert Morris for reading drafts of this.
[](https://s.turbifycdn.com/aah/paulgraham/you-weren-t-meant-to-have-a-boss-11.gif) 想创业吗? 获得 Y Combinator 的资金支持。
2008年3月,2008年6月修订 科技往往将“正常”与“自然”割裂。我们的身体本不适合富裕国家人们惯常的饮食方式,也不适应如此缺乏运动的生活。我们的工作方式或许存在类似问题:普通工作对智力的损害,可能不亚于白面粉或白糖对身体的伤害。 与初创公司创始人共事数年后,我开始怀疑这一点。如今我已接触过200多位创始人,明显注意到自主创业的程序员与为大机构工作的程序员之间存在差异。并非创始人一定更快乐——创业压力巨大。或许更准确的说法是,他们的快乐如同长跑时身体的状态:虽辛苦,却比瘫在沙发上吃甜甜圈更接近本质。 尽管从统计学看创始人属于异类,但他们的工作方式似乎更符合人类天性。 去年我在非洲目睹了许多曾只在动物园见过的野生动物,它们展现出的生命力令人震撼,尤其是狮子。野外的狮子活力是动物园里的十倍,简直是截然不同的生物。我猜想,为自己工作带给人类的愉悦,正如野外生存给狮子这类广域掠食者带来的满足。动物园生活更轻松,却非它们与生俱来的宿命。 树状结构 为大公司工作为何违背天性?根源在于人类本不适合在庞大群体中劳作。 观察野生动物时你会发现,每个物种都有其适宜的群体规模:黑斑羚群约100头,狒狒群约20只,狮群很少超过10头。人类同样适合小团体协作,根据我对狩猎采集部落的研究、组织行为学资料及个人经验,理想规模约为8人——20人已难管理,50人则彻底失控[1]。 无论上限如何,数百人的协作规模显然违背人性。然而受技术条件(而非人类本性)驱动,无数人供职于员工数以千计的企业。 企业明白大规模群体效率低下,于是拆分为小团队。但为协调这些单元,必须引入新事物:管理者。 这些小团队始终呈树状结构。你的上司是团队与组织树的连接点。但采用这种分割方式时,会发生某种无人明确指出的奇异现象:在你团队的上层结构中,你的老板代表着整个团队。10名经理组成的群体不仅是10人的协作单元,实质上是10个团队的集合。这意味着要让经理层像10人小组般运作,每个经理的团队必须如同单一个体般行动——员工与经理共享的决策自由度,仅相当于一个人的份额。 实践中群体永远无法像个体般行动。但在树状分割的大型组织里,压力始终指向这个方向。每个团队竭力模仿人类天性适应的小型协作单元(这正是拆分初衷),当约束层层传导,结果就是个人自由度与组织规模成反比[2]。 任何大公司员工都深有体会。万人企业与百人企业的体感差异,即便所在团队同为10人亦昭然若揭。 玉米糖浆 大公司里的10人团队是种虚假部落。互动人数看似合理,却缺失了关键要素:个人能动性。狩猎部落享有更多自由——首领虽比成员略有权势,但不会像现代老板那样发号施令。 这并非上司的过错。症结在于:在上级眼中,你的整个团队只是个虚拟个体,而老板不过是约束传导的中介。 因此大公司里的小团队既对且错:表面符合人类协作规模,内核却严重缺失。大公司职位如同高果糖玉米糖浆——具备某些吸引要素,却灾难性地缺乏关键养分。 用食物比喻能清晰阐释常规工作的弊端。 比如,大公司就业是程序员默认选择。这能有多糟?食物类比给出了答案:若随机空降美国,周围几乎全是垃圾食品。人类本不适合消化精制面粉、白糖、高果糖玉米糖浆及氢化植物油,但这些恰是超市货架上的热量主角。“正常”饮食极其有害,唯有伯克利几个穿勃肯鞋的怪人才吃符合人类天性的食物。 既然“正常”饮食如此糟糕,为何大行其道?主因有二:即时诱惑(披萨前几口的愉悦远胜一小时后不适)与规模经济(垃圾食品可工业化生产,新鲜蔬菜则不然)。这意味着(a)垃圾食品极其廉价,(b)值得巨额营销投入。 面对短期诱人、廉价且铺天盖地营销的产品,与昂贵、小众但长期有益的选择,多数人会如何抉择? 工作亦然。MIT毕业生趋之若鹜地加入谷歌微软——品牌响亮、待遇优厚、安全稳妥,这如同选择午餐披萨。弊端日后才会显现,且仅以模糊的萎靡感呈现。 与此同时,初创企业创始人及早期员工就像伯克利的勃肯鞋怪人:虽是人群极少数,却活出了人类应有的样子。在人工构建的世界里,唯有极端者才能自然生存。 程序员 大公司职位对程序员的束缚尤为严重,因为编程的本质是创造。销售日复一日重复话术,客服解答雷同问题,但代码一旦写完便无需重写。因此真正的程序员永远在创造。当组织架构使个人自由度与规模成反比时,创新必然遭遇阻力。 这是大企业无可避免的宿命,即便最聪明的公司也不例外。我曾与某位创始人交谈,他毕业时本欲创业,最终选择谷歌以求成长,却未达预期。程序员通过实践学习,而他想做的大多受阻——有时源于公司禁令,更多源于代码限制。在遗留系统拖累、大企业开发流程与跨团队接口约束下,他能尝试的想法十不存一。他说自主创业后学得更多(尽管需兼顾杂务与编程),至少编程时能随心所欲。 下游障碍会逆流传导。若无法实施新想法,创意便会枯竭。反之,行动自由催生更多创意。因此为自己工作能增强思维效能,如同低阻力排气系统提升引擎功率。 自主工作未必等于创业。但程序员若在大公司与创业间抉择,选择后者通常收获更多。 通过调整公司规模可调控自由度。创业获得最大自由,前10号员工享有近乎创始人的自由,百人公司体感亦与千人企业迥异。 小公司不必然保证自由——大树结构设定的是自由度上限而非下限。小公司老板仍可能独断专行,但大公司因其结构注定如此。 后果 这对组织和个人皆有深远影响。其一是企业壮大后必然减速,无论多努力保持创业活力——这是所有大型组织采用树状结构的宿命。 准确地说,唯有规避树状结构,大组织才可能避免减速。鉴于人性限制协作规模,我能设想的唯一方案是完全无结构:每个小组真正独立,像市场经济单元般协作。 这值得探索。某些高度可分业务已倾向此模式,但尚未见科技公司实践。 企业若不采用海绵结构,唯有一途:保持小规模。若我所言不虚,那么企业每个阶段都应尽可能精简,科技公司尤甚。这意味着顶尖人才至关重要——平庸员工造成双重伤害:效率低下且迫使团队膨胀。 对个人而言结论相同:瞄准小规模。为大组织工作永远令人窒息,规模越大窒息感越强。 两年前某篇文章中,我建议毕业生先为大公司工作两年再创业。现在我会修正:若想去大公司,只选小企业;若想创业,即刻出发。 当年建议源于对失败率的顾虑。的确多数会失败,但对雄心勃勃的程序员而言,失败的自创业远胜大公司工作。他们能学到更多,财务状况甚至可能更好——许多二十出头的年轻人陷入债务,因为支出膨胀速度远超初入社会时的高薪。创业失败至少净资产归零而非负数[3]。 我们资助过形形色色的创始人,数据显示大公司经历毫无助益。工作数年者看似优于应届生,但这纯粹源于年龄增长。 来自大公司的申请者往往显得保守。难辨多少源于大公司驯化,多少是其选择大公司的本性使然。但很大程度属后天习得——我见证过这种束缚的消散。 多次目睹这种转变让我确信:为自己或小团队工作,才是程序员的天性归宿。初到Y Combinator的创始人常带着难民般的颓唐,三个月后却脱胎换骨——自信暴涨如身高增长[4]。看似矛盾的是,他们同时更焦虑也更快乐,恰如我所描述的野生狮群状态。 目睹员工蜕变为创始人的过程清晰表明:二者差异主要源于环境——尤其大公司环境对程序员堪称毒害。开始创业的头几周,他们重获生机,只因终于以人类应有的方式工作。 注释 [1] 当提及人类“注定”或“设计”的生存方式时,我指进化塑造的结果。 [2] 不只基层员工受困。约束会双向传导,管理者同样受限——他们必须通过下属行动,无法亲力亲为。 [3] 切勿用信用卡融资创业。债务融资通常愚蠢,信用卡债务尤甚。信用卡债务是邪恶公司为绝望者和愚者设置的陷阱。 [4] 早期资助的创始人更年轻(最初我们鼓励本科生申请),前几次见到这种蜕变时,我甚至怀疑他们是否真的长高了。 致谢 感谢Trevor Blackwell、Ross Boucher、Aaron Iba、Abby Kirigin、Ivan Kirigin、Jessica Livingston和Robert Morris阅读本文草稿。
[](https://s.turbifycdn.com/aah/paulgraham/six-principles-for-making-new-things-11.gif) February 2008 The fiery reaction to the release of Arc had an unexpected consequence: it made me realize I had a design philosophy. The main complaint of the more articulate critics was that Arc seemed so flimsy. After years of working on it, all I had to show for myself were a few thousand lines of macros? Why hadn't I worked on more substantial problems? As I was mulling over these remarks it struck me how familiar they seemed. This was exactly the kind of thing people said at first about Viaweb, and Y Combinator, and most of my essays. When we launched Viaweb, it seemed laughable to VCs and e-commerce "experts." We were just a couple guys in an apartment, which did not seem cool in 1995 the way it does now. And the thing we'd built, as far as they could tell, wasn't even software. Software, to them, equalled big, honking Windows apps. Since Viaweb was the first web-based app they'd seen, it seemed to be nothing more than a website. They were even more contemptuous when they discovered that Viaweb didn't process credit card transactions (we didn't for the whole first year). Transaction processing seemed to them what e-commerce was all about. It sounded serious and difficult. And yet, mysteriously, Viaweb ended up crushing all its competitors. The initial reaction to Y Combinator was almost identical. It seemed laughably lightweight. Startup funding meant series A rounds: millions of dollars given to a small number of startups founded by people with established credentials after months of serious, businesslike meetings, on terms described in a document a foot thick. Y Combinator seemed inconsequential. It's too early to say yet whether Y Combinator will turn out like Viaweb, but judging from the number of imitations, a lot of people seem to think we're on to something.
I can't measure whether my essays are successful, except in page views, but the reaction to them is at least different from when I started. At first the default reaction of the Slashdot trolls was (translated into articulate terms): "Who is this guy and what authority does he have to write about these topics? I haven't read the essay, but there's no way anything so short and written in such an informal style could have anything useful to say about such and such topic, when people with degrees in the subject have already written many thick books about it." Now there's a new generation of trolls on a new generation of sites, but they have at least started to omit the initial "Who is this guy?" Now people are saying the same things about Arc that they said at first about Viaweb and Y Combinator and most of my essays. Why the pattern? The answer, I realized, is that my m.o. for all four has been the same. Here it is: I like to find (a) simple solutions (b) to overlooked problems (c) that actually need to be solved, and (d) deliver them as informally as possible, (e) starting with a very crude version 1, then (f) iterating rapidly. When I first laid out these principles explicitly, I noticed something striking: this is practically a recipe for generating a contemptuous initial reaction. Though simple solutions are better, they don't seem as impressive as complex ones. Overlooked problems are by definition problems that most people think don't matter. Delivering solutions in an informal way means that instead of judging something by the way it's presented, people have to actually understand it, which is more work. And starting with a crude version 1 means your initial effort is always small and incomplete. I'd noticed, of course, that people never seemed to grasp new ideas at first. I thought it was just because most people were stupid. Now I see there's more to it than that.
Like a contrarian investment fund, someone following this strategy will almost always be doing things that seem wrong to the average person. As with contrarian investment strategies, that's exactly the point. This technique is successful (in the long term) because it gives you all the advantages other people forgo by trying to seem legit. If you work on overlooked problems, you're more likely to discover new things, because you have less competition. If you deliver solutions informally, you (a) save all the effort you would have had to expend to make them look impressive, and (b) avoid the danger of fooling yourself as well as your audience. And if you release a crude version 1 then iterate, your solution can benefit from the imagination of nature, which, as Feynman pointed out, is more powerful than your own. In the case of Viaweb, the simple solution was to make the software run on the server. The overlooked problem was to generate web sites automatically; in 1995, online stores were all made by hand by human designers, but we knew this wouldn't scale. The part that actually mattered was graphic design, not transaction processing. The informal delivery mechanism was me, showing up in jeans and a t-shirt at some retailer's office. And the crude version 1 was, if I remember correctly, less than 10,000 lines of code when we launched. The power of this technique extends beyond startups and programming languages and essays. It probably extends to any kind of creative work. Certainly it can be used in painting: this is exactly what Cezanne and Klee did. At Y Combinator we bet money on it, in the sense that we encourage the startups we fund to work this way. There are always new ideas right under your nose. So look for simple things that other people have overlooked—things people will later claim were "obvious"—especially when they've been led astray by obsolete conventions, or by trying to do things that are superficially impressive.
Figure out what the real problem is, and make sure you solve that. Don't worry about trying to look corporate; the product is what wins in the long term. And launch as soon as you can, so you start learning from users what you should have been making. Reddit is a classic example of this approach. When Reddit first launched, it seemed like there was nothing to it. To the graphically unsophisticated its deliberately minimal design seemed like no design at all. But Reddit solved the real problem, which was to tell people what was new and otherwise stay out of the way. As a result it became massively successful. Now that conventional ideas have caught up with it, it seems obvious. People look at Reddit and think the founders were lucky. Like all such things, it was harder than it looked. The Reddits pushed so hard against the current that they reversed it; now it looks like they're merely floating downstream. So when you look at something like Reddit and think "I wish I could think of an idea like that," remember: ideas like that are all around you. But you ignore them because they look wrong..
[](https://s.turbifycdn.com/aah/paulgraham/six-principles-for-making-new-things-11.gif) 2008年2月 Arc语言发布引发的激烈反响带来了一个意外收获:它让我意识到自己有一套设计哲学。那些能言善辩的批评者主要抱怨Arc看起来太过单薄——经过多年研发,我拿出的成果仅仅是几千行宏代码?为什么不去解决更实质性的问题? 当我反复琢磨这些评论时,突然意识到它们何其熟悉。这正是人们最初对Viaweb、Y Combinator和我大多数文章的评语。 我们推出Viaweb时,风险投资人和电商"专家"都觉得可笑。1995年,几个年轻人在公寓里创业可不像现在这么酷。在他们看来,我们开发的东西甚至算不上软件——那时软件等同于庞大的Windows应用程序。作为他们见过的首个基于网页的应用程序,Viaweb在他们眼中不过是个网站。当发现Viaweb不支持信用卡交易时(我们第一年确实没做),他们更加不屑——在他们看来,交易处理才是电商的核心,既严肃又困难。 然而吊诡的是,Viaweb最终碾压了所有竞争对手。 人们对Y Combinator的初反应几乎如出一辙。它看起来轻量得可笑——创业融资本该是A轮融资:经过数月正式商务会谈,向少数由资历深厚者创立的初创企业投入数百万美元,条款书厚达一英尺。而Y Combinator简直不值一提。现在断言Y Combinator能否复制Viaweb的成功为时尚早,但从模仿者的数量来看,许多人似乎认为我们摸到了门道。 除浏览量外,我无法量化文章的成功程度,但至少现在的反响与我写作初期不同。最初Slashdot论坛喷子的标准反应(翻译成文明用语)是:"这谁啊?有什么资格写这些话题?虽然没读文章,但如此简短随意的文字怎么可能对某某话题有真知灼见?该领域的专家早就出版过许多大部头著作了。"如今新一代网站的喷子们至少省去了开头的"这谁啊?" 现在人们对Arc的评语,与当年对Viaweb、Y Combinator和我大多数文章的初评如出一辙。为何存在这种模式?我意识到答案在于:这四件事我都遵循了相同的方法论。 我的方法论是:寻找(a)被忽视问题中(b)真正需要解决的(c)简单方案,(d)以最随意的方式交付,(e)从极其粗糙的1.0版本开始,(f)然后快速迭代。 当我首次明确列出这些原则时,注意到一个惊人事实:这简直是招致轻蔑初评的配方。虽然简单方案更优,但不如复杂方案夺人眼球;被忽视的问题自然被多数人认为无关紧要;非正式交付意味着人们必须真正理解而非凭呈现方式判断,这更费功夫;而粗糙的1.0版本注定最初成果总是微小且不完善。 当然我早就发现人们最初总难以理解新事物,原以为只因多数人愚钝。现在我明白远不止如此——就像逆向投资基金,遵循此策略者做的事在常人眼中几乎总是错的。 正如逆向投资策略,这正是关键所在。这种方法(长期)奏效,是因为它让你获得他人为追求表面正统而放弃的优势:解决被忽视的问题意味着更少竞争,更易发现新事物;非正式交付既省去粉饰功夫,又避免自欺欺人;发布粗糙1.0版本后迭代,则能让方案受益于大自然的想象力——正如费曼所言,这远胜人类自己的想象力。 Viaweb的案例中:简单方案是让软件在服务器运行;被忽视的痛点是自动生成网站(1995年所有网店都由设计师手工制作,但我们知道这不可持续);真正重要的是平面设计而非交易处理;非正式交付体现在我穿着T恤牛仔裤去零售商办公室演示;如果没记错,粗糙的1.0版本上线时不足1万行代码。 这种方法的威力不仅限于初创企业、编程语言和文章,可能适用于任何创造性工作。塞尚和克利正是这样作画的。 在Y Combinator,我们真金白银押注此法——鼓励资助的初创公司如此运作。新创意总在眼前,所以要寻找他人忽视的简单事物(那些事后被称作"显而易见"的点子),尤其当人们被过时惯例或表面光鲜之事误导时。弄清真正问题并确保解决它,别操心装点门面——长期制胜的终归是产品。尽早发布,才能从用户反馈中明白该做什么。 Reddit是此方法的典范。初版Reddit看似空无一物,其刻意极简的设计在审美粗陋者眼中等于毫无设计。但它解决了核心问题:告诉人们新内容,其余则保持克制。结果它大获成功。当传统观念追上它时,一切显得理所当然。人们觉得创始人只是幸运。但如所有类似案例,实际比看起来困难得多——Reddit团队曾如此逆流而上,如今看起来却像顺流而下。 所以当你看着Reddit心想"要是我能想到这种点子多好",请记住:这样的点子无处不在,只是它们看起来"不对",所以被你忽视了。.
February 2008 A user on Hacker News recently posted a comment that set me thinking: > Something about hacker culture that never really set well with me was this � the nastiness. ... I just don't understand why people troll like they do.
2008年2月 Hacker News上的一位用户最近发表了一条评论,引发了我的思考: > 黑客文化中一直让我难以接受的一点就是——那种恶意。......我就是不明白为什么人们要那样恶意挑衅。
过去几年间,我对网络喷子问题进行了深入思考。这一现象由来已久,与论坛历史同样悠久,但我们对它的成因和应对之策仍处于探索阶段。
"喷子"一词有两层含义。最初它特指那些(通常是外来者)故意在论坛发表煽动性言论挑起争端的人。[1] 比如,某个非编程语言使用者可能潜入该语言的用户论坛,发表贬损言论后坐观用户群起攻之。这类行为本质上是恶作剧,犹如在人群密集处释放蝙蝠。
I've thought a lot over the last couple years about the problem of trolls. It's an old one, as old as forums, but we're still just learning what the causes are and how to address them. There are two senses of the word "troll." In the original sense it meant someone, usually an outsider, who deliberately stirred up fights in a forum by saying controversial things. [1] For example, someone who didn't use a certain programming language might go to a forum for users of that language and make disparaging remarks about it, then sit back and watch as people rose to the bait. This sort of trolling was in the nature of a practical joke, like letting a bat loose in a room full of people. The definition then spread to people who behaved like assholes in forums, whether intentionally or not. Now when people talk about trolls they usually mean this broader sense of the word. Though in a sense this is historically inaccurate, it is in other ways more accurate, because when someone is being an asshole it's usually uncertain even in their own mind how much is deliberate. That is arguably one of the defining qualities of an asshole. I think trolling in the broader sense has four causes. The most important is distance. People will say things in anonymous forums that they'd never dare say to someone's face, just as they'll do things in cars that they'd never do as pedestrians � like tailgate people, or honk at them, or cut them off. Trolling tends to be particularly bad in forums related to computers, and I think that's due to the kind of people you find there. Most of them (myself included) are more comfortable dealing with abstract ideas than with people. Hackers can be abrupt even in person. Put them on an anonymous forum, and the problem gets worse. The third cause of trolling is incompetence. If you disagree with something, it's easier to say "you suck" than to figure out and explain exactly what you disagree with.
后来该词外延扩大,泛指论坛中举止恶劣者,无论其是否蓄意。如今人们谈论喷子时通常采用这个更宽泛的定义。虽然从历史角度看不够精确,但反而更贴近现实——因为即便施恶者本人,往往也难以分辨自己行为中有多少是刻意为之。这种模糊性或许正是恶劣行径的本质特征。
我认为广义的喷子现象有四大成因。最重要的是距离感。人们在匿名论坛的发言往往比当面交谈更肆无忌惮,就像司机在车内做出的跟车太近、鸣笛抢道等行为绝不会出现在行人身上。
计算机相关论坛的喷子现象尤为严重,我认为这与用户群体特性有关。其中多数人(包括我自己)更擅长处理抽象概念而非人际关系。即便现实中,黑客们也常显得唐突。当环境变成匿名论坛,问题自然加剧。
第三大成因是能力不足。相比费心推敲并阐述反对意见,直接甩出"你真烂"要轻松得多。这种策略还能规避反驳风险。就此而言,喷子行为与涂鸦颇为相似。涂鸦产生于野心与无能的交汇点:人们渴望留下印记,却只能以最原始的方式实现。[2]
You're also safe that way from refutation. In this respect trolling is a lot like graffiti. Graffiti happens at the intersection of ambition and incompetence: people want to make their mark on the world, but have no other way to do it than literally making a mark on the world. [2] The final contributing factor is the culture of the forum. Trolls are like children (many _are_ children) in that they're capable of a wide range of behavior depending on what they think will be tolerated. In a place where rudeness isn't tolerated, most can be polite. But vice versa as well. There's a sort of Gresham's Law of trolls: trolls are willing to use a forum with a lot of thoughtful people in it, but thoughtful people aren't willing to use a forum with a lot of trolls in it. Which means that once trolling takes hold, it tends to become the dominant culture. That had already happened to Slashdot and Digg by the time I paid attention to comment threads there, but I watched it happen to Reddit. News.YC is, among other things, an experiment to see if this fate can be avoided. The sites's guidelines explicitly ask people not to say things they wouldn't say face to face. If someone starts being rude, other users will step in and tell them to stop. And when people seem to be deliberately trolling, we ban them ruthlessly. Technical tweaks may also help. On Reddit, votes on your comments don't affect your karma score, but they do on News.YC. And it does seem to influence people when they can see their reputation in the eyes of their peers drain away after making an asshole remark. Often users have second thoughts and delete such comments. One might worry this would prevent people from expressing controversial ideas, but empirically that doesn't seem to be what happens. When people say something substantial that gets modded down, they stubbornly leave it up.
最后是论坛文化的影响。喷子如同孩童(许多本就是孩童),其行为尺度取决于环境容忍度。在抵制粗鄙的社区,多数人能保持礼貌;反之亦然。
喷子界存在"劣币驱逐良币"现象:喷子愿意混迹于智者云集的论坛,而智者绝不愿与喷子为伍。这意味着一旦喷子文化扎根,往往就会成为主导。当我开始关注Slashdot和Digg的评论区时,这种蜕变已然完成,而我在Reddit见证了全过程。
News.YC本质上是一场避免重蹈覆辙的社会实验。网站《指南》明确要求用户谨记"当面不说的话,网上也不说"。当有人失礼时,其他用户会立即制止。对于蓄意挑衅者,我们坚决封禁。
技术调整也有助益。Reddit的评论投票不影响用户 karma值,但News.YC不同。当人们发现刻薄言论会导致社区声望值骤降时,往往会三思而后删帖。
What people delete are wisecracks, because they have less invested in them. So far the experiment seems to be working. The level of conversation on News.YC is as high as on any forum I've seen. But we still only have about 8,000 uniques a day. The conversations on Reddit were good when it was that small. The challenge is whether we can keep things this way. I'm optimistic we will. We're not depending just on technical tricks. The core users of News.YC are mostly refugees from other sites that were overrun by trolls. They feel about trolls roughly the way refugees from Cuba or Eastern Europe feel about dictatorships. So there are a lot of people working to keep this from happening again. Notes [1] I mean forum in the general sense of a place to exchange views. The original Internet forums were not web sites but Usenet newsgroups. [2] I'm talking here about everyday tagging. Some graffiti is quite impressive (anything becomes art if you do it well enough) but the median tag is just visual spam.
有人担忧这会抑制争议性观点表达,但实证显示并非如此。当实质性观点被踩时,发布者通常坚持保留;而被删除的多是俏皮话,因其情感投入较浅。
目前实验成效显著。News.YC的讨论质量是我见过最高的——尽管日均用户仅8000人。Reddit在同等规模时也曾保持良好氛围,真正的挑战在于能否持续。
我持乐观态度。我们不仅依靠技术手段,News.YC核心用户多是其他喷子泛滥平台的"难民"。他们对喷子的厌恶,堪比古巴或东欧移民对独裁政权的憎恶。正因如此,无数人在共同守护这片净土。
注释 [1] 此处"论坛"泛指观点交流场所。最早的互联网论坛并非网站,而是Usenet新闻组。 [2] 本文指日常涂鸦。某些街头艺术令人惊叹(任何事物做到极致皆成艺术),但多数涂鸦只是视觉污染。
Want to start a startup? Get funded by Y Combinator.
October 2007 _(This essay is derived from a keynote at FOWA in October 2007.)_ There's something interesting happening right now. Startups are undergoing the same transformation that technology does when it becomes cheaper. It's a pattern we see over and over in technology. Initially there's some device that's very expensive and made in small quantities. Then someone discovers how to make them cheaply; many more get built; and as a result they can be used in new ways. Computers are a familiar example. When I was a kid, computers were big, expensive machines built one at a time. Now they're a commodity. Now we can stick computers in everything. This pattern is very old. Most of the turning points in economic history are instances of it. It happened to steel in the 1850s, and to power in the 1780s. It happened to cloth manufacture in the thirteenth century, generating the wealth that later brought about the Renaissance. Agriculture itself was an instance of this pattern. Now as well as being produced by startups, this pattern is happening _to_ startups. It's so cheap to start web startups that orders of magnitudes more will be started. If the pattern holds true, that should cause dramatic changes. 1\. Lots of Startups So my first prediction about the future of web startups is pretty straightforward: there will be a lot of them. When starting a startup was expensive, you had to get the permission of investors to do it. Now the only threshold is courage. Even that threshold is getting lower, as people watch others take the plunge and survive. In the last batch of startups we funded, we had several founders who said they'd thought of applying before, but weren't sure and got jobs instead. It was only after hearing reports of friends who'd done it that they decided to try it themselves.
Starting a startup is hard, but having a 9 to 5 job is hard too, and in some ways a worse kind of hard. In a startup you have lots of worries, but you don't have that feeling that your life is flying by like you do in a big company. Plus in a startup you could make much more money. As word spreads that startups work, the number may grow to a point that would now seem surprising. We now think of it as normal to have a job at a company, but this is the thinnest of historical veneers. Just two or three lifetimes ago, most people in what are now called industrialized countries lived by farming. So while it may seem surprising to propose that large numbers of people will change the way they make a living, it would be more surprising if they didn't. 2\. Standardization When technology makes something dramatically cheaper, standardization always follows. When you make things in large volumes you tend to standardize everything that doesn't need to change. At Y Combinator we still only have four people, so we try to standardize everything. We could hire employees, but we want to be forced to figure out how to scale investing. We often tell startups to release a minimal version one quickly, then let the needs of the users determine what to do next. In essense, let the market design the product. We've done the same thing ourselves. We think of the techniques we're developing for dealing with large numbers of startups as like software. Sometimes it literally is software, like Hacker News and our application system. One of the most important things we've been working on standardizing are investment terms. Till now investment terms have been individually negotiated. This is a problem for founders, because it makes raising money take longer and cost more in legal fees.
So as well as using the same paperwork for every deal we do, we've commissioned generic angel paperwork that all the startups we fund can use for future rounds. Some investors will still want to cook up their own deal terms. Series A rounds, where you raise a million dollars or more, will be custom deals for the forseeable future. But I think angel rounds will start to be done mostly with standardized agreements. An angel who wants to insert a bunch of complicated terms into the agreement is probably not one you want anyway. 3\. New Attitude to Acquisition Another thing I see starting to get standardized is acquisitions. As the volume of startups increases, big companies will start to develop standardized procedures that make acquisitions little more work than hiring someone. Google is the leader here, as in so many areas of technology. They buy a lot of startups— more than most people realize, because they only announce a fraction of them. And being Google, they're figuring out how to do it efficiently. One problem they've solved is how to think about acquisitions. For most companies, acquisitions still carry some stigma of inadequacy. Companies do them because they have to, but there's usually some feeling they shouldn't have to—that their own programmers should be able to build everything they need. Google's example should cure the rest of the world of this idea. Google has by far the best programmers of any public technology company. If they don't have a problem doing acquisitions, the others should have even less problem. However many Google does, Microsoft should do ten times as many. One reason Google doesn't have a problem with acquisitions is that they know first-hand the quality of the people they can get that way. Larry and Sergey only started Google after making the rounds of the search engines trying to sell their idea and finding no takers.
They've _been_ the guys coming in to visit the big company, so they know who might be sitting across that conference table from them. 4\. Riskier Strategies are Possible Risk is always proportionate to reward. The way to get really big returns is to do things that seem crazy, like starting a new search engine in 1998, or turning down a billion dollar acquisition offer. This has traditionally been a problem in venture funding. Founders and investors have different attitudes to risk. Knowing that risk is on average proportionate to reward, investors like risky strategies, while founders, who don't have a big enough sample size to care what's true on average, tend to be more conservative. If startups are easy to start, this conflict goes away, because founders can start them younger, when it's rational to take more risk, and can start more startups total in their careers. When founders can do lots of startups, they can start to look at the world in the same portfolio-optimizing way as investors. And that means the overall amount of wealth created can be greater, because strategies can be riskier. 5\. Younger, Nerdier Founders If startups become a cheap commodity, more people will be able to have them, just as more people could have computers once microprocessors made them cheap. And in particular, younger and more technical founders will be able to start startups than could before. Back when it cost a lot to start a startup, you had to convince investors to let you do it. And that required very different skills from actually doing the startup. If investors were perfect judges, the two would require exactly the same skills. But unfortunately most investors are terrible judges. I know because I see behind the scenes what an enormous amount of work it takes to raise money, and the amount of selling required in an industry is always inversely proportional to the judgement of the buyers.
Fortunately, if startups get cheaper to start, there's another way to convince investors. Instead of going to venture capitalists with a business plan and trying to convince them to fund it, you can get a product launched on a few tens of thousands of dollars of seed money from us or your uncle, and approach them with a working company instead of a plan for one. Then instead of having to seem smooth and confident, you can just point them to Alexa. This way of convincing investors is better suited to hackers, who often went into technology in part because they felt uncomfortable with the amount of fakeness required in other fields. 6\. Startup Hubs Will Persist It might seem that if startups get cheap to start, it will mean the end of startup hubs like Silicon Valley. If all you need to start a startup is rent money, you should be able to do it anywhere. This is kind of true and kind of false. It's true that you can now _start_ a startup anywhere. But you have to do more with a startup than just start it. You have to make it succeed. And that is more likely to happen in a startup hub. I've thought a lot about this question, and it seems to me the increasing cheapness of web startups will if anything increase the importance of startup hubs. The value of startup hubs, like centers for any kind of business, lies in something very old-fashioned: face to face meetings. No technology in the immediate future will replace walking down University Ave and running into a friend who tells you how to fix a bug that's been bothering you all weekend, or visiting a friend's startup down the street and ending up in a conversation with one of their investors. The question of whether to be in a startup hub is like the question of whether to take outside investment. The question is not whether you _need_ it, but whether it brings any advantage at all.
Because anything that brings an advantage will give your competitors an advantage over you if they do it and you don't. So if you hear someone saying "we don't need to be in Silicon Valley," that use of the word "need" is a sign they're not even thinking about the question right. And while startup hubs are as powerful magnets as ever, the increasing cheapness of starting a startup means the particles they're attracting are getting lighter. A startup now can be just a pair of 22 year old guys. A company like that can move much more easily than one with 10 people, half of whom have kids. We know because we make people move for Y Combinator, and it doesn't seem to be a problem. The advantage of being able to work together face to face for three months outweighs the inconvenience of moving. Ask anyone who's done it. The mobility of seed-stage startups means that seed funding is a national business. One of the most common emails we get is from people asking if we can help them set up a local clone of Y Combinator. But this just wouldn't work. Seed funding isn't regional, just as big research universities aren't. Is seed funding not merely national, but international? Interesting question. There are signs it may be. We've had an ongoing stream of founders from outside the US, and they tend to do particularly well, because they're all people who were so determined to succeed that they were willing to move to another country to do it. The more mobile startups get, the harder it would be to start new silicon valleys. If startups are mobile, the best local talent will go to the real Silicon Valley, and all they'll get at the local one will be the people who didn't have the energy to move. This is not a nationalistic idea, incidentally. It's cities that compete, not countries. Atlanta is just as hosed as Munich. 7\.
Better Judgement Needed If the number of startups increases dramatically, then the people whose job is to judge them are going to have to get better at it. I'm thinking particularly of investors and acquirers. We now get on the order of 1000 applications a year. What are we going to do if we get 10,000? That's actually an alarming idea. But we'll figure out some kind of answer. We'll have to. It will probably involve writing some software, but fortunately we can do that. Acquirers will also have to get better at picking winners. They generally do better than investors, because they pick later, when there's more performance to measure. But even at the most advanced acquirers, identifying companies to buy is extremely ad hoc, and completing the acquisition often involves a great deal of unneccessary friction. I think acquirers may eventually have chief acquisition officers who will both identify good acquisitions and make the deals happen. At the moment those two functions are separate. Promising new startups are often discovered by developers. If someone powerful enough wants to buy them, the deal is handed over to corp dev guys to negotiate. It would be better if both were combined in one group, headed by someone with a technical background and some vision of what they wanted to accomplish. Maybe in the future big companies will have both a VP of Engineering responsible for technology developed in-house, and a CAO responsible for bringing technology in from outside. At the moment, there is no one within big companies who gets in trouble when they buy a startup for $200 million that they could have bought earlier for $20 million. There should start to be someone who gets in trouble for that. 8\. College Will Change If the best hackers start their own companies after college instead of getting jobs, that will change what happens in college. Most of these changes will be for the better.
I think the experience of college is warped in a bad way by the expectation that afterward you'll be judged by potential employers. One change will be in the meaning of "after college," which will switch from when one graduates from college to when one leaves it. If you're starting your own company, why do you need a degree? We don't encourage people to start startups during college, but the best founders are certainly capable of it. Some of the most successful companies we've funded were started by undergrads. I grew up in a time where college degrees seemed really important, so I'm alarmed to be saying things like this, but there's nothing magical about a degree. There's nothing that magically changes after you take that last exam. The importance of degrees is due solely to the administrative needs of large organizations. These can certainly affect your life—it's hard to get into grad school, or to get a work visa in the US, without an undergraduate degree—but tests like this will matter less and less. As well as mattering less whether students get degrees, it will also start to matter less where they go to college. In a startup you're judged by users, and they don't care where you went to college. So in a world of startups, elite universities will play less of a role as gatekeepers. In the US it's a national scandal how easily children of rich parents game college admissions. But the way this problem ultimately gets solved may not be by reforming the universities but by going around them. We in the technology world are used to that sort of solution: you don't beat the incumbents; you redefine the problem to make them irrelevant. The greatest value of universities is not the brand name or perhaps even the classes so much as the people you meet. If it becomes common to start a startup after college, students may start trying to maximize this.
Instead of focusing on getting internships at companies they want to work for, they may start to focus on working with other students they want as cofounders. What students do in their classes will change too. Instead of trying to get good grades to impress future employers, students will try to learn things. We're talking about some pretty dramatic changes here. 9\. Lots of Competitors If it gets easier to start a startup, it's easier for competitors too. That doesn't erase the advantage of increased cheapness, however. You're not all playing a zero-sum game. There's not some fixed number of startups that can succeed, regardless of how many are started. In fact, I don't think there's any limit to the number of startups that could succeed. Startups succeed by creating wealth, which is the satisfaction of people's desires. And people's desires seem to be effectively infinite, at least in the short term. What the increasing number of startups does mean is that you won't be able to sit on a good idea. Other people have your idea, and they'll be increasingly likely to do something about it. 10\. Faster Advances There's a good side to that, at least for consumers of technology. If people get right to work implementing ideas instead of sitting on them, technology will evolve faster. Some kinds of innovations happen a company at a time, like the punctuated equilibrium model of evolution. There are some kinds of ideas that are so threatening that it's hard for big companies even to think of them. Look at what a hard time Microsoft is having discovering web apps. They're like a character in a movie that everyone in the audience can see something bad is about to happen to, but who can't see it himself. The big innovations that happen a company at a time will obviously happen faster if the rate of new companies increases. But in fact there will be a double speed increase.
People won't wait as long to act on new ideas, but also those ideas will increasingly be developed within startups rather than big companies. Which means technology will evolve faster per company as well. Big companies are just not a good place to make things happen fast. I talked recently to a founder whose startup had been acquired by a big company. He was a precise sort of guy, so he'd measured their productivity before and after. He counted lines of code, which can be a dubious measure, but in this case was meaningful because it was the same group of programmers. He found they were one thirteenth as productive after the acquisition. The company that bought them was not a particularly stupid one. I think what he was measuring was mostly the cost of bigness. I experienced this myself, and his number sounds about right. There's something about big companies that just sucks the energy out of you. Imagine what all that energy could do if it were put to use. There is an enormous latent capacity in the world's hackers that most people don't even realize is there. That's the main reason we do Y Combinator: to let loose all this energy by making it easy for hackers to start their own startups. A Series of Tubes The process of starting startups is currently like the plumbing in an old house. The pipes are narrow and twisty, and there are leaks in every joint. In the future this mess will gradually be replaced by a single, huge pipe. The water will still have to get from A to B, but it will get there faster and without the risk of spraying out through some random leak. This will change a lot of things for the better. In a big, straight pipe like that, the force of being measured by one's performance will propagate back through the whole system. Performance is always the ultimate test, but there are so many kinks in the plumbing now that most people are insulated from it most of the time.
So you end up with a world in which high school students think they need to get good grades to get into elite colleges, and college students think they need to get good grades to impress employers, within which the employees waste most of their time in political battles, and from which consumers have to buy anyway because there are so few choices. Imagine if that sequence became a big, straight pipe. Then the effects of being measured by performance would propagate all the way back to high school, flushing out all the arbitrary stuff people are measured by now. That is the future of web startups. Thanks to Brian Oberkirch and Simon Willison for inviting me to speak, and the crew at Carson Systems for making everything run smoothly.
想创业吗? 获得 Y Combinator 的资助。
2007年10月 _(本文源自2007年10月FOWA大会的主题演讲。)_ 当下正在发生一些有趣的事情。初创企业正在经历与技术成本下降时相同的变革。 这种模式在技术领域屡见不鲜。最初,某种设备昂贵且产量稀少。随后有人找到了低成本制造的方法,产量激增,进而催生出全新的应用场景。 计算机就是熟悉的例子。我小时候,计算机还是昂贵的大型设备,一次只能生产一台。如今它们已成为普通商品,可以被嵌入任何事物中。 这一模式历史悠久。经济史上的多数转折点都遵循此规律:19世纪50年代的钢铁业、18世纪80年代的能源业、13世纪的纺织业(其创造的财富后来催生了文艺复兴),甚至农业本身也是如此。 如今,这一模式不仅由初创企业推动,更在初创企业领域上演。网络创业成本之低,将催生数量级增长的创业公司。若模式应验,必将引发剧变。 1. 创业大爆发 关于网络创业未来的第一个预测很简单:数量将激增。当创业成本高昂时,需获得投资者首肯;如今唯一的门槛仅是勇气。 随着先驱者成功案例的涌现,勇气门槛也在降低。在我们最新资助的初创团队中,多位创始人坦言曾因犹豫选择就业,直到听闻朋友创业经历才决心尝试。 创业固然艰难,但朝九晚五的工作同样不易,甚至在某些方面更为煎熬。创业虽充满焦虑,却不会像在大公司那样感到生命虚度,且可能收获更丰厚回报。 随着创业成功案例的传播,其规模或将达到今人难以想象的程度。 现代人视公司就业为常态,但这不过是历史长河中的短暂现象。两三辈人之前,"工业化国家"的多数居民仍以务农为生。因此,当大量人群改变谋生方式时,固守传统反而更令人惊讶。 2. 标准化浪潮 技术带来的成本骤降总会伴随标准化进程。大规模生产必然推动非必要差异的消除。 Y Combinator至今仅四人,因此我们力推全面标准化。本可雇佣员工,但我们刻意逼迫自己探索规模化投资之道。 我们常建议初创团队快速推出极简首版,让用户需求指引方向——本质上是让市场设计产品。我们自身亦如此实践,将应对大量初创公司的方法视作软件研发,部分确实转化为软件(如Hacker News和申请系统)。 投资条款标准化是重点突破领域。传统模式下每笔交易都需单独谈判,创始人不仅耗时还需承担高额法律费用。为此我们不仅统一自身交易文件,还开发了通用天使投资文书供被投企业后续轮次使用。 部分投资者仍会定制条款。A轮(融资百万美元以上)在未来仍将个性化。但我认为天使轮将普遍采用标准化协议——毕竟执着于复杂条款的天使本就不值得合作。 3. 并购新思维 并购也在走向标准化。随着初创企业数量增长,大公司将建立标准化收购流程,使其如招聘般便捷。 谷歌仍是技术领域的先行者。其收购初创企业的数量远超公众认知(仅公布部分案例),并持续优化收购效率。 关键突破在于观念转变。多数公司仍视并购为能力不足的耻辱,不得已而为之。谷歌的实践应能破除这种偏见——这家拥有顶尖工程师的公司尚且频繁收购,其他企业更应坦然效仿。微软的收购量理应十倍于谷歌。 谷歌的从容源于切身体验。佩奇和布林当年兜售搜索引擎创意屡遭拒绝后,才选择自主创业。他们曾坐在会议桌另一端,深谙创业者的价值。 4. 高风险战略可行 风险与回报永恒正相关。获取超额回报需采取看似疯狂的行动,如1998年创建新搜索引擎,或拒绝十亿美元收购要约。 这曾是风险投资的痛点。创始人与投资者风险偏好天然不同:投资者基于大数定律青睐高风险策略;而创始人样本有限往往趋于保守。 创业成本降低将化解这一矛盾。年轻创始人更理性承担风险,职业生涯可尝试更多项目。当创始人能多次创业,他们就会像投资者那样用组合思维看待世界,整体财富创造因此增长。 5. 更年轻极客的崛起 若创业变得如微机般廉价,更多人群——特别是年轻技术人才——将加入创业大军。 昔日高昂成本迫使创业者必须说服投资者,这种能力与实际创业技能截然不同。若投资者判断力完美,二者本应一致。但现实是多数投资者缺乏洞见——融资所需工作量与买方判断力成反比。 幸运的是,低成本创业提供了新路径:用产品而非商业计划说服投资者。先用数万美元种子资金(来自Y Combinator或亲友)推出产品,再带着运营实体而非PPT接触风投。此时无需包装自信,直接展示Alexa排名即可。 这种方式更适合黑客——他们选择技术领域本就因厌恶其他行业的虚饰。 6. 创业中心永续 创业成本下降看似会削弱硅谷等创业中心的意义——若仅需租金就能创业,何不就地开展? 此观点半对半错。创业确实随处可始,但成功仍需生态支持。枢纽价值在于古老的面对面交流——短期内没有技术能替代在大学街偶遇朋友解决困扰周末的bug,或在街角初创公司与投资人偶遇畅谈的价值。 是否进驻创业中心如同是否接受外部投资——问题不在于"是否需要",而在于"是否具有优势"。任何优势若被竞争对手获取就会成为你的劣势。当有人说"我们不必去硅谷"时,"不必"一词已暴露其思维谬误。 同时,创业中心磁力虽强,吸引的"粒子"却更轻——如今两个22岁青年就能组成团队,其流动性远超半数成员拖家带口的十人公司。 Y Combinator要求团队迁移的经验证明:三个月面对面协作的收益远超搬迁成本。 种子期初创的流动性使种子投资成为全国性业务。常有人邮件咨询如何建立本地Y Combinator克隆,但这注定失败——种子投资如同顶尖研究型大学,无法区域化。 它是否国际化?迹象显示可能。我们的国际创始人表现尤为突出,因为他们展现出了跨国创业的决心。 初创企业流动性越强,新建硅谷越难。顶尖人才将涌向真正的硅谷,地方枢纽只能吸引缺乏迁徙动力者。 (这无关民族主义——城市间竞争,国家无涉。亚特兰大与慕尼黑处境相同。) 7. 判断力升级 初创企业激增将倒逼评判者(投资者与收购方)提升判断力。我们每年处理约1000份申请,若增至10000份该如何应对? 这令人警醒,但必须找到解决方案——很可能需要开发特定软件(所幸我们擅长此事)。 收购方也需改进筛选机制。他们通常比投资者更准确(因决策时点靠后,有更多数据参考)。但即便最成熟的收购方,其标的识别仍极随意,交易完成过程充满不必要的摩擦。 未来企业或设首席收购官,统管标的发掘与交易达成。目前这两项职能分离:有潜力的初创常由技术团队发现,交易却交由企业开发部门谈判。理想状态是组建兼具技术背景与战略视野的专职团队。或许未来大公司将同时设立负责内部技术的工程副总裁,与负责外部技术引进的首席收购官。 当前,错失2亿美元收购(本可以2000万美元早期介入)无人担责。这种情况必须改变。 8. 大学教育变革 顶尖黑客毕业后选择创业而非就业,将重塑大学教育。多数变化是积极的——当前大学体验被"求职导向"严重扭曲。 首先,"毕业"的定义将从获取学位变为离开校园。自主创业何需文凭?我们不鼓励在读创业,但顶尖创始人完全具备这种能力(我们资助的多个成功企业由本科生创建)。 成长于文凭崇拜时代的我,说出这些话自己都惊讶。但学位本无魔力——最后一场考试后不会发生质变。文凭重要性仅源于大型组织的管理需求(如申请研究生或美国工作签证),但这些评估标准将日益弱化。 名校光环也会褪色。初创企业由用户评判,他们不在乎创始人母校。在创业主导的世界里,精英大学作为守门人的角色将减弱。美国富裕家庭子女轻易操纵名校录取已是丑闻,但解决方案或许非改革大学,而是绕过它们——技术界惯用此道:不击败既得利益者,重新定义问题使其无关紧要。 大学最大价值非品牌或课程,而是人际网络。若毕业后创业成为常态,学生将优先考虑寻找联合创始人,而非争夺名企实习。 课堂行为也会改变:学生将为求知而非求职而学习。这些都将引发深刻变革。 9. 竞争白热化 创业门槛降低意味着竞争对手激增,但这不抵消成本下降的优势——创业非零和游戏,成功企业数量没有上限。 事实上,我认为成功初创数量可以无限增长。它们通过满足人类欲望创造财富,而欲望至少在短期内是无限的。 唯一变化是:你无法再坐拥好创意。越来越多人会想到并实施相同点子。 10. 技术加速演进 对技术消费者而言,这至少有好的一面:当人们立即实践创意而非束之高阁,技术进化将加速。 某些创新遵循"间断平衡"模式——大公司甚至难以构想某些颠覆性创意(如微软开发网络应用的窘境,就像观众预知危险而剧中人浑然不觉的电影角色)。新公司增速提升将直接加速此类突破。 实际将产生双重加速:人们更快实践创意,且更多创意源自初创企业而非大公司。这意味着单公司层面的技术进化也会加快。 大公司本就不是快速行动的沃土。一位被收购的创始人(严谨型)测量发现:同一组程序员,收购后产出效率降为1/13。收购方并非特别愚蠢——这主要反映"规模成本"。我的亲历印证这个数字——大公司某种特质在吞噬能量。 想象这些能量释放的威力。全球黑客蕴藏着世人尚未认知的巨大潜能,这正是Y Combinator存在的核心意义:通过降低创业门槛,释放这股力量。 管道革命 当前创业流程如同老宅水管:曲折狭窄,接口处处渗漏。未来这套系统将被单一巨管取代——水流仍需从A到B,但更快速且无泄漏风险。 这将带来诸多改善。在笔直巨管中,绩效评估的压力将回溯至整个系统。绩效本是终极检验,但现有体系扭曲使多数人长期绝缘于此,导致:高中生为进名校苦攻成绩→大学生为求职刷绩点→雇员陷于办公室政治→消费者因选择匮乏被迫买单。当这一切变为通畅管道,绩效评估的效应将直贯高中体系,冲刷所有现行 arbitrary 标准——这就是网络创业的未来。 致谢 Brian Oberkirch和Simon Willison的演讲邀请,以及Carson Systems团队的完美执行。
日语译本.
[](https://s.turbifycdn.com/aah/paulgraham/why-to-move-to-a-startup-hub-11.gif) October 2007 After the last talk I gave, one of the organizers got up on the stage to deliver an impromptu rebuttal. That never happened before. I only heard the first few sentences, but that was enough to tell what I said that upset him: that startups would do better if they moved to Silicon Valley. This conference was in London, and most of the audience seemed to be from the UK. So saying startups should move to Silicon Valley seemed like a nationalistic remark: an obnoxious American telling them that if they wanted to do things right they should all just move to America. Actually I'm less American than I seem. I didn't say so, but I'm British by birth. And just as Jews are ex officio allowed to tell Jewish jokes, I don't feel like I have to bother being diplomatic with a British audience. The idea that startups would do better to move to Silicon Valley is not even a nationalistic one. [1] It's the same thing I say to startups in the US. Y Combinator alternates between coasts every 6 months. Every other funding cycle is in Boston. And even though Boston is the second biggest startup hub in the US (and the world), we tell the startups from those cycles that their best bet is to move to Silicon Valley. If that's true of Boston, it's even more true of every other city. This is about cities, not countries. And I think I can prove I'm right. You can easily reduce the opposing argument ad what most people would agree was absurdum. Few would be willing to claim that it doesn't matter at all where a startup is—that a startup operating out of a small agricultural town wouldn't benefit from moving to a startup hub. Most people could see how it might be helpful to be in a place where there was infrastructure for startups, accumulated knowledge about how to make them work, and other people trying to do it.
[](https://s.turbifycdn.com/aah/paulgraham/why-to-move-to-a-startup-hub-11.gif)
在我上次演讲结束后,一位主办方成员突然登台即兴反驳。这种事从未发生过。我只听到前几句话,但已足够明白触怒他的观点:如果初创企业搬到硅谷会发展得更好。
这场会议在伦敦举行,大多数听众似乎来自英国。因此建议初创企业迁往硅谷听起来像民族主义言论——一个讨厌的美国人在暗示他们,若想成功就必须全盘美式化。
实际上我的美国身份并不像表面那么鲜明。虽未明说,但我出生在英国。就像犹太人有权讲犹太笑话一样,面对英国观众时,我觉得无需刻意外交辞令。
"初创企业应迁往硅谷"的观点甚至与民族主义无关。[1]我对美国本土初创企业也这么说。Y Combinator每六个月在东西海岸轮换一次,每隔一轮融资周期就在波士顿进行。尽管波士顿是美国(乃至全球)第二大创业中心,我们仍建议那里的初创企业最佳选择是搬去硅谷。若这对波士顿成立,对其他城市更是如此。
And yet whatever argument you use to prove that startups don't need to move from London to Silicon Valley could equally well be used to prove startups don't need to move from smaller towns to London. The difference between cities is a matter of degree. And if, as nearly everyone who knows agrees, startups are better off in Silicon Valley than Boston, then they're better off in Silicon Valley than everywhere else too. I realize I might seem to have a vested interest in this conclusion, because startups that move to the US might do it through Y Combinator. But the American startups we've funded will attest that I say the same thing to them. I'm not claiming of course that every startup has to go to Silicon Valley to succeed. Just that all other things being equal, the more of a startup hub a place is, the better startups will do there. But other considerations can outweigh the advantages of moving. I'm not saying founders with families should uproot them to move halfway around the world; that might be too much of a distraction. Immigration difficulties might be another reason to stay put. Dealing with immigration problems is like raising money: for some reason it seems to consume all your attention. A startup can't afford much of that. One Canadian startup we funded spent about 6 months working on moving to the US. Eventually they just gave up, because they couldn't afford to take so much time away from working on their software. (If another country wanted to establish a rival to Silicon Valley, the single best thing they could do might be to create a special visa for startup founders. US immigration policy is one of Silicon Valley's biggest weaknesses.) If your startup is connected to a specific industry, you may be better off in one of its centers. A startup doing something related to entertainment might want to be in New York or LA.
这关乎城市,而非国家。
我认为可以证明自己的正确性。反对论点很容易被归谬——很少有人敢断言初创企业的选址毫无影响,否认农业小镇的初创公司迁往创业中心会获益。多数人都能理解,置身于拥有创业基础设施、成熟经验积累和同行者的地方确有助益。然而,任何用来反驳"伦敦初创企业无需迁往硅谷"的论据,同样适用于反驳"小城镇初创企业无需迁往伦敦"。
城市间的差异只是程度问题。如果如知情者普遍认同的那样,硅谷比波士顿更适合初创企业,那么硅谷也比其他任何地方更优越。
我意识到这个结论可能显得有私心,因为迁往美国的初创企业可能通过Y Combinator实现。但我们资助过的美国初创团队能证实,我对他们说过同样的话。
当然,我并非宣称所有初创企业必须去硅谷才能成功。只是在其他条件相同时,一个地方的创业生态越成熟,初创企业表现就越好。但某些因素可能压倒迁移优势。我不会建议拖家带口的创始人举家迁徙半个地球——那可能过度分散精力。
移民难题可能是另一个留守理由。处理移民问题如同融资:总会莫名消耗全部精力。初创企业承受不起这种消耗。我们资助的一家加拿大初创公司花了约六个月筹划迁美,最终因无法持续荒废软件开发而放弃。
And finally, if a good investor has committed to fund you if you stay where you are, you should probably stay. Finding investors is hard. You generally shouldn't pass up a definite funding offer to move. [2] In fact, the quality of the investors may be the main advantage of startup hubs. Silicon Valley investors are noticeably more aggressive than Boston ones. Over and over, I've seen startups we've funded snatched by west coast investors out from under the noses of Boston investors who saw them first but acted too slowly. At this year's Boston Demo Day, I told the audience that this happened every year, so if they saw a startup they liked, they should make them an offer. And yet within a month it had happened again: an aggressive west coast VC who had met the founder of a YC-funded startup a week before beat out a Boston VC who had known him for years. By the time the Boston VC grasped what was happening, the deal was already gone. Boston investors will admit they're more conservative. Some want to believe this comes from the city's prudent Yankee character. But Occam's razor suggests the truth is less flattering. Boston investors are probably more conservative than Silicon Valley investors for the same reason Chicago investors are more conservative than Boston ones. They don't understand startups as well. West coast investors aren't bolder because they're irresponsible cowboys, or because the good weather makes them optimistic. They're bolder because they know what they're doing. They're the skiers who ski on the diamond slopes. Boldness is the essence of venture investing. The way you get big returns is not by trying to avoid losses, but by trying to ensure you get some of the big hits. And the big hits often look risky at first. Like Facebook. Facebook was started in Boston. Boston VCs had the first shot at them. But they said no, so Facebook moved to Silicon Valley and raised money there.
(若有国家想打造硅谷的竞争对手,最佳策略或许是设立创业者专属签证。美国移民政策正是硅谷最大软肋之一。)
若你的初创企业与特定行业绑定,选址该行业中心可能更有利。比如娱乐相关初创企业或许适合纽约或洛杉矶。
最后,若有可靠投资者承诺为留守原地的你提供资金,你或许应该留下。寻找投资者本就不易,通常不该为迁移放弃确定的融资机会。[2]
事实上,优质投资者群体或许是创业中心的主要优势。硅谷投资者明显比波士顿同行更具侵略性。我屡次见证Y Combinator资助的企业被西海岸投资者捷足先登,尽管波士顿投资者更早接触却行动迟缓。今年波士顿演示日上,我提醒观众这种现象年年发生,若看到心仪项目应当场报价。然而一个月内历史重演:一位与YC创始人相识仅一周的激进西海岸风投,击败了与之相识多年的波士顿风投。当后者醒悟时,交易早已尘埃落定。
波士顿投资者承认自己更保守。有人将其归因于这座城市谨慎的"扬基"性格。但奥卡姆剃刀定律暗示真相可能更简单:波士顿投资者对初创企业的理解不如硅谷投资者,正如芝加哥投资者不如波士顿投资者。
The partner who turned them down now says that "may turn out to have been a mistake." Empirically, boldness wins. If the aggressive ways of west coast investors are going to come back to bite them, it has been a long time coming. Silicon Valley has been pulling ahead of Boston since the 1970s. If there was going to be a comeuppance for the west coast investors, the bursting of the Bubble would have been it. But since then the west coast has just pulled further ahead. West coast investors are confident enough of their judgement to act boldly; east coast investors, not so much; but anyone who thinks east coast investors act that way out of prudence should see the frantic reactions of an east coast VC in the process of losing a deal to a west coast one. In addition to the concentration that comes from specialization, startup hubs are also markets. And markets are usually centralized. Even now, when traders could be anywhere, they cluster in a few cities. It's hard to say exactly what it is about face to face contact that makes deals happen, but whatever it is, it hasn't yet been duplicated by technology. Walk down University Ave at the right time, and you might overhear five different people talking on the phone about deals. In fact, this is part of the reason Y Combinator is in Boston half the time: it's hard to stand that year round. But though it can sometimes be annoying to be surrounded by people who only think about one thing, it's the place to be if that one thing is what you're trying to do. I was talking recently to someone who works on search at Google. He knew a lot of people at Yahoo, so he was in a good position to compare the two companies. I asked him why Google was better at search. He said it wasn't anything specific Google did, but simply that they understood search so much better. And that's why startups thrive in startup hubs like Silicon Valley.
西海岸投资者的大胆并非因为他们是鲁莽牛仔,或是阳光让他们盲目乐观。他们胆识过人是因为专业——就像钻石级滑雪道上的高手。冒险精神是风险投资的本质。获取巨额回报不在于规避损失,而在于确保抓住那些爆发性机会。而这些机会初看往往风险极高。
以Facebook为例。它诞生于波士顿,当地风投本有首投权。但他们拒绝了,于是Facebook西迁硅谷融资。当年拒绝的合伙人如今承认"这可能是个错误"。
实证表明,胆识制胜。如果西海岸投资者的激进风格终将反噬,这个"终将"未免来得太迟。自1970年代起硅谷就持续领先波士顿。若说西海岸投资者会遭报应,互联网泡沫破灭本应是转折点。但此后差距反而进一步扩大。
西海岸投资者对自己的判断力足够自信,因此敢于果断行动;东海岸投资者则不然。但若有人认为东海岸的谨慎源于深谋远虑,不妨看看他们在交易被西海岸对手截胡时的慌乱反应。
除专业化带来的集聚效应外,创业中心也是市场。而市场天然趋向集中。即便在交易员可随处办公的今天,他们仍聚集于少数城市。难以确切说明面对面交流促成交易的魔力何在,但技术尚未能复制这种魔力。
若在恰当时刻漫步大学街,你或许会听见五个人同时电话洽谈交易。这也正是Y Combinator半年驻扎波士顿的原因之一——常年沉浸其中令人窒息。尽管被只关心一件事的人群包围有时令人烦躁,但若你正专注此事,这里就是最佳所在。
Startups are a very specialized business, as specialized as diamond cutting. And in startup hubs they understand it. Notes [1] The nationalistic idea is the converse: that startups should stay in a certain city because of the country it's in. If you really have a "one world" viewpoint, deciding to move from London to Silicon Valley is no different from deciding to move from Chicago to Silicon Valley. [2] An investor who merely seems like he will fund you, however, you can ignore. Seeming like they will fund you one day is the way investors say No. Thanks to Sam Altman, Jessica Livingston, Harjeet Taggar, and Kulveer Taggar for reading drafts of this. Comment on this essay.
最近与一位谷歌搜索部门员工交谈。因认识许多雅虎员工,他很有资格比较两家公司。当我问及谷歌搜索优势时,他归因于非具体策略,而是整体更深刻的理解。
这正是初创企业在硅谷等创业中心蓬勃发展的原因。初创企业是高度专业化的领域,如同钻石切割。而在创业中心,人们深谙此道。
注释 [1] 民族主义观点恰恰相反:初创企业应因其所在国家而留守某城。若持"天下一家"视角,从伦敦迁往硅谷与从芝加哥迁往硅谷并无二致。 [2] 但对于仅"看似"会投资的人,尽可忽略。"某天会投资"正是投资者婉拒的套路。
致谢 Sam Altman、Jessica Livingston、Harjeet Taggar和Kulveer Taggar审阅了本文草稿。
评论本文。
| 日文译本
[](https://s.turbifycdn.com/aah/paulgraham/how-to-do-philosophy-11.gif) September 2007 In high school I decided I was going to study philosophy in college. I had several motives, some more honorable than others. One of the less honorable was to shock people. College was regarded as job training where I grew up, so studying philosophy seemed an impressively impractical thing to do. Sort of like slashing holes in your clothes or putting a safety pin through your ear, which were other forms of impressive impracticality then just coming into fashion. But I had some more honest motives as well. I thought studying philosophy would be a shortcut straight to wisdom. All the people majoring in other things would just end up with a bunch of domain knowledge. I would be learning what was really what. I'd tried to read a few philosophy books. Not recent ones; you wouldn't find those in our high school library. But I tried to read Plato and Aristotle. I doubt I believed I understood them, but they sounded like they were talking about something important. I assumed I'd learn what in college. The summer before senior year I took some college classes. I learned a lot in the calculus class, but I didn't learn much in Philosophy 101\. And yet my plan to study philosophy remained intact. It was my fault I hadn't learned anything. I hadn't read the books we were assigned carefully enough. I'd give Berkeley's _Principles of Human Knowledge_ another shot in college. Anything so admired and so difficult to read must have something in it, if one could only figure out what. Twenty-six years later, I still don't understand Berkeley. I have a nice edition of his collected works. Will I ever read it? Seems unlikely. The difference between then and now is that now I understand why Berkeley is probably not worth trying to understand.
[](https://s.turbifycdn.com/aah/paulgraham/how-to-do-philosophy-11.gif)
高中时我决定大学要攻读哲学。动机有好几个,有些高尚些,有些则不然。不太高尚的一个动机是想吓唬人。在我成长的地方,大学被视为职业培训,所以学哲学似乎是件令人印象深刻却不切实际的事——就像在衣服上剪几个洞或是给耳朵穿个安全别针,这些当时刚流行起来的标新立异之举。
不过我也有些更真诚的动机。我以为学哲学会是直达智慧的捷径。其他专业的人最终只会掌握些领域知识,而我将参透世界的本质。
I think I see now what went wrong with philosophy, and how we might fix it. Words I did end up being a philosophy major for most of college. It didn't work out as I'd hoped. I didn't learn any magical truths compared to which everything else was mere domain knowledge. But I do at least know now why I didn't. Philosophy doesn't really have a subject matter in the way math or history or most other university subjects do. There is no core of knowledge one must master. The closest you come to that is a knowledge of what various individual philosophers have said about different topics over the years. Few were sufficiently correct that people have forgotten who discovered what they discovered. Formal logic has some subject matter. I took several classes in logic. I don't know if I learned anything from them. [1] It does seem to me very important to be able to flip ideas around in one's head: to see when two ideas don't fully cover the space of possibilities, or when one idea is the same as another but with a couple things changed. But did studying logic teach me the importance of thinking this way, or make me any better at it? I don't know. There are things I know I learned from studying philosophy. The most dramatic I learned immediately, in the first semester of freshman year, in a class taught by Sydney Shoemaker. I learned that I don't exist. I am (and you are) a collection of cells that lurches around driven by various forces, and calls itself _I_. But there's no central, indivisible thing that your identity goes with. You could conceivably lose half your brain and live. Which means your brain could conceivably be split into two halves and each transplanted into different bodies. Imagine waking up after such an operation. You have to imagine being two people. The real lesson here is that the concepts we use in everyday life are fuzzy, and break down if pushed too hard. Even a concept as dear to us as _I_.
我曾试着读几本哲学书。不是近现代的——高中图书馆里找不到那些。我啃过柏拉图和亚里士多德,虽不确信自己读懂了,但他们的文字似乎关乎某些重大命题。我指望大学能教会我答案。
高三前的暑假,我修了几门大学课程。微积分课让我受益匪浅,但哲学导论课却收获寥寥。即便如此,我攻读哲学的计划仍未动摇。没学到东西是我的错——布置的阅读材料我没认真读。等进了大学,我要再挑战伯克利的《人类知识原理》。既然这本书备受推崇又艰深晦涩,其中必藏真知,只要我能参透。
二十六年过去了,我依然没读懂伯克利。我收藏了他的精装文集,但真会去读吗?恐怕不会。
It took me a while to grasp this, but when I did it was fairly sudden, like someone in the nineteenth century grasping evolution and realizing the story of creation they'd been told as a child was all wrong. [2] Outside of math there's a limit to how far you can push words; in fact, it would not be a bad definition of math to call it the study of terms that have precise meanings. Everyday words are inherently imprecise. They work well enough in everyday life that you don't notice. Words seem to work, just as Newtonian physics seems to. But you can always make them break if you push them far enough. I would say that this has been, unfortunately for philosophy, the central fact of philosophy. Most philosophical debates are not merely afflicted by but driven by confusions over words. Do we have free will? Depends what you mean by "free." Do abstract ideas exist? Depends what you mean by "exist." Wittgenstein is popularly credited with the idea that most philosophical controversies are due to confusions over language. I'm not sure how much credit to give him. I suspect a lot of people realized this, but reacted simply by not studying philosophy, rather than becoming philosophy professors. How did things get this way? Can something people have spent thousands of years studying really be a waste of time? Those are interesting questions. In fact, some of the most interesting questions you can ask about philosophy. The most valuable way to approach the current philosophical tradition may be neither to get lost in pointless speculations like Berkeley, nor to shut them down like Wittgenstein, but to study it as an example of reason gone wrong. History Western philosophy really begins with Socrates, Plato, and Aristotle. What we know of their predecessors comes from fragments and references in later works; their doctrines could be described as speculative cosmology that occasionally strays into analysis.
如今的我不再纠结,因为我明白了为何伯克利不值得钻研。我想我已看清哲学的问题所在,以及如何修正。
大学期间我确实主修了哲学,但结果与预期相去甚远。我并未获得超越一切领域知识的终极真理,但至少明白了原因:哲学不像数学、历史或其他学科那样有明确的研究对象。它没有必须掌握的核心知识体系,最接近的不过是历代哲学家对各类话题的论述。其中鲜有真知灼见到让人忘记发现者姓名的案例。
形式逻辑倒算个例外。我修过几门逻辑课,却说不清是否有所得。[1] 在脑中翻转概念的能力确实重要——比如判断两个观点是否穷尽可能性,或识别某个观点是否只是另一观点的变体。但逻辑学是否教会我这种思维方式的价值或提升了相关能力?我不得而知。
Presumably they were driven by whatever makes people in every other society invent cosmologies. [3] With Socrates, Plato, and particularly Aristotle, this tradition turned a corner. There started to be a lot more analysis. I suspect Plato and Aristotle were encouraged in this by progress in math. Mathematicians had by then shown that you could figure things out in a much more conclusive way than by making up fine sounding stories about them. [4] People talk so much about abstractions now that we don't realize what a leap it must have been when they first started to. It was presumably many thousands of years between when people first started describing things as hot or cold and when someone asked "what is heat?" No doubt it was a very gradual process. We don't know if Plato or Aristotle were the first to ask any of the questions they did. But their works are the oldest we have that do this on a large scale, and there is a freshness (not to say naivete) about them that suggests some of the questions they asked were new to them, at least. Aristotle in particular reminds me of the phenomenon that happens when people discover something new, and are so excited by it that they race through a huge percentage of the newly discovered territory in one lifetime. If so, that's evidence of how new this kind of thinking was. [5] This is all to explain how Plato and Aristotle can be very impressive and yet naive and mistaken. It was impressive even to ask the questions they did. That doesn't mean they always came up with good answers. It's not considered insulting to say that ancient Greek mathematicians were naive in some respects, or at least lacked some concepts that would have made their lives easier. So I hope people will not be too offended if I propose that ancient philosophers were similarly naive.
哲学确实教会我一些事。最震撼的一课来自大一上学期的悉尼·休梅克教授:我发现自己并不存在。你我只是被各种力量驱使的细胞集合体,自称为"我"。根本不存在与身份绑定的不可分割核心。理论上失去半边大脑仍可存活,这意味着你的大脑可能被分成两半移植到不同身体里。想象术后醒来时,你将同时成为两个人。
这揭示出日常概念的模糊性——即便如"我"这般根本的概念,过度推敲也会瓦解。理解这点花了我些时间,但顿悟时刻如同十九世纪的人突然领会进化论,意识到童年听闻的创世故事全是谬误。[2] 数学之外,词语的适用有其限度。事实上,将数学定义为研究精确术语的学科未尝不可。日常用语天生不精确,只是日常使用中不易察觉。词语就像牛顿力学,看似有效,但推到极致必然崩溃。
可悲的是,这恰是哲学的核心困境。多数哲学争论不仅受困于、更是由词语的混淆驱动。"我们是否有自由意志?"取决于如何定义"自由"。"抽象概念是否存在?"取决于如何理解"存在"。
In particular, they don't seem to have fully grasped what I earlier called the central fact of philosophy: that words break if you push them too far. "Much to the surprise of the builders of the first digital computers," Rod Brooks wrote, "programs written for them usually did not work." [6] Something similar happened when people first started trying to talk about abstractions. Much to their surprise, they didn't arrive at answers they agreed upon. In fact, they rarely seemed to arrive at answers at all. They were in effect arguing about artifacts induced by sampling at too low a resolution. The proof of how useless some of their answers turned out to be is how little effect they have. No one after reading Aristotle's _Metaphysics_ does anything differently as a result. [7] Surely I'm not claiming that ideas have to have practical applications to be interesting? No, they may not have to. Hardy's boast that number theory had no use whatsoever wouldn't disqualify it. But he turned out to be mistaken. In fact, it's suspiciously hard to find a field of math that truly has no practical use. And Aristotle's explanation of the ultimate goal of philosophy in Book A of the _Metaphysics_ implies that philosophy should be useful too. Theoretical Knowledge Aristotle's goal was to find the most general of general principles. The examples he gives are convincing: an ordinary worker builds things a certain way out of habit; a master craftsman can do more because he grasps the underlying principles. The trend is clear: the more general the knowledge, the more admirable it is. But then he makes a mistake—possibly the most important mistake in the history of philosophy. He has noticed that theoretical knowledge is often acquired for its own sake, out of curiosity, rather than for any practical need. So he proposes there are two kinds of theoretical knowledge: some that's useful in practical matters and some that isn't.
维特根斯坦因"哲学争议多源于语言混淆"的观点闻名。但我不确定该归功于他——或许许多人早已意识到这点,只是选择远离哲学而非成为哲学教授。
哲学何以至此?人们耗费数千年研究的领域真可能毫无价值?这些问题本身正是关于哲学最有趣的问题。对待哲学传统的正确方式,或许既非如伯克利般沉迷无谓思辨,也非如维特根斯坦般全盘否定,而是将其视为理性误入歧途的典型案例加以研究。
西方哲学真正始于苏格拉底、柏拉图和亚里士多德。前人的学说仅存于后世著作的片段中,可被描述为偶尔涉足分析的思辨宇宙论。[3]
Since people interested in the latter are interested in it for its own sake, it must be more noble. So he sets as his goal in the _Metaphysics_ the exploration of knowledge that has no practical use. Which means no alarms go off when he takes on grand but vaguely understood questions and ends up getting lost in a sea of words. His mistake was to confuse motive and result. Certainly, people who want a deep understanding of something are often driven by curiosity rather than any practical need. But that doesn't mean what they end up learning is useless. It's very valuable in practice to have a deep understanding of what you're doing; even if you're never called on to solve advanced problems, you can see shortcuts in the solution of simple ones, and your knowledge won't break down in edge cases, as it would if you were relying on formulas you didn't understand. Knowledge is power. That's what makes theoretical knowledge prestigious. It's also what causes smart people to be curious about certain things and not others; our DNA is not so disinterested as we might think. So while ideas don't have to have immediate practical applications to be interesting, the kinds of things we find interesting will surprisingly often turn out to have practical applications. The reason Aristotle didn't get anywhere in the _Metaphysics_ was partly that he set off with contradictory aims: to explore the most abstract ideas, guided by the assumption that they were useless. He was like an explorer looking for a territory to the north of him, starting with the assumption that it was located to the south. And since his work became the map used by generations of future explorers, he sent them off in the wrong direction as well. [8] Perhaps worst of all, he protected them from both the criticism of outsiders and the promptings of their own inner compass by establishing the principle that the most noble sort of theoretical knowledge had to be useless.
从苏格拉底到亚里士多德,这一传统发生转向。分析比重大幅增加,我猜是受数学进步的启发。数学家已证明,相比编造动听的故事,存在更具结论性的探究方式。[4]
现代人谈论抽象已成习惯,却忽略了这曾是多大的跨越。从用"冷热"描述事物到追问"热是什么",人类可能花费了上万年。柏拉图与亚里士多德未必是首批提问者,但他们的著作是现存最早系统探讨这些问题的文献,字里行间透着新鲜感(甚至天真),暗示至少对他们而言,某些问题确是崭新的。
亚里士多德尤其让我想起这种现象:当人们发现新事物时,会因兴奋而在有生之年探索该领域的绝大部分。若真如此,正说明这类思考当时多么新颖。[5]
The _Metaphysics_ is mostly a failed experiment. A few ideas from it turned out to be worth keeping; the bulk of it has had no effect at all. The _Metaphysics_ is among the least read of all famous books. It's not hard to understand the way Newton's _Principia_ is, but the way a garbled message is. Arguably it's an interesting failed experiment. But unfortunately that was not the conclusion Aristotle's successors derived from works like the _Metaphysics_. [9] Soon after, the western world fell on intellectual hard times. Instead of version 1s to be superseded, the works of Plato and Aristotle became revered texts to be mastered and discussed. And so things remained for a shockingly long time. It was not till around 1600 (in Europe, where the center of gravity had shifted by then) that one found people confident enough to treat Aristotle's work as a catalog of mistakes. And even then they rarely said so outright. If it seems surprising that the gap was so long, consider how little progress there was in math between Hellenistic times and the Renaissance. In the intervening years an unfortunate idea took hold: that it was not only acceptable to produce works like the _Metaphysics_ , but that it was a particularly prestigious line of work, done by a class of people called philosophers. No one thought to go back and debug Aristotle's motivating argument. And so instead of correcting the problem Aristotle discovered by falling into it—that you can easily get lost if you talk too loosely about very abstract ideas—they continued to fall into it. The Singularity Curiously, however, the works they produced continued to attract new readers. Traditional philosophy occupies a kind of singularity in this respect. If you write in an unclear way about big ideas, you produce something that seems tantalizingly attractive to inexperienced but intellectually ambitious students.
这解释了为何柏拉图与亚里士多德既令人惊叹又显幼稚。能提出那些问题本身已了不起,但未必总能给出好答案。说古希腊数学家在某些方面很天真(或缺乏简化问题的概念)并不冒犯,因此我希望指出古希腊哲学家的类似天真也不会太得罪人。他们显然未完全理解我所说的哲学核心困境:词语经不起过度推敲。
"首批数字计算机建造者们震惊地发现",罗德·布鲁克斯写道,"为它们编写的程序通常无法运行。"[6] 人类初探抽象领域时同样遭遇意外:他们很少能达成共识,甚至很少得出任何结论。
本质上,他们争论的只是低分辨率采样导致的人为假象。
Till one knows better, it's hard to distinguish something that's hard to understand because the writer was unclear in his own mind from something like a mathematical proof that's hard to understand because the ideas it represents are hard to understand. To someone who hasn't learned the difference, traditional philosophy seems extremely attractive: as hard (and therefore impressive) as math, yet broader in scope. That was what lured me in as a high school student. This singularity is even more singular in having its own defense built in. When things are hard to understand, people who suspect they're nonsense generally keep quiet. There's no way to prove a text is meaningless. The closest you can get is to show that the official judges of some class of texts can't distinguish them from placebos. [10] And so instead of denouncing philosophy, most people who suspected it was a waste of time just studied other things. That alone is fairly damning evidence, considering philosophy's claims. It's supposed to be about the ultimate truths. Surely all smart people would be interested in it, if it delivered on that promise. Because philosophy's flaws turned away the sort of people who might have corrected them, they tended to be self-perpetuating. Bertrand Russell wrote in a letter in 1912: > Hitherto the people attracted to philosophy have been mostly those who loved the big generalizations, which were all wrong, so that few people with exact minds have taken up the subject. [11].
其答案的无用性体现在毫无影响力上。读完亚里士多德的《形而上学》,没人会因此改变任何行为。[7]
我并非主张思想必须有实际用途才有趣?不,未必。哈代夸耀数论毫无用处,但这不妨碍其价值——尽管后来证明他错了。事实上,几乎找不到真正无用的数学领域。而亚里士多德在《形而上学》A卷中对哲学终极目标的阐述,也暗示哲学应具实用性。
理论知识的迷思
His response was to launch Wittgenstein at it, with dramatic results. I think Wittgenstein deserves to be famous not for the discovery that most previous philosophy was a waste of time, which judging from the circumstantial evidence must have been made by every smart person who studied a little philosophy and declined to pursue it further, but for how he acted in response. [12] Instead of quietly switching to another field, he made a fuss, from inside. He was Gorbachev. The field of philosophy is still shaken from the fright Wittgenstein gave it. [13] Later in life he spent a lot of time talking about how words worked. Since that seems to be allowed, that's what a lot of philosophers do now. Meanwhile, sensing a vacuum in the metaphysical speculation department, the people who used to do literary criticism have been edging Kantward, under new names like "literary theory," "critical theory," and when they're feeling ambitious, plain "theory." The writing is the familiar word salad:
亚里士多德的目标是寻找最普遍的通用原则。他举的例子很有说服力:普通工匠凭习惯制作物品,大师级工匠则因掌握原理而技艺更高。趋势很明显:知识越普遍越可贵。但随后他犯了哲学史上可能最严重的错误——他注意到理论知识常因好奇心而非实际需求获得,便提出存在两种理论知识:实用型与非实用型。由于后者纯粹为知识本身而存在,故更为高贵。于是他设定《形而上学》的目标是探索无实用价值的知识。这意味着当他处理宏大而模糊的问题并最终迷失在词语海洋中时,没有任何警报会响起。
他的错误在于混淆动机与结果。固然,追求深刻理解常源于好奇心而非实际需求,但这不意味着所得知识无用。实践中,深刻理解所从事领域极有价值——即便从不需解决复杂问题,也能在简单问题中发现捷径,且知识在边缘情况下不会崩溃(若依赖不理解公式则不然)。知识就是力量,正是这点赋予理论知识声望,也促使聪明人对某些事物而非其他产生好奇——我们的DNA并非如想象般超然。
因此,虽然思想不必立即有用才算有趣,但我们感兴趣的事物往往出人意料地终将有用。
> Gender is not like some of the other grammatical modes which express precisely a mode of conception without any reality that corresponds to the conceptual mode, and consequently do not express precisely something in reality by which the intellect could be moved to conceive a thing the way it does, even where that motive is not something in the thing as such. [14]
亚里士多德在《形而上学》中毫无建树的部分原因,在于他出发时就怀着矛盾目标:在"抽象思想无用"的假设指导下探索最抽象的思想。这就像探险家假设北方领土位于南方,然后启程寻找。
而他的著作成为后世探险者的地图,也将他们引向错误方向。[8] 最糟的是,他通过确立"最高贵理论知识必无实用"的原则,使后人既免受外界批评,又压抑了内心罗盘的指引。
《形而上学》大体是次失败实验。少数观点值得保留,主体则毫无影响。这本名著鲜有人读,难懂之处不同于牛顿《原理》的艰深,而像段混乱的讯息。
The singularity I've described is not going away. There's a market for writing that sounds impressive and can't be disproven. There will always be both supply and demand. So if one group abandons this territory, there will always be others ready to occupy it. A Proposal We may be able to do better. Here's an intriguing possibility. Perhaps we should do what Aristotle meant to do, instead of what he did. The goal he announces in the _Metaphysics_ seems one worth pursuing: to discover the most general truths. That sounds good. But instead of trying to discover them because they're useless, let's try to discover them because they're useful. I propose we try again, but that we use that heretofore despised criterion, applicability, as a guide to keep us from wondering off into a swamp of abstractions. Instead of trying to answer the question:
可以说这是次有趣的失败。但不幸的是,亚里士多德的继承者并未从中吸取教训。[9] 此后西方世界陷入思想低谷。柏拉图与亚里士多德的著作未被视作待超越的1.0版本,反而成为需要精通和讨论的神圣文本。这种状态可悲地持续了太久。直到约1600年(当时学术重心已转移至欧洲),才有人足够自信地将亚里士多德著作视为错误目录——即便那时他们也鲜少直言。
若觉得这空白期长得出奇,不妨想想希腊化时代到文艺复兴期间数学的停滞。
在此期间,一个不幸观念生根发芽:生产《形而上学》这类作品不仅可接受,还是由"哲学家"阶层从事的崇高事业。无人想到回头检视亚里士多德的动机论证。于是他们非但未纠正亚里士多德陷入的问题(过度松散地讨论抽象概念易致迷失),反而持续重蹈覆辙。
> What are the most general truths?
但吊诡的是,这些作品始终吸引新读者。传统哲学在这方面占据某种奇点:用模糊语言书写宏大思想,对经验不足但智力雄心勃勃的学生具有致命吸引力。在学会分辨前,人们很难区分因作者思维混乱导致的艰深与因思想本身深奥导致的艰深(如数学证明)。对未谙此道者,传统哲学极具魅力:如数学般艰深(因而令人印象深刻),却拥有更广视野。这正是高中时吸引我的原因。
这个奇点更奇特之处在于其内置防御机制。面对难解文本,怀疑其无意义者通常保持沉默——无法证明文本毫无意义,最多只能证明某类文本的权威评审无法区分其与安慰剂。[10]
因此多数怀疑哲学浪费时间的人只是转投他处,这本身已是对哲学主张的严厉控诉。哲学自称关乎终极真理,若真如此,所有聪明人都该趋之若鹜。
let's try to answer the question
由于哲学缺陷赶走了可能修正它们的人,这些问题往往自我延续。伯特兰·罗素在1912年的信中写道:
> 迄今被哲学吸引的多是热爱大而化之错误概括之人,故鲜有思维精确者投身此领域。[11]
他的对策是祭出维特根斯坦,结果石破天惊。
> Of all the useful things we can say, which are the most general?
我认为维特根斯坦的名声不应建立在他发现前人大半哲学都是浪费时间——毕竟从间接证据来看,每个稍涉哲学便抽身而去的聪明人想必都得出过这个结论——而应建立在他对此的应对方式。[12] 他没有默默转投其他领域,而是从内部掀起波澜。他就是哲学界的戈尔巴乔夫。
哲学领域至今仍在维特根斯坦带来的震撼中战栗。[13] 晚年他花费大量时间探讨语言运作机制。既然这似乎是被允许的,如今众多哲学家便纷纷效仿。与此同时,察觉到形而上思辨领域的真空,那些曾从事文学批评的人正以"文学理论"、"批判理论"等新名目,或野心勃勃时干脆自称"理论",悄然向康德靠拢。其文风仍是熟悉的文字沙拉:
> 性别不同于某些仅精确表达概念模式却无相应现实存在的语法范畴,因而并非精确表达现实中能促使理智以特定方式构想事物的动因——即便该动因并非事物本身的属性。[14]
The test of utility I propose is whether we cause people who read what we've written to do anything differently afterward. Knowing we have to give definite (if implicit) advice will keep us from straying beyond the resolution of the words we're using. The goal is the same as Aristotle's; we just approach it from a different direction. As an example of a useful, general idea, consider that of the controlled experiment. There's an idea that has turned out to be widely applicable. Some might say it's part of science, but it's not part of any specific science; it's literally meta-physics (in our sense of "meta"). The idea of evolution is another. It turns out to have quite broad applications—for example, in genetic algorithms and even product design. Frankfurt's distinction between lying and bullshitting seems a promising recent example. [15] These seem to me what philosophy should look like: quite general observations that would cause someone who understood them to do something differently. Such observations will necessarily be about things that are imprecisely defined. Once you start using words with precise meanings, you're doing math. So starting from utility won't entirely solve the problem I described above—it won't flush out the metaphysical singularity. But it should help. It gives people with good intentions a new roadmap into abstraction. And they may thereby produce things that make the writing of the people with bad intentions look bad by comparison. One drawback of this approach is that it won't produce the sort of writing that gets you tenure. And not just because it's not currently the fashion. In order to get tenure in any field you must not arrive at conclusions that members of tenure committees can disagree with. In practice there are two kinds of solutions to this problem.
我所描述的这种奇异现象不会消失。那些听起来高深莫测又无法证伪的论述永远存在市场,供需关系将长期维持。因此若有一派放弃这片领地,总有其他派系准备接管。
我们或许能做得更好。这里有个耐人寻味的可能性:也许我们该践行亚里士多德的本意,而非效仿他的实际作为。他在《形而上学》中宣称的目标——发现最普遍的真理——似乎值得追求。这听起来不错。但与其因其无用而探索,不如因其有用而追寻。
我提议我们重新出发,但要以迄今备受轻视的"实用性"为指南,防止迷失在抽象概念的沼泽中。与其试图回答:
In math and the sciences, you can prove what you're saying, or at any rate adjust your conclusions so you're not claiming anything false ("6 of 8 subjects had lower blood pressure after the treatment"). In the humanities you can either avoid drawing any definite conclusions (e.g. conclude that an issue is a complex one), or draw conclusions so narrow that no one cares enough to disagree with you. The kind of philosophy I'm advocating won't be able to take either of these routes. At best you'll be able to achieve the essayist's standard of proof, not the mathematician's or the experimentalist's. And yet you won't be able to meet the usefulness test without implying definite and fairly broadly applicable conclusions. Worse still, the usefulness test will tend to produce results that annoy people: there's no use in telling people things they already believe, and people are often upset to be told things they don't. Here's the exciting thing, though. Anyone can do this. Getting to general plus useful by starting with useful and cranking up the generality may be unsuitable for junior professors trying to get tenure, but it's better for everyone else, including professors who already have it. This side of the mountain is a nice gradual slope. You can start by writing things that are useful but very specific, and then gradually make them more general. Joe's has good burritos. What makes a good burrito? What makes good food? What makes anything good? You can take as long as you want. You don't have to get all the way to the top of the mountain. You don't have to tell anyone you're doing philosophy. If it seems like a daunting task to do philosophy, here's an encouraging thought. The field is a lot younger than it seems.
> 什么是最普遍的真理?
> 在所有有价值的陈述中,哪些最具普遍性?
我提出的实用性检验标准是:我们写下的文字能否让读者在阅读后采取不同的行动。意识到必须提供明确(哪怕是隐含的)建议,能防止我们迷失在用词模糊的迷雾中。
Though the first philosophers in the western tradition lived about 2500 years ago, it would be misleading to say the field is 2500 years old, because for most of that time the leading practitioners weren't doing much more than writing commentaries on Plato or Aristotle while watching over their shoulders for the next invading army. In the times when they weren't, philosophy was hopelessly intermingled with religion. It didn't shake itself free till a couple hundred years ago, and even then was afflicted by the structural problems I've described above. If I say this, some will say it's a ridiculously overbroad and uncharitable generalization, and others will say it's old news, but here goes: judging from their works, most philosophers up to the present have been wasting their time. So in a sense the field is still at the first step. [16] That sounds a preposterous claim to make. It won't seem so preposterous in 10,000 years. Civilization always seems old, because it's always the oldest it's ever been. The only way to say whether something is really old or not is by looking at structural evidence, and structurally philosophy is young; it's still reeling from the unexpected breakdown of words. Philosophy is as young now as math was in 1500. There is a lot more to discover. Notes [1] In practice formal logic is not much use, because despite some progress in the last 150 years we're still only able to formalize a small percentage of statements. We may never do that much better, for the same reason 1980s-style "knowledge representation" could never have worked; many statements may have no representation more concise than a huge, analog brain state. [2] It was harder for Darwin's contemporaries to grasp this than we can easily imagine. The story of creation in the Bible is not just a Judeo-Christian concept; it's roughly what everyone must have believed since before people were people.
这一目标与亚里士多德并无二致,只是我们选择了不同的路径。
以"受控实验"这一实用而普适的概念为例。这个理念已被证明具有广泛适用性。有人或许认为它属于科学范畴,但它并不专属于任何具体学科;严格来说它属于元物理学(取"元"的本义)。进化论是另一个例证——从遗传算法到产品设计,其应用范围令人惊叹。法兰克福对"说谎"与"胡扯"的区分则是近年来的潜力范例[15]。
在我看来,这才是哲学应有的模样:那些能改变人们行为的普遍洞见。
The hard part of grasping evolution was to realize that species weren't, as they seem to be, unchanging, but had instead evolved from different, simpler organisms over unimaginably long periods of time. Now we don't have to make that leap. No one in an industrialized country encounters the idea of evolution for the first time as an adult. Everyone's taught about it as a child, either as truth or heresy. [3] Greek philosophers before Plato wrote in verse. This must have affected what they said. If you try to write about the nature of the world in verse, it inevitably turns into incantation. Prose lets you be more precise, and more tentative. [4] Philosophy is like math's ne'er-do-well brother. It was born when Plato and Aristotle looked at the works of their predecessors and said in effect "why can't you be more like your brother?" Russell was still saying the same thing 2300 years later. Math is the precise half of the most abstract ideas, and philosophy the imprecise half. It's probably inevitable that philosophy will suffer by comparison, because there's no lower bound to its precision. Bad math is merely boring, whereas bad philosophy is nonsense. And yet there are _some_ good ideas in the imprecise half. [5] Aristotle's best work was in logic and zoology, both of which he can be said to have invented. But the most dramatic departure from his predecessors was a new, much more analytical style of thinking. He was arguably the first scientist. [6] Brooks, Rodney, _Programming in Common Lisp_ , Wiley, 1985, p. 94. [7] Some would say we depend on Aristotle more than we realize, because his ideas were one of the ingredients in our common culture. Certainly a lot of the words we use have a connection with Aristotle, but it seems a bit much to suggest that we wouldn't have the concept of the essence of something or the distinction between matter and form if Aristotle hadn't written about them.
这类洞见必然涉及定义模糊的事物。一旦使用精确术语,你便进入了数学领域。因此实用性标准虽不能彻底解决前文所述问题——无法消除形而上学的奇点——但确有助益。它为善意探索者提供了通往抽象的新路标,其产出的成果或能反衬出恶意写作者的荒谬。
这种方法的缺陷在于难以产出符合终身教职评审标准的论文。不仅因为不合时令——任何领域要获得终身教职,结论都不得与评审委员相左。实践中存在两种解决方案:在数理领域,你可以证明观点,或调整结论至无可指摘(如"8名受试者中6人治疗后血压降低");在人文学科,要么回避明确结论(如宣称问题具有复杂性),要么将结论限定至无人质疑的狭窄范围。
我倡导的哲学无法采用这两种策略。至多只能达到散文家的论证标准,而非数学家或实验科学家的水准。但若不能暗示明确且广泛适用的结论,又无法通过实用性检验。更糟的是,实用性往往催生令人不快的结论——重复已知真理毫无意义,而新知常会触怒固有认知者。
One way to see how much we really depend on Aristotle would be to diff European culture with Chinese: what ideas did European culture have in 1800 that Chinese culture didn't, in virtue of Aristotle's contribution? [8] The meaning of the word "philosophy" has changed over time. In ancient times it covered a broad range of topics, comparable in scope to our "scholarship" (though without the methodological implications). Even as late as Newton's time it included what we now call "science." But core of the subject today is still what seemed to Aristotle the core: the attempt to discover the most general truths. Aristotle didn't call this "metaphysics." That name got assigned to it because the books we now call the _Metaphysics_ came after (meta = after) the _Physics_ in the standard edition of Aristotle's works compiled by Andronicus of Rhodes three centuries later. What we call "metaphysics" Aristotle called "first philosophy." [9] Some of Aristotle's immediate successors may have realized this, but it's hard to say because most of their works are lost. [10] Sokal, Alan, "Transgressing the Boundaries: Toward a Transformative Hermeneutics of Quantum Gravity," _Social Text_ 46/47, pp. 217-252. Abstract-sounding nonsense seems to be most attractive when it's aligned with some axe the audience already has to grind. If this is so we should find it's most popular with groups that are (or feel) weak. The powerful don't need its reassurance. [11] Letter to Ottoline Morrell, December 1912. Quoted in: Monk, Ray, _Ludwig Wittgenstein: The Duty of Genius_ , Penguin, 1991, p. 75. [12] A preliminary result, that all metaphysics between Aristotle and 1783 had been a waste of time, is due to I.
但令人振奋的是:人人都能实践这种哲学。从实用出发逐步提升普适性,或许不适合谋求终身教职的助理教授,却适合包括已获终身教职者在内的所有人。这条进路如同平缓的山坡——你可以从具体实用的观察起步(如"Joe家的墨西哥卷不错"),逐步延伸至"好卷饼的要素""美食的标准""何为良善"。这个过程没有时限,无需登顶,甚至不必宣称自己在从事哲学。
若觉哲学艰深,请记住:这个领域远比想象中年轻。虽然西方哲学传统可追溯至2500年前,但称其有2500年历史实属误导——因大部分时间里,领军者不过是在战火间隙为柏拉图或亚里士多德作注。当未被宗教裹挟时,哲学又深陷前述结构性问题。直至两百年前才真正独立。恕我直言:迄今多数哲学家都在虚掷光阴[16]。某种意义上,这个领域仍处于蹒跚学步阶段。
此论看似荒谬,但万年之后回望自明。文明总显得古老,只因它始终处于时间轴末端。判断事物真正年龄需看结构证据——哲学在结构上仍属年轻,尚在应对语言意外崩溃的余震。
Kant. [13] Wittgenstein asserted a sort of mastery to which the inhabitants of early 20th century Cambridge seem to have been peculiarly vulnerable—perhaps partly because so many had been raised religious and then stopped believing, so had a vacant space in their heads for someone to tell them what to do (others chose Marx or Cardinal Newman), and partly because a quiet, earnest place like Cambridge in that era had no natural immunity to messianic figures, just as European politics then had no natural immunity to dictators. [14] This is actually from the _Ordinatio_ of Duns Scotus (ca. 1300), with "number" replaced by "gender." Plus ca change. Wolter, Allan (trans), _Duns Scotus: Philosophical Writings_ , Nelson, 1963, p. 92. [15] Frankfurt, Harry, _On Bullshit_ , Princeton University Press, 2005. [16] Some introductions to philosophy now take the line that philosophy is worth studying as a process rather than for any particular truths you'll learn. The philosophers whose works they cover would be rolling in their graves at that. They hoped they were doing more than serving as examples of how to argue: they hoped they were getting results. Most were wrong, but it doesn't seem an impossible hope. This argument seems to me like someone in 1500 looking at the lack of results achieved by alchemy and saying its value was as a process. No, they were going about it wrong. It turns out it is possible to transmute lead into gold (though not economically at current energy prices), but the route to that knowledge was to backtrack and try another approach. Thanks to Trevor Blackwell, Paul Buchheit, Jessica Livingston, Robert Morris, Mark Nitzberg, and Peter Norvig for reading drafts of this.
当今哲学正如1500年的数学,尚有无数奥秘待发掘。
注: [15] 法兰克福《论扯淡》 [16] 某些哲学导论如今声称哲学价值在于思辨过程而非具体真理。若先哲有知,定当愤慨——他们自认不止于论证示范,而是追求真知。虽多数失败,但这希望并非虚妄。这就像1500年某人面对炼金术的失败,声称其价值在于过程。非也,只是方法错误。事实上铅确能变金(虽在当前能耗下不经济),但达此认知需另辟蹊径。
致谢:特雷弗·布莱克韦尔、保罗·布赫海特等诸位审阅者。
September 2007 A few weeks ago I had a thought so heretical that it really surprised me. It may not matter all that much where you go to college. For me, as for a lot of middle class kids, getting into a good college was more or less the meaning of life when I was growing up. What was I? A student. To do that well meant to get good grades. Why did one have to get good grades? To get into a good college. And why did one want to do that? There seemed to be several reasons: you'd learn more, get better jobs, make more money. But it didn't matter exactly what the benefits would be. College was a bottleneck through which all your future prospects passed; everything would be better if you went to a better college. A few weeks ago I realized that somewhere along the line I had stopped believing that. What first set me thinking about this was the new trend of worrying obsessively about what kindergarten your kids go to. It seemed to me this couldn't possibly matter. Either it won't help your kid get into Harvard, or if it does, getting into Harvard won't mean much anymore. And then I thought: how much does it mean even now? It turns out I have a lot of data about that. My three partners and I run a seed stage investment firm called Y Combinator. We invest when the company is just a couple guys and an idea. The idea doesn't matter much; it will change anyway. Most of our decision is based on the founders. The average founder is three years out of college. Many have just graduated; a few are still in school. So we're in much the same position as a graduate program, or a company hiring people right out of college. Except our choices are immediately and visibly tested. There are two possible outcomes for a startup: success or failure—and usually you know within a year which it will be. The test applied to a startup is among the purest of real world tests.
几周前,我产生了一个如此离经叛道的想法,连我自己都感到震惊:一个人上哪所大学可能并没有那么重要。
对我以及许多中产阶级孩子来说,考上好大学几乎就是我成长过程中的人生意义。我是谁?一名学生。做好学生意味着取得好成绩。为什么要取得好成绩?为了进入好大学。为什么要上好大学?似乎有几个理由:你会学到更多,获得更好的工作,赚更多的钱。但具体有什么好处并不重要。大学是一个瓶颈,你所有的未来前景都要通过它;如果你进入更好的大学,一切都会更好。
几周前我意识到,不知从何时起,我已经不再相信这一点了。
最初让我思考这个问题的是最近流行的一种现象——人们开始过分担心孩子上哪所幼儿园。在我看来,这根本不重要。要么它不会帮助你的孩子进入哈佛,要么如果真的有用,那么进入哈佛也就不再意味着什么了。然后我想:即使在现在,上哈佛又有多大意义呢?
A startup succeeds or fails depending almost entirely on the efforts of the founders. Success is decided by the market: you only succeed if users like what you've built. And users don't care where you went to college. As well as having precisely measurable results, we have a lot of them. Instead of doing a small number of large deals like a traditional venture capital fund, we do a large number of small ones. We currently fund about 40 companies a year, selected from about 900 applications representing a total of about 2000 people. [1] Between the volume of people we judge and the rapid, unequivocal test that's applied to our choices, Y Combinator has been an unprecedented opportunity for learning how to pick winners. One of the most surprising things we've learned is how little it matters where people went to college. I thought I'd already been cured of caring about that. There's nothing like going to grad school at Harvard to cure you of any illusions you might have about the average Harvard undergrad. And yet Y Combinator showed us we were still overestimating people who'd been to elite colleges. We'd interview people from MIT or Harvard or Stanford and sometimes find ourselves thinking: they _must_ be smarter than they seem. It took us a few iterations to learn to trust our senses. Practically everyone thinks that someone who went to MIT or Harvard or Stanford must be smart. Even people who hate you for it believe it. But when you think about what it means to have gone to an elite college, how could this be true? We're talking about a decision made by admissions officers—basically, HR people—based on a cursory examination of a huge pile of depressingly similar applications submitted by seventeen year olds. And what do they have to go on? An easily gamed standardized test; a short essay telling you what the kid thinks you want to hear; an interview with a random alum; a high school record that's largely an index of obedience.
事实证明,我有很多数据可以回答这个问题。我和另外三位合伙人经营着一家名为Y Combinator的种子期投资公司。我们在公司只有几个人和一个想法时就进行投资。想法并不重要,因为它总会改变。我们的决策主要基于创始人。创始人的平均年龄是大学毕业三年。许多人刚毕业,少数人还在上学。因此,我们的立场与研究生项目或直接从大学招聘的公司非常相似。唯一的区别是我们的选择会立即受到现实的检验。初创公司只有两种可能的结果:成功或失败——通常一年内就能知道答案。
对初创公司的考验是现实世界中最纯粹的考验之一。初创公司的成败几乎完全取决于创始人的努力。成功由市场决定:只有当用户喜欢你的产品时,你才会成功。而用户并不关心你上的是哪所大学。
除了结果可精确衡量外,我们还有大量的样本。与传统风险投资基金进行少量大额交易不同,我们进行大量小额交易。目前,我们每年资助约40家公司,从约900份申请中选出,这些申请总共代表了约2000人。[1]
由于我们评估的人数众多,加上选择后会迅速得到明确的结果,Y Combinator为我们提供了一个前所未有的机会,去学习如何挑选赢家。我们学到的最令人惊讶的事情之一就是:人们上哪所大学几乎无关紧要。
我以为自己已经不再在意这件事了。没有什么比在哈佛读研究生更能打破你对哈佛本科生的幻想了。然而,Y Combinator让我们意识到,我们仍然高估了那些上过精英大学的人。我们会面试来自MIT、哈佛或斯坦福的人,有时会想:他们一定比看起来更聪明。经过几次迭代后,我们才学会相信自己的直觉。
Who would rely on such a test? And yet a lot of companies do. A lot of companies are very much influenced by where applicants went to college. How could they be? I think I know the answer to that. There used to be a saying in the corporate world: "No one ever got fired for buying IBM." You no longer hear this about IBM specifically, but the idea is very much alive; there is a whole category of "enterprise" software companies that exist to take advantage of it. People buying technology for large organizations don't care if they pay a fortune for mediocre software. It's not their money. They just want to buy from a supplier who seems safe—a company with an established name, confident salesmen, impressive offices, and software that conforms to all the current fashions. Not necessarily a company that will deliver so much as one that, if they do let you down, will still seem to have been a prudent choice. So companies have evolved to fill that niche. A recruiter at a big company is in much the same position as someone buying technology for one. If someone went to Stanford and is not obviously insane, they're probably a safe bet. And a safe bet is enough. No one ever measures recruiters by the later performance of people they turn down. [2] I'm not saying, of course, that elite colleges have evolved to prey upon the weaknesses of large organizations the way enterprise software companies have. But they work as if they had. In addition to the power of the brand name, graduates of elite colleges have two critical qualities that plug right into the way large organizations work. They're good at doing what they're asked, since that's what it takes to please the adults who judge you at seventeen. And having been to an elite college makes them more confident. Back in the days when people might spend their whole career at one big company, these qualities must have been very valuable.
几乎每个人都认为,上过MIT、哈佛或斯坦福的人一定很聪明。就连那些因此讨厌你的人也相信这一点。
但当你思考上精英大学意味着什么时,这种想法怎么可能成立呢?我们谈论的是招生官(基本上是HR人员)根据对一大堆十七岁学生提交的、令人沮丧的相似申请材料的粗略审查做出的决定。他们依据的是什么?一个容易被操纵的标准化考试;一篇短文,讲述孩子认为你想听的内容;与随机校友的面试;一份主要体现服从性的高中成绩单。谁会依赖这样的测试?
然而,许多公司确实如此。许多公司在招聘时非常看重申请人毕业的学校。他们怎么会这样?我想我知道答案。
企业界曾经有一句话:“没有人会因为购买IBM而被解雇。”现在你不再听到人们专门提到IBM,但这种观念仍然盛行;有一整个“企业”软件行业就是靠利用这种心理生存的。为大型组织采购技术的人并不在乎花大价钱购买平庸的软件。反正不是他们的钱。他们只想从看起来安全的供应商那里购买——一家有知名品牌、自信的销售员、气派的办公室,并且软件符合当前潮流的公司。不一定是能交付成果的公司,而是即使让你失望,看起来仍然是一个谨慎选择的公司。因此,一些公司进化成了专门填补这一空缺的角色。
大公司的招聘人员与为大型组织采购技术的人处境非常相似。如果某人毕业于斯坦福大学,而且看起来不像是疯子,那么他们可能是一个安全的选择。而安全的选择就足够了。没有人会通过被拒绝者的后续表现来评估招聘人员。[2]
Graduates of elite colleges would have been capable, yet amenable to authority. And since individual performance is so hard to measure in large organizations, their own confidence would have been the starting point for their reputation. Things are very different in the new world of startups. We couldn't save someone from the market's judgement even if we wanted to. And being charming and confident counts for nothing with users. All users care about is whether you make something they like. If you don't, you're dead. Knowing that test is coming makes us work a lot harder to get the right answers than anyone would if they were merely hiring people. We can't afford to have any illusions about the predictors of success. And what we've found is that the variation between schools is so much smaller than the variation between individuals that it's negligible by comparison. We can learn more about someone in the first minute of talking to them than by knowing where they went to school. It seems obvious when you put it that way. Look at the individual, not where they went to college. But that's a weaker statement than the idea I began with, that it doesn't matter much where a given individual goes to college. Don't you learn things at the best schools that you wouldn't learn at lesser places? Apparently not. Obviously you can't prove this in the case of a single individual, but you can tell from aggregate evidence: you can't, without asking them, distinguish people who went to one school from those who went to another three times as far down the _US News_ list. [3] Try it and see. How can this be? Because how much you learn in college depends a lot more on you than the college. A determined party animal can get through the best school without learning anything. And someone with a real thirst for knowledge will be able to find a few smart people to learn from at a school that isn't prestigious at all.
当然,我并不是说精英大学像企业软件公司一样,进化到利用大型组织的弱点。但它们的效果就像是这样。除了品牌的力量外,精英大学的毕业生还有两个关键特质,完全符合大型组织的运作方式。他们擅长按要求做事,因为这是取悦十七岁时评判你的成年人所需要的。而上过精英大学让他们更加自信。
在过去,人们可能在一家大公司度过整个职业生涯,这些特质一定非常有价值。精英大学的毕业生既有能力,又服从权威。而在大型组织中,个人表现很难衡量,他们的自信会成为他们声誉的起点。
在初创公司的新世界中,情况完全不同。即使我们想,也无法将任何人从市场的评判中拯救出来。而魅力和自信对用户毫无意义。用户只关心你是否做出了他们喜欢的东西。如果没有,你就完蛋了。
知道即将面临这样的考验,我们会更加努力地寻找正确答案,而不仅仅是像普通招聘那样。我们不能对成功的预测因素抱有任何幻想。我们发现,学校之间的差异远小于个人之间的差异,相比之下可以忽略不计。在与某人交谈的第一分钟,我们能了解的信息比知道他们上哪所学校更多。
The other students are the biggest advantage of going to an elite college; you learn more from them than the professors. But you should be able to reproduce this at most colleges if you make a conscious effort to find smart friends. At most colleges you can find at least a handful of other smart students, and most people have only a handful of close friends in college anyway. [4] The odds of finding smart professors are even better. The curve for faculty is a lot flatter than for students, especially in math and the hard sciences; you have to go pretty far down the list of colleges before you stop finding smart professors in the math department. So it's not surprising that we've found the relative prestige of different colleges useless in judging individuals. There's a lot of randomness in how colleges select people, and what they learn there depends much more on them than the college. Between these two sources of variation, the college someone went to doesn't mean a lot. It is to some degree a predictor of ability, but so weak that we regard it mainly as a source of error and try consciously to ignore it. I doubt what we've discovered is an anomaly specific to startups. Probably people have always overestimated the importance of where one goes to college. We're just finally able to measure it. The unfortunate thing is not just that people are judged by such a superficial test, but that so many judge themselves by it. A lot of people, probably the majority of people in America, have some amount of insecurity about where, or whether, they went to college. The tragedy of the situation is that by far the greatest liability of not having gone to the college you'd have liked is your own feeling that you're thereby lacking something. Colleges are a bit like exclusive clubs in this respect. There is only one real advantage to being a member of most exclusive clubs: you know you wouldn't be missing much if you weren't.
这么说似乎显而易见:看个人,而不是他们上哪所大学。但这比我最初的想法要弱——即一个人上哪所大学并不重要。难道你在顶尖学校学到的东西,在普通学校就学不到吗?
显然不是。当然,你无法对单一个体证明这一点,但从整体证据可以看出:如果不问,你无法区分一个人上的是某所学校,还是另一所在《美国新闻》排名低三倍的学校。[3] 试试看就知道了。
为什么会这样?因为你在大学学到的东西更多地取决于你自己,而不是大学。一个决心混日子的学生可以在最好的学校毕业却什么都没学到。而真正渴望知识的人,在一所毫无名气的学校也能找到几个聪明人向他们学习。
其他学生是上精英大学的最大优势;你从他们身上学到的东西比从教授那里更多。但如果你有意识地努力寻找聪明的朋友,在大多数大学里你也能重现这一点。在大多数大学里,你至少能找到一小群其他聪明的学生,而大多数人上大学时也只有几个亲密朋友。[4] 找到聪明的教授的机会更大。教师的水平曲线比学生平坦得多,尤其是在数学和硬科学领域;你必须把大学名单往下翻很远,才会在数学系找不到聪明的教授。
因此,我们发现不同学校的相对声望在评估个人时毫无用处,这并不奇怪。学校选拔学生的方式有很多随机性,而他们在学校学到的东西更多地取决于他们自己,而不是学校。在这两种变异的来源之间,一个人上哪所大学并不重要。它在某种程度上是能力的预测指标,但非常微弱,以至于我们主要将其视为误差来源,并有意识地忽略它。
When you're excluded, you can only imagine the advantages of being an insider. But invariably they're larger in your imagination than in real life. So it is with colleges. Colleges differ, but they're nothing like the stamp of destiny so many imagine them to be. People aren't what some admissions officer decides about them at seventeen. They're what they make themselves. Indeed, the great advantage of not caring where people went to college is not just that you can stop judging them (and yourself) by superficial measures, but that you can focus instead on what really matters. What matters is what you make of yourself. I think that's what we should tell kids. Their job isn't to get good grades so they can get into a good college, but to learn and do. And not just because that's more rewarding than worldly success. That will increasingly _be_ the route to worldly success. Notes [1] Is what we measure worth measuring? I think so. You can get rich simply by being energetic and unscrupulous, but getting rich from a technology startup takes some amount of brains. It is just the kind of work the upper middle class values; it has about the same intellectual component as being a doctor. [2] Actually, someone did, once. Mitch Kapor's wife Freada was in charge of HR at Lotus in the early years. (As he is at pains to point out, they did not become romantically involved till afterward.) At one point they worried Lotus was losing its startup edge and turning into a big company. So as an experiment she sent their recruiters the resumes of the first 40 employees, with identifying details changed. These were the people who had made Lotus into the star it was. Not one got an interview. [3] The _US News_ list? Surely no one trusts that.
我怀疑我们的发现是否是初创公司特有的异常现象。可能人们一直高估了上哪所大学的重要性。只是我们终于能够衡量它了。
不幸的不仅是人们被如此肤浅的测试评判,还有许多人用它来评判自己。很多人,可能是美国的大多数人,对自己上哪所大学或是否上大学感到某种不安全感。这种状况的悲剧在于,没有上你心仪的大学的最大负担,是你自己觉得自己因此缺少了什么。在这方面,大学有点像排他性俱乐部。成为大多数排他性俱乐部会员的唯一真正优势是:你知道如果你不是会员,也不会错过太多。当你被排除在外时,你只能想象成为内部人士的优势。但这些优势在你的想象中总是比现实中更大。
大学也是如此。大学之间确实有差异,但它们远非许多人想象的那种命运印记。人不是某个招生官在十七岁时对他们的判断决定的。人是自己造就的。
事实上,不在乎人们上哪所大学的最大优势不仅是你可以停止用肤浅的标准评判他们(和你自己),而是你可以专注于真正重要的东西。重要的是你如何塑造自己。我认为这才是我们应该告诉孩子们的。他们的任务不是取得好成绩以便进入好大学,而是学习和做事。这不仅是因为这比世俗的成功更有回报。这越来越成为通往世俗成功的途径。
[1] 我们衡量的东西值得衡量吗?我认为值得。仅仅靠精力和无原则就能致富,但从科技初创公司致富需要一定的头脑。这正是中上层阶级重视的工作;它的智力成分与当医生差不多。
Even if the statistics they consider are useful, how do they decide on the relative weights? The reason the _US News_ list is meaningful is precisely because they are so intellectually dishonest in that respect. There is no external source they can use to calibrate the weighting of the statistics they use; if there were, we could just use that instead. What they must do is adjust the weights till the top schools are the usual suspects in about the right order. So in effect what the _US News_ list tells us is what the editors think the top schools are, which is probably not far from the conventional wisdom on the matter. The amusing thing is, because some schools work hard to game the system, the editors will have to keep tweaking their algorithm to get the rankings they want. [4] Possible doesn't mean easy, of course. A smart student at a party school will inevitably be something of an outcast, just as he or she would be in most high schools. Thanks to Trevor Blackwell, Sarah Harlin, Jessica Livingston, Jackie McDonough, Peter Norvig, and Robert Morris for reading drafts of this.
[2] 实际上,曾经有人这样做过。Mitch Kapor的妻子Freada在Lotus早期负责人力资源。(他强调,他们是在那之后才发展为恋爱关系的。)有一次,他们担心Lotus正在失去初创公司的锐气,变成一家大公司。于是她做了一个实验,将前40名员工的简历(修改了识别细节)发给招聘人员。正是这些人让Lotus成为明星。没有一个人获得面试机会。
[3] 《美国新闻》的排名?肯定没人相信它。即使他们考虑的统计数据有用,他们如何决定权重?《美国新闻》排名有意义的原因恰恰是因为他们在这方面非常不诚实。他们没有外部来源可以用来校准统计数据的权重;如果有,我们就可以直接用那个。他们必须调整权重,直到排名靠前的学校是那些通常被认为顶尖的学校,顺序也大致正确。因此,《美国新闻》排名实际上告诉我们的是编辑认为的顶尖学校,这可能与传统的看法相差不远。有趣的是,由于一些学校努力钻营系统,编辑们不得不不断调整算法以获得他们想要的排名。
[4] 可能并不意味着容易。在派对学校,聪明的学生不可避免地会成为某种局外人,就像在大多数高中一样。
感谢 Trevor Blackwell、Sarah Harlin、Jessica Livingston、Jackie McDonough、Peter Norvig和Robert Morris阅读本文草稿。
| 法语翻译
August 2007 A good programmer working intensively on his own code can hold it in his mind the way a mathematician holds a problem he's working on. Mathematicians don't answer questions by working them out on paper the way schoolchildren are taught to. They do more in their heads: they try to understand a problem space well enough that they can walk around it the way you can walk around the memory of the house you grew up in. At its best programming is the same. You hold the whole program in your head, and you can manipulate it at will. That's particularly valuable at the start of a project, because initially the most important thing is to be able to change what you're doing. Not just to solve the problem in a different way, but to change the problem you're solving. Your code is your understanding of the problem you're exploring. So it's only when you have your code in your head that you really understand the problem. It's not easy to get a program into your head. If you leave a project for a few months, it can take days to really understand it again when you return to it. Even when you're actively working on a program it can take half an hour to load into your head when you start work each day. And that's in the best case. Ordinary programmers working in typical office conditions never enter this mode. Or to put it more dramatically, ordinary programmers working in typical office conditions never really understand the problems they're solving. Even the best programmers don't always have the whole program they're working on loaded into their heads. But there are things you can do to help: 1. Avoid distractions. Distractions are bad for many types of work, but especially bad for programming, because programmers tend to operate at the limit of the detail they can handle. The danger of a distraction depends not on how long it is, but on how much it scrambles your brain.
一位专注于自己代码的优秀程序员,能够像数学家把握正在钻研的难题那样,将整个程序装载在脑海中。数学家解题从不似学童般依赖纸笔演算。他们更多在脑中推演:通过深入理解问题空间,得以如漫步于童年故居的记忆般自如穿梭。编程的至高境界亦复如是。你将完整程序存于脑中,便能随心所欲地调遣它。
这种能力在项目初期尤为珍贵,因为最初阶段最重要的是保持调整方向的灵活性。不仅是换种方式解决问题,更要能随时修正问题本身。
A programmer can leave the office and go and get a sandwich without losing the code in his head. But the wrong kind of interruption can wipe your brain in 30 seconds. Oddly enough, scheduled distractions may be worse than unscheduled ones. If you know you have a meeting in an hour, you don't even start working on something hard..
你的代码即是你对探索中问题的认知。唯有当代码烙印在脑海中时,你才真正理解这个问题。
将程序装入大脑并非易事。若中断项目数月,重拾时可能需要数日才能重新透彻理解。即便每日持续开发,每次开工仍需半小时"加载"程序到脑中。这尚且是最理想状况。在典型办公室环境中工作的普通程序员,从未进入过这种状态。或更直白地说——他们从未真正理解自己正在解决的问题。
2. Work in long stretches. Since there's a fixed cost each time you start working on a program, it's more efficient to work in a few long sessions than many short ones. There will of course come a point where you get stupid because you're tired. This varies from person to person. I've heard of people hacking for 36 hours straight, but the most I've ever been able to manage is about 18, and I work best in chunks of no more than 12. The optimum is not the limit you can physically endure. There's an advantage as well as a cost of breaking up a project. Sometimes when you return to a problem after a rest, you find your unconscious mind has left an answer waiting for you.
即使最优秀的程序员,也并非时刻将整个程序装载于脑中。但有些方法能帮助你接近这种状态:
1. 规避干扰。干扰对多数工作都有害,对编程尤甚,因为程序员通常游走在所能处理的信息复杂度极限边缘。
干扰的危害性不取决于时长,而在于其对思维秩序的破坏程度。程序员离座购买三明治时,脑中代码不会消失。但错误的打断方式,三十秒就足以清空你的思维缓存。
3. Use succinct languages. More powerful programming languages make programs shorter. And programmers seem to think of programs at least partially in the language they're using to write them. The more succinct the language, the shorter the program, and the easier it is to load and keep in your head. You can magnify the effect of a powerful language by using a style called bottom-up programming, where you write programs in multiple layers, the lower ones acting as programming languages for those above. If you do this right, you only have to keep the topmost layer in your head.
吊诡的是,计划内的干扰可能比突发干扰更致命。若知晓一小时后要开会,你根本不会着手处理复杂任务。
2. 长时间连续工作。 由于每次开始编程时都有固定的启动成本,因此长时间集中工作比多次短时间工作更高效。当然,过度疲劳会导致效率下降——这个临界点因人而异。我听说过有人能连续编程36小时,但我个人最多只能坚持18小时,而最佳状态通常不超过12小时。
4. Keep rewriting your program. Rewriting a program often yields a cleaner design. But it would have advantages even if it didn't: you have to understand a program completely to rewrite it, so there is no better way to get one loaded into your head.
身体承受极限并非最优解。分段工作既有代价也有益处:有时休息后重返问题,你会发现潜意识已为你准备好了答案。
3. 使用简洁的语言。 更强大的编程语言能让代码更短。程序员思考程序时往往受所用语言的影响。语言越简洁,程序就越短,也越容易在脑中加载和留存。
5. Write rereadable code. All programmers know it's good to write readable code. But you yourself are the most important reader. Especially in the beginning; a prototype is a conversation with yourself. And when writing for yourself you have different priorities. If you're writing for other people, you may not want to make code too dense. Some parts of a program may be easiest to read if you spread things out, like an introductory textbook. Whereas if you're writing code to make it easy to reload into your head, it may be best to go for brevity.
采用自底向上的编程风格能放大高效语言的优势:通过分层编写程序,底层代码充当上层的编程语言。若处理得当,你只需在脑中维护最顶层的逻辑。
4. 持续重写程序。 重写常能催生更清晰的设计。即便没有这个效果,重写也迫使你完全理解程序——这是将代码装入大脑的最佳方式。
5. 编写可重读的代码。 所有程序员都知道代码可读性很重要。但你自己才是最重要的读者,尤其是在初期——原型阶段就是与自我的对话。为自己写代码时,优先级会有所不同:为他人编写时可能需要避免过度紧凑,像教科书般展开某些部分;而为脑内重载优化时,简洁才是王道。
6. Work in small groups. When you manipulate a program in your head, your vision tends to stop at the edge of the code you own. Other parts you don't understand as well, and more importantly, can't take liberties with. So the smaller the number of programmers, the more completely a project can mutate. If there's just one programmer, as there often is at first, you can do all-encompassing redesigns.
6. 小团队协作。 当你在脑中构建程序时,思维边界往往止于自己负责的代码。对其他部分的理解会打折扣,更重要的是无法自由修改。因此团队规模越小,项目越能彻底演化。若只有一名程序员(初期常见),你甚至能进行全盘重构。
7. 避免多人修改同一段代码。 你永远无法像理解自己的代码那样透彻地理解他人的代码。无论你多么仔细地阅读过,那也只是阅读而非创作。因此,如果一段代码由多人共同编写,没有一个人能像单一作者那样完全理解它。
7. Don't have multiple people editing the same piece of code. You never understand other people's code as well as your own. No matter how thoroughly you've read it, you've only read it, not written it. So if a piece of code is written by multiple authors, none of them understand it as well as a single author would. And of course you can't safely redesign something other people are working on. It's not just that you'd have to ask permission. You don't even let yourself think of such things. Redesigning code with several authors is like changing laws; redesigning code you alone control is like seeing the other interpretation of an ambiguous image. If you want to put several people to work on a project, divide it into components and give each to one person.
更何况,你无法安全地重构他人正在修改的代码。这不仅仅是需要获得许可的问题——你甚至不会允许自己产生这种念头。多人协作的代码重构如同修改法律;而独自掌控的代码重构则像是突然看懂了视觉错觉图的另一种解读方式。
若要让多人协作项目,应将项目拆分为独立模块并分配给个人负责。
8. Start small. A program gets easier to hold in your head as you become familiar with it. You can start to treat parts as black boxes once you feel confident you've fully explored them. But when you first start working on a project, you're forced to see everything. If you start with too big a problem, you may never quite be able to encompass it. So if you need to write a big, complex program, the best way to begin may not be to write a spec for it, but to write a prototype that solves a subset of the problem. Whatever the advantages of planning, they're often outweighed by the advantages of being able to keep a program in your head.
8. 从小处着手。 随着对程序的熟悉度增加,你会更容易在脑海中构建其完整图景。当你确信某些部分已被彻底探索后,就能将其视为黑箱处理。但项目初期时,你不得不直面所有细节。若一开始就处理过于庞大的问题,可能永远无法完全掌握全局。因此,当需要编写大型复杂程序时,最佳起点或许不是撰写详细规范,而是先构建能解决子问题的原型。无论计划有多少优势,往往都比不上将完整程序清晰映射在脑海中的价值。
程序员们常常会意外地同时满足这八点,这令人惊讶。某人有了一个新项目的想法,但由于未获官方批准,他只能在业余时间进行——结果反而效率更高,因为没有干扰。出于对新项目的热情,他连续工作数小时。由于最初只是个实验,他没有使用“生产级”语言,而是选择了“脚本”语言——实际上后者强大得多。他彻底重写程序多次;这在正式项目中不可行,但这是出于热爱的劳动,他追求完美。而且除了给自己看的笔记外,他不添加任何注释,因为只有他自己会看这段代码。他被迫在小团队中工作,要么是因为尚未向他人透露想法,要么是想法看起来太不靠谱而不允许其他人参与。即使有团队,也无法多人同时编辑同一代码,因为代码变化太快。项目最初规模很小,因为想法本身就很微小;他只是想尝试某个很酷的 hack。
更令人惊讶的是,许多官方批准的项目竟能完美避开这八点。事实上,观察大多数组织中软件的开发方式,几乎像是刻意反其道而行。某种意义上确实如此。自组织诞生以来,其核心特征之一就是将个体视为可互换的零件。这对可并行化的任务(如战争)很有效。历史上,训练有素的专业军队总能击败个人英雄主义的战士,无论后者多么勇猛。但构思想法很难并行化。而程序正是:想法。
It's striking how often programmers manage to hit all eight points by accident. Someone has an idea for a new project, but because it's not officially sanctioned, he has to do it in off hours—which turn out to be more productive because there are no distractions. Driven by his enthusiasm for the new project he works on it for many hours at a stretch. Because it's initially just an experiment, instead of a "production" language he uses a mere "scripting" language—which is in fact far more powerful. He completely rewrites the program several times; that wouldn't be justifiable for an official project, but this is a labor of love and he wants it to be perfect. And since no one is going to see it except him, he omits any comments except the note-to-self variety. He works in a small group perforce, because he either hasn't told anyone else about the idea yet, or it seems so unpromising that no one else is allowed to work on it. Even if there is a group, they couldn't have multiple people editing the same code, because it changes too fast for that to be possible. And the project starts small because the idea _is_ small at first; he just has some cool hack he wants to try out. Even more striking are the number of officially sanctioned projects that manage to do _all eight things wrong_. In fact, if you look at the way software gets written in most organizations, it's almost as if they were deliberately trying to do things wrong. In a sense, they are. One of the defining qualities of organizations since there have been such a thing is to treat individuals as interchangeable parts. This works well for more parallelizable tasks, like fighting wars. For most of history a well-drilled army of professional soldiers could be counted on to beat an army of individual warriors, no matter how valorous. But having ideas is not very parallelizable. And that's what programs are: ideas.
组织不仅不喜欢依赖个人天才的想法,这甚至是一种同义反复。不依赖个人正是组织定义的一部分——至少是我们当前对组织的理解。
或许我们可以定义一种新型组织,既能整合个人努力,又不要求他们可互换。可以说市场就是这样一种组织形式,尽管更准确的说法可能是:市场是组织无法形成时的默认退化形态。
It's not merely true that organizations dislike the idea of depending on individual genius, it's a tautology. It's part of the definition of an organization not to. Of our current concept of an organization, at least. Maybe we could define a new kind of organization that combined the efforts of individuals without requiring them to be interchangeable. Arguably a market is such a form of organization, though it may be more accurate to describe a market as a degenerate case—as what you get by default when organization isn't possible. Probably the best we'll do is some kind of hack, like making the programming parts of an organization work differently from the rest. Perhaps the optimal solution is for big companies not even to try to develop ideas in house, but simply to buy them. But regardless of what the solution turns out to be, the first step is to realize there's a problem. There is a contradiction in the very phrase "software company." The two words are pulling in opposite directions. Any good programmer in a large organization is going to be at odds with it, because organizations are designed to prevent what programmers strive for. Good programmers manage to get a lot done anyway. But often it requires practically an act of rebellion against the organizations that employ them. Perhaps it will help if more people understand that the way programmers behave is driven by the demands of the work they do. It's not because they're irresponsible that they work in long binges during which they blow off all other obligations, plunge straight into programming instead of writing specs first, and rewrite code that already works. It's not because they're unfriendly that they prefer to work alone, or growl at people who pop their head in the door to say hello. This apparently random collection of annoying habits has a single explanation: the power of holding a program in one's head.
也许我们能做的最佳方案是某种折中,比如让组织中的编程部门以不同方式运作。对大公司而言,最优解可能甚至不是内部研发想法,而是直接收购它们。但无论解决方案是什么,第一步是意识到问题的存在。“软件公司”这个词本身就存在矛盾——两个词在相互拉扯。任何优秀程序员在大组织中都会与之冲突,因为组织设计的目标正是阻止程序员所追求的东西。
优秀程序员仍能设法完成很多工作。但这往往需要近乎反抗组织的行动。或许更多人能理解程序员的行为是由工作需求驱动的,这会有所帮助。他们并非不负责任才长时间沉迷工作、忽略其他义务,不写规格直接编程,或重写已能运行的代码;也并非不友善才偏好独自工作,或对敲门打招呼的人低吼。这些看似随机的恼人习惯有一个共同解释:将程序保持在脑海中的力量。
Whether or not understanding this can help large organizations, it can certainly help their competitors. The weakest point in big companies is that they don't let individual programmers do great work. So if you're a little startup, this is the place to attack them. Take on the kind of problems that have to be solved in one big brain. Thanks to Sam Altman, David Greenspan, Aaron Iba, Jessica Livingston, Robert Morris, Peter Norvig, Lisa Randall, Emmett Shear, Sergei Tsarev, and Stephen Wolfram for reading drafts of this.
| Japanese Translation | | | Simplified Chinese Translation | Portuguese Translation | | | Bulgarian Translation | Russian Translation.
Want to start a startup? Get funded by Y Combinator.
August 2007 _(This is a talk I gave at the last Y Combinator dinner of the summer. Usually we don't have a speaker at the last dinner; it's more of a party. But it seemed worth spoiling the atmosphere if I could save some of the startups from preventable deaths. So at the last minute I cooked up this rather grim talk. I didn't mean this as an essay; I wrote it down because I only had two hours before dinner and think fastest while writing.)_ A couple days ago I told a reporter that we expected about a third of the companies we funded to succeed. Actually I was being conservative. I'm hoping it might be as much as a half. Wouldn't it be amazing if we could achieve a 50% success rate? Another way of saying that is that half of you are going to die. Phrased that way, it doesn't sound good at all. In fact, it's kind of weird when you think about it, because our definition of success is that the founders get rich. If half the startups we fund succeed, then half of you are going to get rich and the other half are going to get nothing. If you can just avoid dying, you get rich. That sounds like a joke, but it's actually a pretty good description of what happens in a typical startup. It certainly describes what happened in Viaweb. We avoided dying till we got rich. It was really close, too. When we were visiting Yahoo to talk about being acquired, we had to interrupt everything and borrow one of their conference rooms to talk down an investor who was about to back out of a new funding round we needed to stay alive. So even in the middle of getting rich we were fighting off the grim reaper. You may have heard that quote about luck consisting of opportunity meeting preparation. You've now done the preparation. The work you've done so far has, in effect, put you in a position to get lucky: you can now get rich by not letting your company die.
That's more than most people have. So let's talk about how not to die. We've done this five times now, and we've seen a bunch of startups die. About 10 of them so far. We don't know exactly what happens when they die, because they generally don't die loudly and heroically. Mostly they crawl off somewhere and die. For us the main indication of impending doom is when we don't hear from you. When we haven't heard from, or about, a startup for a couple months, that's a bad sign. If we send them an email asking what's up, and they don't reply, that's a really bad sign. So far that is a 100% accurate predictor of death. Whereas if a startup regularly does new deals and releases and either sends us mail or shows up at YC events, they're probably going to live. I realize this will sound naive, but maybe the linkage works in both directions. Maybe if you can arrange that we keep hearing from you, you won't die. That may not be so naive as it sounds. You've probably noticed that having dinners every Tuesday with us and the other founders causes you to get more done than you would otherwise, because every dinner is a mini Demo Day. Every dinner is a kind of a deadline. So the mere constraint of staying in regular contact with us will push you to make things happen, because otherwise you'll be embarrassed to tell us that you haven't done anything new since the last time we talked. If this works, it would be an amazing hack. It would be pretty cool if merely by staying in regular contact with us you could get rich. It sounds crazy, but there's a good chance that would work. A variant is to stay in touch with other YC-funded startups. There is now a whole neighborhood of them in San Francisco. If you move there, the peer pressure that made you work harder all summer will continue to operate. When startups die, the official cause of death is always either running out of money or a critical founder bailing.
Often the two occur simultaneously. But I think the underlying cause is usually that they've become demoralized. You rarely hear of a startup that's working around the clock doing deals and pumping out new features, and dies because they can't pay their bills and their ISP unplugs their server. Startups rarely die in mid keystroke. So keep typing! If so many startups get demoralized and fail when merely by hanging on they could get rich, you have to assume that running a startup can be demoralizing. That is certainly true. I've been there, and that's why I've never done another startup. The low points in a startup are just unbelievably low. I bet even Google had moments where things seemed hopeless. Knowing that should help. If you know it's going to feel terrible sometimes, then when it feels terrible you won't think "ouch, this feels terrible, I give up." It feels that way for everyone. And if you just hang on, things will probably get better. The metaphor people use to describe the way a startup feels is at least a roller coaster and not drowning. You don't just sink and sink; there are ups after the downs. Another feeling that seems alarming but is in fact normal in a startup is the feeling that what you're doing isn't working. The reason you can expect to feel this is that what you do probably won't work. Startups almost never get it right the first time. Much more commonly you launch something, and no one cares. Don't assume when this happens that you've failed. That's normal for startups. But don't sit around doing nothing. Iterate. I like Paul Buchheit's suggestion of trying to make something that at least someone really loves. As long as you've made something that a few users are ecstatic about, you're on the right track. It will be good for your morale to have even a handful of users who really love you, and startups run on morale. But also it will tell you what to focus on.
What is it about you that they love? Can you do more of that? Where can you find more people who love that sort of thing? As long as you have some core of users who love you, all you have to do is expand it. It may take a while, but as long as you keep plugging away, you'll win in the end. Both Blogger and Delicious did that. Both took years to succeed. But both began with a core of fanatically devoted users, and all Evan and Joshua had to do was grow that core incrementally. Wufoo is on the same trajectory now. So when you release something and it seems like no one cares, look more closely. Are there zero users who really love you, or is there at least some little group that does? It's quite possible there will be zero. In that case, tweak your product and try again. Every one of you is working on a space that contains at least one winning permutation somewhere in it. If you just keep trying, you'll find it. Let me mention some things not to do. The number one thing not to do is other things. If you find yourself saying a sentence that ends with "but we're going to keep working on the startup," you are in big trouble. Bob's going to grad school, but we're going to keep working on the startup. We're moving back to Minnesota, but we're going to keep working on the startup. We're taking on some consulting projects, but we're going to keep working on the startup. You may as well just translate these to "we're giving up on the startup, but we're not willing to admit that to ourselves," because that's what it means most of the time. A startup is so hard that working on it can't be preceded by "but." In particular, don't go to graduate school, and don't start other projects. Distraction is fatal to startups. Going to (or back to) school is a huge predictor of death because in addition to the distraction it gives you something to say you're doing. If you're only doing a startup, then if the startup fails, you fail.
If you're in grad school and your startup fails, you can say later "Oh yeah, we had this startup on the side when I was in grad school, but it didn't go anywhere." You can't use euphemisms like "didn't go anywhere" for something that's your only occupation. People won't let you. One of the most interesting things we've discovered from working on Y Combinator is that founders are more motivated by the fear of looking bad than by the hope of getting millions of dollars. So if you want to get millions of dollars, put yourself in a position where failure will be public and humiliating. When we first met the founders of Octopart, they seemed very smart, but not a great bet to succeed, because they didn't seem especially committed. One of the two founders was still in grad school. It was the usual story: he'd drop out if it looked like the startup was taking off. Since then he has not only dropped out of grad school, but appeared full length in Newsweek with the word "Billionaire" printed across his chest. He just cannot fail now. Everyone he knows has seen that picture. Girls who dissed him in high school have seen it. His mom probably has it on the fridge. It would be unthinkably humiliating to fail now. At this point he is committed to fight to the death. I wish every startup we funded could appear in a Newsweek article describing them as the next generation of billionaires, because then none of them would be able to give up. The success rate would be 90%. I'm not kidding. When we first knew the Octoparts they were lighthearted, cheery guys. Now when we talk to them they seem grimly determined. The electronic parts distributors are trying to squash them to keep their monopoly pricing. (If it strikes you as odd that people still order electronic parts out of thick paper catalogs in 2007, there's a reason for that.
The distributors want to prevent the transparency that comes from having prices online.) I feel kind of bad that we've transformed these guys from lighthearted to grimly determined. But that comes with the territory. If a startup succeeds, you get millions of dollars, and you don't get that kind of money just by asking for it. You have to assume it takes some amount of pain. And however tough things get for the Octoparts, I predict they'll succeed. They may have to morph themselves into something totally different, but they won't just crawl off and die. They're smart; they're working in a promising field; and they just cannot give up. All of you guys already have the first two. You're all smart and working on promising ideas. Whether you end up among the living or the dead comes down to the third ingredient, not giving up. So I'll tell you now: bad shit is coming. It always is in a startup. The odds of getting from launch to liquidity without some kind of disaster happening are one in a thousand. So don't get demoralized. When the disaster strikes, just say to yourself, ok, this was what Paul was talking about. What did he say to do? Oh, yeah. Don't give up.
| Japanese Translation | | | Arabic Translation.
想创业吗? 获得 Y Combinator 的资金支持。
2007年8月 _(这是我在夏季最后一次Y Combinator晚餐会上的演讲。通常最后一次晚餐我们不会安排演讲,更像是一场派对。但如果能帮助一些初创公司避免可预防的死亡,破坏一下气氛似乎也值得。于是在最后一刻,我准备了这场相当严肃的谈话。这原本不是一篇文章;我之所以写下来,是因为晚餐前只有两小时准备时间,而我在写作时思维最敏捷。)_ 几天前我告诉记者,我们预计资助的公司中约有三分之一会成功。实际上我是保守估计。我希望成功率能达到一半。如果能实现50%的成功率,岂不是很惊人? 换个说法就是:你们当中有一半人会失败。这样听起来可一点都不美好。仔细想想甚至有点奇怪,因为我们对成功的定义是创始人变得富有。如果我们资助的初创公司有一半成功,那么你们中有一半人会变得富有,另一半则一无所获。 只要避免死亡,你就能致富。这听起来像玩笑,但确实是典型初创公司的真实写照。Viaweb的经历就是如此。我们撑到没有死,然后就富了。 而且过程相当惊险。在雅虎洽谈收购时,我们不得不中断会议,借用他们的会议室说服一位投资者——他差点退出我们急需的新一轮融资,而那笔钱关乎生死。所以即便在致富过程中,我们也在与死神搏斗。 你可能听过那句关于运气是机会遇上准备的名言。你们已经完成了准备阶段。截至目前的工作本质上已为你们创造了走运的条件:现在只要不让公司死掉,你们就能致富。这已经比大多数人强了。那么我们来谈谈如何避免死亡。 我们已进行过五次创业孵化,见证过不少初创公司的死亡。至今大约有十家。我们并不完全清楚他们死亡时的具体情形,因为初创公司通常不会轰轰烈烈地倒下,大多是悄无声息地消失。 对我们而言,末日将至的主要征兆就是失去联系。如果几个月没收到某家公司的消息或动态,那就是坏迹象。如果我们发邮件询问近况却得不到回复,那更是凶兆。截至目前,这一预兆的准确率是100%。 反之,如果一家公司持续达成新交易、发布新产品,并保持邮件往来或参加YC活动,他们很可能存活。 我知道这听起来很天真,但或许这种关联是双向的。也许只要设法让我们持续听到你们的消息,你们就不会死。 这可能不像听上去那么天真。你们或许已经注意到,每周二与我们和其他创始人共进晚餐能促使你们完成更多工作,因为每次晚餐都是迷你演示日,都是一次截止期限。仅仅是保持定期联系这个约束,就会推动你们不断行动——否则你们会羞于告诉我们自上次交流后毫无进展。 如果这招奏效,将是个惊人的黑客技巧。仅通过定期与我们保持联系就能致富,这听起来很酷。虽然疯狂,但很可能有效。 另一种方式是与其他YC投资的初创公司保持联络。旧金山现在已形成他们的聚集区。如果你们搬到那里,整个夏天驱使你们加倍努力的同伴压力将持续发挥作用。 初创公司死亡的官方原因总是资金耗尽或关键创始人退出。二者常同时发生。但我认为深层原因通常是士气崩溃。你几乎听不到哪家初创公司在昼夜不停地谈生意、推新功能,却因付不起账单被ISP拔掉服务器而倒闭。 初创公司很少在敲键盘的中途猝死。所以继续敲下去吧! 既然这么多初创公司因士气低落而失败,而实际上只要坚持就能致富,你就必须承认经营初创公司可能令人崩溃。确实如此。我经历过,所以再也没创过业。初创公司的低谷深不可测。我打赌即便是谷歌也有过绝望时刻。 意识到这点应该有帮助。如果你知道有时会感觉糟透了,那么当糟糕时刻来临时,你就不会想着"好痛,太难受了,我放弃"。每个人都会经历这种感受。只要坚持住,情况很可能好转。人们用"坐过山车"而非"溺水"来形容创业感受是有道理的——你不会一直下沉,低谷之后会有高峰。 另一种看似 alarming 实则正常的感受是"我们在做无用功"。产生这种感受很正常,因为你们的工作可能确实暂时无效。初创公司几乎从第一次尝试就能做对。更常见的情况是:你们推出产品,却无人问津。别因此认定自己失败了。这对初创公司很正常。但别坐着不动,要持续迭代。 我欣赏Paul Buchheit的建议:先做出至少让某些人狂热喜爱的产品。只要有小部分用户为你们疯狂,就走对了路。少数忠实用户能极大提振士气,而初创公司靠士气运转。同时这也能指明方向:用户爱你们的什么特质?能否强化这个优势?去哪里找更多同类用户?只要拥有核心粉丝群,你们要做的就是扩大它。这可能需要时间,但只要持续努力,终会成功。Blogger和Delicious都走这条路,都花了数年才成功。但最初它们都有一批狂热用户,Evan和Joshua只需逐步扩大这个群体。Wufoo现在正循此轨迹前进。 所以当你们发布产品却看似无人问津时,请仔细观察:是完全没有狂热用户,还是至少存在一个小群体?完全没人喜欢确实有可能。这时就调整产品再试一次。你们每个人探索的领域都至少存在一个成功组合。只要不断尝试,就会找到它。 现在说说禁忌事项。头号禁忌就是三心二意。如果你们发现自己说出"但我们会继续创业"结尾的句子,那就麻烦大了。"鲍勃要去读研,但我们会继续创业"、"我们要搬回明尼苏达,但会继续创业"、"我们接了咨询项目,但会继续创业"——这些都可以翻译成"我们要放弃创业了,只是不愿承认",因为大多数情况下这就是实情。创业艰难到容不得任何"但是"前缀。 特别要警惕读研和启动其他项目。分心是创业的致命伤。读研(或返校)是死亡的强预测指标,因为除了分散精力,它还给了你们失败的借口。如果只创业,失败就是失败;如果边读研边创业,失败后可以说"哦,读研时顺便创了个业,没什么进展"。 当创业是你们的唯一事业时,就不能用"没什么进展"这类委婉语。人们不会允许。 YC工作中最有趣的发现之一是:比起获取百万财富的希望,创始人更受"怕丢脸"的驱动。所以若想赚大钱,就把自己置于会当众出丑的失败风险中。 初次见到Octopart创始人时,他们很聪明但成功概率不高,因为缺乏破釜沉舟的决心。两位创始人之一仍在读研,打算等创业有起色再退学。后来他不仅退了学,还登上《新闻周刊》封面,胸前印着"亿万富翁"。现在他绝不能失败——所有认识的人都见过那张照片,高中时看不起他的女生见过,他妈可能把它贴在冰箱上。此刻失败将带来难以想象的羞辱,他注定要战斗到底。 真希望我们投资的每家初创公司都能登上《新闻周刊》,被称为"下一代亿万富翁",这样他们就都无法放弃。成功率将达90%。我不是在开玩笑。 初识Octopart团队时,他们是轻松愉快的小伙子。如今交谈时,他们眼中只有背水一战的决绝。电子零件分销商正试图扼杀他们以维持垄断定价。(若你觉得2007年还有人通过纸质目录订购电子零件很荒谬,原因正在于此——分销商想阻止线上价格带来的透明度。)把这些年轻人从轻松愉快逼到破釜沉舟,我有些愧疚。但这就是游戏规则。创业成功意味着数百万美元,而这类财富不会凭空而来,必然伴随痛苦。 无论Octopart前路多艰难,我预测他们会成功。他们可能需要彻底转型,但绝不会悄无声息地死去。他们聪明,身处朝阳行业,而且已无退路。 在座各位都已具备前两个要素:聪明才智和有潜力的创意。最终成为幸存者还是阵亡者,取决于第三个要素——永不放弃。 所以我现在提前告知:坏事即将发生。创业路上永远如此。从创业到上市而不遭遇任何灾难的概率只有千分之一。所以别灰心。当灾难降临时,只需告诉自己:这就是Paul预言的时刻。他建议怎么做?对了,别放弃。
July 2007 An investor wants to give you money for a certain percentage of your startup. Should you take it? You're about to hire your first employee. How much stock should you give him? These are some of the hardest questions founders face. And yet both have the same answer: 1/(1 - n) Whenever you're trading stock in your company for anything, whether it's money or an employee or a deal with another company, the test for whether to do it is the same. You should give up n% of your company if what you trade it for improves your average outcome enough that the (100 - n)% you have left is worth more than the whole company was before. For example, if an investor wants to buy half your company, how much does that investment have to improve your average outcome for you to break even? Obviously it has to double: if you trade half your company for something that more than doubles the company's average outcome, you're net ahead. You have half as big a share of something worth more than twice as much. In the general case, if n is the fraction of the company you're giving up, the deal is a good one if it makes the company worth more than 1/(1 - n). For example, suppose Y Combinator offers to fund you in return for 7% of your company. In this case, n is .07 and 1/(1 - n) is 1.075. So you should take the deal if you believe we can improve your average outcome by more than 7.5%. If we improve your outcome by 10%, you're net ahead, because the remaining .93 you hold is worth .93 x 1.1 = 1.023. [1] One of the things the equity equation shows us is that, financially at least, taking money from a top VC firm can be a really good deal. Greg Mcadoo from Sequoia recently said at a YC dinner that when Sequoia invests alone they like to take about 30% of a company. 1/.7 = 1.43, meaning that deal is worth taking if they can improve your outcome by more than 43%. For the average startup, that would be an extraordinary bargain.
It would improve the average startup's prospects by more than 43% just to be able to _say_ they were funded by Sequoia, even if they never actually got the money. The reason Sequoia is such a good deal is that the percentage of the company they take is artificially low. They don't even try to get market price for their investment; they limit their holdings to leave the founders enough stock to feel the company is still theirs. The catch is that Sequoia gets about 6000 business plans a year and funds about 20 of them, so the odds of getting this great deal are 1 in 300. The companies that make it through are not average startups. Of course, there are other factors to consider in a VC deal. It's never just a straight trade of money for stock. But if it were, taking money from a top firm would generally be a bargain. You can use the same formula when giving stock to employees, but it works in the other direction. If i is the average outcome for the company with the addition of some new person, then they're worth n such that i = 1/(1 - n). Which means n = (i - 1)/i. For example, suppose you're just two founders and you want to hire an additional hacker who's so good you feel he'll increase the average outcome of the whole company by 20%. n = (1.2 - 1)/1.2 = .167. So you'll break even if you trade 16.7% of the company for him. That doesn't mean 16.7% is the right amount of stock to give him. Stock is not the only cost of hiring someone: there's usually salary and overhead as well. And if the company merely breaks even on the deal, there's no reason to do it. I think to translate salary and overhead into stock you should multiply the annual rate by about 1.5. Most startups grow fast or die; if you die you don't have to pay the guy, and if you grow fast you'll be paying next year's salary out of next year's valuation, which should be 3x this year's.
If your valuation grows 3x a year, the total cost in stock of a new hire's salary and overhead is 1.5 years' cost at the present valuation. [2] How much of an additional margin should the company need as the "activation energy" for the deal? Since this is in effect the company's profit on a hire, the market will determine that: if you're a hot opportunity, you can charge more. Let's run through an example. Suppose the company wants to make a "profit" of 50% on the new hire mentioned above. So subtract a third from 16.7% and we have 11.1% as his "retail" price. Suppose further that he's going to cost $60k a year in salary and overhead, x 1.5 = $90k total. If the company's valuation is $2 million, $90k is 4.5%. 11.1% - 4.5% = an offer of 6.6%. Incidentally, notice how important it is for early employees to take little salary. It comes right out of stock that could otherwise be given to them. Obviously there is a great deal of play in these numbers. I'm not claiming that stock grants can now be reduced to a formula. Ultimately you always have to guess. But at least know what you're guessing. If you choose a number based on your gut feel, or a table of typical grant sizes supplied by a VC firm, understand what those are estimates of. And more generally, when you make any decision involving equity, run it through 1/(1 - n) to see if it makes sense. You should always feel richer after trading equity. If the trade didn't increase the value of your remaining shares enough to put you net ahead, you wouldn't have (or shouldn't have) done it. Notes [1] This is why we can't believe anyone would think Y Combinator was a bad deal. Does anyone really think we're so useless that in three months we can't improve a startup's prospects by 7.5%? [2] The obvious choice for your present valuation is the post-money valuation of your last funding round.
This probably undervalues the company, though, because (a) unless your last round just happened, the company is presumably worth more, and (b) the valuation of an early funding round usually reflects some other contribution by the investors. Thanks to Sam Altman, Trevor Blackwell, Paul Buchheit, Hutch Fishman, David Hornik, Paul Kedrosky, Jessica Livingston, Gary Sabot, and Joshua Schachter for reading drafts of this..
2007年7月 一位投资者想用资金换取你初创公司的一定股份。你该接受吗?你即将雇佣第一位员工,该分配多少股份给他? 这些是创始人面临的最棘手问题。但两者答案相同: 1/(1 - n) 当你用公司股权交换任何资源时——无论是资金、人才还是商业合作,判断标准始终一致:只有当交易带来的效益提升足以让你保留的(100 - n)%股权价值超过交易前公司整体价值时,才值得放弃n%的股份。 举例来说,若投资者要收购公司50%股份,这项投资需要将公司平均效益提升多少才能盈亏平衡?显然需要翻倍:若用半数股权换取公司价值增长超一倍,你便稳赚不赔——虽然持股减半,但公司整体价值倍增。 通用公式是:若放弃公司n比例的股权,交易后公司价值需超过1/(1 - n)倍才划算。 假设Y Combinator以7%股权为条件提供融资。此时n为0.07,1/(1-n)为1.075。只要相信我们能提升公司7.5%以上的平均效益,交易就值得进行。若提升幅度达10%,你的剩余93%股权价值将增至0.93×1.1=1.023,实现净收益[1]。 股权公式揭示:从顶级风投融资可能是超值交易。红杉资本Greg Mcadoo在YC晚宴透露,当其单独投资时通常获取30%股份。1/0.7≈1.43,意味着只要他们能提升43%以上的效益,交易就成立。对普通初创企业而言,仅宣称"获红杉投资"即便未获资金,其价值提升就已远超43%。 红杉交易如此优惠的原因在于其刻意压低持股比例。他们不追求市场对价,而是限制持股以确保创始人控股感。 关键在于:红杉每年收到6000份商业计划,仅投资20家,中标概率仅1/300。能入围的绝非普通初创公司。 当然,风投交易还需考量其他因素,绝非简单的股权换资金。但若仅考虑财务因素,顶级机构的投资往往是笔好买卖。 该公式同样适用于员工股权分配,但需逆向运用。若某人才加入能使公司平均效益提升i倍,则其应得股权n满足i=1/(1-n),即n=(i-1)/i。 例如两位创始人拟雇佣一位顶尖黑客,预估其能使公司效益提升20%。则n=(1.2-1)/1.2≈0.167。用16.7%股权换取该人才可盈亏平衡。 但这不意味着16.7%就是合理分配比例。股权并非雇佣唯一成本,还需考虑薪资和管理费用。若交易仅达盈亏平衡,则无必要进行。 将薪资和管理费用折算为股权时,建议将年成本乘以1.5倍。初创企业要么高速发展要么消亡:若失败则无需支付,若成功则次年估值可达当年3倍,可用增值部分支付后续薪资。若估值年增3倍,新员工薪资总成本折算为当前估值下的股权约为1.5年年费[2]。 公司还应预留多少"交易活化能"作为额外利润空间?这本质上是雇佣行为的利润,由市场决定:项目越热门,溢价空间越大。 举例说明:假设公司希望从上述人才获取50%的"利润",则从16.7%扣除三分之一,零售价为11.1%。若其年薪加管理费合计6万美元,1.5倍即9万美元。当公司估值200万美元时,9万占4.5%。最终股权报价为11.1%-4.5%=6.6%。 值得注意的是:早期员工低薪的重要性——省下的薪资可直接转化为给他们的股权。 显然这些数字存在很大弹性空间。我并非主张股权分配可完全公式化,最终仍需主观判断。但至少要明白判断依据。若凭直觉或参照风投提供的典型股权表做决定,需清楚这些数据的估算逻辑。 更广义而言,任何涉及股权的决策都可用1/(1-n)验证。股权交易后你应感到更富有。若剩余股权增值未能实现净收益,这个交易本不该发生。 注释 [1] 正因如此,我们难以相信会有人认为YC交易不划算。真有人觉得我们三个月内连7.5%的价值都提升不了吗? [2] 当前估值通常参考最近一轮融资后估值。但这可能低估公司价值,因为:(a)除非刚完成融资,否则公司价值理应增长;(b)早期融资估值通常包含投资者的附加贡献。 致谢 Sam Altman、Trevor Blackwell、Paul Buchheit、Hutch Fishman、David Hornik、Paul Kedrosky、Jessica Livingston、Gary Sabot和Joshua Schachter对本文草稿的审阅。
July 2007 I have too much stuff. Most people in America do. In fact, the poorer people are, the more stuff they seem to have. Hardly anyone is so poor that they can't afford a front yard full of old cars. It wasn't always this way. Stuff used to be rare and valuable. You can still see evidence of that if you look for it. For example, in my house in Cambridge, which was built in 1876, the bedrooms don't have closets. In those days people's stuff fit in a chest of drawers. Even as recently as a few decades ago there was a lot less stuff. When I look back at photos from the 1970s, I'm surprised how empty houses look. As a kid I had what I thought was a huge fleet of toy cars, but they'd be dwarfed by the number of toys my nephews have. All together my Matchboxes and Corgis took up about a third of the surface of my bed. In my nephews' rooms the bed is the only clear space. Stuff has gotten a lot cheaper, but our attitudes toward it haven't changed correspondingly. We overvalue stuff. That was a big problem for me when I had no money. I felt poor, and stuff seemed valuable, so almost instinctively I accumulated it. Friends would leave something behind when they moved, or I'd see something as I was walking down the street on trash night (beware of anything you find yourself describing as "perfectly good"), or I'd find something in almost new condition for a tenth its retail price at a garage sale. And pow, more stuff. In fact these free or nearly free things weren't bargains, because they were worth even less than they cost. Most of the stuff I accumulated was worthless, because I didn't need it. What I didn't understand was that the value of some new acquisition wasn't the difference between its retail price and what I paid for it. It was the value I derived from it. Stuff is an extremely illiquid asset.
Unless you have some plan for selling that valuable thing you got so cheaply, what difference does it make what it's "worth?" The only way you're ever going to extract any value from it is to use it. And if you don't have any immediate use for it, you probably never will. Companies that sell stuff have spent huge sums training us to think stuff is still valuable. But it would be closer to the truth to treat stuff as worthless. In fact, worse than worthless, because once you've accumulated a certain amount of stuff, it starts to own you rather than the other way around. I know of one couple who couldn't retire to the town they preferred because they couldn't afford a place there big enough for all their stuff. Their house isn't theirs; it's their stuff's. And unless you're extremely organized, a house full of stuff can be very depressing. A cluttered room saps one's spirits. One reason, obviously, is that there's less room for people in a room full of stuff. But there's more going on than that. I think humans constantly scan their environment to build a mental model of what's around them. And the harder a scene is to parse, the less energy you have left for conscious thoughts. A cluttered room is literally exhausting. (This could explain why clutter doesn't seem to bother kids as much as adults. Kids are less perceptive. They build a coarser model of their surroundings, and this consumes less energy.) I first realized the worthlessness of stuff when I lived in Italy for a year. All I took with me was one large backpack of stuff. The rest of my stuff I left in my landlady's attic back in the US. And you know what? All I missed were some of the books. By the end of the year I couldn't even remember what else I had stored in that attic. And yet when I got back I didn't discard so much as a box of it. Throw away a perfectly good rotary telephone? I might need that one day.
The really painful thing to recall is not just that I accumulated all this useless stuff, but that I often spent money I desperately needed on stuff that I didn't. Why would I do that? Because the people whose job is to sell you stuff are really, really good at it. The average 25 year old is no match for companies that have spent years figuring out how to get you to spend money on stuff. They make the experience of buying stuff so pleasant that "shopping" becomes a leisure activity. How do you protect yourself from these people? It can't be easy. I'm a fairly skeptical person, and their tricks worked on me well into my thirties. But one thing that might work is to ask yourself, before buying something, "is this going to make my life noticeably better?" A friend of mine cured herself of a clothes buying habit by asking herself before she bought anything "Am I going to wear this all the time?" If she couldn't convince herself that something she was thinking of buying would become one of those few things she wore all the time, she wouldn't buy it. I think that would work for any kind of purchase. Before you buy anything, ask yourself: will this be something I use constantly? Or is it just something nice? Or worse still, a mere bargain? The worst stuff in this respect may be stuff you don't use much because it's too good. Nothing owns you like fragile stuff. For example, the "good china" so many households have, and whose defining quality is not so much that it's fun to use, but that one must be especially careful not to break it. Another way to resist acquiring stuff is to think of the overall cost of owning it. The purchase price is just the beginning. You're going to have to _think_ about that thing for years—perhaps for the rest of your life. Every thing you own takes energy away from you. Some give more than they take. Those are the only things worth having. I've now stopped accumulating stuff.
Except books—but books are different. Books are more like a fluid than individual objects. It's not especially inconvenient to own several thousand books, whereas if you owned several thousand random possessions you'd be a local celebrity. But except for books, I now actively avoid stuff. If I want to spend money on some kind of treat, I'll take services over goods any day. I'm not claiming this is because I've achieved some kind of zenlike detachment from material things. I'm talking about something more mundane. A historical change has taken place, and I've now realized it. Stuff used to be valuable, and now it's not. In industrialized countries the same thing happened with food in the middle of the twentieth century. As food got cheaper (or we got richer; they're indistinguishable), eating too much started to be a bigger danger than eating too little. We've now reached that point with stuff. For most people, rich or poor, stuff has become a burden. The good news is, if you're carrying a burden without knowing it, your life could be better than you realize. Imagine walking around for years with five pound ankle weights, then suddenly having them removed.
| Spanish Translation | | | Russian Translation | Italian Translation | | | Polish Translation | Turkish Translation | | | French Translation | Slovak Translation | | | Romanian Translation | German Translation.
2007年7月 我拥有太多东西了。大多数美国人都是如此。事实上,越穷的人似乎拥有的东西越多。几乎没有人会穷到连前院都停不满旧车的地步。 过去并非如此。物品曾稀有而珍贵。仔细观察仍能发现痕迹。比如我在剑桥建于1876年的房子里,卧室都没有壁橱。那个年代人们的家当只需一个五斗橱就能装下。即便近至几十年前,物品也少得多。回看1970年代的照片,我会惊讶于房屋的空荡。儿时自以为拥有庞大玩具车队的火柴盒和柯基模型车,如今在我外甥们的玩具面前相形见绌——当年它们只占我床铺三分之一面积,而现在外甥们的房间里唯一整洁的空间只剩床铺。 物品价格已大幅下降,但我们的态度却未相应改变。我们高估了物品的价值。 这在我经济拮据时是个大问题。因感到贫穷而珍视物品,我几乎本能地囤积它们:朋友搬家留下的物件、垃圾回收夜街头发现的"完好无损"的宝贝、车库拍卖中以零售价一成淘到的九成新物品...转眼间,东西又多了。 其实这些免费或近乎免费的物品并非划算,因为它们实际价值甚至低于获取成本。我囤积的大多数东西毫无价值,因为我根本不需要。 当年我不明白:新物品的价值不在于零售价与实付价的差额,而在于它能带来的效用。物品是流动性极差的资产。除非计划转售那些廉价获得的"贵重物品",否则它们的"价值"毫无意义。实现物品价值的唯一途径是使用它——若当下用不上,很可能永远用不上。 销售商花费巨资让我们坚信物品仍有价值。但更接近真相的做法是把物品视为无价值。 事实上,物品比无价值更糟。当积累达到某个临界点,物品就开始反客为主。我认识一对夫妇因无法负担容纳所有物品的房子,被迫放弃理想的退休小镇。他们的房子不属于他们,而属于他们的物品。 除非极善整理,满屋物品会令人压抑。杂乱房间消耗人的精力。原因不仅是物品挤占了人的空间,更深层的是人类需要持续扫描环境来构建心理模型。场景越难解析,留给主动思考的精力就越少——杂乱房间本质上是种消耗。 (这解释了为何孩子不像成人那样受杂物困扰:他们的感知较粗糙,构建环境模型消耗的能量更少。) 我在意大利旅居那年首次认识到物品的无价值。当时只带了一个大背包,其余物品留在美国房东的阁楼。结果呢?我只想念部分书籍。到年末,我甚至记不清阁楼里还存着什么。 然而归来后,我连一箱物品都没丢弃。"扔掉完好的转盘电话?说不定哪天会用上"。真正痛心的不仅在于囤积无用之物,更在于曾为它们耗费急需的金钱。 为何会这样?因为销售人员的本领实在高超。普通25岁年轻人绝非那些钻研消费心理多年的企业的对手。他们让购物体验如此愉悦,以致"血拼"成了休闲活动。 如何防范?这并不容易。我算相当多疑的人,但直到三十多岁仍被套路。或许有效的办法是在购买前自问:"这会让我的生活明显改善吗?" 我一位朋友用"我会经常穿吗"的自问戒掉了买衣瘾。若无法确信某件衣服会成为高频穿着,她就不买。我认为这适用于任何消费。购买前请自问:这是日常必需品,还是仅仅好看?或是更糟——只因便宜? 最糟糕的或许是那些因太贵重而很少使用的物品。没有什么比易碎品更奴役人了。比如许多家庭拥有的"精美瓷器",其核心特质并非使用乐趣,而是需要格外小心避免打碎。 另一种抵制囤积的方法是计算总体拥有成本。购买价格只是开始——你将为此物耗费数年心力,甚至余生。每件物品都在夺取你的能量。唯有给予大于索取之物,才值得拥有。 如今我已停止囤积——除书籍外(书籍不同,它们更像流动的整体)。拥有数千本书不算负担,但若拥有数千件杂货,你早成社区名人了。除书籍外,我现在积极回避物品。若想消费,我永远选择服务而非商品。 并非我达到了超脱物欲的境界,而是认清了一个更朴实的现实:历史性转变已经发生。物品曾珍贵,而今已非。 二十世纪中叶,工业化国家的食物也经历了同样转变。当食物变得廉价(或我们变得富裕,这两者难以区分),过量饮食的危害开始超过营养不良。如今物品也到了这个临界点——对多数人而言,无论贫富,物品已成负担。 好消息是:若你正背负不自知的负担,你的生活可能比想象中更有提升空间。想象戴着五磅脚镣行走多年后突然卸下它的感觉。
| 西班牙语译本 | | | 俄语译本 | 意大利语译本 | | | 波兰语译本 | 土耳其语译本 | | | 法语译本 | 斯洛伐克语译本 | | | 罗马尼亚语译本 | 德语译本.
[](https://s.turbifycdn.com/aah/paulgraham/an-alternative-theory-of-unions-11.gif) May 2007 People who worry about the increasing gap between rich and poor generally look back on the mid twentieth century as a golden age. In those days we had a large number of high-paying union manufacturing jobs that boosted the median income. I wouldn't quite call the high-paying union job a myth, but I think people who dwell on it are reading too much into it. Oddly enough, it was working with startups that made me realize where the high-paying union job came from. In a rapidly growing market, you don't worry too much about efficiency. It's more important to grow fast. If there's some mundane problem getting in your way, and there's a simple solution that's somewhat expensive, just take it and get on with more important things. EBay didn't win by paying less for servers than their competitors. Difficult though it may be to imagine now, manufacturing was a growth industry in the mid twentieth century. This was an era when small firms making everything from cars to candy were getting consolidated into a new kind of corporation with national reach and huge economies of scale. You had to grow fast or die. Workers were for these companies what servers are for an Internet startup. A reliable supply was more important than low cost. If you looked in the head of a 1950s auto executive, the attitude must have been: sure, give 'em whatever they ask for, so long as the new model isn't delayed. In other words, those workers were not paid what their work was worth. Circumstances being what they were, companies would have been stupid to insist on paying them so little. If you want a less controversial example of this phenomenon, ask anyone who worked as a consultant building web sites during the Internet Bubble. In the late nineties you could get paid huge sums of money for building the most trivial things.
[](https://s.turbifycdn.com/aah/paulgraham/an-alternative-theory-of-unions-11.gif)
那些担忧贫富差距不断扩大的人,通常将二十世纪中叶视作黄金时代。那时我们拥有大量高薪的工会制造业岗位,拉高了中位数收入。我不愿将高薪工会工作完全称为神话,但我认为过度推崇它的人赋予了它太多意义。
奇怪的是,正是与初创公司合作的经历让我明白了高薪工会岗位的起源。在快速增长的市场中,人们不会过分纠结效率问题。快速扩张才更重要。如果某个琐碎问题阻碍了进程,而解决方法虽昂贵但简单,那就直接采用它,把精力留给更重要的事。eBay的胜出并非靠比竞争对手支付更低的服务器成本。
尽管如今难以想象,但制造业在二十世纪中叶确实是增长型行业。那是一个从小型汽车厂到糖果商都被整合为具有全国影响力、享受巨大规模经济的新型企业的时代。要么快速成长,要么灭亡。对这些公司而言,工人就如同互联网初创公司的服务器——稳定供应比低成本更重要。
若你能窥见1950年代汽车高管的想法,他们的态度必然是:行,只要不耽误新车发布,他们要什么就给什么。
And yet does anyone who was there have any expectation those days will ever return? I doubt it. Surely everyone realizes that was just a temporary aberration. The era of labor unions seems to have been the same kind of aberration, just spread over a longer period, and mixed together with a lot of ideology that prevents people from viewing it with as cold an eye as they would something like consulting during the Bubble. Basically, unions were just Razorfish. People who think the labor movement was the creation of heroic union organizers have a problem to explain: why are unions shrinking now? The best they can do is fall back on the default explanation of people living in fallen civilizations. Our ancestors were giants. The workers of the early twentieth century must have had a moral courage that's lacking today. In fact there's a simpler explanation. The early twentieth century was just a fast-growing startup overpaying for infrastructure. And we in the present are not a fallen people, who have abandoned whatever mysterious high-minded principles produced the high-paying union job. We simply live in a time when the fast-growing companies overspend on different things..
换言之,那些工人的报酬并非基于其劳动的真实价值。在当时的背景下,若企业坚持压低工资,那才是愚蠢之举。
若想要一个争议较小的例子,不妨问问互联网泡沫时期从事网站建设的顾问。九十年代末,即便搭建最简陋的网站也能获得巨额报酬。但亲历者中有谁期待那种日子会重现吗?恐怕没有。所有人都明白那只是暂时的异常现象。
工会时代似乎也是同类异常,只不过持续更久,且掺杂了大量意识形态,使人们无法像看待泡沫时期的咨询业那样冷静审视它。
本质上,工会不过是另一个Razorfish(注:泡沫时期著名的昂贵设计公司)。
那些将劳工运动归功于英勇工会组织者的人面临一个无法解释的问题:为何如今工会日渐式微?他们最多只能搬出衰落文明论者的陈词滥调——我们的祖先是巨人,二十世纪初的工人必定拥有今人缺失的道德勇气。
事实上解释更简单:二十世纪初只是个为基础设施过度付费的快速成长型初创公司。当下的我们并非道德沦丧的族群,也未曾抛弃那些神秘高尚的原则(假设这些原则真能催生高薪工会岗位)。我们只是生活在另一个时代——如今快速发展的企业将超额支出投向了不同领域。
April 2007 A few days ago I suddenly realized Microsoft was dead. I was talking to a young startup founder about how Google was different from Yahoo. I said that Yahoo had been warped from the start by their fear of Microsoft. That was why they'd positioned themselves as a "media company" instead of a technology company. Then I looked at his face and realized he didn't understand. It was as if I'd told him how much girls liked Barry Manilow in the mid 80s. Barry who? Microsoft? He didn't say anything, but I could tell he didn't quite believe anyone would be frightened of them. Microsoft cast a shadow over the software world for almost 20 years starting in the late 80s. I can remember when it was IBM before them. I mostly ignored this shadow. I never used Microsoft software, so it only affected me indirectly—for example, in the spam I got from botnets. And because I wasn't paying attention, I didn't notice when the shadow disappeared. But it's gone now. I can sense that. No one is even afraid of Microsoft anymore. They still make a lot of money—so does IBM, for that matter. But they're not dangerous. When did Microsoft die, and of what? I know they seemed dangerous as late as 2001, because I wrote an essay then about how they were less dangerous than they seemed. I'd guess they were dead by 2005. I know when we started Y Combinator we didn't worry about Microsoft as competition for the startups we funded. In fact, we've never even invited them to the demo days we organize for startups to present to investors. We invite Yahoo and Google and some other Internet companies, but we've never bothered to invite Microsoft. Nor has anyone there ever even sent us an email. They're in a different world. What killed them? Four things, I think, all of them occurring simultaneously in the mid 2000s. The most obvious is Google. There can only be one big man in town, and they're clearly it.
几天前我突然意识到微软已经死了。当时我正在和一位年轻的初创公司创始人谈论谷歌与雅虎的不同之处。我说雅虎从一开始就被对微软的恐惧所扭曲,这就是为什么他们将自身定位为"媒体公司"而非技术公司。这时我看着他的脸,意识到他并不理解。就好像我告诉他80年代中期女孩们有多喜欢巴里·马尼洛——巴里是谁?
微软?他什么都没说,但我能看出他并不相信有人会害怕他们。
从80年代末开始,微软在软件世界投下了长达近20年的阴影。我记得在他们之前是IBM。我大多忽视了这个阴影。我从未使用过微软的软件,所以它只间接影响我——比如通过僵尸网络发送的垃圾邮件。正因没有关注,我甚至没注意到这个阴影何时消失。
但它现在确实消失了。我能感觉到。再没有人害怕微软了。他们仍在赚大钱——IBM也是。但他们不再具有威胁性。
Google is the most dangerous company now by far, in both the good and bad senses of the word. Microsoft can at best limp along afterward. When did Google take the lead? There will be a tendency to push it back to their IPO in August 2004, but they weren't setting the terms of the debate then. I'd say they took the lead in 2005\. Gmail was one of the things that put them over the edge. Gmail showed they could do more than search. Gmail also showed how much you could do with web-based software, if you took advantage of what later came to be called "Ajax." And that was the second cause of Microsoft's death: everyone can see the desktop is over. It now seems inevitable that applications will live on the web—not just email, but everything, right up to Photoshop. Even Microsoft sees that now. Ironically, Microsoft unintentionally helped create Ajax. The x in Ajax is from the XMLHttpRequest object, which lets the browser communicate with the server in the background while displaying a page. (Originally the only way to communicate with the server was to ask for a new page.) XMLHttpRequest was created by Microsoft in the late 90s because they needed it for Outlook. What they didn't realize was that it would be useful to a lot of other people too—in fact, to anyone who wanted to make web apps work like desktop ones. The other critical component of Ajax is Javascript, the programming language that runs in the browser. Microsoft saw the danger of Javascript and tried to keep it broken for as long as they could. [1] But eventually the open source world won, by producing Javascript libraries that grew over the brokenness of Explorer the way a tree grows over barbed wire. The third cause of Microsoft's death was broadband Internet. Anyone who cares can have fast Internet access now. And the bigger the pipe to the server, the less you need the desktop.
微软何时死亡?死于什么?我知道直到2001年他们似乎还很危险,因为我当时写过一篇文章讨论他们实际没有看起来那么危险。我猜他们在2005年前就已死亡。我记得创办Y Combinator时,我们根本不担心微软会成为所投资初创公司的竞争对手。事实上,我们甚至从未邀请他们参加为初创公司面向投资者举办的演示日。我们邀请雅虎、谷歌和其他互联网公司,但从没费心邀请微软。他们那边也从未有人给我们发过邮件。他们活在另一个世界。
杀死他们的是什么?我认为是四件事,都发生在2000年代中期同时发生。
最明显的是谷歌。一个领域只能有一个巨头,而谷歌显然就是。谷歌现在是迄今为止最危险的公司,无论从褒义还是贬义来说。微软充其量只能蹒跚跟随。
谷歌何时领先?人们倾向于追溯到2004年8月他们的IPO,但那时他们还未设定行业标准。我认为是在2005年。Gmail是推动他们跨越界限的因素之一。Gmail证明他们能做的不仅是搜索。
Gmail还展示了基于网络的软件能实现多少功能,如果你利用后来被称为"Ajax"的技术。这就是微软死亡的第二个原因:所有人都看到桌面时代结束了。应用程序将存在于网络上——不仅是电子邮件,而是一切,直到Photoshop——现在看起来不可避免。甚至微软现在也明白了。
The last nail in the coffin came, of all places, from Apple. Thanks to OS X, Apple has come back from the dead in a way that is extremely rare in technology. [2] Their victory is so complete that I'm now surprised when I come across a computer running Windows. Nearly all the people we fund at Y Combinator use Apple laptops. It was the same in the audience at startup school. All the computer people use Macs or Linux now. Windows is for grandmas, like Macs used to be in the 90s. So not only does the desktop no longer matter, no one who cares about computers uses Microsoft's anyway. And of course Apple has Microsoft on the run in music too, with TV and phones on the way. I'm glad Microsoft is dead. They were like Nero or Commodus—evil in the way only inherited power can make you. Because remember, the Microsoft monopoly didn't begin with Microsoft. They got it from IBM. The software business was overhung by a monopoly from about the mid-1950s to about 2005. For practically its whole existence, that is. One of the reasons "Web 2.0" has such an air of euphoria about it is the feeling, conscious or not, that this era of monopoly may finally be over. Of course, as a hacker I can't help thinking about how something broken could be fixed. Is there some way Microsoft could come back? In principle, yes. To see how, envision two things: (a) the amount of cash Microsoft now has on hand, and (b) Larry and Sergey making the rounds of all the search engines ten years ago trying to sell the idea for Google for a million dollars, and being turned down by everyone. The surprising fact is, brilliant hackers—dangerously brilliant hackers—can be had very cheaply, by the standards of a company as rich as Microsoft. They can't hire smart people anymore, but they could buy as many as they wanted for only an order of magnitude more.
讽刺的是,微软无意中帮助创造了Ajax。Ajax中的x来自XMLHttpRequest对象,它让浏览器在显示页面时能在后台与服务器通信。(最初与服务器通信的唯一方式是请求新页面。)XMLHttpRequest是微软在90年代末为Outlook需求而创建的。他们没意识到这对其他许多人——实际上是想让网络应用像桌面应用一样工作的任何人——也会有用。
Ajax的另一个关键组件是Javascript这种在浏览器中运行的编程语言。微软看到了Javascript的危险,并尽可能长时间地阻碍其发展。[1]但最终开源世界通过开发克服Explorer缺陷的Javascript库获胜,就像树木生长覆盖铁丝网一样。
微软死亡的第三个原因是宽带互联网。现在任何在意的人都能拥有快速网络连接。通往服务器的管道越大,对桌面的需求就越少。
棺材上的最后一颗钉子来自苹果。多亏OS X,苹果以一种在科技界极为罕见的方式起死回生。[2]他们的胜利如此彻底,以至于我现在看到运行Windows的电脑会感到惊讶。Y Combinator资助的几乎所有人都使用苹果笔记本。在初创学校观众中也是如此。现在所有懂电脑的人都用Mac或Linux。Windows是为祖母们准备的,就像90年代的Mac。所以不仅桌面不再重要,而且关心电脑的人也不再使用微软的产品。
So if they wanted to be a contender again, this is how they could do it: 1. Buy all the good "Web 2.0" startups. They could get substantially all of them for less than they'd have to pay for Facebook..
当然,苹果在音乐领域也让微软节节败退,电视和手机领域也即将如此。
我很高兴微软死了。他们就像尼禄或康茂德——只有继承的权力才能造就的那种邪恶。因为记住,微软的垄断并非始于微软。他们是从IBM获得的。软件行业从大约1950年代中期到2005年一直笼罩在垄断之下。几乎贯穿其整个存在时期。"Web 2.0"之所以充满兴奋感,原因之一就是人们有意或无意地感觉到这个垄断时代可能终于结束了。
当然,作为黑客,我不禁思考如何修复破损的东西。微软有可能卷土重来吗?原则上是的。要明白这点,想象两件事:(a)微软现在持有的现金数量,(b)十年前拉里和谢尔盖试图以一百万美元出售谷歌的想法被所有搜索引擎拒绝。
令人惊讶的事实是,以微软这样富有的公司的标准来看,才华横溢的黑客——危险地才华横溢的黑客——可以非常廉价地获得。他们不能再雇佣聪明人,但可以以仅高一个数量级的价格购买任意数量。所以如果他们想再次成为竞争者,可以这样做:
1. 收购所有优秀的"Web 2.0"初创公司。他们可以用低于收购Facebook的价格买下几乎所有这类公司。
2. Put them all in a building in Silicon Valley, surrounded by lead shielding to protect them from any contact with Redmond.
2. 把他们全部安置在硅谷的一栋大楼里,用铅屏蔽层包裹起来,防止他们与雷德蒙德有任何接触。
我提出这个建议很放心,因为他们永远不会这么做。微软最大的弱点在于,他们仍然没有意识到自己有多糟糕。他们依然认为自己可以内部开发软件。也许以桌面世界的标准来看,他们确实可以。但那个世界几年前就已经终结了。
我早已预见到这篇文章会引发的反应。一半读者会说微软仍然是利润极其丰厚的公司,并指责我不该基于我们封闭的"Web 2.0"小圈子里少数人的想法就妄下结论。另一半更年轻的读者则会抱怨说这早已是旧闻。
另见:微软已死:简明版
I feel safe suggesting this, because they'd never do it. Microsoft's biggest weakness is that they still don't realize how much they suck. They still think they can write software in house. Maybe they can, by the standards of the desktop world. But that world ended a few years ago. I already know what the reaction to this essay will be. Half the readers will say that Microsoft is still an enormously profitable company, and that I should be more careful about drawing conclusions based on what a few people think in our insular little "Web 2.0" bubble. The other half, the younger half, will complain that this is old news. See also: Microsoft is Dead: the Cliffs Notes Notes [1] It doesn't take a conscious effort to make software incompatible. All you have to do is not work too hard at fixing bugs—which, if you're a big company, you produce in copious quantities. The situation is analogous to the writing of "literary theorists." Most don't try to be obscure; they just don't make an effort to be clear. It wouldn't pay. [2] In part because Steve Jobs got pushed out by John Sculley in a way that's rare among technology companies. If Apple's board hadn't made that blunder, they wouldn't have had to bounce back.
| Portuguese Translation | Simplified Chinese Translation | Korean Translation
April 2007 _(This essay is derived from a keynote talk at the 2007 ASES Summit at Stanford.)_ The world of investors is a foreign one to most hackers—partly because investors are so unlike hackers, and partly because they tend to operate in secret. I've been dealing with this world for many years, both as a founder and an investor, and I still don't fully understand it. In this essay I'm going to list some of the more surprising things I've learned about investors. Some I only learned in the past year. Teaching hackers how to deal with investors is probably the second most important thing we do at Y Combinator. The most important thing for a startup is to make something good. But everyone knows that's important. The dangerous thing about investors is that hackers don't know how little they know about this strange world. 1\. The investors are what make a startup hub. About a year ago I tried to figure out what you'd need to reproduce Silicon Valley. I decided the critical ingredients were rich people and nerds—investors and founders. People are all you need to make technology, and all the other people will move. If I had to narrow that down, I'd say investors are the limiting factor. Not because they contribute more to the startup, but simply because they're least willing to move. They're rich. They're not going to move to Albuquerque just because there are some smart hackers there they could invest in. Whereas hackers will move to the Bay Area to find investors. 2\. Angel investors are the most critical. There are several types of investors. The two main categories are angels and VCs: VCs invest other people's money, and angels invest their own. Though they're less well known, the angel investors are probably the more critical ingredient in creating a silicon valley. Most companies that VCs invest in would never have made it that far if angels hadn't invested first.
(本文改编自2007年斯坦福ASES峰会上的主题演讲。)
对大多数黑客而言,投资人的世界陌生而遥远——部分原因是投资人与黑客截然不同,部分则因为他们行事隐秘。作为创业者和投资人,我与这个世界打了多年交道,却仍未能完全参透其中奥妙。
在这篇文章中,我将列举关于投资人的一些反常识认知,其中有些是我去年才领悟到的。
在Y Combinator,教授黑客如何与投资人打交道可能是我们第二重要的工作。对初创企业而言,最重要的是打造优秀产品——这一点人尽皆知。但投资人的危险之处在于,黑客往往意识不到自己对这个陌生世界的认知有多么匮乏。
1. 投资人塑造了创业中心
VCs say between half and three quarters of companies that raise series A rounds have taken some outside investment already. [1] Angels are willing to fund riskier projects than VCs. They also give valuable advice, because (unlike VCs) many have been startup founders themselves. Google's story shows the key role angels play. A lot of people know Google raised money from Kleiner and Sequoia. What most don't realize is how late. That VC round was a series B round; the premoney valuation was $75 million. Google was already a successful company at that point. Really, Google was funded with angel money. It may seem odd that the canonical Silicon Valley startup was funded by angels, but this is not so surprising. Risk is always proportionate to reward. So the most successful startup of all is likely to have seemed an extremely risky bet at first, and that is exactly the kind VCs won't touch. Where do angel investors come from? From other startups. So startup hubs like Silicon Valley benefit from something like the marketplace effect, but shifted in time: startups are there because startups were there. 3\. Angels don't like publicity. If angels are so important, why do we hear more about VCs? Because VCs like publicity. They need to market themselves to the investors who are their "customers"—the endowments and pension funds and rich families whose money they invest—and also to founders who might come to them for funding. Angels don't need to market themselves to investors because they invest their own money. Nor do they want to market themselves to founders: they don't want random people pestering them with business plans. Actually, neither do VCs. Both angels and VCs get deals almost exclusively through personal introductions. [2] The reason VCs want a strong brand is not to draw in more business plans over the transom, but so they win deals when competing against other VCs.
大约一年前,我曾试图推演如何复制硅谷的成功。我认为核心要素是富人和极客——即投资人与创业者。技术创造只需这两类人,其他角色自会随之而来。
若要进一步精简,投资人才是决定性因素。并非因为他们对初创企业贡献更大,而是因为他们最不愿意迁移。他们足够富有,绝不会因为阿尔伯克基有几个聪明黑客值得投资就搬去那里。而黑客却会为了寻找投资人涌向湾区。
2. 天使投资人才是关键
投资人分为多种类型,主要两类是天使投资人和风险投资人(VC):前者投入自有资金,后者管理他人资本。
尽管知名度较低,天使投资人才是硅谷生态更关键的要素。多数获得风投的企业,若没有天使投资人早期注资根本走不到A轮融资。据VC透露,50%-75%完成A轮融资的公司此前都接受过外部投资[1]。
天使投资人比VC更愿意押注高风险项目。他们往往拥有创业经历(这与VC不同),因此能提供宝贵建议。
Whereas angels are rarely in direct competition, because (a) they do fewer deals, (b) they're happy to split them, and (c) they invest at a point where the stream is broader. 4\. Most investors, especially VCs, are not like founders. Some angels are, or were, hackers. But most VCs are a different type of people: they're dealmakers. If you're a hacker, here's a thought experiment you can run to understand why there are basically no hacker VCs: How would you like a job where you never got to make anything, but instead spent all your time listening to other people pitch (mostly terrible) projects, deciding whether to fund them, and sitting on their boards if you did? That would not be fun for most hackers. Hackers like to make things. This would be like being an administrator. Because most VCs are a different species of people from founders, it's hard to know what they're thinking. If you're a hacker, the last time you had to deal with these guys was in high school. Maybe in college you walked past their fraternity on your way to the lab. But don't underestimate them. They're as expert in their world as you are in yours. What they're good at is reading people, and making deals work to their advantage. Think twice before you try to beat them at that. 5\. Most investors are momentum investors. Because most investors are dealmakers rather than technology people, they generally don't understand what you're doing. I knew as a founder that most VCs didn't get technology. I also knew some made a lot of money. And yet it never occurred to me till recently to put those two ideas together and ask "How can VCs make money by investing in stuff they don't understand?" The answer is that they're like momentum investors. You can (or could once) make a lot of money by noticing sudden changes in stock prices. When a stock jumps upward, you buy, and when it suddenly drops, you sell.
谷歌的案例揭示了天使投资人的核心作用。众所周知谷歌曾接受Kleiner和Sequoia的投资,但鲜有人知这轮融资来得有多晚——这是7500万美元估值的B轮融资,当时的谷歌已是成功企业。真正支撑谷歌起步的,是天使资金。
硅谷标杆企业由天使投资培育看似反常,实则合乎逻辑。风险与回报永远成正比。史上最成功的初创企业,最初必然显得风险极高——而这正是VC避之不及的类型。
天使投资人从何而来?来自其他创业公司。因此硅谷等创业中心受益于类似市场效应的机制,只是存在时滞:初创企业聚集于此,正是因为曾经有初创企业在此聚集。
3. 天使投资人不爱抛头露面
既然天使如此重要,为何我们更常听闻VC的事迹?因为VC需要曝光。他们既要向"客户"(捐赠基金、养老基金、富豪家族等资金提供方)推销自己,也要吸引寻求融资的创业者。
In effect you're insider trading, without knowing what you know. You just know someone knows something, and that's making the stock move. This is how most venture investors operate. They don't try to look at something and predict whether it will take off. They win by noticing that something _is_ taking off a little sooner than everyone else. That generates almost as good returns as actually being able to pick winners. They may have to pay a little more than they would if they got in at the very beginning, but only a little. Investors always say what they really care about is the team. Actually what they care most about is your traffic, then what other investors think, then the team. If you don't yet have any traffic, they fall back on number 2, what other investors think. And this, as you can imagine, produces wild oscillations in the "stock price" of a startup. One week everyone wants you, and they're begging not to be cut out of the deal. But all it takes is for one big investor to cool on you, and the next week no one will return your phone calls. We regularly have startups go from hot to cold or cold to hot in a matter of days, and literally nothing has changed. There are two ways to deal with this phenomenon. If you're feeling really confident, you can try to ride it. You can start by asking a comparatively lowly VC for a small amount of money, and then after generating interest there, ask more prestigious VCs for larger amounts, stirring up a crescendo of buzz, and then "sell" at the top. This is extremely risky, and takes months even if you succeed. I wouldn't try it myself. My advice is to err on the side of safety: when someone offers you a decent deal, just take it and get on with building the company. Startups win or lose based on the quality of their product, not the quality of their funding deals. 6\. Most investors are looking for big hits. Venture investors like companies that could go public.
天使投资人无需向资金方营销——他们动用的是自有资本。他们也不愿吸引创业者:不想被随机出现的商业计划书骚扰。实际上VC同样如此,天使和VC的交易几乎都通过私人引荐达成[2]。
VC打造强势品牌并非为了接收更多陌生商业计划,而是在与同行竞争中赢得项目。天使投资人很少直接竞争,因为:(a)他们交易频次更低;(b)乐于分摊投资;(c)介入阶段市场更广阔。
4. 多数投资人(尤其是VC)与创业者截然不同
有些天使投资人曾是黑客,但多数VC属于另一类人:交易撮合者。
黑客读者不妨做个思想实验:假设有份工作从不让你创造产品,而是整天聆听(大多是拙劣的)项目路演、决定是否投资、并在注资后担任董事——这对大多数黑客而言堪称折磨。黑客热爱创造,这种工作却像行政事务。
正因VC与创业者属于不同物种,揣测其想法尤为困难。对黑客来说,上次与这类人打交道可能要追溯到高中时代,大学时或许曾在去实验室路上经过他们的兄弟会。但千万别低估他们——这些人在自己领域的专业程度,不亚于你在编程世界的造诣。他们擅长识人读心,让交易朝有利方向发展。若想在这方面战胜他们,务必三思。
That's where the big returns are. They know the odds of any individual startup going public are small, but they want to invest in those that at least have a _chance_ of going public. Currently the way VCs seem to operate is to invest in a bunch of companies, most of which fail, and one of which is Google. Those few big wins compensate for losses on their other investments. What this means is that most VCs will only invest in you if you're a potential Google. They don't care about companies that are a safe bet to be acquired for $20 million. There needs to be a chance, however small, of the company becoming really big. Angels are different in this respect. They're happy to invest in a company where the most likely outcome is a $20 million acquisition if they can do it at a low enough valuation. But of course they like companies that could go public too. So having an ambitious long-term plan pleases everyone. If you take VC money, you have to mean it, because the structure of VC deals prevents early acquisitions. If you take VC money, they won't let you sell early. 7\. VCs want to invest large amounts. The fact that they're running investment funds makes VCs want to invest large amounts. A typical VC fund is now hundreds of millions of dollars. If $400 million has to be invested by 10 partners, they have to invest $40 million each. VCs usually sit on the boards of companies they fund. If the average deal size was $1 million, each partner would have to sit on 40 boards, which would not be fun. So they prefer bigger deals, where they can put a lot of money to work at once. VCs don't regard you as a bargain if you don't need a lot of money. That may even make you less attractive, because it means their investment creates less of a barrier to entry for competitors. Angels are in a different position because they're investing their own money.
5. 多数投资人是趋势追随者
由于多数投资人是交易专家而非技术专家,他们通常不理解你在做什么。我创业时就明白大多数VC不懂技术,但直到最近才将两个现象联系起来思考:为何不懂技术的VC能赚大钱?
答案在于他们如同动量投资者。通过捕捉股价突变获利(曾经)是可行策略——暴涨时买入,暴跌时抛售。这本质上是一种无需内幕消息的"内幕交易":你只需察觉有人掌握了某些信息并推动股价波动。
多数风险投资者正是如此运作。他们不试图预测项目潜力,而是争取比他人更早发现已显现势头的项目。这种策略的回报几乎不亚于精准押注,虽然需要支付略高成本,但差额很小。
投资人总说最看重团队,实则优先级是:用户数据>其他投资人看法>团队。若没有用户数据,他们便依赖第二指标——其他投资人的判断。可想而知,这会导致初创企业"股价"剧烈震荡:本周众人争相投资唯恐错过,下周若某大牌投资人态度转冷,所有电话都会无人接听。我们经常见证初创企业几天内从炙手可热到门庭冷落(或反之),尽管实质毫无变化。
They're happy to invest small amounts—sometimes as little as $20,000—as long as the potential returns look good enough. So if you're doing something inexpensive, go to angels. 8\. Valuations are fiction. VCs admit that valuations are an artifact. They decide how much money you need and how much of the company they want, and those two constraints yield a valuation. Valuations increase as the size of the investment does. A company that an angel is willing to put $50,000 into at a valuation of a million can't take $6 million from VCs at that valuation. That would leave the founders less than a seventh of the company between them (since the option pool would also come out of that seventh). Most VCs wouldn't want that, which is why you never hear of deals where a VC invests $6 million at a premoney valuation of $1 million. If valuations change depending on the amount invested, that shows how far they are from reflecting any kind of value of the company. Since valuations are made up, founders shouldn't care too much about them. That's not the part to focus on. In fact, a high valuation can be a bad thing. If you take funding at a premoney valuation of $10 million, you won't be selling the company for 20. You'll have to sell for over 50 for the VCs to get even a 5x return, which is low to them. More likely they'll want you to hold out for 100. But needing to get a high price decreases the chance of getting bought at all; many companies can buy you for $10 million, but only a handful for 100. And since a startup is like a pass/fail course for the founders, what you want to optimize is your chance of a good outcome, not the percentage of the company you keep. So why do founders chase high valuations? They're tricked by misplaced ambition. They feel they've achieved more if they get a higher valuation.
应对此现象有两种策略:若信心十足,可顺势操作——先向二线VC小额融资,引发关注后吸引顶级VC大额注资,制造舆论高潮后"高位套现"。此法风险极高且耗时数月,我本人不会尝试。更稳妥的建议是:遇到合理报价立即接受,专注公司建设。初创企业成败取决于产品质量,而非融资条款优劣。
6. 多数投资人追逐本垒打
风险投资者青睐可能上市的企业——那里才有巨额回报。他们清楚单个初创企业上市概率渺茫,但仍希望投资至少存在上市可能的项目。
当前VC的典型策略是广撒网:多数项目失败,但只要押中一个谷歌就能弥补所有损失。这意味着除非你具备成为谷歌的潜力,否则多数VC不会投资。他们不关心那些稳获2000万美元收购要约的企业——公司必须存在做大的可能性,哪怕微乎其微。
天使投资人则不同。若估值足够低,他们乐意投资最可能以2000万美元被收购的企业。当然他们也喜欢潜在上市公司。因此制定雄心勃勃的长期计划能让各方满意。
接受VC投资意味着破釜沉舟——其交易结构会阻碍早期收购。拿了VC的钱,他们不会让你提前退出。
They usually know other founders, and if they get a higher valuation they can say "mine is bigger than yours." But funding is not the real test. The real test is the final outcome for the founder, and getting too high a valuation may just make a good outcome less likely. The one advantage of a high valuation is that you get less dilution. But there is another less sexy way to achieve that: just take less money. 9\. Investors look for founders like the current stars. Ten years ago investors were looking for the next Bill Gates. This was a mistake, because Microsoft was a very anomalous startup. They started almost as a contract programming operation, and the reason they became huge was that IBM happened to drop the PC standard in their lap. Now all the VCs are looking for the next Larry and Sergey. This is a good trend, because Larry and Sergey are closer to the ideal startup founders. Historically investors thought it was important for a founder to be an expert in business. So they were willing to fund teams of MBAs who planned to use the money to pay programmers to build their product for them. This is like funding Steve Ballmer in the hope that the programmer he'll hire is Bill Gates—kind of backward, as the events of the Bubble showed. Now most VCs know they should be funding technical guys. This is more pronounced among the very top funds; the lamer ones still want to fund MBAs. If you're a hacker, it's good news that investors are looking for Larry and Sergey. The bad news is, the only investors who can do it right are the ones who knew them when they were a couple of CS grad students, not the confident media stars they are today. What investors still don't get is how clueless and tentative great founders can seem at the very beginning. 10\. The contribution of investors tends to be underestimated. Investors do more for startups than give them money.
7. VC偏好大额投资
基金管理规模迫使VC追求大额投资。如今典型风投基金规模数亿美元,若10位合伙人需管理4亿美元,人均投资额达4000万美元。VC通常需入驻被投企业董事会,若单笔投资仅100万美元,每位合伙人需入驻40家董事会,这显然难以承受。因此他们偏好能一次性投入巨资的大项目。
不需要大额融资对VC而言并非优势,反而可能降低吸引力——这意味着他们的投资难以构筑竞争壁垒。
天使投资人处境不同,他们动用自有资金。只要回报诱人,小额投资(有时仅2万美元)也能接受。因此若项目成本低廉,应寻求天使投资。
8. 估值纯属虚构
They're helpful in doing deals and arranging introductions, and some of the smarter ones, particularly angels, can give good advice about the product. In fact, I'd say what separates the great investors from the mediocre ones is the quality of their advice. Most investors give advice, but the top ones give _good_ advice. Whatever help investors give a startup tends to be underestimated. It's to everyone's advantage to let the world think the founders thought of everything. The goal of the investors is for the company to become valuable, and the company seems more valuable if it seems like all the good ideas came from within. This trend is compounded by the obsession that the press has with founders. In a company founded by two people, 10% of the ideas might come from the first guy they hire. Arguably they've done a bad job of hiring otherwise. And yet this guy will be almost entirely overlooked by the press. I say this as a founder: the contribution of founders is always overestimated. The danger here is that new founders, looking at existing founders, will think that they're supermen that one couldn't possibly equal oneself. Actually they have a hundred different types of support people just offscreen making the whole show possible. [3] 11\. VCs are afraid of looking bad. I've been very surprised to discover how timid most VCs are. They seem to be afraid of looking bad to their partners, and perhaps also to the limited partners—the people whose money they invest. You can measure this fear in how much less risk VCs are willing to take. You can tell they won't make investments for their fund that they might be willing to make themselves as angels. Though it's not quite accurate to say that VCs are less willing to take risks. They're less willing to do things that might look bad. That's not the same thing.
VC承认估值是人为产物。他们根据你需要多少钱、想保留多少股权这两个约束条件倒推估值。
估值随投资规模水涨船高。天使投资人可能以100万美元估值注资5万美元,但VC绝不会以同等估值投资600万美元——这会让创始人团队持股不足七分之一(期权池也将从中扣除)。你从未听闻VC以100万估值投资600万,正因多数VC无法接受这种股权结构。
估值随投资额变化的事实,说明其与公司真实价值相去甚远。
既然估值是虚构的,创始人不必过分在意——这不是该关注的重点。事实上高估值可能有害:若以1000万估值融资,你不可能以2000万出售公司。VC需要5倍回报(对他们而言已属偏低)意味着售价需超5000万,更可能要求你坚守1亿报价。但高价必然降低成交概率——能出价1000万的买家很多,能出1亿的凤毛麟角。由于创业对创始人如同通过性考试,你该优化的是成功概率而非持股比例。
为何创始人仍追逐高估值?源于错位的野心——高估值带来心理成就感,能在与其他创始人的比较中占据上风。但融资不是终极考验,创始人最终收益才是。过高的估值反而可能降低理想结局的概率。
高估值唯一优势是减少股权稀释,但更务实的解决方案是:少融些钱。
For example, most VCs would be very reluctant to invest in a startup founded by a pair of 18 year old hackers, no matter how brilliant, because if the startup failed their partners could turn on them and say "What, you invested $x million of our money in a pair of 18 year olds?" Whereas if a VC invested in a startup founded by three former banking executives in their 40s who planned to outsource their product development—which to my mind is actually a lot riskier than investing in a pair of really smart 18 year olds—he couldn't be faulted, if it failed, for making such an apparently prudent investment. As a friend of mine said, "Most VCs can't do anything that would sound bad to the kind of doofuses who run pension funds." Angels can take greater risks because they don't have to answer to anyone. 12\. Being turned down by investors doesn't mean much. Some founders are quite dejected when they get turned down by investors. They shouldn't take it so much to heart. To start with, investors are often wrong. It's hard to think of a successful startup that wasn't turned down by investors at some point. Lots of VCs rejected Google. So obviously the reaction of investors is not a very meaningful test. Investors will often reject you for what seem to be superficial reasons. I read of one VC who turned down a startup simply because they'd given away so many little bits of stock that the deal required too many signatures to close. [4] The reason investors can get away with this is that they see so many deals. It doesn't matter if they underestimate you because of some surface imperfection, because the next best deal will be almost as good. Imagine picking out apples at a grocery store. You grab one with a little bruise.
9. 投资人寻找当下明星的翻版
十年前投资人寻找下一个比尔·盖茨,这是误区——微软是非常规的创业案例:起步近乎外包编程,因IBM意外交付PC标准而壮大。
如今所有VC都在寻找下一个拉里和谢尔盖。这是积极趋势,因为谷歌创始人更接近理想创业者原型。
历史上投资人曾认为商业专长至关重要,因此愿意资助MBA团队——他们计划用融资款雇佣程序员开发产品。这如同投资史蒂夫·鲍尔默,指望他雇到比尔·盖茨。泡沫时代证明此乃本末倒置。如今多数VC明白该投资技术人才,顶级基金尤其如此,只有落后者仍钟爱MBA。
对黑客而言,投资人寻找技术型创始人是好消息。坏消息是:真正懂行的投资人,是那些在拉里和谢尔盖还是CS研究生时就赏识他们的人,而非今日追捧媒体明星的跟风者。投资人至今未领悟的是:伟大的创始人在起步阶段往往显得懵懂而踌躇。
Maybe it's just a surface bruise, but why even bother checking when there are so many other unbruised apples to choose from? Investors would be the first to admit they're often wrong. So when you get rejected by investors, don't think "we suck," but instead ask "do we suck?" Rejection is a question, not an answer. 13\. Investors are emotional. I've been surprised to discover how emotional investors can be. You'd expect them to be cold and calculating, or at least businesslike, but often they're not. I'm not sure if it's their position of power that makes them this way, or the large sums of money involved, but investment negotiations can easily turn personal. If you offend investors, they'll leave in a huff. A while ago an eminent VC firm offered a series A round to a startup we'd seed funded. Then they heard a rival VC firm was also interested. They were so afraid that they'd be rejected in favor of this other firm that they gave the startup what's known as an "exploding termsheet." They had, I think, 24 hours to say yes or no, or the deal was off. Exploding termsheets are a somewhat dubious device, but not uncommon. What surprised me was their reaction when I called to talk about it. I asked if they'd still be interested in the startup if the rival VC didn't end up making an offer, and they said no. What rational basis could they have had for saying that? If they thought the startup was worth investing in, what difference should it make what some other VC thought? Surely it was their duty to their limited partners simply to invest in the best opportunities they found; they should be delighted if the other VC said no, because it would mean they'd overlooked a good opportunity. But of course there was no rational basis for their decision. They just couldn't stand the idea of taking this rival firm's rejects. In this case the exploding termsheet was not (or not only) a tactic to pressure the startup.
10. 投资人的贡献常被低估
投资人为初创企业提供的不仅是资金。他们在交易促成、人脉引荐方面大有助益,部分聪明者(尤其是天使投资人)还能给出产品建议。
事实上,我认为顶级投资人与平庸者的分水岭正在于建议质量。多数投资人会给建议,但顶尖者给出的是好建议。
投资人的帮助总被低估。让外界认为所有好主意都来自创始团队符合各方利益——公司若显得完全自力更生,会显得更有价值。
媒体对创始人的迷恋加剧了这一趋势。两人创立的公司中,首个雇员可能贡献了10%的创意(否则招聘就算失败),但媒体几乎完全忽视这些角色。
作为过来人我坦言:创始人的贡献总被高估。其危险性在于,新晋创业者会误以为前辈是难以企及的超人。实则幕后有数百种支持力量共同成就这场演出[3]。
It was more like the high school trick of breaking up with someone before they can break up with you. In an earlier essay I said that VCs were a lot like high school girls. A few VCs have joked about that characterization, but none have disputed it. 14\. The negotiation never stops till the closing. Most deals, for investment or acquisition, happen in two phases. There's an initial phase of negotiation about the big questions. If this succeeds you get a termsheet, so called because it outlines the key terms of a deal. A termsheet is not legally binding, but it is a definite step. It's supposed to mean that a deal is going to happen, once the lawyers work out all the details. In theory these details are minor ones; by definition all the important points are supposed to be covered in the termsheet. Inexperience and wishful thinking combine to make founders feel that when they have a termsheet, they have a deal. They want there to be a deal; everyone acts like they have a deal; so there must be a deal. But there isn't and may not be for several months. A lot can change for a startup in several months. It's not uncommon for investors and acquirers to get buyer's remorse. So you have to keep pushing, keep selling, all the way to the close. Otherwise all the "minor" details left unspecified in the termsheet will be interpreted to your disadvantage. The other side may even break the deal; if they do that, they'll usually seize on some technicality or claim you misled them, rather than admitting they changed their minds. It can be hard to keep the pressure on an investor or acquirer all the way to the closing, because the most effective pressure is competition from other investors or acquirers, and these tend to drop away when you get a termsheet. You should try to stay as close friends as you can with these rivals, but the most important thing is just to keep up the momentum in your startup.
11. VC害怕形象受损
令我惊讶的是,多数VC非常怯懦。他们似乎害怕在合伙人乃至有限合伙人(委托他们投资的人)面前显得愚蠢。
这种恐惧体现在VC承担风险的意愿上。他们不会为基金做出自己作为天使投资人可能接受的投资。准确地说,并非VC不愿冒险,而是不愿做可能显得愚蠢的事——这两者存在微妙差别。
例如,多数VC极不情愿投资18岁黑客创建的初创企业(无论其多么天才),因为若项目失败,合伙人可能指责:"什么?你拿我们X百万美元投资两个毛头小子?"但若投资由三位40岁前银行高管创立、计划外包产品开发的公司(在我看来风险远高于投资天才少年),即便失败,也没人能指责这个看似审慎的决定。
正如我朋友所说:"多数VC不敢做任何可能让养老基金那些蠢货觉得不妥的事。"天使投资人因无需对他人负责,故能承担更大风险。
The investors or acquirers chose you because you seemed hot. Keep doing whatever made you seem hot. Keep releasing new features; keep getting new users; keep getting mentioned in the press and in blogs. 15\. Investors like to co-invest. I've been surprised how willing investors are to split deals. You might think that if they found a good deal they'd want it all to themselves, but they seem positively eager to syndicate. This is understandable with angels; they invest on a smaller scale and don't like to have too much money tied up in any one deal. But VCs also share deals a lot. Why? Partly I think this is an artifact of the rule I quoted earlier: after traffic, VCs care most what other VCs think. A deal that has multiple VCs interested in it is more likely to close, so of deals that close, more will have multiple investors. There is one rational reason to want multiple VCs in a deal: Any investor who co-invests with you is one less investor who could fund a competitor. Apparently Kleiner and Sequoia didn't like splitting the Google deal, but it did at least have the advantage, from each one's point of view, that there probably wouldn't be a competitor funded by the other. Splitting deals thus has similar advantages to confusing paternity. But I think the main reason VCs like splitting deals is the fear of looking bad. If another firm shares the deal, then in the event of failure it will seem to have been a prudent choice—a consensus decision, rather than just the whim of an individual partner. 16\. Investors collude. Investing is not covered by antitrust law. At least, it better not be, because investors regularly do things that would be illegal otherwise. I know personally of cases where one investor has talked another out of making a competitive offer, using the promise of sharing future deals.
12. 被拒不等于否定
有些创始人遭投资人拒绝后非常沮丧。他们不该如此介怀。首先,投资人常犯错误——几乎每个成功初创企业都曾在某个阶段被投资人拒绝。许多VC曾错过谷歌,显然投资人的反应并非有效检验标准。
投资人常因表面理由拒绝你。我读过某VC只因股权分散导致交易需过多签名就否决项目的案例[4]。投资人敢如此武断,只因他们面对海量项目——因表面瑕疵低估你无关紧要,因为次优选择同样出色。想象在超市挑选苹果:发现轻微瘀伤时,何必费心检查?毕竟有无数完好苹果可供选择。
投资人会率先承认自己常犯错。因此遭拒时别想"我们糟透了",而该问"我们糟透了吗?"拒绝是提问,而非答案。
13. 投资人情绪化
令我惊讶的是,投资人可能非常情绪化。你以为他们冷静算计、至少公事公办,但往往并非如此。不知是权力地位还是巨额资金所致,投资谈判极易掺杂个人情绪。若冒犯投资人,他们会愤然离场。
In principle investors are all competing for the same deals, but the spirit of cooperation is stronger than the spirit of competition. The reason, again, is that there are so many deals. Though a professional investor may have a closer relationship with a founder he invests in than with other investors, his relationship with the founder is only going to last a couple years, whereas his relationship with other firms will last his whole career. There isn't so much at stake in his interactions with other investors, but there will be a lot of them. Professional investors are constantly trading little favors. Another reason investors stick together is to preserve the power of investors as a whole. So you will not, as of this writing, be able to get investors into an auction for your series A round. They'd rather lose the deal than establish a precedent of VCs competitively bidding against one another. An efficient startup funding market may be coming in the distant future; things tend to move in that direction; but it's certainly not here now. 17\. Large-scale investors care about their portfolio, not any individual company. The reason startups work so well is that everyone with power also has equity. The only way any of them can succeed is if they all do. This makes everyone naturally pull in the same direction, subject to differences of opinion about tactics. The problem is, larger scale investors don't have exactly the same motivation. Close, but not identical. They don't need any given startup to succeed, like founders do, just their portfolio as a whole to. So in borderline cases the rational thing for them to do is to sacrifice unpromising startups. Large-scale investors tend to put startups in three categories: successes, failures, and the "living dead"—companies that are plugging along but don't seem likely in the immediate future to get bought or go public. To the founders, "living dead" sounds harsh.
某知名VC曾向我们孵化的初创企业提供A轮条款书,得知竞品VC也有意投资后,因害怕被拒竟给出"爆炸性条款书"——限24小时内接受,否则作废。这种手段虽不罕见但值得商榷。更令我惊讶的是电话沟通时的反应:当我询问若竞品VC退出是否仍有意向时,对方断然否认。这有何理性依据?若认为项目值得投资,其他VC的看法有何影响?按理他们应为竞品VC的疏忽而庆幸,因为这意味发现了被忽视的好机会。但显然毫无理性可言——他们只是无法接受接手竞争对手"淘汰"的项目。
此案例中爆炸性条款书不仅是施压手段,更类似高中生"抢先甩人"的把戏。我在早期文章中称VC极像高中女生,几位VC曾调侃这个比喻,但无人反驳。
14. 谈判持续到交割最后一刻
多数投融资或并购交易分两阶段:首先协商核心问题,达成一致后签署条款书(概述交易关键条款)。条款书虽无法律约束力,却是重要节点——理论上待律师完善细节后交易就将完成,所有重要事项应已涵盖其中。
经验不足与一厢情愿让创始人误以为签署条款书等于交易落定。他们渴望交易达成,所有人表现得像已成交,但事实并非如此——最终交割可能还需数月。对初创企业而言,数月间可能天翻地覆。投资人及收购方产生悔意并不罕见。因此你必须持续推动、推销,直至最终交割。否则条款书中未明确的"细节"都会被解释为对你不利。对方甚至可能毁约——此时他们通常会揪住某些技术细节或指控你误导,而非承认改变主意。
These companies may be far from failures by ordinary standards. But they might as well be from a venture investor's point of view, and they suck up just as much time and attention as the successes. So if such a company has two possible strategies, a conservative one that's slightly more likely to work in the end, or a risky one that within a short time will either yield a giant success or kill the company, VCs will push for the kill-or-cure option. To them the company is already a write-off. Better to have resolution, one way or the other, as soon as possible. If a startup gets into real trouble, instead of trying to save it VCs may just sell it at a low price to another of their portfolio companies. Philip Greenspun said in _Founders at Work_ that Ars Digita's VCs did this to them. 18\. Investors have different risk profiles from founders. Most people would rather a 100% chance of $1 million than a 20% chance of $10 million. Investors are rich enough to be rational and prefer the latter. So they'll always tend to encourage founders to keep rolling the dice. If a company is doing well, investors will want founders to turn down most acquisition offers. And indeed, most startups that turn down acquisition offers ultimately do better. But it's still hair-raising for the founders, because they might end up with nothing. When someone's offering to buy you for a price at which your stock is worth $5 million, saying no is equivalent to having $5 million and betting it all on one spin of the roulette wheel. Investors will tell you the company is worth more. And they may be right. But that doesn't mean it's wrong to sell. Any financial advisor who put all his client's assets in the stock of a single, private company would probably lose his license for it. More and more, investors are letting founders cash out partially. That should correct the problem.
向投资人/收购方持续施压可能很难,因为最有效的压力来自竞争对手,而签署条款书后这些竞争者往往退出。你应尽力与这些对手保持友好,但最重要的是保持公司发展势头——投资人/收购方选择你是因为你看起来炙手可热。持续发布新功能、获取新用户、赢得媒体和博客关注,保持这种热度。
15. 投资人喜欢联合投资
投资人分摊交易的意愿令我惊讶。你以为发现好项目会想独占,但他们似乎热衷联合投资。这对天使可以理解——他们投资规模较小,不愿在任何项目投入过多。但VC也经常共享交易,为何?
部分原因在于前文所述规则:除用户数据外,VC最在意其他VC的看法。多人感兴趣的交易更可能完成,因此成交项目中联合投资比例更高。
联合投资有个理性优势:每个共同投资人都是少了一个可能资助竞争对手的对手。Kleiner与Sequoia或许不愿分摊谷歌投资,但从各自角度看至少确保对方不会资助竞品。联合投资类似混淆亲子关系策略。
但我认为VC喜欢联合投资的主因仍是"怕显得愚蠢"。若有其他机构共同投资,失败时这会被视为审慎决策(集体共识而非个人独断)。
Most founders have such low standards that they'll feel rich with a sum that doesn't seem huge to investors. But this custom is spreading too slowly, because VCs are afraid of seeming irresponsible. No one wants to be the first VC to give someone fuck-you money and then actually get told "fuck you." But until this does start to happen, we know VCs are being too conservative. 19\. Investors vary greatly. Back when I was a founder I used to think all VCs were the same. And in fact they do all look the same. They're all what hackers call "suits." But since I've been dealing with VCs more I've learned that some suits are smarter than others. They're also in a business where winners tend to keep winning and losers to keep losing. When a VC firm has been successful in the past, everyone wants funding from them, so they get the pick of all the new deals. The self-reinforcing nature of the venture funding market means that the top ten firms live in a completely different world from, say, the hundredth. As well as being smarter, they tend to be calmer and more upstanding; they don't need to do iffy things to get an edge, and don't want to because they have more brand to protect. There are only two kinds of VCs you want to take money from, if you have the luxury of choosing: the "top tier" VCs, meaning about the top 20 or so firms, plus a few new ones that are not among the top 20 only because they haven't been around long enough. It's particularly important to raise money from a top firm if you're a hacker, because they're more confident. That means they're less likely to stick you with a business guy as CEO, like VCs used to do in the 90s. If you seem smart and want to do it, they'll let you run the company. 20\. Investors don't realize how much it costs to raise money from them. Raising money is a huge time suck at just the point where startups can least afford it.
16. 投资人存在合谋
投资行为不受反垄断法约束(至少最好别受约束),因为投资人常做在其他领域属非法的勾当。我亲历过投资人以"未来交易共享"为筹码,劝说竞争对手放弃竞价。
理论上投资人都在争夺相同交易,但合作精神强于竞争意识。原因仍是交易数量庞大——专业投资人与被投创始人的关系通常仅维持几年,而与其他机构的关系贯穿整个职业生涯。虽然与同行互动风险较低,但频次极高,专业投资人 constantly 在进行小规模利益交换。
另一合谋动机是维护投资人整体权力。因此在本文撰写时,你仍无法让投资人为A轮融资竞标——他们宁愿放弃交易,也不愿开创VC互相竞价的先例。高效的初创企业融资市场或许终将到来,但绝非今日。
17. 大型投资人关注组合而非单体
It's not unusual for it to take five or six months to close a funding round. Six weeks is fast. And raising money is not just something you can leave running as a background process. When you're raising money, it's inevitably the main focus of the company. Which means building the product isn't. Suppose a Y Combinator company starts talking to VCs after demo day, and is successful in raising money from them, closing the deal after a comparatively short 8 weeks. Since demo day occurs after 10 weeks, the company is now 18 weeks old. Raising money, rather than working on the product, has been the company's main focus for 44% of its existence. And mind you, this an example where things turned out _well_. When a startup does return to working on the product after a funding round finally closes, it's as if they were returning to work after a months-long illness. They've lost most of their momentum. Investors have no idea how much they damage the companies they invest in by taking so long to do it. But companies do. So there is a big opportunity here for a new kind of venture fund that invests smaller amounts at lower valuations, but promises to either close or say no very quickly. If there were such a firm, I'd recommend it to startups in preference to any other, no matter how prestigious. Startups live on speed and momentum. 21\. Investors don't like to say no. The reason funding deals take so long to close is mainly that investors can't make up their minds. VCs are not big companies; they can do a deal in 24 hours if they need to. But they usually let the initial meetings stretch out over a couple weeks. The reason is the selection algorithm I mentioned earlier. Most don't try to predict whether a startup will win, but to notice quickly that it already is winning. They care what the market thinks of you and what other VCs think of you, and they can't judge those just from meeting you.
初创企业高效运转的原因在于,所有掌权者都持有股权。任何人成功的唯一途径是集体成功,这自然让众人目标一致(战术分歧除外)。
问题在于,大型投资人的动机并不完全一致。他们不需要每家被投企业都成功(像创始人那样),只需整体组合成功。因此在边际案例中,牺牲前景黯淡的企业是其理性选择。
大型投资人通常将初创企业分为三类:成功者、失败者、"活死人"(勉强运营但短期内难被收购或上市)。对创始人而言"活死人"听起来刺耳,这些公司按常标准距失败甚远。但对风险投资者而言与失败无异,且消耗与成功企业同等的时间精力。因此若这类企业有两种策略:保守方案(最终成功概率略高)或激进方案(短期内要么大成要么猝死),VC会推动后者——对他们而言这些企业已是坏账,尽快了结(无论方式)才是上策。
当初创企业陷入危机,VC可能将其低价转售给投资组合中的其他公司,而非试图挽救。菲利普·格林斯潘在《创业者实录》中透露,Ars Digita的VC曾如此操作。
18. 投资人与创始人的风险偏好不同
多数人宁愿选择100%获得100万美元,而非20%概率赢得1000万美元。投资人因足够富有而更理性,倾向于后者。因此他们总鼓励创始人持续冒险。若公司发展顺利,投资人会建议拒绝多数收购要约。事实上,多数拒绝收购的初创企业最终表现更好。但对创始人而言这仍令人胆战——他们可能血本无归。当有人出价500万美元收购时,拒绝等同于将这笔钱押注于单次轮盘赌。
Because they're investing in things that (a) change fast and (b) they don't understand, a lot of investors will reject you in a way that can later be claimed not to have been a rejection. Unless you know this world, you may not even realize you've been rejected. Here's a VC saying no: > We're really excited about your project, and we want to keep in close touch as you develop it further..
投资人会坚称公司价值更高,或许没错。但这不意味着接受收购是错误。若理财顾问将客户全部资产押注于单一私企股票,很可能会被吊销执照。
越来越多投资人允许创始人部分套现,这应能纠正问题。多数创始
用更直白的语言来说,这意味着:我们目前不会投资你,但如果你的项目有起色,我们可能会改变主意。有时他们会更坦率地明确表示需要"看到一些进展迹象"——如果你开始获得大量用户,他们就会投资。但任何风投都会这么做。所以他们的潜台词其实是:你仍处于起步阶段。
判断风投回复是肯定还是否定,这里有个测试方法:低头看看你的手——你拿到投资意向书了吗?
22. 你需要投资人
Translated into more straightforward language, this means: We're not investing in you, but we may change our minds if it looks like you're taking off. Sometimes they're more candid and say explicitly that they need to "see some traction." They'll invest in you if you start to get lots of users. But so would any VC. So all they're saying is that you're still at square 1. Here's a test for deciding whether a VC's response was yes or no. Look down at your hands. Are you holding a termsheet? 22\. You need investors. Some founders say "Who needs investors?" Empirically the answer seems to be: everyone who wants to succeed. Practically every successful startup takes outside investment at some point. Why? What the people who think they don't need investors forget is that they will have competitors. The question is not whether you _need_ outside investment, but whether it could help you at all. If the answer is yes, and you don't take investment, then competitors who do will have an advantage over you. And in the startup world a little advantage can expand into a lot. Mike Moritz famously said that he invested in Yahoo because he thought they had a few weeks' lead over their competitors. That may not have mattered quite so much as he thought, because Google came along three years later and kicked Yahoo's ass. But there is something in what he said. Sometimes a small lead can grow into the yes half of a binary choice. Maybe as it gets cheaper to start a startup, it will start to be possible to succeed in a competitive market without outside funding. There are certainly costs to raising money. But as of this writing the empirical evidence says it's a net win. 23\. Investors like it when you don't need them. A lot of founders approach investors as if they needed their permission to start a company—as if it were like getting into college. But you don't need investors to start most companies; they just make it easier.
有些创始人会说"谁需要投资人?"现实给出的答案似乎是:所有渴望成功的人。几乎所有成功的初创企业都会在某个阶段引入外部投资。
为什么?那些认为自己不需要投资的人往往忽略了一个事实:你将面对竞争对手。问题不在于你是否"必须"获得外部投资,而在于这笔投资是否能为你带来助益。如果答案是肯定的却拒绝融资,那么获得投资的竞争对手就会占据优势。在创业领域,微小的优势可能演变为巨大的差距。
迈克·莫里茨有句名言,他投资雅虎是因为认为其领先竞争对手数周。这个优势或许没他想象的那么关键——毕竟三年后谷歌就后来居上击败了雅虎。但其中确有真谛:有时微小的领先能决定生死存亡。
随着创业成本降低,或许未来不依赖外部融资也能在竞争激烈的市场成功。融资确实存在代价。但截至目前,实证数据表明这仍是利大于弊的选择。
23. 投资人偏爱"非你不可"的创业者
许多创始人接触投资人时,仿佛在申请创办公司的许可——就像大学入学申请。但大多数公司创立时根本不需要投资人,他们只是让过程更轻松。
And in fact, investors greatly prefer it if you don't need them. What excites them, both consciously and unconsciously, is the sort of startup that approaches them saying "the train's leaving the station; are you in or out?" not the one saying "please can we have some money to start a company?" Most investors are "bottoms" in the sense that the startups they like most are those that are rough with them. When Google stuck Kleiner and Sequoia with a $75 million premoney valuation, their reaction was probably "Ouch! That feels so good." And they were right, weren't they? That deal probably made them more than any other they've done. The thing is, VCs are pretty good at reading people. So don't try to act tough with them unless you really are the next Google, or they'll see through you in a second. Instead of acting tough, what most startups should do is simply always have a backup plan. Always have some alternative plan for getting started if any given investor says no. Having one is the best insurance against needing one. So you shouldn't start a startup that's expensive to start, because then you'll be at the mercy of investors. If you ultimately want to do something that will cost a lot, start by doing a cheaper subset of it, and expand your ambitions when and if you raise more money. Apparently the most likely animals to be left alive after a nuclear war are cockroaches, because they're so hard to kill. That's what you want to be as a startup, initially. Instead of a beautiful but fragile flower that needs to have its stem in a plastic tube to support itself, better to be small, ugly, and indestructible. Notes [1] I may be underestimating VCs. They may play some behind the scenes role in IPOs, which you ultimately need if you want to create a silicon valley. [2] A few VCs have an email address you can send your business plan to, but the number of startups that get funded this way is basically zero.
事实上,投资人更青睐那些不需要他们的创业者。真正能打动投资人的(无论他们是否意识到),是那种宣告"列车即将启程,你上不上车?"的初创企业,而非哀求"请给我们些启动资金吧"的团队。
多数投资人在心理层面是"受方"——他们最钟爱的正是那些态度强势的初创企业。当谷歌以7500万美元的投前估值让Kleiner和红杉忍痛接受时,投资人的反应很可能是"痛死了!但真带劲!"事实证明他们是对的,不是吗?那笔交易带来的回报可能超过他们所有其他投资。
关键在于,风投们深谙识人之道。除非你真是下一个谷歌,否则别假装强势——他们瞬间就能看穿。对多数初创企业而言,更明智的做法是永远准备B计划:确保每次被拒时都有替代方案。拥有备选计划才是避免陷入绝境的最佳保障。
因此不要创办启动成本高昂的项目,否则你将受制于投资人。若最终目标是需要大笔资金的事业,不妨先实施成本较低的简化版本,待融资成功后再扩展版图。
据说核战争后最可能存活的生物是蟑螂,因其极难被杀死。这就是创业初期该有的姿态:与其做需要塑料管支撑茎秆的娇艳花朵,不如成为渺小丑陋却坚不可摧的存在。
You should always get a personal introduction—and to a partner, not an associate. [3] Several people have told us that the most valuable thing about startup school was that they got to see famous startup founders and realized they were just ordinary guys. Though we're happy to provide this service, this is not generally the way we pitch startup school to potential speakers. [4] Actually this sounds to me like a VC who got buyer's remorse, then used a technicality to get out of the deal. But it's telling that it even seemed a plausible excuse. Thanks to Sam Altman, Paul Buchheit, Hutch Fishman, and Robert Morris for reading drafts of this, and to Kenneth King of ASES for inviting me to speak. Comment on this essay..
[1] 我可能低估了风投的作用。在最终实现上市(这是打造硅谷的必经之路)的过程中,他们或许在幕后发挥着某些作用。
[2] 少数风投提供商业计划书投递邮箱,但通过这种方式获得融资的案例基本为零。务必争取私人引荐——且必须是引荐给合伙人,而非投资经理。
[3] 多人向我们反馈,创业学校最有价值之处,是让他们发现那些著名创始人原来只是普通人。虽然我们乐于提供这种认知服务,但这通常不是我们邀请演讲嘉宾时的说辞。
[4] 在我看来,这更像是投资人反悔后利用条款漏洞脱身。但连这种借口都显得可信,本身就说明问题。
致谢 感谢萨姆·奥尔特曼、保罗·布赫海特、哈奇·菲什曼和罗伯特·莫里斯审阅本文草稿,以及ASES的肯尼斯·金邀请我演讲。
评论本文。
April 2007 There are two different ways people judge you. Sometimes judging you correctly is the end goal. But there's a second much more common type of judgement where it isn't. We tend to regard all judgements of us as the first type. We'd probably be happier if we realized which are and which aren't. The first type of judgement, the type where judging you is the end goal, include court cases, grades in classes, and most competitions. Such judgements can of course be mistaken, but because the goal is to judge you correctly, there's usually some kind of appeals process. If you feel you've been misjudged, you can protest that you've been treated unfairly. Nearly all the judgements made on children are of this type, so we get into the habit early in life of thinking that all judgements are. But in fact there is a second much larger class of judgements where judging you is only a means to something else. These include college admissions, hiring and investment decisions, and of course the judgements made in dating. This kind of judgement is not really about you. Put yourself in the position of someone selecting players for a national team. Suppose for the sake of simplicity that this is a game with no positions, and that you have to select 20 players. There will be a few stars who clearly should make the team, and many players who clearly shouldn't. The only place your judgement makes a difference is in the borderline cases. Suppose you screw up and underestimate the 20th best player, causing him not to make the team, and his place to be taken by the 21st best. You've still picked a good team. If the players have the usual distribution of ability, the 21st best player will be only slightly worse than the 20th best. Probably the difference between them will be less than the measurement error. The 20th best player may feel he has been misjudged. But your goal here wasn't to provide a service estimating people's ability.
保罗·格雷厄姆《两种评判》第一部分(共两部分)
人们评判你的方式有两种。有时准确评判本身就是最终目的。但第二种更常见的评判却并非如此。我们往往把所有评判都当作第一种。若能分清二者区别,我们或许会活得更轻松。
第一种以评判为最终目的的情形包括法庭判决、课程评分和大多数竞赛。这类评判当然可能存在误差,但由于目标是准确评判,通常设有申诉机制。若感到被误判,你可以抗议遭受不公。
儿童时期经历的评判几乎全属此类,因此我们自幼便养成思维定式,认为所有评判皆然。
It was to pick a team, and if the difference between the 20th and 21st best players is less than the measurement error, you've still done that optimally. It's a false analogy even to use the word unfair to describe this kind of misjudgement. It's not aimed at producing a correct estimate of any given individual, but at selecting a reasonably optimal set. One thing that leads us astray here is that the selector seems to be in a position of power. That makes him seem like a judge. If you regard someone judging you as a customer instead of a judge, the expectation of fairness goes away. The author of a good novel wouldn't complain that readers were _unfair_ for preferring a potboiler with a racy cover. Stupid, perhaps, but not unfair. Our early training and our self-centeredness combine to make us believe that every judgement of us is about us. In fact most aren't. This is a rare case where being less self-centered will make people more confident. Once you realize how little most people judging you care about judging you accurately—once you realize that because of the normal distribution of most applicant pools, it matters least to judge accurately in precisely the cases where judgement has the most effect—you won't take rejection so personally. And curiously enough, taking rejection less personally may help you to get rejected less often. If you think someone judging you will work hard to judge you correctly, you can afford to be passive. But the more you realize that most judgements are greatly influenced by random, extraneous factors—that most people judging you are more like a fickle novel buyer than a wise and perceptive magistrate—the more you realize you can do things to influence the outcome. One good place to apply this principle is in college applications.
但事实上,存在第二种更广泛的评判——评判你只是实现其他目的的手段。大学录取、招聘决策、投资选择乃至约会中的评判皆属此类。这类评判本质上与你无关。
试想自己担任国家队选拔委员。假设这是项无位置分工的运动,需选拔20人。少数明星选手必然入选,多数人显然落选。你的评判真正产生影响的,只有那些边缘案例。假设你误判了第20优秀的选手导致其落选,由第21名替补。你依然组建了优秀的队伍。若选手能力呈正态分布,第21名与第20名的差距可能小于测量误差。
落选者或许觉得自己被误判。但你的目标本就不是提供能力评估服务,而是组建最佳团队。当第20与21名选手差距小于误差范围时,你的选择已然最优。
用"不公"形容这类误判本身就是错误类比。这种评判的目的不在于准确评估个体,而在于选出整体最优组合。
Most high school students applying to college do it with the usual child's mix of inferiority and self-centeredness: inferiority in that they assume that admissions committees must be all-seeing; self-centeredness in that they assume admissions committees care enough about them to dig down into their application and figure out whether they're good or not. These combine to make applicants passive in applying and hurt when they're rejected. If college applicants realized how quick and impersonal most selection processes are, they'd make more effort to sell themselves, and take the outcome less personally.
| Spanish Translation | | | Russian Translation | Arabic Translation.
令人误解的是,选拔者看似拥有裁判般的权力。若将评判者视为顾客而非法官,对公平性的期待自然消解。优秀小说家不会因读者偏爱艳俗封面的小说而抱怨其"不公"——顶多觉得读者愚蠢罢了。
早期教育叠加自我中心意识,使我们误以为所有评判都针对自身。实则多数并非如此。这个罕见案例中,减少自我关注反而能增强自信。当你意识到多数评判者根本不在意评判准确性——当你明白因候选者呈正态分布,恰恰在评判影响最大的环节,准确性反而最无关紧要——你就不会把拒绝视为针对个人。
有趣的是,不过分在意拒绝反而可能减少被拒概率。若以为评判者会竭力准确评估,你大可以被动应对。但越是意识到多数评判受随机外部因素影响——多数评判者更像善变的书商而非明察秋毫的法官——就越明白自己可以主动影响结果。
大学申请正是运用此理的绝佳场景。多数高中生带着孩童式的自卑与自我中心混合作申请:自卑地认为录取委员会明察秋毫;自我中心地假设委员们会认真研读申请材料评估其价值。这导致申请者被动等待,被拒时又倍感伤害。若明白多数选拔过程的仓促与 impersonal(非个人化),他们会更努力自我营销,同时更淡然看待结果。
Want to start a startup? Get funded by Y Combinator.
March 2007 _(This essay is derived from talks at the 2007 Startup School and the Berkeley CSUA.)_ We've now been doing Y Combinator long enough to have some data about success rates. Our first batch, in the summer of 2005, had eight startups in it. Of those eight, it now looks as if at least four succeeded. Three have been acquired: Reddit was a merger of two, Reddit and Infogami, and a third was acquired that we can't talk about yet. Another from that batch was Loopt, which is doing so well they could probably be acquired in about ten minutes if they wanted to. So about half the founders from that first summer, less than two years ago, are now rich, at least by their standards. (One thing you learn when you get rich is that there are many degrees of it.) I'm not ready to predict our success rate will stay as high as 50%. That first batch could have been an anomaly. But we should be able to do better than the oft-quoted (and probably made up) standard figure of 10%. I'd feel safe aiming at 25%. Even the founders who fail don't seem to have such a bad time. Of those first eight startups, three are now probably dead. In two cases the founders just went on to do other things at the end of the summer. I don't think they were traumatized by the experience. The closest to a traumatic failure was Kiko, whose founders kept working on their startup for a whole year before being squashed by Google Calendar. But they ended up happy. They sold their software on eBay for a quarter of a million dollars. After they paid back their angel investors, they had about a year's salary each. [1] Then they immediately went on to start a new and much more exciting startup, Justin.TV. So here is an even more striking statistic: 0% of that first batch had a terrible experience.
They had ups and downs, like every startup, but I don't think any would have traded it for a job in a cubicle. And that statistic is probably not an anomaly. Whatever our long-term success rate ends up being, I think the rate of people who wish they'd gotten a regular job will stay close to 0%. The big mystery to me is: why don't more people start startups? If nearly everyone who does it prefers it to a regular job, and a significant percentage get rich, why doesn't everyone want to do this? A lot of people think we get thousands of applications for each funding cycle. In fact we usually only get several hundred. Why don't more people apply? And while it must seem to anyone watching this world that startups are popping up like crazy, the number is small compared to the number of people with the necessary skills. The great majority of programmers still go straight from college to cubicle, and stay there. It seems like people are not acting in their own interest. What's going on? Well, I can answer that. Because of Y Combinator's position at the very start of the venture funding process, we're probably the world's leading experts on the psychology of people who aren't sure if they want to start a company. There's nothing wrong with being unsure. If you're a hacker thinking about starting a startup and hesitating before taking the leap, you're part of a grand tradition. Larry and Sergey seem to have felt the same before they started Google, and so did Jerry and Filo before they started Yahoo. In fact, I'd guess the most successful startups are the ones started by uncertain hackers rather than gung-ho business guys. We have some evidence to support this. Several of the most successful startups we've funded told us later that they only decided to apply at the last moment. Some decided only hours before the deadline. The way to deal with uncertainty is to analyze it into components.
Most people who are reluctant to do something have about eight different reasons mixed together in their heads, and don't know themselves which are biggest. Some will be justified and some bogus, but unless you know the relative proportion of each, you don't know whether your overall uncertainty is mostly justified or mostly bogus. So I'm going to list all the components of people's reluctance to start startups, and explain which are real. Then would-be founders can use this as a checklist to examine their own feelings. I admit my goal is to increase your self-confidence. But there are two things different here from the usual confidence-building exercise. One is that I'm motivated to be honest. Most people in the confidence-building business have already achieved their goal when you buy the book or pay to attend the seminar where they tell you how great you are. Whereas if I encourage people to start startups who shouldn't, I make my own life worse. If I encourage too many people to apply to Y Combinator, it just means more work for me, because I have to read all the applications. The other thing that's going to be different is my approach. Instead of being positive, I'm going to be negative. Instead of telling you "come on, you can do it" I'm going to consider all the reasons you aren't doing it, and show why most (but not all) should be ignored. We'll start with the one everyone's born with. 1\. Too young A lot of people think they're too young to start a startup. Many are right. The median age worldwide is about 27, so probably a third of the population can truthfully say they're too young. What's too young? One of our goals with Y Combinator was to discover the lower bound on the age of startup founders. It always seemed to us that investors were too conservative here—that they wanted to fund professors, when really they should be funding grad students or even undergrads.
The main thing we've discovered from pushing the edge of this envelope is not where the edge is, but how fuzzy it is. The outer limit may be as low as 16. We don't look beyond 18 because people younger than that can't legally enter into contracts. But the most successful founder we've funded so far, Sam Altman, was 19 at the time. Sam Altman, however, is an outlying data point. When he was 19, he seemed like he had a 40 year old inside him. There are other 19 year olds who are 12 inside. There's a reason we have a distinct word "adult" for people over a certain age. There is a threshold you cross. It's conventionally fixed at 21, but different people cross it at greatly varying ages. You're old enough to start a startup if you've crossed this threshold, whatever your age. How do you tell? There are a couple tests adults use. I realized these tests existed after meeting Sam Altman, actually. I noticed that I felt like I was talking to someone much older. Afterward I wondered, what am I even measuring? What made him seem older? One test adults use is whether you still have the kid flake reflex. When you're a little kid and you're asked to do something hard, you can cry and say "I can't do it" and the adults will probably let you off. As a kid there's a magic button you can press by saying "I'm just a kid" that will get you out of most difficult situations. Whereas adults, by definition, are not allowed to flake. They still do, of course, but when they do they're ruthlessly pruned. The other way to tell an adult is by how they react to a challenge. Someone who's not yet an adult will tend to respond to a challenge from an adult in a way that acknowledges their dominance. If an adult says "that's a stupid idea," a kid will either crawl away with his tail between his legs, or rebel. But rebelling presumes inferiority as much as submission.
The adult response to "that's a stupid idea," is simply to look the other person in the eye and say "Really? Why do you think so?" There are a lot of adults who still react childishly to challenges, of course. What you don't often find are kids who react to challenges like adults. When you do, you've found an adult, whatever their age. 2\. Too inexperienced I once wrote that startup founders should be at least 23, and that people should work for another company for a few years before starting their own. I no longer believe that, and what changed my mind is the example of the startups we've funded. I still think 23 is a better age than 21. But the best way to get experience if you're 21 is to start a startup. So, paradoxically, if you're too inexperienced to start a startup, what you should do is start one. That's a way more efficient cure for inexperience than a normal job. In fact, getting a normal job may actually make you less able to start a startup, by turning you into a tame animal who thinks he needs an office to work in and a product manager to tell him what software to write. What really convinced me of this was the Kikos. They started a startup right out of college. Their inexperience caused them to make a lot of mistakes. But by the time we funded their second startup, a year later, they had become extremely formidable. They were certainly not tame animals. And there is no way they'd have grown so much if they'd spent that year working at Microsoft, or even Google. They'd still have been diffident junior programmers. So now I'd advise people to go ahead and start startups right out of college. There's no better time to take risks than when you're young. Sure, you'll probably fail. But even failure will get you to the ultimate goal faster than getting a job. It worries me a bit to be saying this, because in effect we're advising people to educate themselves by failing at our expense, but it's the truth. 3\.
Not determined enough You need a lot of determination to succeed as a startup founder. It's probably the single best predictor of success. Some people may not be determined enough to make it. It's hard for me to say for sure, because I'm so determined that I can't imagine what's going on in the heads of people who aren't. But I know they exist. Most hackers probably underestimate their determination. I've seen a lot become visibly more determined as they get used to running a startup. I can think of several we've funded who would have been delighted at first to be bought for $2 million, but are now set on world domination. How can you tell if you're determined enough, when Larry and Sergey themselves were unsure at first about starting a company? I'm guessing here, but I'd say the test is whether you're sufficiently driven to work on your own projects. Though they may have been unsure whether they wanted to start a company, it doesn't seem as if Larry and Sergey were meek little research assistants, obediently doing their advisors' bidding. They started projects of their own. 4\. Not smart enough You may need to be moderately smart to succeed as a startup founder. But if you're worried about this, you're probably mistaken. If you're smart enough to worry that you might not be smart enough to start a startup, you probably are. And in any case, starting a startup just doesn't require that much intelligence. Some startups do. You have to be good at math to write Mathematica. But most companies do more mundane stuff where the decisive factor is effort, not brains. Silicon Valley can warp your perspective on this, because there's a cult of smartness here. People who aren't smart at least try to act that way. But if you think it takes a lot of intelligence to get rich, try spending a couple days in some of the fancier bits of New York or LA.
If you don't think you're smart enough to start a startup doing something technically difficult, just write enterprise software. Enterprise software companies aren't technology companies, they're sales companies, and sales depends mostly on effort. 5\. Know nothing about business This is another variable whose coefficient should be zero. You don't need to know anything about business to start a startup. The initial focus should be the product. All you need to know in this phase is how to build things people want. If you succeed, you'll have to think about how to make money from it. But this is so easy you can pick it up on the fly. I get a fair amount of flak for telling founders just to make something great and not worry too much about making money. And yet all the empirical evidence points that way: pretty much 100% of startups that make something popular manage to make money from it. And acquirers tell me privately that revenue is not what they buy startups for, but their strategic value. Which means, because they made something people want. Acquirers know the rule holds for them too: if users love you, you can always make money from that somehow, and if they don't, the cleverest business model in the world won't save you. So why do so many people argue with me? I think one reason is that they hate the idea that a bunch of twenty year olds could get rich from building something cool that doesn't make any money. They just don't want that to be possible. But how possible it is doesn't depend on how much they want it to be. For a while it annoyed me to hear myself described as some kind of irresponsible pied piper, leading impressionable young hackers down the road to ruin. But now I realize this kind of controversy is a sign of a good idea. The most valuable truths are the ones most people don't believe. They're like undervalued stocks. If you start with them, you'll have the whole field to yourself.
So when you find an idea you know is good but most people disagree with, you should not merely ignore their objections, but push aggressively in that direction. In this case, that means you should seek out ideas that would be popular but seem hard to make money from. We'll bet a seed round you can't make something popular that we can't figure out how to make money from. 6\. No cofounder Not having a cofounder is a real problem. A startup is too much for one person to bear. And though we differ from other investors on a lot of questions, we all agree on this. All investors, without exception, are more likely to fund you with a cofounder than without. We've funded two single founders, but in both cases we suggested their first priority should be to find a cofounder. Both did. But we'd have preferred them to have cofounders before they applied. It's not super hard to get a cofounder for a project that's just been funded, and we'd rather have cofounders committed enough to sign up for something super hard. If you don't have a cofounder, what should you do? Get one. It's more important than anything else. If there's no one where you live who wants to start a startup with you, move where there are people who do. If no one wants to work with you on your current idea, switch to an idea people want to work on. If you're still in school, you're surrounded by potential cofounders. A few years out it gets harder to find them. Not only do you have a smaller pool to draw from, but most already have jobs, and perhaps even families to support. So if you had friends in college you used to scheme about startups with, stay in touch with them as well as you can. That may help keep the dream alive. It's possible you could meet a cofounder through something like a user's group or a conference. But I wouldn't be too optimistic.
You need to work with someone to know whether you want them as a cofounder. [2] The real lesson to draw from this is not how to find a cofounder, but that you should start startups when you're young and there are lots of them around. 7\. No idea In a sense, it's not a problem if you don't have a good idea, because most startups change their idea anyway. In the average Y Combinator startup, I'd guess 70% of the idea is new at the end of the first three months. Sometimes it's 100%. In fact, we're so sure the founders are more important than the initial idea that we're going to try something new this funding cycle. We're going to let people apply with no idea at all. If you want, you can answer the question on the application form that asks what you're going to do with "We have no idea." If you seem really good we'll accept you anyway. We're confident we can sit down with you and cook up some promising project. Really this just codifies what we do already. We put little weight on the idea. We ask mainly out of politeness. The kind of question on the application form that we really care about is the one where we ask what cool things you've made. If what you've made is version one of a promising startup, so much the better, but the main thing we care about is whether you're good at making things. Being lead developer of a popular open source project counts almost as much. That solves the problem if you get funded by Y Combinator. What about in the general case? Because in another sense, it is a problem if you don't have an idea. If you start a startup with no idea, what do you do next? So here's the brief recipe for getting startup ideas. Find something that's missing in your own life, and supply that need—no matter how specific to you it seems. Steve Wozniak built himself a computer; who knew so many other people would want them? A need that's narrow but genuine is a better starting point than one that's broad but hypothetical.
So even if the problem is simply that you don't have a date on Saturday night, if you can think of a way to fix that by writing software, you're onto something, because a lot of other people have the same problem. 8\. No room for more startups A lot of people look at the ever-increasing number of startups and think "this can't continue." Implicit in their thinking is a fallacy: that there is some limit on the number of startups there could be. But this is false. No one claims there's any limit on the number of people who can work for salary at 1000-person companies. Why should there be any limit on the number who can work for equity at 5-person companies? [3] Nearly everyone who works is satisfying some kind of need. Breaking up companies into smaller units doesn't make those needs go away. Existing needs would probably get satisfied more efficiently by a network of startups than by a few giant, hierarchical organizations, but I don't think that would mean less opportunity, because satisfying current needs would lead to more. Certainly this tends to be the case in individuals. Nor is there anything wrong with that. We take for granted things that medieval kings would have considered effeminate luxuries, like whole buildings heated to spring temperatures year round. And if things go well, our descendants will take for granted things we would consider shockingly luxurious. There is no absolute standard for material wealth. Health care is a component of it, and that alone is a black hole. For the foreseeable future, people will want ever more material wealth, so there is no limit to the amount of work available for companies, and for startups in particular. Usually the limited-room fallacy is not expressed directly. Usually it's implicit in statements like "there are only so many startups Google, Microsoft, and Yahoo can buy." Maybe, though the list of acquirers is a lot longer than that.
And whatever you think of other acquirers, Google is not stupid. The reason big companies buy startups is that they've created something valuable. And why should there be any limit to the number of valuable startups companies can acquire, any more than there is a limit to the amount of wealth individual people want? Maybe there would be practical limits on the number of startups any one acquirer could assimilate, but if there is value to be had, in the form of upside that founders are willing to forgo in return for an immediate payment, acquirers will evolve to consume it. Markets are pretty smart that way. 9\. Family to support This one is real. I wouldn't advise anyone with a family to start a startup. I'm not saying it's a bad idea, just that I don't want to take responsibility for advising it. I'm willing to take responsibility for telling 22 year olds to start startups. So what if they fail? They'll learn a lot, and that job at Microsoft will still be waiting for them if they need it. But I'm not prepared to cross moms. What you can do, if you have a family and want to start a startup, is start a consulting business you can then gradually turn into a product business. Empirically the chances of pulling that off seem very small. You're never going to produce Google this way. But at least you'll never be without an income. Another way to decrease the risk is to join an existing startup instead of starting your own. Being one of the first employees of a startup is a lot like being a founder, in both the good ways and the bad. You'll be roughly 1/n^2 founder, where n is your employee number. As with the question of cofounders, the real lesson here is to start startups when you're young. 10\. Independently wealthy This is my excuse for not starting a startup. Startups are stressful.
Why do it if you don't need the money? For every "serial entrepreneur," there are probably twenty sane ones who think "Start another company? Are you crazy?" I've come close to starting new startups a couple times, but I always pull back because I don't want four years of my life to be consumed by random schleps. I know this business well enough to know you can't do it half-heartedly. What makes a good startup founder so dangerous is his willingness to endure infinite schleps. There is a bit of a problem with retirement, though. Like a lot of people, I like to work. And one of the many weird little problems you discover when you get rich is that a lot of the interesting people you'd like to work with are not rich. They need to work at something that pays the bills. Which means if you want to have them as colleagues, you have to work at something that pays the bills too, even though you don't need to. I think this is what drives a lot of serial entrepreneurs, actually. That's why I love working on Y Combinator so much. It's an excuse to work on something interesting with people I like. 11\. Not ready for commitment This was my reason for not starting a startup for most of my twenties. Like a lot of people that age, I valued freedom most of all. I was reluctant to do anything that required a commitment of more than a few months. Nor would I have wanted to do anything that completely took over my life the way a startup does. And that's fine. If you want to spend your time travelling around, or playing in a band, or whatever, that's a perfectly legitimate reason not to start a company. If you start a startup that succeeds, it's going to consume at least three or four years. (If it fails, you'll be done a lot quicker.) So you shouldn't do it if you're not ready for commitments on that scale.
Be aware, though, that if you get a regular job, you'll probably end up working there for as long as a startup would take, and you'll find you have much less spare time than you might expect. So if you're ready to clip on that ID badge and go to that orientation session, you may also be ready to start that startup. 12\. Need for structure I'm told there are people who need structure in their lives. This seems to be a nice way of saying they need someone to tell them what to do. I believe such people exist. There's plenty of empirical evidence: armies, religious cults, and so on. They may even be the majority. If you're one of these people, you probably shouldn't start a startup. In fact, you probably shouldn't even go to work for one. In a good startup, you don't get told what to do very much. There may be one person whose job title is CEO, but till the company has about twelve people no one should be telling anyone what to do. That's too inefficient. Each person should just do what they need to without anyone telling them. If that sounds like a recipe for chaos, think about a soccer team. Eleven people manage to work together in quite complicated ways, and yet only in occasional emergencies does anyone tell anyone else what to do. A reporter once asked David Beckham if there were any language problems at Real Madrid, since the players were from about eight different countries. He said it was never an issue, because everyone was so good they never had to talk. They all just did the right thing. How do you tell if you're independent-minded enough to start a startup? If you'd bristle at the suggestion that you aren't, then you probably are. 13\. Fear of uncertainty Perhaps some people are deterred from starting startups because they don't like the uncertainty. If you go to work for Microsoft, you can predict fairly accurately what the next few years will be like—all too accurately, in fact.
If you start a startup, anything might happen. Well, if you're troubled by uncertainty, I can solve that problem for you: if you start a startup, it will probably fail. Seriously, though, this is not a bad way to think about the whole experience. Hope for the best, but expect the worst. In the worst case, it will at least be interesting. In the best case you might get rich. No one will blame you if the startup tanks, so long as you made a serious effort. There may once have been a time when employers would regard that as a mark against you, but they wouldn't now. I asked managers at big companies, and they all said they'd prefer to hire someone who'd tried to start a startup and failed over someone who'd spent the same time working at a big company. Nor will investors hold it against you, as long as you didn't fail out of laziness or incurable stupidity. I'm told there's a lot of stigma attached to failing in other places—in Europe, for example. Not here. In America, companies, like practically everything else, are disposable. 14\. Don't realize what you're avoiding One reason people who've been out in the world for a year or two make better founders than people straight from college is that they know what they're avoiding. If their startup fails, they'll have to get a job, and they know how much jobs suck. If you've had summer jobs in college, you may think you know what jobs are like, but you probably don't. Summer jobs at technology companies are not real jobs. If you get a summer job as a waiter, that's a real job. Then you have to carry your weight. But software companies don't hire students for the summer as a source of cheap labor. They do it in the hope of recruiting them when they graduate. So while they're happy if you produce, they don't expect you to. That will change if you get a real job after you graduate. Then you'll have to earn your keep.
And since most of what big companies do is boring, you're going to have to work on boring stuff. Easy, compared to college, but boring. At first it may seem cool to get paid for doing easy stuff, after paying to do hard stuff in college. But that wears off after a few months. Eventually it gets demoralizing to work on dumb stuff, even if it's easy and you get paid a lot. And that's not the worst of it. The thing that really sucks about having a regular job is the expectation that you're supposed to be there at certain times. Even Google is afflicted with this, apparently. And what this means, as everyone who's had a regular job can tell you, is that there are going to be times when you have absolutely no desire to work on anything, and you're going to have to go to work anyway and sit in front of your screen and pretend to. To someone who likes work, as most good hackers do, this is torture. In a startup, you skip all that. There's no concept of office hours in most startups. Work and life just get mixed together. But the good thing about that is that no one minds if you have a life at work. In a startup you can do whatever you want most of the time. If you're a founder, what you want to do most of the time is work. But you never have to pretend to. If you took a nap in your office in a big company, it would seem unprofessional. But if you're starting a startup and you fall asleep in the middle of the day, your cofounders will just assume you were tired. 15\. Parents want you to be a doctor A significant number of would-be startup founders are probably dissuaded from doing it by their parents. I'm not going to say you shouldn't listen to them. Families are entitled to their own traditions, and who am I to argue with them? But I will give you a couple reasons why a safe career might not be what your parents really want for you. One is that parents tend to be more conservative for their kids than they would be for themselves.
This is actually a rational response to their situation. Parents end up sharing more of their kids' ill fortune than good fortune. Most parents don't mind this; it's part of the job; but it does tend to make them excessively conservative. And erring on the side of conservatism is still erring. In almost everything, reward is proportionate to risk. So by protecting their kids from risk, parents are, without realizing it, also protecting them from rewards. If they saw that, they'd want you to take more risks. The other reason parents may be mistaken is that, like generals, they're always fighting the last war. If they want you to be a doctor, odds are it's not just because they want you to help the sick, but also because it's a prestigious and lucrative career. [4] But not so lucrative or prestigious as it was when their opinions were formed. When I was a kid in the seventies, a doctor was _the_ thing to be. There was a sort of golden triangle involving doctors, Mercedes 450SLs, and tennis. All three vertices now seem pretty dated. The parents who want you to be a doctor may simply not realize how much things have changed. Would they be that unhappy if you were Steve Jobs instead? So I think the way to deal with your parents' opinions about what you should do is to treat them like feature requests. Even if your only goal is to please them, the way to do that is not simply to give them what they ask for. Instead think about why they're asking for something, and see if there's a better way to give them what they need. 16\. A job is the default This leads us to the last and probably most powerful reason people get regular jobs: it's the default thing to do. Defaults are enormously powerful, precisely because they operate without any conscious choice. To almost everyone except criminals, it seems an axiom that if you need money, you should get a job. Actually this tradition is not much more than a hundred years old.
Before that, the default way to make a living was by farming. It's a bad plan to treat something only a hundred years old as an axiom. By historical standards, that's something that's changing pretty rapidly. We may be seeing another such change right now. I've read a lot of economic history, and I understand the startup world pretty well, and it now seems to me fairly likely that we're seeing the beginning of a change like the one from farming to manufacturing. And you know what? If you'd been around when that change began (around 1000 in Europe) it would have seemed to nearly everyone that running off to the city to make your fortune was a crazy thing to do. Though serfs were in principle forbidden to leave their manors, it can't have been that hard to run away to a city. There were no guards patrolling the perimeter of the village. What prevented most serfs from leaving was that it seemed insanely risky. Leave one's plot of land? Leave the people you'd spent your whole life with, to live in a giant city of three or four thousand complete strangers? How would you live? How would you get food, if you didn't grow it? Frightening as it seemed to them, it's now the default with us to live by our wits. So if it seems risky to you to start a startup, think how risky it once seemed to your ancestors to live as we do now. Oddly enough, the people who know this best are the very ones trying to get you to stick to the old model. How can Larry and Sergey say you should come work as their employee, when they didn't get jobs themselves? Now we look back on medieval peasants and wonder how they stood it. How grim it must have been to till the same fields your whole life with no hope of anything better, under the thumb of lords and priests you had to give all your surplus to and acknowledge as your masters. I wouldn't be surprised if one day people look back on what we consider a normal job in the same way.
How grim it would be to commute every day to a cubicle in some soulless office complex, and be told what to do by someone you had to acknowledge as a boss—someone who could call you into their office and say "take a seat," and you'd sit! Imagine having to ask _permission_ to release software to users. Imagine being sad on Sunday afternoons because the weekend was almost over, and tomorrow you'd have to get up and go to work. How did they stand it? It's exciting to think we may be on the cusp of another shift like the one from farming to manufacturing. That's why I care about startups. Startups aren't interesting just because they're a way to make a lot of money. I couldn't care less about other ways to do that, like speculating in securities. At most those are interesting the way puzzles are. There's more going on with startups. They may represent one of those rare, historic shifts in the way wealth is created. That's ultimately what drives us to work on Y Combinator. We want to make money, if only so we don't have to stop doing it, but that's not the main goal. There have only been a handful of these great economic shifts in human history. It would be an amazing hack to make one happen faster. Notes [1] The only people who lost were us. The angels had convertible debt, so they had first claim on the proceeds of the auction. Y Combinator only got 38 cents on the dollar. [2] The best kind of organization for that might be an open source project, but those don't involve a lot of face to face meetings.
Maybe it would be worth starting one that did. [3] There need to be some number of big companies to acquire the startups, so the number of big companies couldn't decrease to zero. [4] Thought experiment: If doctors did the same work, but as impoverished outcasts, which parents would still want their kids to be doctors? Thanks to Trevor Blackwell, Jessica Livingston, and Robert Morris for reading drafts of this, to the founders of Zenter for letting me use their web-based PowerPoint killer even though it isn't launched yet, and to Ming-Hay Luk of the Berkeley CSUA for inviting me to speak. Comment on this essay.
| Russian Translation | | | Japanese Translation | Korean Translation.
想创业吗? 获得Y Combinator的资助。
2007年3月 _(本文源自2007年创业学校及伯克利CSUA的演讲。)_ 我们运营Y Combinator已足够久,积累了一些关于成功率的数据。2005年夏季的首批八家初创企业中,目前至少有四家可视为成功。其中三家被收购:Reddit由Reddit和Infogami合并而成,另一家尚不能透露名称;还有一家是Loopt,其发展势头强劲,若有意向几乎可随时被收购。 因此,不到两年前的首批创业者中,约半数已实现财富自由——至少按他们的标准而言。(致富后你会明白,财富自由有无数层级。) 我不敢预言50%的成功率能持续。首批可能是特例,但我们理应比常被引用的(且可能是虚构的)10%标准做得更好。25%的目标我认为是稳妥的。 即便失败的创业者似乎也未受重创。首批八家企业中,三家可能已终止。其中两位创始人在夏季结束后转向其他事业,未见心理创伤。最接近惨败的是Kiko,其团队坚持一年后被Google Calendar碾压,但结局圆满:他们在eBay上以25万美元售出软件,偿还天使投资后每人获得约一年薪资[1],随后立即投身更激动人心的新项目Justin.TV。 更惊人的数据是:首批创业者中,0%有过糟糕体验。他们如所有创业者般经历起伏,但无人愿用这段经历交换格子间工作。这一数据或许非偶然。无论长期成功率如何,后悔未选择普通工作的人比例将始终接近0%。 令我困惑的是:为何更多人不去创业?若几乎所有创业者都更享受这个过程,且可观比例能致富,为何不是人人趋之若鹜?许多人以为我们每轮融资会收到数千份申请,实际仅几百份。为何申请者不多?尽管外界可能觉得初创企业遍地开花,但相比具备相应技能的人群基数,创业者仍是少数。绝大多数程序员仍从校园直奔格子间,并扎根于此。 人们似乎未按自身利益行事。原因何在?我有答案。Y Combinator处于风投链条最前端,我们可能是全球最懂"犹豫是否创业"人群心理的专家。 犹豫无可厚非。若你作为黑客正犹豫是否创业,你正延续伟大传统。拉里与谢尔盖创建谷歌前也曾迟疑,杨致远和大卫·费罗创立雅虎时亦然。事实上,最成功的初创企业往往源自犹豫的黑客,而非热情过头的商人。 有数据佐证:我们资助的多个最成功团队事后透露,他们是在最后一刻才决定申请,有的甚至在截止前数小时才敲定。 应对犹豫的方法是分解成因。多数人抗拒某事时,脑中混杂约八种理由,却不知孰轻孰重。有些合理有些荒谬,除非厘清各自权重,否则无法判断整体犹豫是否合理。 我将列出人们抗拒创业的所有因素,并指明哪些真实。潜在创业者可借此清单检视自身感受。 我承认目标是增强你的自信。但这与寻常自信训练有两点不同:其一,我有保持诚实的动机。多数自信课程在你购书或付费参会时已达成目标,而若我鼓励不该创业的人创业,只会自找麻烦——更多申请意味着更多审阅工作。 其二,我的方法不同。我不说"加油你能行",而是剖析所有阻碍你的理由,证明多数(非全部)应被忽略。我们从与生俱来的第一项开始: 1. 太年轻 许多人自认太年轻不宜创业。部分人没错。全球年龄中位数约27岁,约三分之一人口确实年轻。 何为太年轻?Y Combinator的目标之一就是探索创业者年龄下限。我们始终认为投资者过于保守——他们想资助教授,实则应资助研究生甚至本科生。 推动边界后我们发现:边界本身模糊不清。下限可能低至16岁。我们不考虑18岁以下者因其无法合法签约。但迄今最成功的受资助者萨姆·奥尔特曼当时仅19岁。 萨姆是异常值。19岁的他仿佛体内住着40岁的灵魂。另有19岁者心智仅12岁。 "成年人"一词存在有其道理。存在一个跨越的阈值,传统定为21岁,但每人跨越时间迥异。只要跨过此阈值,无论年龄你都适合创业。 如何判断?成年人有几个测试标准。遇见萨姆后我才意识到这些测试:我感受到与年长者对话的气场,随后思考:我在衡量什么?何种特质显其成熟? 测试一:是否仍保留孩童式逃避反应。幼时被要求做难事,你可哭诉"我不会"而获豁免。孩童有"我只是孩子"的魔法按钮逃避困境。成年人则无权逃避——当然也有人逃避,但会遭无情淘汰。 测试二:应对挑战的方式。未成熟者面对成人挑战时,反应会默认对方权威。若成人说"这主意真蠢",孩子要么夹尾退缩,要么叛逆。但叛逆与顺从同样预设了弱势。成年人的回应是直视对方:"真的吗?为何这么认为?" 当然,许多成年人应对挑战仍显幼稚。但你极少见到孩子如成人般应对挑战。若遇见,无论年龄,你已找到一位成年人。 2. 经验不足 我曾撰文称创业者至少需23岁,应先就业数年。现不再认同此观点,因所见案例改变了看法。 我仍认为23岁优于21岁。但21岁获取经验的最佳方式正是创业。矛盾的是:若你因经验不足而犹豫,解决方案恰是创业。这比普通工作更能快速弥补经验缺口。事实上,普通工作可能削弱创业能力,将你驯化为依赖办公室与产品经理指示的温顺动物。 说服我的典型案例是Kiko团队。他们毕业即创业,因经验不足屡屡犯错。但一年后我们资助其二次创业时,他们已脱胎换骨。绝非温顺动物。若那年在微软或谷歌工作,他们绝无可能如此成长——仍将是怯懦的初级程序员。 因此现建议毕业后立即创业。年轻时是冒险最佳时机。当然可能失败。但即使失败,也比就业更快接近终极目标。 说这些令我稍感不安,因本质上是建议人们以我们的成本试错学习,但这是事实。 3. 决心不足 创业成功需极强决心,这可能是最佳成功预测指标。 部分人可能决心不足。我难以确知,因我决心太强而无法想象犹豫者的心态。但这类人确实存在。 多数黑客可能低估自身决心。我见证许多人随创业进程愈发坚定。多个受资助团队最初会为200万美元收购欣喜,现却志在征服世界。 当拉里与谢尔盖都曾犹豫时,如何判断自己决心足够?我的测试标准是:你是否执着于自主项目。尽管他们可能犹豫是否创业,但显然非顺从导师指示的研究助理——他们启动了自有项目。 4. 不够聪明 创业成功或需中等智商。但若你因此忧虑,可能多虑了。能担忧"智商是否够创业",说明你已足够聪明。 何况创业本不需极高智商。某些领域需要——编写Mathematica需数学天赋。但多数公司从事常规工作,决胜因素是努力非智力。硅谷可能扭曲认知,因这里崇拜聪明。不够聪明者至少试图伪装。若你认为致富需极高智商,不妨去纽约或洛杉矶高档街区观察几日。 若自觉不够聪明攻克技术难题,就开发企业软件。企业软件公司实为销售公司,而销售主要靠勤奋。 5. 不懂商业 这是另一项系数应为零的变量。创业初期只需专注产品,核心是打造人们需要的东西。成功后赚钱方法自然水到渠成。 我因建议创始人专注打造伟大产品而非赚钱而备受指责。但所有实证都指向:100%做出受欢迎产品的初创企业最终都盈利。收购方私下透露:他们看中的是战略价值(即产品受用户喜爱),非营收。收购方也明白法则:用户爱你,赚钱方式自会浮现;用户不爱,再精妙的商业模式也徒劳。 为何许多人反驳?部分人憎恶二十岁青年凭酷炫但不赚钱的产品致富的可能性。他们拒绝接受这种可能——但可能性不因主观意愿改变。 曾几何时,被描述为引诱年轻黑客走向毁灭的吹笛手令我恼怒。如今我明白:争议恰是好理念的标志。 最有价值的真理往往最不被相信,如同低估的股票。以此起步你将独占赛场。因此当发现一个你确信正确但多数人反对的理念时,不仅要忽略反对声,更需强势推进。这意味着应寻找受欢迎但看似难盈利的创意。 我们愿用种子轮赌你无法做出我们找不到盈利模式的受欢迎产品。 6. 缺乏联合创始人 独行侠是真实困境。创业重担一人难扛。尽管我们在多数问题上与投资者意见相左,但这点完全一致:所有投资者都更倾向资助有联合创始人的团队。 我们资助过两位独行侠,但都建议其首要任务是寻找伙伴。他们都做到了。但我们更希望申请时已有搭档。项目获资助后找联合创始人并不太难,我们更青睐愿为艰难事业签约的团队。 若无联合创始人怎么办?去找。这比任何事都重要。若所在地无人愿共事,就搬去有志者聚集处。若当前创意无人响应,就转向他人愿参与的创意。 若你仍在校园,周围满是潜在伙伴。毕业数年后难度剧增——不仅候选人减少,多数人已有工作甚至家庭。因此若大学时有创业畅谈的伙伴,请竭力保持联系,这有助于延续梦想。 通过用户组或会议结识联合创始人或有可能,但别太乐观。你需要共事过才能确定是否适合[2]。 真正启示是:应在年轻时、周围充满潜在伙伴时创业。 7. 没有创意 某种意义上,缺乏好创意不是问题,因多数初创企业会调整方向。Y Combinator团队平均在首三个月迭代70%的创意,有时达100%。 事实上,我们坚信创始人比初始创意更重要,因此本轮融资将尝试新方式:允许无创意者申请。申请表"计划"栏可填"暂无创意"。若你足够优秀,我们仍会接纳——我们有信心与你共同策划有前景的项目。 这仅是现有做法的规范化。我们本就不看重创意,提问仅是礼节。我们真正关注的是"你创造过什么酷东西"。若你创造过有潜力的初代产品更好,但核心是确认你擅长创造。领导过热门开源项目同样有价值。 若获Y Combinator资助,此问题已解。但普遍情况如何?另一角度看,无创意确是问题。创业后下一步是什么? 获取创业创意的速成法:发现你生活中的缺失,然后填补——无论多小众。沃兹尼亚克为自己造电脑时,谁知数百万人会需要?窄而真实的需求优于宽而假设的。因此即便问题只是"周六晚没约会",若能用软件解决,你就找到了痛点——因众人同病相怜。 8. 创业空间饱和 许多人见初创企业激增便想"这不可持续"。其思维隐含谬误:创业数量存在上限。但这是错的。没人认为千人规模公司的雇员数有上限,为何五人规模公司的股权工作者就有上限?[3] 几乎所有工作者都在满足某种需求。将大公司拆分为小单元不会让需求消失。初创企业网络可能比少数巨头更高效满足现有需求,但这不意味着机会减少——满足现有需求会催生新需求。个体层面同样如此。这并非坏事。中世纪国王视为奢侈的全年恒温建筑,今人已习以为常。若一切顺利,后人看待我们眼中的奢侈亦将如此。物质财富无绝对标准,医疗保健仅是其中深不可测的一环。可预见的未来,人类对物质财富的追求永无止境,因此企业(尤其是初创企业)的工作机会亦无限。 "空间有限论"通常不直述,而隐含于"谷歌/微软/雅虎能收购的初创企业有限"等表述。但收购方远不止这些。且不论其他收购方,谷歌绝不愚蠢。大公司收购初创企业因其创造了价值。为何有价值初创企业的数量会有上限?正如个人对财富的渴望无上限。单一收购方的消化能力或有极限,但只要存在创始人愿为即时回报放弃的潜在价值,收购方自会进化以吸纳。市场在此方面极为智慧。 9. 需要养家 这是真实障碍。我不建议有家室者创业。非谓其不可行,只是我不愿担此建议之责。我愿对22岁青年说"去创业吧",失败又何妨?他们将收获经验,必要时微软职位仍虚位以待。但我不敢得罪母亲们。 若有家室又想创业,可先成立咨询公司再逐步转型产品。实证表明此路成功率极低,绝无可能诞生谷歌,但至少收入不断。 另一降险方式是加入现有初创企业而非自创。作为早期员工,体验近似创始人(好坏皆然)。你的创始人系数约为1/n²(n为员工编号)。 如同联合创始人问题,真正启示仍是:趁年轻创业。 10. 财务自由 这是我未再创业的借口。创业压力山大,既已财务自由,何必自讨苦吃?每位"连续创业者"背后,或有二十位理智者认为"再创公司?疯了吗?" 我曾几近启动新项目,终因不愿被琐事吞噬四年而却步。我深谙此道:半心半意必败。优秀创始人的危险特质正是愿忍受无尽琐碎。 但退休也有问题。如多数人,我热爱工作。致富后发现的怪事之一是:你想共事的许多有趣之人尚未致富,他们需要养家糊口。这意味着若想与他们共事,你仍需从事赚钱工作——尽管你已无需。我认为这恰是许多连续创业者的驱动力。 这也是我热爱Y Combinator的原因——它让我能与欣赏之人共事有趣之事。 11. 不愿承诺 这是我二十多岁时不创业的主因。如多数同龄人,我最珍视自由,抗拒任何需数月以上承诺之事,更不愿让创业完全主宰生活。这无可厚非。若你想周游世界或玩乐队,这完全是不创业的正当理由。 成功创业至少需三四年(失败则快得多)。若未准备好如此承诺,就不应开始。但请注意:普通工作同样耗时,且闲暇远比预期少。若你已准备好别上工牌参加入职培训,或许也准备好创业了。 12. 需要结构 据说有人需要生活被结构化。这实为"需要他人指挥"的婉辞。我信其存在,证据充足:军队、宗教 cult等。他们甚至是多数。 若你属此类,可能不应创业,甚至不应加入初创企业。优秀初创企业中,无人会频繁指挥你。即便有CEO头衔,十二人以下公司里,指挥他人效率过低。每人应主动完成分内之事。 若觉此言将致混乱,想想足球队:十一人以复杂方式协作,仅紧急时才会相互指挥。记者曾问贝克汉姆皇马是否存语言障碍(球员来自八国),他答道从非问题,因众人皆强到无需言语,自会做正确之事。 如何判断你是否足够自主?若对"你不够自主"的建议感到恼怒,你很可能已足够自主。 13. 恐惧不确定性 或许有人因厌恶不确定性而却步。为微软工作可精准预测未来数年(事实上过于精准)。创业则一切皆可能。 若你困扰于不确定性,我可解决:若你创业,很可能失败。严肃而言,这是思考全程的不错角度:抱最好希望,做最坏打算。最坏不过经历有趣,最好则可能致富。 只要尽力而为,无人会因失败指责你。雇主曾视创业失败为污点,今非昔比。我询问过大公司管理者,他们均表示:相比同期在大公司工作者,更愿雇佣创业失败者。 投资者亦不会因此否定你——只要非因懒惰或愚蠢而败。据说欧洲等地创业失败污名化严重,但美国不然。在这里,公司如万物皆可弃。 14. 未意识到所逃避之物 有过一两年职场经历者比应届生更适合创业,因他们知晓所逃避何物。若创业失败需重返职场,他们深知工作之糟。 暑期工经历或让你自认了解工作,实则不然。科技公司暑期工非真实工作——若做服务员才是。后者需真正担责。而软件公司雇佣学生意在毕业招聘,故虽乐见产出,却无硬性要求。 毕业后正式工作将截然不同。你需创造价值,而大公司多从事乏味工作。起初为简单工作获酬可能觉酷(尤其对比付费读大学的艰辛),但数月后魅力尽失。最终,即便高薪易事,从事愚蠢工作也会消磨斗志。 更糟的是:常规工作最糟处在于必须定时现身。谷歌亦难幸免。如所有过来人所述,这意味着当你毫无干劲时,仍须上班对屏装忙。对热爱工作(如多数优秀黑客)者,这实为酷刑。 创业则跳过这一切。多数初创企业无"办公时间"概念,工作生活浑然一体。好处是无人介意你在工作中生活。创业者多数时间可随心所欲——创始人最想做的本就是工作,且无需伪装。 大公司午睡显得不专业,但初创企业里,白天入睡的合伙人只会被认作太累。 15. 父母希望你当医生 相当数量潜在创业者被父母劝阻。我不劝你违抗父母。家庭有权保有传统,我无意干涉。但可提供两个"安稳职业未必是父母真愿"的理由。 其一,父母对子女的保守倾向超过对自身。这实为理性反应——父母需分担子女霉运多于好运。多数父母不介意,这是职责所在,但确实导致过度保守。而保守之误仍是错误。几乎所有领域,回报与风险成正比。父母护子避险时,无意中也屏蔽了回报。若意识到这点,他们会愿你承担更多风险。 其二,父母如将军,总在打上一场战争。若他们愿你从医,不仅因救死扶伤,更因此职业体面高薪[4]。但其观念形成时的光环今已.
February 2007 A few days ago I finally figured out something I've wondered about for 25 years: the relationship between wisdom and intelligence. Anyone can see they're not the same by the number of people who are smart, but not very wise. And yet intelligence and wisdom do seem related. How? What is wisdom? I'd say it's knowing what to do in a lot of situations. I'm not trying to make a deep point here about the true nature of wisdom, just to figure out how we use the word. A wise person is someone who usually knows the right thing to do. And yet isn't being smart also knowing what to do in certain situations? For example, knowing what to do when the teacher tells your elementary school class to add all the numbers from 1 to 100? [1] Some say wisdom and intelligence apply to different types of problems—wisdom to human problems and intelligence to abstract ones. But that isn't true. Some wisdom has nothing to do with people: for example, the wisdom of the engineer who knows certain structures are less prone to failure than others. And certainly smart people can find clever solutions to human problems as well as abstract ones. [2] Another popular explanation is that wisdom comes from experience while intelligence is innate. But people are not simply wise in proportion to how much experience they have. Other things must contribute to wisdom besides experience, and some may be innate: a reflective disposition, for example. Neither of the conventional explanations of the difference between wisdom and intelligence stands up to scrutiny. So what is the difference? If we look at how people use the words "wise" and "smart," what they seem to mean is different shapes of performance. Curve "Wise" and "smart" are both ways of saying someone knows what to do. The difference is that "wise" means one has a high average outcome across all situations, and "smart" means one does spectacularly well in a few.
That is, if you had a graph in which the x axis represented situations and the y axis the outcome, the graph of the wise person would be high overall, and the graph of the smart person would have high peaks. The distinction is similar to the rule that one should judge talent at its best and character at its worst. Except you judge intelligence at its best, and wisdom by its average. That's how the two are related: they're the two different senses in which the same curve can be high. So a wise person knows what to do in most situations, while a smart person knows what to do in situations where few others could. We need to add one more qualification: we should ignore cases where someone knows what to do because they have inside information. [3] But aside from that, I don't think we can get much more specific without starting to be mistaken. Nor do we need to. Simple as it is, this explanation predicts, or at least accords with, both of the conventional stories about the distinction between wisdom and intelligence. Human problems are the most common type, so being good at solving those is key in achieving a high average outcome. And it seems natural that a high average outcome depends mostly on experience, but that dramatic peaks can only be achieved by people with certain rare, innate qualities; nearly anyone can learn to be a good swimmer, but to be an Olympic swimmer you need a certain body type. This explanation also suggests why wisdom is such an elusive concept: there's no such thing. "Wise" means something—that one is on average good at making the right choice. But giving the name "wisdom" to the supposed quality that enables one to do that doesn't mean such a thing exists.
To the extent "wisdom" means anything, it refers to a grab-bag of qualities as various as self-discipline, experience, and empathy. [4] Likewise, though "intelligent" means something, we're asking for trouble if we insist on looking for a single thing called "intelligence." And whatever its components, they're not all innate. We use the word "intelligent" as an indication of ability: a smart person can grasp things few others could. It does seem likely there's some inborn predisposition to intelligence (and wisdom too), but this predisposition is not itself intelligence. One reason we tend to think of intelligence as inborn is that people trying to measure it have concentrated on the aspects of it that are most measurable. A quality that's inborn will obviously be more convenient to work with than one that's influenced by experience, and thus might vary in the course of a study. The problem comes when we drag the word "intelligence" over onto what they're measuring. If they're measuring something inborn, they can't be measuring intelligence. Three year olds aren't smart. When we describe one as smart, it's shorthand for "smarter than other three year olds." Split Perhaps it's a technicality to point out that a predisposition to intelligence is not the same as intelligence. But it's an important technicality, because it reminds us that we can become smarter, just as we can become wiser. The alarming thing is that we may have to choose between the two. If wisdom and intelligence are the average and peaks of the same curve, then they converge as the number of points on the curve decreases. If there's just one point, they're identical: the average and maximum are the same. But as the number of points increases, wisdom and intelligence diverge. And historically the number of points on the curve seems to have been increasing: our ability is tested in an ever wider range of situations.
In the time of Confucius and Socrates, people seem to have regarded wisdom, learning, and intelligence as more closely related than we do. Distinguishing between "wise" and "smart" is a modern habit. [5] And the reason we do is that they've been diverging. As knowledge gets more specialized, there are more points on the curve, and the distinction between the spikes and the average becomes sharper, like a digital image rendered with more pixels. One consequence is that some old recipes may have become obsolete. At the very least we have to go back and figure out if they were really recipes for wisdom or intelligence. But the really striking change, as intelligence and wisdom drift apart, is that we may have to decide which we prefer. We may not be able to optimize for both simultaneously. Society seems to have voted for intelligence. We no longer admire the sage—not the way people did two thousand years ago. Now we admire the genius. Because in fact the distinction we began with has a rather brutal converse: just as you can be smart without being very wise, you can be wise without being very smart. That doesn't sound especially admirable. That gets you James Bond, who knows what to do in a lot of situations, but has to rely on Q for the ones involving math. Intelligence and wisdom are obviously not mutually exclusive. In fact, a high average may help support high peaks. But there are reasons to believe that at some point you have to choose between them. One is the example of very smart people, who are so often unwise that in popular culture this now seems to be regarded as the rule rather than the exception. Perhaps the absent-minded professor is wise in his way, or wiser than he seems, but he's not wise in the way Confucius or Socrates wanted people to be. [6] New For both Confucius and Socrates, wisdom, virtue, and happiness were necessarily related.
The wise man was someone who knew what the right choice was and always made it; to be the right choice, it had to be morally right; he was therefore always happy, knowing he'd done the best he could. I can't think of many ancient philosophers who would have disagreed with that, so far as it goes. "The superior man is always happy; the small man sad," said Confucius. [7] Whereas a few years ago I read an interview with a mathematician who said that most nights he went to bed discontented, feeling he hadn't made enough progress. [8] The Chinese and Greek words we translate as "happy" didn't mean exactly what we do by it, but there's enough overlap that this remark contradicts them. Is the mathematician a small man because he's discontented? No; he's just doing a kind of work that wasn't very common in Confucius's day. Human knowledge seems to grow fractally. Time after time, something that seemed a small and uninteresting area—experimental error, even—turns out, when examined up close, to have as much in it as all knowledge up to that point. Several of the fractal buds that have exploded since ancient times involve inventing and discovering new things. Math, for example, used to be something a handful of people did part-time. Now it's the career of thousands. And in work that involves making new things, some old rules don't apply. Recently I've spent some time advising people, and there I find the ancient rule still works: try to understand the situation as well as you can, give the best advice you can based on your experience, and then don't worry about it, knowing you did all you could. But I don't have anything like this serenity when I'm writing an essay. Then I'm worried. What if I run out of ideas? And when I'm writing, four nights out of five I go to bed discontented, feeling I didn't get enough done. Advising people and writing are fundamentally different types of work.
When people come to you with a problem and you have to figure out the right thing to do, you don't (usually) have to invent anything. You just weigh the alternatives and try to judge which is the prudent choice. But _prudence_ can't tell me what sentence to write next. The search space is too big. Someone like a judge or a military officer can in much of his work be guided by duty, but duty is no guide in making things. Makers depend on something more precarious: inspiration. And like most people who lead a precarious existence, they tend to be worried, not contented. In that respect they're more like the small man of Confucius's day, always one bad harvest (or ruler) away from starvation. Except instead of being at the mercy of weather and officials, they're at the mercy of their own imagination. Limits To me it was a relief just to realize it might be ok to be discontented. The idea that a successful person should be happy has thousands of years of momentum behind it. If I was any good, why didn't I have the easy confidence winners are supposed to have? But that, I now believe, is like a runner asking "If I'm such a good athlete, why do I feel so tired?" Good runners still get tired; they just get tired at higher speeds. People whose work is to invent or discover things are in the same position as the runner. There's no way for them to do the best they can, because there's no limit to what they could do. The closest you can come is to compare yourself to other people. But the better you do, the less this matters. An undergrad who gets something published feels like a star. But for someone at the top of the field, what's the test of doing well? Runners can at least compare themselves to others doing exactly the same thing; if you win an Olympic gold medal, you can be fairly content, even if you think you could have run a bit faster.
But what is a novelist to do? Whereas if you're doing the kind of work in which problems are presented to you and you have to choose between several alternatives, there's an upper bound on your performance: choosing the best every time. In ancient societies, nearly all work seems to have been of this type. The peasant had to decide whether a garment was worth mending, and the king whether or not to invade his neighbor, but neither was expected to invent anything. In principle they could have; the king could have invented firearms, then invaded his neighbor. But in practice innovations were so rare that they weren't expected of you, any more than goalkeepers are expected to score goals. [9] In practice, it seemed as if there was a correct decision in every situation, and if you made it you'd done your job perfectly, just as a goalkeeper who prevents the other team from scoring is considered to have played a perfect game. In this world, wisdom seemed paramount. [10] Even now, most people do work in which problems are put before them and they have to choose the best alternative. But as knowledge has grown more specialized, there are more and more types of work in which people have to make up new things, and in which performance is therefore unbounded. Intelligence has become increasingly important relative to wisdom because there is more room for spikes. Recipes Another sign we may have to choose between intelligence and wisdom is how different their recipes are. Wisdom seems to come largely from curing childish qualities, and intelligence largely from cultivating them. Recipes for wisdom, particularly ancient ones, tend to have a remedial character. To achieve wisdom one must cut away all the debris that fills one's head on emergence from childhood, leaving only the important stuff.
Both self-control and experience have this effect: to eliminate the random biases that come from your own nature and from the circumstances of your upbringing respectively. That's not all wisdom is, but it's a large part of it. Much of what's in the sage's head is also in the head of every twelve year old. The difference is that in the head of the twelve year old it's mixed together with a lot of random junk. The path to intelligence seems to be through working on hard problems. You develop intelligence as you might develop muscles, through exercise. But there can't be too much compulsion here. No amount of discipline can replace genuine curiosity. So cultivating intelligence seems to be a matter of identifying some bias in one's character—some tendency to be interested in certain types of things—and nurturing it. Instead of obliterating your idiosyncrasies in an effort to make yourself a neutral vessel for the truth, you select one and try to grow it from a seedling into a tree. The wise are all much alike in their wisdom, but very smart people tend to be smart in distinctive ways. Most of our educational traditions aim at wisdom. So perhaps one reason schools work badly is that they're trying to make intelligence using recipes for wisdom. Most recipes for wisdom have an element of subjection. At the very least, you're supposed to do what the teacher says. The more extreme recipes aim to break down your individuality the way basic training does. But that's not the route to intelligence. Whereas wisdom comes through humility, it may actually help, in cultivating intelligence, to have a mistakenly high opinion of your abilities, because that encourages you to keep working. Ideally till you realize how mistaken you were. (The reason it's hard to learn new skills late in life is not just that one's brain is less malleable. Another probably even worse obstacle is that one has higher standards.) I realize we're on dangerous ground here.
I'm not proposing the primary goal of education should be to increase students' "self-esteem." That just breeds laziness. And in any case, it doesn't really fool the kids, not the smart ones. They can tell at a young age that a contest where everyone wins is a fraud. A teacher has to walk a narrow path: you want to encourage kids to come up with things on their own, but you can't simply applaud everything they produce. You have to be a good audience: appreciative, but not too easily impressed. And that's a lot of work. You have to have a good enough grasp of kids' capacities at different ages to know when to be surprised. That's the opposite of traditional recipes for education. Traditionally the student is the audience, not the teacher; the student's job is not to invent, but to absorb some prescribed body of material. (The use of the term "recitation" for sections in some colleges is a fossil of this.) The problem with these old traditions is that they're too much influenced by recipes for wisdom. Different I deliberately gave this essay a provocative title; of course it's worth being wise. But I think it's important to understand the relationship between intelligence and wisdom, and particularly what seems to be the growing gap between them. That way we can avoid applying rules and standards to intelligence that are really meant for wisdom. These two senses of "knowing what to do" are more different than most people realize. The path to wisdom is through discipline, and the path to intelligence through carefully selected self-indulgence. Wisdom is universal, and intelligence idiosyncratic. And while wisdom yields calmness, intelligence much of the time leads to discontentment. That's particularly worth remembering. A physicist friend recently told me half his department was on Prozac. Perhaps if we acknowledge that some amount of frustration is inevitable in certain kinds of work, we can mitigate its effects.
Perhaps we can box it up and put it away some of the time, instead of letting it flow together with everyday sadness to produce what seems an alarmingly large pool. At the very least, we can avoid being discontented about being discontented. If you feel exhausted, it's not necessarily because there's something wrong with you. Maybe you're just running fast. Notes [1] Gauss was supposedly asked this when he was 10. Instead of laboriously adding together the numbers like the other students, he saw that they consisted of 50 pairs that each summed to 101 (100 \+ 1, 99 + 2, etc), and that he could just multiply 101 by 50 to get the answer, 5050. [2] A variant is that intelligence is the ability to solve problems, and wisdom the judgement to know how to use those solutions. But while this is certainly an important relationship between wisdom and intelligence, it's not the _distinction between_ them. Wisdom is useful in solving problems too, and intelligence can help in deciding what to do with the solutions. [3] In judging both intelligence and wisdom we have to factor out some knowledge. People who know the combination of a safe will be better at opening it than people who don't, but no one would say that was a test of intelligence or wisdom. But knowledge overlaps with wisdom and probably also intelligence. A knowledge of human nature is certainly part of wisdom. So where do we draw the line? Perhaps the solution is to discount knowledge that at some point has a sharp drop in utility. For example, understanding French will help you in a large number of situations, but its value drops sharply as soon as no one else involved knows French. Whereas the value of understanding vanity would decline more gradually. The knowledge whose utility drops sharply is the kind that has little relation to other knowledge.
This includes mere conventions, like languages and safe combinations, and also what we'd call "random" facts, like movie stars' birthdays, or how to distinguish 1956 from 1957 Studebakers. [4] People seeking some single thing called "wisdom" have been fooled by grammar. Wisdom is just knowing the right thing to do, and there are a hundred and one different qualities that help in that. Some, like selflessness, might come from meditating in an empty room, and others, like a knowledge of human nature, might come from going to drunken parties. Perhaps realizing this will help dispel the cloud of semi-sacred mystery that surrounds wisdom in so many people's eyes. The mystery comes mostly from looking for something that doesn't exist. And the reason there have historically been so many different schools of thought about how to achieve wisdom is that they've focused on different components of it. When I use the word "wisdom" in this essay, I mean no more than whatever collection of qualities helps people make the right choice in a wide variety of situations. [5] Even in English, our sense of the word "intelligence" is surprisingly recent. Predecessors like "understanding" seem to have had a broader meaning. [6] There is of course some uncertainty about how closely the remarks attributed to Confucius and Socrates resemble their actual opinions. I'm using these names as we use the name "Homer," to mean the hypothetical people who said the things attributed to them. [7] _Analects_ VII:36, Fung trans. Some translators use "calm" instead of "happy." One source of difficulty here is that present-day English speakers have a different idea of happiness from many older societies. Every language probably has a word meaning "how one feels when things are going well," but different cultures react differently when things go well. We react like children, with smiles and laughter.
But in a more reserved society, or in one where life was tougher, the reaction might be a quiet contentment. [8] It may have been Andrew Wiles, but I'm not sure. If anyone remembers such an interview, I'd appreciate hearing from you. [9] Confucius claimed proudly that he had never invented anything—that he had simply passed on an accurate account of ancient traditions. [ _Analects_ VII:1] It's hard for us now to appreciate how important a duty it must have been in preliterate societies to remember and pass on the group's accumulated knowledge. Even in Confucius's time it still seems to have been the first duty of the scholar. [10] The bias toward wisdom in ancient philosophy may be exaggerated by the fact that, in both Greece and China, many of the first philosophers (including Confucius and Plato) saw themselves as teachers of administrators, and so thought disproportionately about such matters. The few people who did invent things, like storytellers, must have seemed an outlying data point that could be ignored. Thanks to Trevor Blackwell, Sarah Harlin, Jessica Livingston, and Robert Morris for reading drafts of this.
| Polish Translation | | | French Translation | Russian Translation | | | Russian Translation.
2007年2月 二十五年来我一直困惑的问题终于在几天前有了答案:智慧与智力的关系。从众多聪明却不睿智的人身上,任何人都能看出这两者并不相同。然而智慧与智力似乎又存在某种关联。这种关联究竟是什么? 什么是智慧?我认为它是在多数情境中知晓如何行事的能力。在此我并不试图对智慧的本质进行深刻探讨,只是想厘清这个词的日常用法。智者通常知道什么是正确的选择。 但聪明不也意味着在某些情境中知道如何行事吗?比如当小学老师要求全班计算1到100所有数字之和时,知道解题方法?[1] 有人认为智慧与智力适用于不同类型的问题——智慧用于处理人际关系,智力用于解决抽象问题。但事实并非如此。有些智慧与人类毫无关联:比如工程师知道某些结构更不易坍塌的经验智慧。而聪明人既能解决抽象问题,也能为人类问题找到巧妙方案。[2] 另一种流行解释认为智慧来自经验,智力则是与生俱来。但人的智慧并非与经验多寡成正比。除经验外,其他因素也影响着智慧的形成,其中某些可能是天赋:比如善于反思的性格特质。 这两种关于智慧与智力区别的传统解释都经不起推敲。那么真正的区别何在?若观察人们使用"wise"(智慧)与"smart"(聪明)的语境,其差异似乎体现在能力表现形态的不同。 曲线 "智慧"与"聪明"都是形容人知道如何行事的词汇。区别在于:"智慧"意味着在所有情境中都能保持较高水准的表现,而"聪明"则是在少数情境中表现极为出色。如果用曲线图表示,横轴代表不同情境,纵轴代表表现水平,智者的曲线整体处于高位,而聪明人的曲线则呈现出陡峭的波峰。 这种区分类似于"评判才能要看其巅峰表现,评判品格要看其最低表现"的准则。只不过评判智力要看巅峰值,评判智慧则看平均值。二者的关联在于:它们是对同一条曲线不同维度的评价。 因此智者能在多数情境中做出正确选择,而聪明人能在常人束手无策的情境中找到解决方案。还需补充一个限定条件:我们需排除那些依靠内部信息做出决策的情况。[3]除此之外,我认为过度细化定义反而会导致误解。 也无需过度细化。这个简单解释预测(或至少符合)关于智慧与智力区别的两种传统说法。人类问题是最常见的类型,因此擅长解决此类问题是保持高平均值的关键。高平均值主要依赖经验积累,而突出的峰值则需要某些罕见的天赋特质——这似乎很自然:几乎人人都能学会游泳,但要成为奥运选手必须拥有特定体型。 这个解释也揭示了"智慧"概念难以捉摸的原因:它本就不存在。"智慧"确实有含义——指一个人通常能做出正确选择。但将这种能力归因于名为"智慧"的特质,并不意味着该特质真实存在。若"智慧"确有指涉,它其实是自律、经验、同理心等各类特质的集合体。[4] 同理,尽管"智力"确有含义,但若执意寻找名为"智力"的单一实体就会陷入困境。无论其构成要素为何,它们都不全是与生俱来的。我们用"智力"作为能力指标:聪明人能理解常人难以掌握的事物。智力(以及智慧)可能存在某种先天倾向,但这种倾向本身并非智力。 人们常将智力视为先天特质,部分原因是测量者专注于最易量化的方面。先天特质显然比受经验影响的变量更便于研究,后者可能在研究过程中发生变化。问题在于我们将"智力"这个标签贴在了测量对象上。若测量的是先天特质,那它就不可能是智力。三岁孩童谈不上聪明。当我们形容某个孩子聪明时,其实是"比其他三岁孩子更聪明"的简略表达。 分野 指出智力倾向不等于智力本身或许显得咬文嚼字。但这个技术细节很重要,它提醒我们:正如可以变得更智慧,我们也能够变得更聪明。 令人不安的是,我们可能必须在两者之间做出选择。 如果智慧与智力是同一条曲线的平均值与峰值,那么当数据点减少时二者会趋同。若只有一个数据点,两者完全重合:平均值就是最大值。但随着数据点增多,智慧与智力逐渐分离。从历史来看,这条曲线上的数据点似乎在持续增加:人类能力正在越来越广泛的情境中接受检验。 孔子与苏格拉底时代,智慧、学识与智力的关系比如今更为紧密。"智慧"与"聪明"的区分是现代习惯。[5]这种区分源于二者的逐渐分离。随着知识日益专业化,曲线上的数据点不断增多,峰值与平均值的差异愈发明显,就像用更多像素呈现的数字图像。 一个后果是某些古老信条可能已经过时。至少我们需要重新审视它们究竟是培养智慧还是智力的方法。但随着智力与智慧渐行渐远,最显著的变化是我们可能必须做出取舍。我们或许无法同时优化两者。 社会似乎已选择了智力。我们不再像两千年前那样尊崇圣贤,转而崇拜天才。因为最初那个区别有个相当残酷的推论:正如你可以聪明而不够智慧,你也可以智慧而不够聪明。后者听起来并不特别令人钦佩——就像詹姆斯·邦德,他在多数情境中游刃有余,但遇到数学问题就得求助于Q博士。 智力与智慧显然并非互斥。事实上,高平均值可能有助于支撑高峰值。但有理由相信发展到某个阶段必须做出选择。一个例证是那些绝顶聪明却常常缺乏智慧的人,在大众文化中这几乎成了规律而非例外。或许心不在焉的教授有其智慧之处,或比表面看起来更睿智,但绝非孔子或苏格拉底期望人们成为的那种智者。[6] 新篇 对孔子和苏格拉底而言,智慧、美德与幸福必然相关。智者知晓正确选择并始终践行;所谓正确选择必须符合道德;因此智者永远快乐,明白自己已竭尽所能。就我所知,古代哲学家鲜有异议。 "君子坦荡荡,小人长戚戚",孔子如是说。[7] 然而几年前我读到一位数学家的访谈,他说多数夜晚都带着未尽之事的不满足感入睡。[8]虽然中文与希腊语中译为"快乐"的词汇与当代含义不尽相同,但重叠程度足以构成矛盾。 这位数学家因不满足而成为小人吗?不,他只是从事着孔子时代罕见的职业。 人类知识似乎呈分形增长。一次次地,某些看似微小无趣的领域(甚至被当作实验误差),经仔细审视后竟包含着与此前全部知识等量的内容。自古至今爆发的若干分形芽体中,许多涉及新事物的发明与发现。比如数学曾是少数人兼职研究的领域,如今成为数千人的职业。在创造新事物的过程中,某些古老法则不再适用。 最近我花时间为人提供建议,发现古老法则依然有效:尽可能理解现状,根据经验给出最佳建议,然后无需忧虑,因你已全力以赴。但撰写文章时我却毫无这般从容。那时我充满焦虑:万一灵感枯竭怎么办?写作时,五个夜晚中有四次带着未完成的不满足感入睡。 提供建议与写作是本质不同的工作。当人们带着问题求助时,(通常)无需创新,只需权衡选项做出审慎选择。但"审慎"无法告诉我下一句该写什么——可能性空间过于庞大。 法官或军官等工作大多可由职责指引,但创造事物时职责无能为力。创造者依赖更不稳定的东西:灵感。与多数生活不稳定者相似,他们往往忧心忡忡而非心满意足。在这方面他们更像孔子时代的小人,随时可能因歉收(或暴政)陷入饥荒——只不过他们受制于自身想象力而非天气与官吏。 局限 于我而言,意识到不满足感或许正常已是种解脱。"成功者理应快乐"的观念有着数千年历史惯性。若我真有才能,为何缺乏胜利者应有的从容自信?但我现在相信,这就像赛跑者质问:"若我真是优秀运动员,为何如此疲惫?"优秀选手同样会疲惫,只是他们在更快的速度下才感到疲惫。 从事发明与发现工作的人处境与赛跑者相同。他们永远无法做到最好,因为可能性没有上限。最接近的方法是与他人比较。但成就越高,这种方法就越失效。本科生发表论文便自觉是明星。但对领域顶尖者而言,优秀的标准何在?赛跑者至少可与同场竞技者比较;赢得奥运金牌后,即便认为自己还能更快,也能感到满足。但小说家又当如何? 相反,若你的工作是面对问题并在有限选项中抉择,表现存在上限:每次都做出最佳选择。古代社会几乎所有工作皆属此类。农夫需判断衣物是否值得修补,国王需决定是否入侵邻国,但无人期待他们创新。理论上他们本可以——国王本可发明火器再入侵邻国。但实际上创新如此罕见,就像没人期待守门员进球。[9]实践中,似乎每种情境都存在正确决策,做出决策即完美完成任务,正如守门员力保球门不失即被视为完美表现。 在这样的世界里,智慧至高无上。[10]即便现在,多数人的工作仍是面对问题并选择最佳方案。但随着知识日益专业化,越来越多的工作需要创新,表现因而没有上限。相对于智慧,智力变得越来越重要,因为峰值存在的空间更大了。 配方 另一个表明我们可能必须在智力与智慧间做出选择的迹象,是二者培养方法的差异。智慧主要来自消除幼稚特质,而智力主要来自培育这些特质。 智慧配方(尤其是古代版本)往往具有矫正性质。要获得智慧,必须清除童年积累的思想杂质,只保留重要部分。自制力与经验都有此效果:分别消除与生俱来的随机偏见和成长环境造成的偏见。这虽非智慧的全部,却是重要组成部分。十二岁孩童脑中已存在智者拥有的许多认知,区别在于这些认知与大量随机垃圾混杂共存。 智力提升似乎需要通过解决难题来实现。就像通过锻炼增强肌肉,你需要通过练习发展智力。但这里不能有太多强制。任何纪律都无法取代真正的好奇心。因此培养智力需要识别性格中的某种倾向——对特定事物的兴趣偏好——并精心培育。你不是通过消除个性来成为真理的中立容器,而是选择某个特质,将其从幼苗培育成大树。 智者的智慧总是相似的,而聪明人的才智各有不同。 我们的教育传统大多以智慧为目标。因此学校效果不佳的原因之一,可能是试图用智慧配方培养智力。多数智慧配方包含服从成分。至少,学生应该听从老师教导。更极端的配方像新兵训练那样旨在打破个性——这绝非智力的培养之道。智慧来自谦卑,而培养智力或许需要某种对自身能力的高估(即便这种高估是错误的),因为这能激励持续努力。理想情况下,这种高估会持续到你意识到它的错误为止。 (晚年难以学习新技能的原因不仅在于大脑可塑性下降,更严峻的障碍可能是标准变得更高。) 我意识到这个话题很敏感。我并非主张教育首要目标是提升学生"自尊心"——这只会滋生懒惰。况且这骗不了孩子,至少骗不了聪明孩子。他们很早就明白人人获胜的比赛是场骗局。 教师需走钢丝:既要鼓励孩子独立思考,又不能对一切产出盲目赞赏。你必须成为优秀的观众:懂得欣赏,但不易被取悦。这需要大量工作。你必须充分掌握不同年龄段孩子的能力水平,才能判断何时应该感到惊喜。 这与传统教育配方背道而驰。传统上学生才是观众,教师不是;学生的任务不是创造,而是吸收规定内容。(某些大学用"recitation"(背诵)指代课程章节正是这种传统的化石。)这些古老传统的问题在于过分受到智慧配方的影响。 差异 我刻意为此文选用挑衅性标题——当然值得追求智慧。但理解智力与智慧的关系(尤其是二者日益扩大的鸿沟)至关重要。这样才能避免将适用于智慧的标准强加于智力。这两种"知道如何行事"的形态差异比多数人想象的更大。通往智慧之路需要纪律,通往智力之路则需要精挑细选的自我放纵。智慧具有普适性,智力则充满独特性。智慧带来平静,智力则常引致不满。 这点尤其值得铭记。一位物理学家朋友最近告诉我,他们系半数同事服用抗抑郁药物。如果我们承认某些工作中挫折感不可避免,或许能减轻其影响。或许我们能偶尔将其封存,而非任其与日常忧伤汇集成看似惊人的深潭。至少,我们可以避免因感到不满而更加不满。 若你感到精疲力竭,未必是你出了问题。也许只是因为你正在飞速奔跑。 注释 [1] 据说高斯十岁时被问到此题。当其他学生费力逐项相加时,他发现这些数字可组成50对和为101的组合(100+1,99+2等),只需将101乘以50即可得到答案5050。 [2] 另一种说法认为智力是解决问题的能力,智慧是运用这些方案的判断力。尽管这确实是智慧与智力的重要关系,但并非二者的区别。智慧在解决问题时同样有用,智力也能帮助决定如何运用解决方案。 [3] 评估智力与智慧时需排除某些知识。知道保险箱密码的人比不知道者更易打开它,但没人会认为这是智力或智慧的测试。 但知识与智慧(可能也包括智力)存在重叠。对人性的了解无疑是智慧的组成部分。那么界限何在? 或许解决方案是排除那些效用会突然下降的知识。比如法语能力在多数情境中有用,但若周围无人懂法语,其价值就骤降。而对虚荣心的理解其价值衰减更为平缓。 效用骤降的知识通常与其他知识关联甚少。这包括语言、保险箱密码等纯惯例,以及影星生日、如何区分1956与1957年款Studebaker汽车等"随机"事实。 [4] 寻求名为"智慧"的单一实体者被语法愚弄了。智慧不过是知道正确行事方式,而有助于此的特质数以百计。有些如无私可能来自空室冥想,有些如对人性的理解可能来自酒会狂欢。 认识到这点或有助于驱散许多人眼中智慧的神秘光环。这种神秘感主要来自寻找不存在的事物。历史上存在众多关于如何获得智慧的学派,原因在于它们关注的是智慧的不同组成部分。 本文使用"智慧"一词时,仅指那些帮助人们在各种情境中做出正确选择的特质集合。 [5] 即使在英语中,"intelligence"的现代含义也出现得意外地晚。其前身如"understanding"似乎含义更广。 [6] 当然,我们无法确定孔子与苏格拉底名下的言论多大程度反映其真实观点。我使用这些名字如同使用"荷马",指代那些被归名的言论的假设性作者。 [7] 《论语》述而第七篇第三十六章,冯译本。 某些译本用"平静"而非"快乐"。翻译难点在于当代英语使用者的"快乐"概念与许多古代社会不同。每种语言都有表达"诸事顺遂时的感受"的词汇,但不同文化对顺境的反应各异。我们像孩童般以微笑和大笑回应。但在更内敛或生活更艰苦的社会,反应可能是安静的满足。 [8] 可能是安德鲁·怀尔斯,但我不确定。若有人记得此类访谈,请不吝告知。 [9] 孔子自豪地宣称自己"述而不作"——只是准确传承古代传统。[《论语》述而第七篇第一章]如今我们很难体会在文字出现前,记忆和传承群体积累的知识是何等重要职责。即便在孔子时代,这似乎仍是学者的首要责任。 [10] 古代哲学对智慧的偏重可能被夸大,因为在希腊和中国,许多早期哲学家(包括孔子和柏拉图)自视为执政者的教师,因此 disproportionately 地思考此类问题。少数创新者如故事讲述者,可能被视为可忽略的离群值。 致谢 Trevor Blackwell、Sarah Harlin、Jessica Livingston和Robert Morris审阅了本文草稿。
January 2007 _(Foreword to Jessica Livingston'sFounders at Work.)_ Apparently sprinters reach their highest speed right out of the blocks, and spend the rest of the race slowing down. The winners slow down the least. It's that way with most startups too. The earliest phase is usually the most productive. That's when they have the really big ideas. Imagine what Apple was like when 100% of its employees were either Steve Jobs or Steve Wozniak. The striking thing about this phase is that it's completely different from most people's idea of what business is like. If you looked in people's heads (or stock photo collections) for images representing "business," you'd get images of people dressed up in suits, groups sitting around conference tables looking serious, Powerpoint presentations, people producing thick reports for one another to read. Early stage startups are the exact opposite of this. And yet they're probably the most productive part of the whole economy. Why the disconnect? I think there's a general principle at work here: the less energy people expend on performance, the more they expend on appearances to compensate. More often than not the energy they expend on seeming impressive makes their actual performance worse. A few years ago I read an article in which a car magazine modified the "sports" model of some production car to get the fastest possible standing quarter mile. You know how they did it? They cut off all the crap the manufacturer had bolted onto the car to make it _look_ fast. Business is broken the same way that car was. The effort that goes into looking productive is not merely wasted, but actually makes organizations less productive. Suits, for example. Suits do not help people to think better. I bet most executives at big companies do their best thinking when they wake up on Sunday morning and go downstairs in their bathrobe to make a cup of coffee.
(本文为杰西卡·利文斯顿所著《创业者》一书序言)
短跑运动员往往在起跑瞬间就达到最高速度,随后全程都在减速,获胜者不过是减速幅度最小的人。大多数初创企业也是如此——早期阶段通常最具创造力,那时会诞生真正伟大的想法。想象一下苹果公司初创时的场景:全体员工只有史蒂夫·乔布斯和史蒂夫·沃兹尼亚克两人。
That's when you have ideas. Just imagine what a company would be like if people could think that well at work. People do in startups, at least some of the time. (Half the time you're in a panic because your servers are on fire, but the other half you're thinking as deeply as most people only get to sitting alone on a Sunday morning.) Ditto for most of the other differences between startups and what passes for productivity in big companies. And yet conventional ideas of professionalism have such an iron grip on our minds that even startup founders are affected by them. In our startup, when outsiders came to visit we tried hard to seem "professional." We'd clean up our offices, wear better clothes, try to arrange that a lot of people were there during conventional office hours. In fact, programming didn't get done by well-dressed people at clean desks during office hours. It got done by badly dressed people (I was notorious for programmming wearing just a towel) in offices strewn with junk at 2 in the morning. But no visitor would understand that. Not even investors, who are supposed to be able to recognize real productivity when they see it. Even we were affected by the conventional wisdom. We thought of ourselves as impostors, succeeding despite being totally unprofessional. It was as if we'd created a Formula 1 car but felt sheepish because it didn't look like a car was supposed to look. In the car world, there are at least some people who know that a high performance car looks like a Formula 1 racecar, not a sedan with giant rims and a fake spoiler bolted to the trunk. Why not in business? Probably because startups are so small. The really dramatic growth happens when a startup only has three or four people, so only three or four people see that, whereas tens of thousands see business as it's practiced by Boeing or Philip Morris.
这个阶段最惊人的特质在于,它与大众对商业的认知截然不同。若在人们脑海中(或图库中)搜寻"商业"的意象,你会看到西装革履的人群、会议桌前正襟危坐的团队、PPT演示文稿,以及人们相互递交厚沓报告的场景。早期初创企业完全是这些形象的反面,然而它们很可能是整个经济体系中最富生产力的部分。
为何存在这种认知偏差?我认为存在一个普遍规律:人们在实质绩效上投入的精力越少,就会在表面功夫上耗费越多来弥补。这些用于塑造光鲜形象的努力,往往反而会损害实际成效。多年前我曾读到一个汽车杂志的案例:编辑们为让某款量产"运动版"车型实现最快零四加速成绩,你知道他们做了什么吗?他们拆掉了厂商为营造"速度感"而安装的所有华而不实的配件。
商业世界就像那辆被改装过的车一样出了问题。那些用于营造高效假象的努力不仅徒劳无功,更会真正削弱组织效能。以西装为例——笔挺的西装无助于提升思考质量。我敢打赌,大公司高管们最高效的思考时刻,往往是周日早晨穿着睡袍下楼煮咖啡的时光。那才是灵光乍现的时刻。试想如果人们在工作时也能保持这种思维状态会怎样?初创企业成员确实能做到这点——至少在某些时刻(虽然另一半时间你会因服务器宕机而焦头烂额,但剩余时间里你的思考深度堪比普通人周日独坐时的冥想状态)。
This book can help fix that problem, by showing everyone what, till now, only a handful people got to see: what happens in the first year of a startup. This is what real productivity looks like. This is the Formula 1 racecar. It looks weird, but it goes fast. Of course, big companies won't be able to do everything these startups do. In big companies there's always going to be more politics, and less scope for individual decisions. But seeing what startups are really like will at least show other organizations what to aim for. The time may soon be coming when instead of startups trying to seem more corporate, corporations will try to seem more like startups. That would be a good thing. Japanese Translation.
初创企业与所谓"大公司高效模式"的其他差异同样如此。然而传统职业理念对我们的桎梏如此之深,连创业者都难以幸免。在我们初创时期,每当有外人来访,我们总会竭力展现"专业"形象:打扫办公室、换上正装、确保常规办公时段座无虚席。但事实上,编程工作从来不是由衣着光鲜的人在整洁工位上完成的,而是由穿着邋遢的人(我曾因裹着浴巾编程而闻名)在凌晨两点堆满杂物的办公室里实现的。可惜没有访客能理解这点——就连本该慧眼识珠的投资人也未能免俗。我们甚至也被这种传统思维影响,自视为凭借完全不专业的运作却侥幸成功的冒牌货,就像造出了F1赛车却因不符合传统汽车外观而自惭形秽。
汽车领域至少还有部分人明白,高性能车的标杆是F1赛车,而非装着巨型轮毂和夸张尾翼的改装轿车。为何商业领域就缺乏这种认知?或许因为初创企业规模太小——真正的爆发式增长往往发生在团队仅有三四人时,而见证者不过三四人;相比之下,波音或菲利普莫里斯等企业的运作模式却被数十万人看在眼里。
本书将改变这种认知困境,向大众揭示迄今为止只有极少数人目睹的真相:初创企业第一年的真实状态。这才是高效能的本来面目——这就是F1赛车。它看起来怪异,但速度惊人。
[](http://www.amazon.com/gp/product/1590597141)| | Founders at Work There can't be more than a couple thousand people who know first-hand what happens in the first month of a successful startup. Jessica Livingston got them to tell us. So despite the interview format, this is really a how-to book. It is probably the single most valuable book a startup founder could read.
当然,大企业无法全盘复制初创企业的做法。大公司永远存在更多政治博弈,个人决策空间也更有限。但了解初创企业的真实样貌,至少能为其他组织指明方向。或许很快我们将迎来这样的时代:不再是初创企业模仿大公司做派,而是大公司开始学习初创企业的气质。那将是件好事。
[](http://www.amazon.com/gp/product/1590597141)| | Founders at Work There can't be more than a couple thousand people who know first-hand what happens in the first month of a successful startup. Jessica Livingston got them to tell us. So despite the interview format, this is really a how-to book. It is probably the single most valuable book a startup founder could read.
[](https://s.turbifycdn.com/aah/paulgraham/how-art-can-be-good-11.gif) December 2006 I grew up believing that taste is just a matter of personal preference. Each person has things they like, but no one's preferences are any better than anyone else's. There is no such thing as _good_ taste. Like a lot of things I grew up believing, this turns out to be false, and I'm going to try to explain why. One problem with saying there's no such thing as good taste is that it also means there's no such thing as good art. If there were good art, then people who liked it would have better taste than people who didn't. So if you discard taste, you also have to discard the idea of art being good, and artists being good at making it. It was pulling on that thread that unravelled my childhood faith in relativism. When you're trying to make things, taste becomes a practical matter. You have to decide what to do next. Would it make the painting better if I changed that part? If there's no such thing as better, it doesn't matter what you do. In fact, it doesn't matter if you paint at all. You could just go out and buy a ready-made blank canvas. If there's no such thing as good, that would be just as great an achievement as the ceiling of the Sistine Chapel. Less laborious, certainly, but if you can achieve the same level of performance with less effort, surely that's more impressive, not less. Yet that doesn't seem quite right, does it? Audience I think the key to this puzzle is to remember that art has an audience. Art has a purpose, which is to interest its audience. Good art (like good anything) is art that achieves its purpose particularly well. The meaning of "interest" can vary. Some works of art are meant to shock, and others to please; some are meant to jump out at you, and others to sit quietly in the background.
[](https://s.turbifycdn.com/aah/paulgraham/how-art-can-be-good-11.gif)
我从小接受的教育是:品味只是个人偏好的问题。每个人都有自己喜欢的东西,但没有人比他人更高明。所谓“好品味”根本不存在。
和我成长过程中相信的许多事情一样,这被证明是错误的。我将尝试解释原因。
否认好品味的存在,意味着也必须否认好艺术的存在。如果存在好艺术,那么喜欢它的人就比不喜欢的人更有品味。因此,若抛弃品味的概念,就必须同时抛弃“艺术可以是好的”以及“艺术家可以擅长创作”的观念。
But all art has to work on an audience, and—here's the critical point—members of the audience share things in common. For example, nearly all humans find human faces engaging. It seems to be wired into us. Babies can recognize faces practically from birth. In fact, faces seem to have co-evolved with our interest in them; the face is the body's billboard. So all other things being equal, a painting with faces in it will interest people more than one without. [1] One reason it's easy to believe that taste is merely personal preference is that, if it isn't, how do you pick out the people with better taste? There are billions of people, each with their own opinion; on what grounds can you prefer one to another? [2] But if audiences have a lot in common, you're not in a position of having to choose one out of a random set of individual biases, because the set isn't random. All humans find faces engaging—practically by definition: face recognition is in our DNA. And so having a notion of good art, in the sense of art that does its job well, doesn't require you to pick out a few individuals and label their opinions as correct. No matter who you pick, they'll find faces engaging. Of course, space aliens probably wouldn't find human faces engaging. But there might be other things they shared in common with us. The most likely source of examples is math. I expect space aliens would agree with us most of the time about which of two proofs was better. Erdos thought so. He called a maximally elegant proof one out of God's book, and presumably God's book is universal. [3] Once you start talking about audiences, you don't have to argue simply that there are or aren't standards of taste. Instead tastes are a series of concentric rings, like ripples in a pond.
正是这条线索,解开了我童年时对相对主义的信仰。当你尝试创作时,品味就成了一个实际问题。你必须决定下一步怎么做。修改这部分会让画作更好吗?如果“更好”不存在,你的选择就毫无意义。事实上,你甚至不必画画——直接买一张现成的空白画布就行。如果“好”不存在,这与西斯廷教堂天顶画将是同等伟大的成就。后者当然更费工夫,但如果能以更少努力达到同等水平,岂不是更令人印象深刻?
但这似乎不太对劲,不是吗?
我认为解开这个谜题的关键在于:艺术需要观众。艺术的目的是吸引观众。好艺术(如同任何好事物)就是能出色达成这一目的的艺术。“吸引”的方式可以多样:有些作品旨在震撼,有些旨在取悦;有些咄咄逼人,有些静默如背景。但所有艺术都需要作用于观众,而关键在于——观众之间存在共性。
例如,几乎所有人类都会被面孔吸引。这似乎是我们的本能。婴儿几乎从出生就能识别面孔。事实上,面孔的进化可能正与我们对它的兴趣相关——面部是身体的广告牌。因此,在其他条件相同时,包含面孔的画作会比没有的更吸引人[1]。
There are some things that will appeal to you and your friends, others that will appeal to most people your age, others that will appeal to most humans, and perhaps others that would appeal to most sentient beings (whatever that means). The picture is slightly more complicated than that, because in the middle of the pond there are overlapping sets of ripples. For example, there might be things that appealed particularly to men, or to people from a certain culture. If good art is art that interests its audience, then when you talk about art being good, you also have to say for what audience. So is it meaningless to talk about art simply being good or bad? No, because one audience is the set of all possible humans. I think that's the audience people are implicitly talking about when they say a work of art is good: they mean it would engage any human. [4] And that is a meaningful test, because although, like any everyday concept, "human" is fuzzy around the edges, there are a lot of things practically all humans have in common. In addition to our interest in faces, there's something special about primary colors for nearly all of us, because it's an artifact of the way our eyes work. Most humans will also find images of 3D objects engaging, because that also seems to be built into our visual perception. [5] And beneath that there's edge-finding, which makes images with definite shapes more engaging than mere blur. Humans have a lot more in common than this, of course. My goal is not to compile a complete list, just to show that there's some solid ground here. People's preferences aren't random.
人们容易相信品味仅是个人偏好,因为若非如此,如何判定谁的品味更好?地球上有数十亿人,各持己见,凭什么认为某些人更高明?[2]
但如果观众存在大量共性,你就不必在随机个体偏见中做选择,因为这些偏见并非完全随机。所有人类都会被面孔吸引——这几乎是定义性的:面孔识别刻在我们的DNA里。因此,认为存在“好艺术”(即能有效达成目的的艺术),并不需要你指定某些人的意见为“正确”。无论选择谁,他们都会对面孔产生兴趣。
当然,外星人可能不会对人类面孔感兴趣。但他们或许与我们存在其他共性。最可能的例子来自数学领域。我认为外星人在多数情况下会与我们判断一致:两个数学证明中哪个更优雅。埃尔德什就持此观点,他将极致优雅的证明称为“来自上帝之书”——而上帝之书理应是普世的[3]。
一旦引入观众视角,关于品味标准的争论就不再是非此即彼。品味如同池塘中的涟漪,呈现为一系列同心圆:有些作品吸引你和朋友,有些吸引同龄人,有些吸引大多数人类,还有些可能吸引大多数有知觉的生命(无论这意味着什么)。
So an artist working on a painting and trying to decide whether to change some part of it doesn't have to think "Why bother? I might as well flip a coin." Instead he can ask "What would make the painting more interesting to people?" And the reason you can't equal Michelangelo by going out and buying a blank canvas is that the ceiling of the Sistine Chapel is more interesting to people. A lot of philosophers have had a hard time believing it was possible for there to be objective standards for art. It seemed obvious that beauty, for example, was something that happened in the head of the observer, not something that was a property of objects. It was thus "subjective" rather than "objective." But in fact if you narrow the definition of beauty to something that works a certain way on humans, and you observe how much humans have in common, it turns out to be a property of objects after all. You don't have to choose between something being a property of the subject or the object if subjects all react similarly. Being good art is thus a property of objects as much as, say, being toxic to humans is: it's good art if it consistently affects humans in a certain way. Error So could we figure out what the best art is by taking a vote? After all, if appealing to humans is the test, we should be able to just ask them, right? Well, not quite. For products of nature that might work. I'd be willing to eat the apple the world's population had voted most delicious, and I'd probably be willing to visit the beach they voted most beautiful, but having to look at the painting they voted the best would be a crapshoot. Man-made stuff is different. For one thing, artists, unlike apple trees, often deliberately try to trick us. Some tricks are quite subtle. For example, any work of art sets expectations by its level of finish. You don't expect photographic accuracy in something that looks like a quick sketch.
实际情况更复杂些,因为池塘中央存在重叠的涟漪。例如,某些作品可能特别吸引男性,或特定文化背景的人群。
如果好艺术是能吸引观众的艺术,那么谈论艺术优劣时就必须明确“对谁而言”。那么,单纯说艺术“好”或“坏”是否无意义?并非如此,因为存在一个默认观众群体——全人类。当人们说某件艺术品“好”时,隐含的评判标准是:它能吸引任何人类[4]。
这是一个有意义的测试。尽管“人类”这个概念边缘模糊(如同所有日常概念),但人类之间存在大量共性。除了对面孔的兴趣,三原色对几乎所有人都有特殊意义——这是人类视觉机制的产物。多数人也会被三维物体的图像吸引,因为这同样植根于我们的视觉感知[5]。更深层的是边缘检测机制,这使得轮廓分明的图像比模糊影像更具吸引力。
当然,人类的共同点远不止于此。我的目标不是穷尽列举,而是证明这里存在坚实基础。人们的偏好并非随机。因此,画家在修改作品时不必想“何必纠结?不如抛硬币”,而可以问“怎样能让画作更吸引人?”你无法通过购买空白画布比肩米开朗基罗,正是因为西斯廷天顶画对人类更具吸引力。
So one widely used trick, especially among illustrators, is to intentionally make a painting or drawing look like it was done faster than it was. The average person looks at it and thinks: how amazingly skillful. It's like saying something clever in a conversation as if you'd thought of it on the spur of the moment, when in fact you'd worked it out the day before. Another much less subtle influence is brand. If you go to see the Mona Lisa, you'll probably be disappointed, because it's hidden behind a thick glass wall and surrounded by a frenzied crowd taking pictures of themselves in front of it. At best you can see it the way you see a friend across the room at a crowded party. The Louvre might as well replace it with copy; no one would be able to tell. And yet the Mona Lisa is a small, dark painting. If you found people who'd never seen an image of it and sent them to a museum in which it was hanging among other paintings with a tag labelling it as a portrait by an unknown fifteenth century artist, most would walk by without giving it a second look. For the average person, brand dominates all other factors in the judgement of art. Seeing a painting they recognize from reproductions is so overwhelming that their response to it as a painting is drowned out. And then of course there are the tricks people play on themselves. Most adults looking at art worry that if they don't like what they're supposed to, they'll be thought uncultured. This doesn't just affect what they claim to like; they actually make themselves like things they're supposed to. That's why you can't just take a vote. Though appeal to people is a meaningful test, in practice you can't measure it, just as you can't find north using a compass with a magnet sitting next to it. There are sources of error so powerful that if you take a vote, all you're measuring is the error. We can, however, approach our goal from another direction, by using ourselves as guinea pigs.
许多哲学家难以相信艺术存在客观标准。美似乎显然是观察者头脑中的体验,而非物体的属性,因此是“主观”而非“客观”的。但事实上,如果将美定义为对人类产生特定效果的事物,并观察人类的高度共性,美就确实成为了物体的属性。当所有主体反应相似时,就无需在“属于主体”或“属于客体”间做选择。艺术之“好”如同“对人类有毒”一样是物体的属性:如果它能持续以特定方式影响人类,它就是好艺术。
那么,我们能否通过投票找出最佳艺术?毕竟,如果吸引力是标准,直接询问人类不就行了?
不完全如此。对自然产物这或许可行。我愿意品尝全球票选最美味的苹果,也愿意游览票选最美丽的海滩,但被迫观看票选最佳画作可能纯属碰运气。
人造物则不同。首先,与苹果树不同,艺术家常刻意愚弄我们。有些手段相当微妙。例如,任何艺术品都通过完成度设定预期——你不会期待速写具有照片级精度。因此,插画师常用技巧是故意让作品显得比实际创作更快。普通人看到会想:“技艺真惊人!”这就像在谈话中看似即兴说出妙语,实则提前精心准备。
You're human. If you want to know what the basic human reaction to a piece of art would be, you can at least approach that by getting rid of the sources of error in your own judgements. For example, while anyone's reaction to a famous painting will be warped at first by its fame, there are ways to decrease its effects. One is to come back to the painting over and over. After a few days the fame wears off, and you can start to see it as a painting. Another is to stand close. A painting familiar from reproductions looks more familiar from ten feet away; close in you see details that get lost in reproductions, and which you're therefore seeing for the first time. There are two main kinds of error that get in the way of seeing a work of art: biases you bring from your own circumstances, and tricks played by the artist. Tricks are straightforward to correct for. Merely being aware of them usually prevents them from working. For example, when I was ten I used to be very impressed by airbrushed lettering that looked like shiny metal. But once you study how it's done, you see that it's a pretty cheesy trick—one of the sort that relies on pushing a few visual buttons really hard to temporarily overwhelm the viewer. It's like trying to convince someone by shouting at them. The way not to be vulnerable to tricks is to explicitly seek out and catalog them. When you notice a whiff of dishonesty coming from some kind of art, stop and figure out what's going on. When someone is obviously pandering to an audience that's easily fooled, whether it's someone making shiny stuff to impress ten year olds, or someone making conspicuously avant-garde stuff to impress would-be intellectuals, learn how they do it. Once you've seen enough examples of specific types of tricks, you start to become a connoisseur of trickery in general, just as professional magicians are. What counts as a trick? Roughly, it's something done with contempt for the audience.
另一个更直白的影响因素是品牌。如果你去看《蒙娜丽莎》,很可能会失望——它藏在厚玻璃后,被疯狂自拍的人群包围,你最多像在拥挤派对上远远望见朋友。卢浮宫大可用复制品替代,无人能分辨。而《蒙娜丽莎》本身是幅小而暗的画。如果让从未见过它的人进入挂有该画的博物馆(标签注明为“15世纪无名艺术家肖像”),多数人会径直走过。
对普通人而言,品牌主导着艺术判断。认出某幅名画的复制品会完全压倒其作为画作本身的感受力。
此外还有人们的自我欺骗。多数成年观众担心,如果不对“该喜欢”的作品表示欣赏,会被认为没文化。这不仅影响他们声称的喜好,实际上也改变了真实喜好。
因此不能简单依赖投票。尽管“吸引人类”是有意义的测试,但实践中无法准确测量——就像不能用旁边放着磁铁的指南针找北方。误差源如此强大,投票结果往往只反映误差本身。
For example, the guys designing Ferraris in the 1950s were probably designing cars that they themselves admired. Whereas I suspect over at General Motors the marketing people are telling the designers, "Most people who buy SUVs do it to seem manly, not to drive off-road. So don't worry about the suspension; just make that sucker as big and tough-looking as you can." [6] I think with some effort you can make yourself nearly immune to tricks. It's harder to escape the influence of your own circumstances, but you can at least move in that direction. The way to do it is to travel widely, in both time and space. If you go and see all the different kinds of things people like in other cultures, and learn about all the different things people have liked in the past, you'll probably find it changes what you like. I doubt you could ever make yourself into a completely universal person, if only because you can only travel in one direction in time. But if you find a work of art that would appeal equally to your friends, to people in Nepal, and to the ancient Greeks, you're probably onto something. My main point here is not how to have good taste, but that there can even be such a thing. And I think I've shown that. There is such a thing as good art. It's art that interests its human audience, and since humans have a lot in common, what interests them is not random. Since there's such a thing as good art, there's also such a thing as good taste, which is the ability to recognize it. If we were talking about the taste of apples, I'd agree that taste is just personal preference. Some people like certain kinds of apples and others like other kinds, but how can you say that one is right and the other wrong? [7] The thing is, art isn't apples. Art is man-made. It comes with a lot of cultural baggage, and in addition the people who make it often try to trick us.
不过,我们可以换种方式接近目标:以自身为实验对象。你是人类。若想了解人类对艺术的基本反应,至少可以通过消除个人判断中的误差源来逼近答案。
例如,虽然人们对名画的初始反应会被其声名扭曲,但有方法减弱这种影响。一是反复观看——几天后名声效应消退,你开始将其视为单纯画作。二是近距离观察——通过复制品熟悉的画作,在十英尺外看起来更“像”;贴近看时,复制品中丢失的细节会首次呈现。
阻碍艺术欣赏的误差主要有两类:个人境遇带来的偏见,以及艺术家的伎俩。后者较易纠正——意识到它们的存在通常就能免疫。例如,我十岁时曾对看起来像闪亮金属的喷绘字母印象深刻。但一旦了解技法,就会发现这只是拙劣把戏——通过强烈刺激某些视觉按钮暂时征服观众,如同靠吼叫说服他人。
抵御伎俩的方法是主动识别并归类。当感受到某类艺术的虚伪气息时,停下来分析其机制。无论是用闪亮物品吸引十岁孩童,还是用标新立异打动伪知识分子,都要学习他们的手法。见识足够多特定伎俩后,你会成为欺骗手段的鉴赏家,如同职业魔术师。
Most people's judgement of art is dominated by these extraneous factors; they're like someone trying to judge the taste of apples in a dish made of equal parts apples and jalapeno peppers. All they're tasting is the peppers. So it turns out you can pick out some people and say that they have better taste than others: they're the ones who actually taste art like apples. Or to put it more prosaically, they're the people who (a) are hard to trick, and (b) don't just like whatever they grew up with. If you could find people who'd eliminated all such influences on their judgement, you'd probably still see variation in what they liked. But because humans have so much in common, you'd also find they agreed on a lot. They'd nearly all prefer the ceiling of the Sistine Chapel to a blank canvas. Making It I wrote this essay because I was tired of hearing "taste is subjective" and wanted to kill it once and for all. Anyone who makes things knows intuitively that's not true. When you're trying to make art, the temptation to be lazy is as great as in any other kind of work. Of course it matters to do a good job. And yet you can see how great a hold "taste is subjective" has even in the art world by how nervous it makes people to talk about art being good or bad. Those whose jobs require them to judge art, like curators, mostly resort to euphemisms like "significant" or "important" or (getting dangerously close) "realized." [8] I don't have any illusions that being able to talk about art being good or bad will cause the people who talk about it to have anything more useful to say. Indeed, one of the reasons "taste is subjective" found such a receptive audience is that, historically, the things people have said about good taste have generally been such nonsense. It's not for the people who talk about art that I want to free the idea of good art, but for those who make it.
什么是“伎俩”?粗略地说,是带着对观众的轻蔑所采取的手段。例如,1950年代设计法拉利的人可能真心欣赏自己的作品;而在通用汽车,市场部或许告诉设计师:“买SUV的人是为彰显男子气概而非越野——别管悬挂系统,只管把车做得又大又威猛。”[6]
通过努力,你几乎能完全免疫伎俩。摆脱自身境遇影响更难,但至少可以努力。方法是广泛“游历”——跨越时空。见识不同文化中的喜好,了解历史上的审美变迁,这很可能改变你的品味。虽然不可能成为完全“普世”的人(毕竟时间单向流动),但如果你发现某件作品能同时吸引朋友、尼泊尔人和古希腊人,那它很可能确有价值。
我的核心观点不是“如何拥有好品味”,而是“好品味可能存在”。我认为已证明这点:好艺术确实存在——它能吸引人类观众;而由于人类的共性,其吸引力并非随机。既然存在好艺术,也就存在好品味——即识别好艺术的能力。
如果讨论的是苹果口味,我会同意品味纯属个人偏好——有人喜欢这类苹果,有人喜欢那类,谁能判定对错?[7]
Right now, ambitious kids going to art school run smack into a brick wall. They arrive hoping one day to be as good as the famous artists they've seen in books, and the first thing they learn is that the concept of good has been retired. Instead everyone is just supposed to explore their own personal vision. [9] When I was in art school, we were looking one day at a slide of some great fifteenth century painting, and one of the students asked "Why don't artists paint like that now?" The room suddenly got quiet. Though rarely asked out loud, this question lurks uncomfortably in the back of every art student's mind. It was as if someone had brought up the topic of lung cancer in a meeting within Philip Morris. "Well," the professor replied, "we're interested in different questions now." He was a pretty nice guy, but at the time I couldn't help wishing I could send him back to fifteenth century Florence to explain in person to Leonardo & Co. how we had moved beyond their early, limited concept of art. Just imagine that conversation. In fact, one of the reasons artists in fifteenth century Florence made such great things was that they believed you could make great things. [10] They were intensely competitive and were always trying to outdo one another, like mathematicians or physicists today—maybe like anyone who has ever done anything really well. The idea that you could make great things was not just a useful illusion. They were actually right. So the most important consequence of realizing there can be good art is that it frees artists to try to make it. To the ambitious kids arriving at art school this year hoping one day to make great things, I say: don't believe it when they tell you this is a naive and outdated ambition.
但艺术不是苹果。艺术是人造的,承载着文化包袱,创作者还常试图欺骗我们。多数人的艺术判断受这些外在因素主导——就像在苹果与辣椒等量混合的菜肴中评判苹果味道,尝到的全是辣椒。因此,确实可以指出某些人拥有更好的品味:他们是真正能尝到“苹果”的人。
更直白地说,这些人(a)不易被欺骗,(b)不囿于成长环境的影响。如果找到完全摆脱这些干扰的人,他们的喜好仍会有差异。但由于人类的深刻共性,他们在许多方面也会一致——几乎所有人都会选择西斯廷天顶画而非空白画布。
我写此文是因为厌倦了“品味是主观的”这一论调,想彻底终结它。任何创作者都本能地知道这不真实。艺术创作中,懒惰的诱惑与其他工作一样强烈。当然要尽力做好。但“品味主观论”的影响力从艺术界谈论作品时的谨小慎微可见一斑——策展人等专业人士多用“重要”“有影响力”或(近乎冒险的)“完成度高”等委婉说法[8]。
我不幻想允许谈论艺术优劣会让评论更有价值。事实上,“品味主观论”盛行的历史原因之一,正是过去关于好品味的言论多为无稽之谈。
There is such a thing as good art, and if you try to make it, there are people who will notice. Notes [1] This is not to say, of course, that good paintings must have faces in them, just that everyone's visual piano has that key on it. There are situations in which you want to avoid faces, precisely because they attract so much attention. But you can see how universally faces work by their prevalence in advertising. [2] The other reason it's easy to believe is that it makes people feel good. To a kid, this idea is crack. In every other respect they're constantly being told that they have a lot to learn. But in this they're perfect. Their opinion carries the same weight as any adult's. You should probably question anything you believed as a kid that you'd want to believe this much. [3] It's conceivable that the elegance of proofs is quantifiable, in the sense that there may be some formal measure that turns out to coincide with mathematicians' judgements. Perhaps it would be worth trying to make a formal language for proofs in which those considered more elegant consistently came out shorter (perhaps after being macroexpanded or compiled). [4] Maybe it would be possible to make art that would appeal to space aliens, but I'm not going to get into that because (a) it's too hard to answer, and (b) I'm satisfied if I can establish that good art is a meaningful idea for human audiences. [5] If early abstract paintings seem more interesting than later ones, it may be because the first abstract painters were trained to paint from life, and their hands thus tended to make the kind of gestures you use in representing physical things. In effect they were saying "scaramara" instead of "uebfgbsb." [6] It's a bit more complicated, because sometimes artists unconsciously use tricks by imitating art that does. [7] I phrased this in terms of the taste of apples because if people can see the apples, they can be fooled.
我解放“好艺术”概念的目的,不是为评论者,而是为创作者[链接]。如今,怀揣抱负的艺术生刚入学就撞上南墙——他们期待有朝一日达到书中大师的水平,却首先被告知“好”的概念已被淘汰,每个人只需探索“个人视野”[9]。
我在艺术学院时,有次观看15世纪名画的幻灯片,一个学生问:“为什么现在没人这样画了?”教室瞬间寂静。尽管鲜少明言,这个问题萦绕在每个艺术生心头——就像在菲利普·莫里斯公司的会议上提起肺癌话题。
“呃,”教授回答,“我们现在关注不同的问题。”他是个好人,但当时我不禁想把他送回15世纪的佛罗伦萨,让他亲自向达芬奇们解释:我们已超越他们“陈旧狭隘”的艺术观——想象那场景吧。
事实上,15世纪佛罗伦萨艺术家能创造伟大作品的原因之一,正是他们相信伟大可以被创造[10]。他们激烈竞争,不断试图超越彼此,如同今天的数学家或物理学家——或许像所有成就卓越者一样。
When I was a kid most apples were a variety called Red Delicious that had been bred to look appealing in stores, but which didn't taste very good. [8] To be fair, curators are in a difficult position. If they're dealing with recent art, they have to include things in shows that they think are bad. That's because the test for what gets included in shows is basically the market price, and for recent art that is largely determined by successful businessmen and their wives. So it's not always intellectual dishonesty that makes curators and dealers use neutral-sounding language. [9] What happens in practice is that everyone gets really good at _talking_ about art. As the art itself gets more random, the effort that would have gone into the work goes instead into the intellectual sounding theory behind it. "My work represents an exploration of gender and sexuality in an urban context," etc. Different people win at that game. [10] There were several other reasons, including that Florence was then the richest and most sophisticated city in the world, and that they lived in a time before photography had (a) killed portraiture as a source of income and (b) made brand the dominant factor in the sale of art. Incidentally, I'm not saying that good art = fifteenth century European art. I'm not saying we should make what they made, but that we should work like they worked. There are fields now in which many people work with the same energy and honesty that fifteenth century artists did, but art is not one of them. Thanks to Trevor Blackwell, Jessica Livingston, and Robert Morris for reading drafts of this, and to Paul Watson for permission to use the image at the top.
| Japanese Translation | | | Simplified Chinese Translation.
“能创造伟大作品”并非有用的幻觉——他们确实正确。因此,认识到“好艺术可能存在”最重要的意义,是解放艺术家去追求它。对于今年入学的艺术生,我想说:当有人告诉你“创造伟大作品是天真的过时抱负”时,别相信。好艺术确实存在,如果你努力创造,总会有人发现。
注释 [1] 并非好画必须包含面孔,而是人人的“视觉键盘”上都有这个琴键。有时你需刻意避开面孔,正因其太引人注目。广告中面孔的普遍性印证了其效力。 [2] 另一易信原因是这让人感觉良好。对孩子而言,这如同毒品——其他方面总被告诫要学习,唯独此事他们“完美无缺”,意见与成人同等重要。对童年时你极度愿意相信的任何事,都该保持怀疑。 [3] 证明的优雅度或可量化——可能存在与数学家判断一致的形式化标准。或许值得创建一种证明语言,使更优雅的证明经宏展开或编译后更简短。 [4] 或许存在吸引外星人的艺术,但我不探讨,因为(a)太难回答;(b)若能证明对人类观众存在“好艺术”足矣。 [5] 早期抽象画比后期更有趣,可能因首批抽象画家受具象训练,手势自然保留物体表现习惯——如同说“scaramara”而非随机字母。 [6] 更复杂的是,艺术家有时通过模仿不自觉地使用伎俩。 [7] 以苹果为例是因为视觉会欺骗。我小时候多数苹果是“红元帅”——为货架吸引力培育,却口感不佳。 [8] 公平地说,策展人处境艰难。若涉及当代艺术,他们必须展出自认糟糕的作品——因为参展标准基本是市场价格,而当代艺术价格主要由富豪及其配偶决定。策展人和经销商使用中性语言不总是因为学术不诚实。 [9] 现实中,人人精于“谈论”艺术。随着艺术本身越发随机,本应用于创作的精力转入听起来高深的理论——“我的作品探索都市语境中的性别与性”等。这游戏自有赢家。 [10] 其他原因包括:佛罗伦萨当时是世界上最富庶和文明的城市;他们所处的时代尚未被摄影(a)终结肖像画收入来源,(b)使品牌成为艺术销售主导因素。
顺便说明,我并非将好艺术等同于15世纪欧洲艺术。我们不必复制他们的作品,但应效仿其工作方式。当今某些领域仍有人以同样能量和真诚创作,但艺术界不在其中。
致谢 感谢Trevor Blackwell、Jessica Livingston和Robert Morris阅读草稿,以及Paul Watson允许使用顶部图片。
Want to start a startup? Get funded by Y Combinator.
October 2006 In the Q & A period after a recent talk, someone asked what made startups fail. After standing there gaping for a few seconds I realized this was kind of a trick question. It's equivalent to asking how to make a startup succeed — if you avoid every cause of failure, you succeed — and that's too big a question to answer on the fly. Afterwards I realized it could be helpful to look at the problem from this direction. If you have a list of all the things you shouldn't do, you can turn that into a recipe for succeeding just by negating. And this form of list may be more useful in practice. It's easier to catch yourself doing something you shouldn't than always to remember to do something you should. [1] In a sense there's just one mistake that kills startups: not making something users want. If you make something users want, you'll probably be fine, whatever else you do or don't do. And if you don't make something users want, then you're dead, whatever else you do or don't do. So really this is a list of 18 things that cause startups not to make something users want. Nearly all failure funnels through that. 1\. Single Founder Have you ever noticed how few successful startups were founded by just one person? Even companies you think of as having one founder, like Oracle, usually turn out to have more. It seems unlikely this is a coincidence. What's wrong with having one founder? To start with, it's a vote of no confidence. It probably means the founder couldn't talk any of his friends into starting the company with him. That's pretty alarming, because his friends are the ones who know him best. But even if the founder's friends were all wrong and the company is a good bet, he's still at a disadvantage. Starting a startup is too hard for one person.
Even if you could do all the work yourself, you need colleagues to brainstorm with, to talk you out of stupid decisions, and to cheer you up when things go wrong. The last one might be the most important. The low points in a startup are so low that few could bear them alone. When you have multiple founders, esprit de corps binds them together in a way that seems to violate conservation laws. Each thinks "I can't let my friends down." This is one of the most powerful forces in human nature, and it's missing when there's just one founder. 2\. Bad Location Startups prosper in some places and not others. Silicon Valley dominates, then Boston, then Seattle, Austin, Denver, and New York. After that there's not much. Even in New York the number of startups per capita is probably a 20th of what it is in Silicon Valley. In towns like Houston and Chicago and Detroit it's too small to measure. Why is the falloff so sharp? Probably for the same reason it is in other industries. What's the sixth largest fashion center in the US? The sixth largest center for oil, or finance, or publishing? Whatever they are they're probably so far from the top that it would be misleading even to call them centers. It's an interesting question why cities become startup hubs, but the reason startups prosper in them is probably the same as it is for any industry: that's where the experts are. Standards are higher; people are more sympathetic to what you're doing; the kind of people you want to hire want to live there; supporting industries are there; the people you run into in chance meetings are in the same business. Who knows exactly how these factors combine to boost startups in Silicon Valley and squish them in Detroit, but it's clear they do from the number of startups per capita in each. 3\.
Marginal Niche Most of the groups that apply to Y Combinator suffer from a common problem: choosing a small, obscure niche in the hope of avoiding competition. If you watch little kids playing sports, you notice that below a certain age they're afraid of the ball. When the ball comes near them their instinct is to avoid it. I didn't make a lot of catches as an eight year old outfielder, because whenever a fly ball came my way, I used to close my eyes and hold my glove up more for protection than in the hope of catching it. Choosing a marginal project is the startup equivalent of my eight year old strategy for dealing with fly balls. If you make anything good, you're going to have competitors, so you may as well face that. You can only avoid competition by avoiding good ideas. I think this shrinking from big problems is mostly unconscious. It's not that people think of grand ideas but decide to pursue smaller ones because they seem safer. Your unconscious won't even let you think of grand ideas. So the solution may be to think about ideas without involving yourself. What would be a great idea for _someone else_ to do as a startup? 4\. Derivative Idea Many of the applications we get are imitations of some existing company. That's one source of ideas, but not the best. If you look at the origins of successful startups, few were started in imitation of some other startup. Where did they get their ideas? Usually from some specific, unsolved problem the founders identified. Our startup made software for making online stores. When we started it, there wasn't any; the few sites you could order from were hand-made at great expense by web consultants. We knew that if online shopping ever took off, these sites would have to be generated by software, so we wrote some. Pretty straightforward. It seems like the best problems to solve are ones that affect you personally.
Apple happened because Steve Wozniak wanted a computer, Google because Larry and Sergey couldn't find stuff online, Hotmail because Sabeer Bhatia and Jack Smith couldn't exchange email at work. So instead of copying the Facebook, with some variation that the Facebook rightly ignored, look for ideas from the other direction. Instead of starting from companies and working back to the problems they solved, look for problems and imagine the company that might solve them. [2] What do people complain about? What do you wish there was? 5\. Obstinacy In some fields the way to succeed is to have a vision of what you want to achieve, and to hold true to it no matter what setbacks you encounter. Starting startups is not one of them. The stick-to-your-vision approach works for something like winning an Olympic gold medal, where the problem is well-defined. Startups are more like science, where you need to follow the trail wherever it leads. So don't get too attached to your original plan, because it's probably wrong. Most successful startups end up doing something different than they originally intended — often so different that it doesn't even seem like the same company. You have to be prepared to see the better idea when it arrives. And the hardest part of that is often discarding your old idea. But openness to new ideas has to be tuned just right. Switching to a new idea every week will be equally fatal. Is there some kind of external test you can use? One is to ask whether the ideas represent some kind of progression. If in each new idea you're able to re-use most of what you built for the previous ones, then you're probably in a process that converges. Whereas if you keep restarting from scratch, that's a bad sign. Fortunately there's someone you can ask for advice: your users. If you're thinking about turning in some new direction and your users seem excited about it, it's probably a good bet. 6\.
Hiring Bad Programmers I forgot to include this in the early versions of the list, because nearly all the founders I know are programmers. This is not a serious problem for them. They might accidentally hire someone bad, but it's not going to kill the company. In a pinch they can do whatever's required themselves. But when I think about what killed most of the startups in the e-commerce business back in the 90s, it was bad programmers. A lot of those companies were started by business guys who thought the way startups worked was that you had some clever idea and then hired programmers to implement it. That's actually much harder than it sounds — almost impossibly hard in fact — because business guys can't tell which are the good programmers. They don't even get a shot at the best ones, because no one really good wants a job implementing the vision of a business guy. In practice what happens is that the business guys choose people they think are good programmers (it says here on his resume that he's a Microsoft Certified Developer) but who aren't. Then they're mystified to find that their startup lumbers along like a World War II bomber while their competitors scream past like jet fighters. This kind of startup is in the same position as a big company, but without the advantages. So how do you pick good programmers if you're not a programmer? I don't think there's an answer. I was about to say you'd have to find a good programmer to help you hire people. But if you can't recognize good programmers, how would you even do that? 7\. Choosing the Wrong Platform A related problem (since it tends to be done by bad programmers) is choosing the wrong platform. For example, I think a lot of startups during the Bubble killed themselves by deciding to build server-based applications on Windows. Hotmail was still running on FreeBSD for years after Microsoft bought it, presumably because Windows couldn't handle the load.
If Hotmail's founders had chosen to use Windows, they would have been swamped. PayPal only just dodged this bullet. After they merged with X.com, the new CEO wanted to switch to Windows — even after PayPal cofounder Max Levchin showed that their software scaled only 1% as well on Windows as Unix. Fortunately for PayPal they switched CEOs instead. Platform is a vague word. It could mean an operating system, or a programming language, or a "framework" built on top of a programming language. It implies something that both supports and limits, like the foundation of a house. The scary thing about platforms is that there are always some that seem to outsiders to be fine, responsible choices and yet, like Windows in the 90s, will destroy you if you choose them. Java applets were probably the most spectacular example. This was supposed to be the new way of delivering applications. Presumably it killed just about 100% of the startups who believed that. How do you pick the right platforms? The usual way is to hire good programmers and let them choose. But there is a trick you could use if you're not a programmer: visit a top computer science department and see what they use in research projects. 8\. Slowness in Launching Companies of all sizes have a hard time getting software done. It's intrinsic to the medium; software is always 85% done. It takes an effort of will to push through this and get something released to users. [3] Startups make all kinds of excuses for delaying their launch. Most are equivalent to the ones people use for procrastinating in everyday life. There's something that needs to happen first. Maybe. But if the software were 100% finished and ready to launch at the push of a button, would they still be waiting? One reason to launch quickly is that it forces you to actually _finish_ some quantum of work.
Nothing is truly finished till it's released; you can see that from the rush of work that's always involved in releasing anything, no matter how finished you thought it was. The other reason you need to launch is that it's only by bouncing your idea off users that you fully understand it. Several distinct problems manifest themselves as delays in launching: working too slowly; not truly understanding the problem; fear of having to deal with users; fear of being judged; working on too many different things; excessive perfectionism. Fortunately you can combat all of them by the simple expedient of forcing yourself to launch _something_ fairly quickly. 9\. Launching Too Early Launching too slowly has probably killed a hundred times more startups than launching too fast, but it is possible to launch too fast. The danger here is that you ruin your reputation. You launch something, the early adopters try it out, and if it's no good they may never come back. So what's the minimum you need to launch? We suggest startups think about what they plan to do, identify a core that's both (a) useful on its own and (b) something that can be incrementally expanded into the whole project, and then get that done as soon as possible. This is the same approach I (and many other programmers) use for writing software. Think about the overall goal, then start by writing the smallest subset of it that does anything useful. If it's a subset, you'll have to write it anyway, so in the worst case you won't be wasting your time. But more likely you'll find that implementing a working subset is both good for morale and helps you see more clearly what the rest should do. The early adopters you need to impress are fairly tolerant. They don't expect a newly launched product to do everything; it just has to do _something_. 10\. Having No Specific User in Mind You can't build things users like without understanding them.
I mentioned earlier that the most successful startups seem to have begun by trying to solve a problem their founders had. Perhaps there's a rule here: perhaps you create wealth in proportion to how well you understand the problem you're solving, and the problems you understand best are your own. [4] That's just a theory. What's not a theory is the converse: if you're trying to solve problems you don't understand, you're hosed. And yet a surprising number of founders seem willing to assume that someone, they're not sure exactly who, will want what they're building. Do the founders want it? No, they're not the target market. Who is? Teenagers. People interested in local events (that one is a perennial tarpit). Or "business" users. What business users? Gas stations? Movie studios? Defense contractors? You can of course build something for users other than yourself. We did. But you should realize you're stepping into dangerous territory. You're flying on instruments, in effect, so you should (a) consciously shift gears, instead of assuming you can rely on your intuitions as you ordinarily would, and (b) look at the instruments. In this case the instruments are the users. When designing for other people you have to be empirical. You can no longer guess what will work; you have to find users and measure their responses. So if you're going to make something for teenagers or "business" users or some other group that doesn't include you, you have to be able to talk some specific ones into using what you're making. If you can't, you're on the wrong track. 11\. Raising Too Little Money Most successful startups take funding at some point. Like having more than one founder, it seems a good bet statistically. How much should you take, though? Startup funding is measured in time. Every startup that isn't profitable (meaning nearly all of them, initially) has a certain amount of time left before the money runs out and they have to stop.
This is sometimes referred to as runway, as in "How much runway do you have left?" It's a good metaphor because it reminds you that when the money runs out you're going to be airborne or dead. Too little money means not enough to get airborne. What airborne means depends on the situation. Usually you have to advance to a visibly higher level: if all you have is an idea, a working prototype; if you have a prototype, launching; if you're launched, significant growth. It depends on investors, because until you're profitable that's who you have to convince. So if you take money from investors, you have to take enough to get to the next step, whatever that is. [5] Fortunately you have some control over both how much you spend and what the next step is. We advise startups to set both low, initially: spend practically nothing, and make your initial goal simply to build a solid prototype. This gives you maximum flexibility. 12\. Spending Too Much It's hard to distinguish spending too much from raising too little. If you run out of money, you could say either was the cause. The only way to decide which to call it is by comparison with other startups. If you raised five million and ran out of money, you probably spent too much. Burning through too much money is not as common as it used to be. Founders seem to have learned that lesson. Plus it keeps getting cheaper to start a startup. So as of this writing few startups spend too much. None of the ones we've funded have. (And not just because we make small investments; many have gone on to raise further rounds.) The classic way to burn through cash is by hiring a lot of people. This bites you twice: in addition to increasing your costs, it slows you down—so money that's getting consumed faster has to last longer. Most hackers understand why that happens; Fred Brooks explained it in The Mythical Man-Month.
We have three general suggestions about hiring: (a) don't do it if you can avoid it, (b) pay people with equity rather than salary, not just to save money, but because you want the kind of people who are committed enough to prefer that, and (c) only hire people who are either going to write code or go out and get users, because those are the only things you need at first. 13\. Raising Too Much Money It's obvious how too little money could kill you, but is there such a thing as having too much? Yes and no. The problem is not so much the money itself as what comes with it. As one VC who spoke at Y Combinator said, "Once you take several million dollars of my money, the clock is ticking." If VCs fund you, they're not going to let you just put the money in the bank and keep operating as two guys living on ramen. They want that money to go to work. [6] At the very least you'll move into proper office space and hire more people. That will change the atmosphere, and not entirely for the better. Now most of your people will be employees rather than founders. They won't be as committed; they'll need to be told what to do; they'll start to engage in office politics. When you raise a lot of money, your company moves to the suburbs and has kids. Perhaps more dangerously, once you take a lot of money it gets harder to change direction. Suppose your initial plan was to sell something to companies. After taking VC money you hire a sales force to do that. What happens now if you realize you should be making this for consumers instead of businesses? That's a completely different kind of selling. What happens, in practice, is that you don't realize that. The more people you have, the more you stay pointed in the same direction. Another drawback of large investments is the time they take. The time required to raise money grows with the amount. [7] When the amount rises into the millions, investors get very cautious.
VCs never quite say yes or no; they just engage you in an apparently endless conversation. Raising VC scale investments is thus a huge time sink — more work, probably, than the startup itself. And you don't want to be spending all your time talking to investors while your competitors are spending theirs building things. We advise founders who go on to seek VC money to take the first reasonable deal they get. If you get an offer from a reputable firm at a reasonable valuation with no unusually onerous terms, just take it and get on with building the company. [8] Who cares if you could get a 30% better deal elsewhere? Economically, startups are an all-or-nothing game. Bargain-hunting among investors is a waste of time. 14\. Poor Investor Management As a founder, you have to manage your investors. You shouldn't ignore them, because they may have useful insights. But neither should you let them run the company. That's supposed to be your job. If investors had sufficient vision to run the companies they fund, why didn't they start them? Pissing off investors by ignoring them is probably less dangerous than caving in to them. In our startup, we erred on the ignoring side. A lot of our energy got drained away in disputes with investors instead of going into the product. But this was less costly than giving in, which would probably have destroyed the company. If the founders know what they're doing, it's better to have half their attention focused on the product than the full attention of investors who don't. How hard you have to work on managing investors usually depends on how much money you've taken. When you raise VC-scale money, the investors get a great deal of control. If they have a board majority, they're literally your bosses.
In the more common case, where founders and investors are equally represented and the deciding vote is cast by neutral outside directors, all the investors have to do is convince the outside directors and they control the company. If things go well, this shouldn't matter. So long as you seem to be advancing rapidly, most investors will leave you alone. But things don't always go smoothly in startups. Investors have made trouble even for the most successful companies. One of the most famous examples is Apple, whose board made a nearly fatal blunder in firing Steve Jobs. Apparently even Google got a lot of grief from their investors early on. 15\. Sacrificing Users to (Supposed) Profit When I said at the beginning that if you make something users want, you'll be fine, you may have noticed I didn't mention anything about having the right business model. That's not because making money is unimportant. I'm not suggesting that founders start companies with no chance of making money in the hope of unloading them before they tank. The reason we tell founders not to worry about the business model initially is that making something people want is so much harder. I don't know why it's so hard to make something people want. It seems like it should be straightforward. But you can tell it must be hard by how few startups do it. Because making something people want is so much harder than making money from it, you should leave business models for later, just as you'd leave some trivial but messy feature for version 2. In version 1, solve the core problem. And the core problem in a startup is how to create wealth (= how much people want something x the number who want it), not how to convert that wealth into money. The companies that win are the ones that put users first. Google, for example. They made search work, then worried about how to make money from it.
And yet some startup founders still think it's irresponsible not to focus on the business model from the beginning. They're often encouraged in this by investors whose experience comes from less malleable industries. It _is_ irresponsible not to think about business models. It's just ten times more irresponsible not to think about the product. 16\. Not Wanting to Get Your Hands Dirty Nearly all programmers would rather spend their time writing code and have someone else handle the messy business of extracting money from it. And not just the lazy ones. Larry and Sergey apparently felt this way too at first. After developing their new search algorithm, the first thing they tried was to get some other company to buy it. Start a company? Yech. Most hackers would rather just have ideas. But as Larry and Sergey found, there's not much of a market for ideas. No one trusts an idea till you embody it in a product and use that to grow a user base. Then they'll pay big time. Maybe this will change, but I doubt it will change much. There's nothing like users for convincing acquirers. It's not just that the risk is decreased. The acquirers are human, and they have a hard time paying a bunch of young guys millions of dollars just for being clever. When the idea is embodied in a company with a lot of users, they can tell themselves they're buying the users rather than the cleverness, and this is easier for them to swallow. [9] If you're going to attract users, you'll probably have to get up from your computer and go find some. It's unpleasant work, but if you can make yourself do it you have a much greater chance of succeeding. In the first batch of startups we funded, in the summer of 2005, most of the founders spent all their time building their applications. But there was one who was away half the time talking to executives at cell phone companies, trying to arrange deals.
Can you imagine anything more painful for a hacker? [10] But it paid off, because this startup seems the most successful of that group by an order of magnitude. If you want to start a startup, you have to face the fact that you can't just hack. At least one hacker will have to spend some of the time doing business stuff. 17\. Fights Between Founders Fights between founders are surprisingly common. About 20% of the startups we've funded have had a founder leave. It happens so often that we've reversed our attitude to vesting. We still don't require it, but now we advise founders to vest so there will be an orderly way for people to quit. A founder leaving doesn't necessarily kill a startup, though. Plenty of successful startups have had that happen. [11] Fortunately it's usually the least committed founder who leaves. If there are three founders and one who was lukewarm leaves, big deal. If you have two and one leaves, or a guy with critical technical skills leaves, that's more of a problem. But even that is survivable. Blogger got down to one person, and they bounced back. Most of the disputes I've seen between founders could have been avoided if they'd been more careful about who they started a company with. Most disputes are not due to the situation but the people. Which means they're inevitable. And most founders who've been burned by such disputes probably had misgivings, which they suppressed, when they started the company. Don't suppress misgivings. It's much easier to fix problems before the company is started than after. So don't include your housemate in your startup because he'd feel left out otherwise. Don't start a company with someone you dislike because they have some skill you need and you worry you won't find anyone else. The people are the most important ingredient in a startup, so don't compromise there. 18\. A Half-Hearted Effort The failed startups you hear most about are the spectacular flameouts.
Those are actually the elite of failures. The most common type is not the one that makes spectacular mistakes, but the one that doesn't do much of anything — the one we never even hear about, because it was some project a couple guys started on the side while working on their day jobs, but which never got anywhere and was gradually abandoned. Statistically, if you want to avoid failure, it would seem like the most important thing is to quit your day job. Most founders of failed startups don't quit their day jobs, and most founders of successful ones do. If startup failure were a disease, the CDC would be issuing bulletins warning people to avoid day jobs. Does that mean you should quit your day job? Not necessarily. I'm guessing here, but I'd guess that many of these would-be founders may not have the kind of determination it takes to start a company, and that in the back of their minds, they know it. The reason they don't invest more time in their startup is that they know it's a bad investment. [12] I'd also guess there's some band of people who could have succeeded if they'd taken the leap and done it full-time, but didn't. I have no idea how wide this band is, but if the winner/borderline/hopeless progression has the sort of distribution you'd expect, the number of people who could have made it, if they'd quit their day job, is probably an order of magnitude larger than the number who do make it. [13] If that's true, most startups that could succeed fail because the founders don't devote their whole efforts to them. That certainly accords with what I see out in the world. Most startups fail because they don't make something people want, and the reason most don't is that they don't try hard enough. In other words, starting startups is just like everything else. The biggest mistake you can make is not to try hard enough.
To the extent there's a secret to success, it's not to be in denial about that. Notes [1] This is not a complete list of the causes of failure, just those you can control. There are also several you can't, notably ineptitude and bad luck. [2] Ironically, one variant of the Facebook that might work is a facebook exclusively for college students. [3] Steve Jobs tried to motivate people by saying "Real artists ship." This is a fine sentence, but unfortunately not true. Many famous works of art are unfinished. It's true in fields that have hard deadlines, like architecture and filmmaking, but even there people tend to be tweaking stuff till it's yanked out of their hands. [4] There's probably also a second factor: startup founders tend to be at the leading edge of technology, so problems they face are probably especially valuable. [5] You should take more than you think you'll need, maybe 50% to 100% more, because software takes longer to write and deals longer to close than you expect. [6] Since people sometimes call us VCs, I should add that we're not. VCs invest large amounts of other people's money. We invest small amounts of our own, like angel investors. [7] Not linearly of course, or it would take forever to raise five million dollars. In practice it just feels like it takes forever. Though if you include the cases where VCs don't invest, it would literally take forever in the median case. And maybe we should, because the danger of chasing large investments is not just that they take a long time. That's the _best_ case. The real danger is that you'll expend a lot of time and get nothing. [8] Some VCs will offer you an artificially low valuation to see if you have the balls to ask for more. It's lame that VCs play such games, but some do.
If you're dealing with one of those you should push back on the valuation a bit. [9] Suppose YouTube's founders had gone to Google in 2005 and told them "Google Video is badly designed. Give us $10 million and we'll tell you all the mistakes you made." They would have gotten the royal raspberry. Eighteen months later Google paid $1.6 billion for the same lesson, partly because they could then tell themselves that they were buying a phenomenon, or a community, or some vague thing like that. I don't mean to be hard on Google. They did better than their competitors, who may have now missed the video boat entirely. [10] Yes, actually: dealing with the government. But phone companies are up there. [11] Many more than most people realize, because companies don't advertise this. Did you know Apple originally had three founders? [12] I'm not dissing these people. I don't have the determination myself. I've twice come close to starting startups since Viaweb, and both times I bailed because I realized that without the spur of poverty I just wasn't willing to endure the stress of a startup. [13] So how do you know whether you're in the category of people who should quit their day job, or the presumably larger one who shouldn't? I got to the point of saying that this was hard to judge for yourself and that you should seek outside advice, before realizing that that's what we do. We think of ourselves as investors, but viewed from the other direction Y Combinator is a service for advising people whether or not to quit their day job.
We could be mistaken, and no doubt often are, but we do at least bet money on our conclusions. Thanks to Sam Altman, Jessica Livingston, Greg McAdoo, and Robert Morris for reading drafts of this.
| Japanese Translation | | | Spanish Translation | Romanian Translation | | | Chinese Translation | Arabic Translation.
想创业吗? 获得 Y Combinator 的资助。
2006年10月 在最近一次演讲的问答环节,有人问是什么导致了创业公司的失败。我愣了几秒后意识到这是个陷阱问题。它等同于询问如何让创业公司成功——只要避开所有失败原因就能成功——而这个问题太大,无法即兴回答。 后来我意识到从这个角度切入或许有帮助。如果列出一份“不该做的事”清单,只需反向操作就能得到成功指南。这种清单在实践中可能更实用。比起时刻牢记“该做什么”,察觉自己“不该做什么”更容易。[1] 从某种意义上说,只有一种错误会扼杀创业公司:没有做出用户想要的产品。只要做出用户想要的东西,其他无论做对或做错什么,你大概率都能活下来;反之,无论其他方面如何,你都注定失败。因此,本文列出的18个问题,本质上是导致创业公司未能满足用户需求的18种原因。几乎所有失败都源于此。 1. 单打独斗 你是否注意到,由单人创立的成功企业少之又少?即便像甲骨文这样看似单人创办的公司,通常也有多位联合创始人。这不太可能是巧合。 单人创业有何问题?首先,这相当于自我否定。很可能意味着创始人无法说服任何朋友共同创业。这非常危险,因为朋友才是最了解他的人。 即便所有朋友都看走眼、这确实是好项目,单人创业者仍处于劣势。创业对一个人来说太难了。即使你能独立完成所有工作,仍需要伙伴来头脑风暴、阻止愚蠢决策,以及在困境时互相打气。 最后一点或许最关键。创业低谷期如此艰难,少有人能独自承受。当多位创始人共同奋斗时,团队精神会产生违反能量守恒定律的凝聚力。每个人都会想“我不能让伙伴失望”。这是人性中最强大的驱动力之一,而单人创业者无法获得这种力量。 2. 选址不当 创业公司在某些地方蓬勃发展,在其他地方却举步维艰。硅谷独占鳌头,其次是波士顿、西雅图、奥斯汀、丹佛和纽约。除此之外几乎再无亮点。即便在纽约,人均创业公司数量可能只有硅谷的二十分之一。在休斯顿、芝加哥、底特律等城市,这一数字小到可以忽略不计。 为何差距如此悬殊?或许与其他行业同理。美国第六大时尚中心是哪里?第六大石油、金融或出版中心呢?无论答案是什么,它们与头部差距之大,甚至称其为“中心”都显得牵强。 城市如何成为创业中心是个有趣命题,但根本原因与其他行业无异:专家聚集之地。这里标准更高;人们更理解你的事业;优秀人才愿意在此定居;配套产业齐全;偶遇的路人可能正是同行。虽然难以量化这些因素如何共同造就硅谷的繁荣与底特律的沉寂,但人均创业公司数量已说明一切。 3. 边缘细分市场 大多数申请Y Combinator的团队存在通病:选择冷门小众领域以回避竞争。 观察儿童运动时会发现,某个年龄段以下的孩子害怕接球。当球飞来时,他们会本能躲避。我八岁打外场时就很少接杀,因为每当高飞球袭来,我总是闭眼举手套,更多是防御而非接球。 选择边缘项目就像我八岁时应对高飞球的策略。只要产品足够好,竞争必然出现,不如直面现实。回避竞争的唯一方式就是不做优秀产品。 这种逃避重大问题的倾向多是无意识的。并非人们想到了宏大创意却因求稳而选择小项目,而是潜意识根本不允许你思考宏大创意。解决方法或许是抽离自我思考:如果让别人来创业,什么会是绝佳创意? 4. 模仿性创意 我们收到的许多申请都在模仿现有公司。这虽是创意来源之一,却非最佳途径。回顾成功创业公司的起源,极少是通过模仿起家。它们的创意从何而来?通常源于创始人发现的某个具体未解难题。 我们的创业项目是开发网店软件。起步时这个领域一片空白,当时少数能在线购物的网站都由网页顾问高价手工打造。我们预见到:如果网购兴起,这些站点必将由软件生成,于是我们编写了相应程序。逻辑很简单。 最佳解决方案往往针对切身之痛。苹果诞生是因为沃兹尼亚克想要一台电脑;谷歌出现源于佩奇和布林找不到在线资料;Hotmail则因巴蒂亚和史密斯无法在工作时互发邮件。 与其带着脸书不屑一顾的“微创新”去复制脸书,不如逆向思考。不要从公司出发倒推它们解决的问题,而要主动发现问题,再构想解决方案。[2] 人们抱怨什么?你希望存在什么? 5. 固执己见 在某些领域,成功之道在于坚守愿景,无论遭遇何种挫折。但创业不属此列。这种“坚持愿景”的方法适用于奥运会金牌等目标明确的事务,而创业更像科学探索——需要跟随线索,无论它指向何方。 因此别对初始计划过于执着,因为它很可能是错的。多数成功创业公司最终从事的业务与初衷大相径庭,有时甚至判若两家。你必须准备好在更好创意出现时抓住它。而最困难的部分往往是放弃旧想法。 但开放心态需要精准把控。每周更换新创意同样致命。是否有外部检验标准?可观察创意是否呈现递进关系。如果每个新创意都能复用之前构建的大部分成果,说明你处于收敛过程中;若不断推倒重来,则是危险信号。 幸运的是,你可以咨询用户意见。当考虑转型新方向时,如果用户表现出兴趣,这很可能是个正确选择。 6. 聘用糟糕程序员 早期版本中我遗漏了这点,因为我认识的创始人几乎都是程序员。这对他们不算严重问题——即便误招庸才也不会致命,危急时刻他们能亲自顶上。 但回顾90年代电商泡沫,多数创业公司死于糟糕的程序员。当时许多公司由商业人士创立,他们认为创业就是提出巧妙创意后雇佣程序员实现。这实际上比听起来困难得多——几乎不可能——因为商业人士无法识别优秀程序员。他们甚至接触不到顶尖人才,因为真正的高手不愿为他人愿景打工。 现实情况是:商业主管选中他们眼中的“优秀程序员”(简历写着“微软认证开发者”),实则不然。随后他们困惑地发现,自己的公司像二战轰炸机般笨拙前行,而竞争对手却如喷气战机呼啸而过。这类创业公司处境类似大企业,却不具备相应优势。 若非技术人员,如何甄别优秀程序员?我认为无解。本想建议找优秀程序员协助招聘,但若你无法识别人才,又该如何找到这样的人? 7. 选择错误平台 相关问题是选择错误平台(通常由糟糕程序员导致)。例如,我认为泡沫时期许多创业公司死于在Windows上构建服务器应用。Hotmail被微软收购后仍多年运行于FreeBSD,很可能因为Windows无法承载负荷。若Hotmail创始人当初选择Windows,他们早已被流量淹没。 PayPal险些重蹈覆辙。与X.com合并后,新CEO欲转向Windows——即便联合创始人列夫琴证明其软件在Windows上的扩展性仅为Unix的1%。所幸PayPal最终更换了CEO而非平台。 “平台”是个宽泛概念,可指操作系统、编程语言或基于语言的“框架”。它如同房屋地基,既提供支撑也构成限制。 平台的可怕之处在于,某些被外界视为稳妥的选择(如90年代的Windows)实则致命。Java小程序堪称最典型案例,它曾被吹捧为应用程序的新载体,却几乎杀死了所有信奉它的创业公司。 如何选择正确平台?常规做法是让优秀程序员决定。若非技术人员,可参考顶尖计算机系研究项目的技术选型。 8. 发布拖延 无论规模大小,公司完成软件都非易事。这是行业本质使然——软件永远处在85%完成状态。需要强大意志力才能突破此状态,向用户发布产品。[3] 创业公司为延迟发布找尽借口,大多与日常生活中的拖延症理由无异。“需要先完成某件事”——或许吧。但如果软件已100%完成,只需按键即可发布,他们还会等待吗? 快速发布的首要意义是迫使你真正完成某个完整模块。唯有发布才算真正完成——任何产品上线前必然伴随紧张赶工,无论你认为它有多完善。另一重意义在于:唯有通过用户反馈,你才能完全理解自己的创意。 发布延迟暴露多重问题:进度缓慢;未真正理解问题;恐惧用户沟通;害怕被评判;同时处理过多事务;过度完美主义。幸运的是,强制自己快速发布能一举攻克所有问题。 9. 过早发布 因发布过慢而死亡的创业公司百倍于发布过快者,但过早发布确实可能发生。其风险在于损害声誉:产品发布后,早期试用者若体验不佳可能永不回头。 那么最低发布标准是什么?我们建议创业者规划目标时,找出兼具以下特性的核心功能:(a) 独立可用;(b) 可逐步扩展为完整项目,然后尽快实现它。 这与我和许多程序员的开发方法一致:构想整体目标后,先编写能实现任何功能的最小子集。既然是子集,迟早都要编写,因此最差情况也不过是没浪费时间。更可能的是,实现可用子集既能提振士气,又能更清晰指引后续方向。 你需要打动.
Want to start a startup? Get funded by Y Combinator.
October 2006 _(This essay is derived from a talk at MIT.)_ Till recently graduating seniors had two choices: get a job or go to grad school. I think there will increasingly be a third option: to start your own startup. But how common will that be? I'm sure the default will always be to get a job, but starting a startup could well become as popular as grad school. In the late 90s my professor friends used to complain that they couldn't get grad students, because all the undergrads were going to work for startups. I wouldn't be surprised if that situation returns, but with one difference: this time they'll be starting their own instead of going to work for other people's. The most ambitious students will at this point be asking: Why wait till you graduate? Why not start a startup while you're in college? In fact, why go to college at all? Why not start a startup instead? A year and a half ago I gave a talk where I said that the average age of the founders of Yahoo, Google, and Microsoft was 24, and that if grad students could start startups, why not undergrads? I'm glad I phrased that as a question, because now I can pretend it wasn't merely a rhetorical one. At the time I couldn't imagine why there should be any lower limit for the age of startup founders. Graduation is a bureaucratic change, not a biological one. And certainly there are undergrads as competent technically as most grad students. So why shouldn't undergrads be able to start startups as well as grad students? I now realize that something does change at graduation: you lose a huge excuse for failing. Regardless of how complex your life is, you'll find that everyone else, including your family and friends, will discard all the low bits and regard you as having a single occupation at any given time.
想创业吗? 获得 Y Combinator 的资助。
(本文改编自在麻省理工学院的一次演讲。)
If you're in college and have a summer job writing software, you still read as a student. Whereas if you graduate and get a job programming, you'll be instantly regarded by everyone as a programmer. The problem with starting a startup while you're still in school is that there's a built-in escape hatch. If you start a startup in the summer between your junior and senior year, it reads to everyone as a summer job. So if it goes nowhere, big deal; you return to school in the fall with all the other seniors; no one regards you as a failure, because your occupation is student, and you didn't fail at that. Whereas if you start a startup just one year later, after you graduate, as long as you're not accepted to grad school in the fall the startup reads to everyone as your occupation. You're now a startup founder, so you have to do well at that. For nearly everyone, the opinion of one's peers is the most powerful motivator of all—more powerful even than the nominal goal of most startup founders, getting rich. [1] About a month into each funding cycle we have an event called Prototype Day where each startup presents to the others what they've got so far. You might think they wouldn't need any more motivation. They're working on their cool new idea; they have funding for the immediate future; and they're playing a game with only two outcomes: wealth or failure. You'd think that would be motivation enough. And yet the prospect of a demo pushes most of them into a rush of activity. Even if you start a startup explicitly to get rich, the money you might get seems pretty theoretical most of the time. What drives you day to day is not wanting to look bad. You probably can't change that. Even if you could, I don't think you'd want to; someone who really, truly doesn't care what his peers think of him is probably a psychopath. So the best you can do is consider this force like a wind, and set up your boat accordingly.
直到最近,应届毕业生还只有两种选择:找份工作或读研究生。我认为未来会越来越多地出现第三种选择:创办自己的初创公司。但这种选择会有多普遍呢?
我确信,默认选择永远是找份工作,但创业很可能会变得和读研究生一样流行。90年代末,我的教授朋友们常常抱怨招不到研究生,因为所有本科生都跑去为初创公司工作了。如果这种情况再次出现,我一点也不会感到惊讶,但这次会有一个不同之处:他们将创办自己的公司,而不是为别人的公司工作。
最有雄心的学生此时会问:为什么要等到毕业?为什么不在大学期间就创业?事实上,为什么还要上大学?为什么不直接创业?
If you know your peers are going to push you in some direction, choose good peers, and position yourself so they push you in a direction you like. Graduation changes the prevailing winds, and those make a difference. Starting a startup is so hard that it's a close call even for the ones that succeed. However high a startup may be flying now, it probably has a few leaves stuck in the landing gear from those trees it barely cleared at the end of the runway. In such a close game, the smallest increase in the forces against you can be enough to flick you over the edge into failure. When we first started Y Combinator we encouraged people to start startups while they were still in college. That's partly because Y Combinator began as a kind of summer program. We've kept the program shape—all of us having dinner together once a week turns out to be a good idea—but we've decided now that the party line should be to tell people to wait till they graduate. Does that mean you can't start a startup in college? Not at all. Sam Altman, the co-founder of Loopt, had just finished his sophomore year when we funded them, and Loopt is probably the most promising of all the startups we've funded so far. But Sam Altman is a very unusual guy. Within about three minutes of meeting him, I remember thinking "Ah, so this is what Bill Gates must have been like when he was 19." If it can work to start a startup during college, why do we tell people not to? For the same reason that the probably apocryphal violinist, whenever he was asked to judge someone's playing, would always say they didn't have enough talent to make it as a pro. Succeeding as a musician takes determination as well as talent, so this answer works out to be the right advice for everyone.
一年半前,我在一次演讲中提到,雅虎、谷歌和微软创始人的平均年龄是24岁,既然研究生可以创业,为什么本科生不行?我很高兴当时用了问句的形式,因为现在我可以假装那不仅仅是个反问。当时我无法想象创业者的年龄应该有什么下限。毕业只是一种官僚程序上的变化,而非生理上的变化。而且,肯定有一些本科生在技术能力上和大多数研究生一样强。那么,为什么本科生不能像研究生一样创业呢?
我现在意识到,毕业确实会带来一些变化:你失去了一个巨大的失败借口。无论你的生活有多复杂,你会发现其他人,包括你的家人和朋友,都会忽略那些次要部分,认为你在任何特定时间只有一个主要身份。如果你在大学期间有一份暑期编程工作,你仍然被视为学生。而如果你毕业后找到一份编程工作,所有人会立刻把你视为程序员。
The ones who are uncertain believe it and give up, and the ones who are sufficiently determined think "screw that, I'll succeed anyway." So our official policy now is only to fund undergrads we can't talk out of it. And frankly, if you're not certain, you _should_ wait. It's not as if all the opportunities to start companies are going to be gone if you don't do it now. Maybe the window will close on some idea you're working on, but that won't be the last idea you'll have. For every idea that times out, new ones become feasible. Historically the opportunities to start startups have only increased with time. In that case, you might ask, why not wait longer? Why not go work for a while, or go to grad school, and then start a startup? And indeed, that might be a good idea. If I had to pick the sweet spot for startup founders, based on who we're most excited to see applications from, I'd say it's probably the mid-twenties. Why? What advantages does someone in their mid-twenties have over someone who's 21? And why isn't it older? What can 25 year olds do that 32 year olds can't? Those turn out to be questions worth examining. Plus If you start a startup soon after college, you'll be a young founder by present standards, so you should know what the relative advantages of young founders are. They're not what you might think. As a young founder your strengths are: stamina, poverty, rootlessness, colleagues, and ignorance. The importance of stamina shouldn't be surprising. If you've heard anything about startups you've probably heard about the long hours. As far as I can tell these are universal. I can't think of any successful startups whose founders worked 9 to 5. And it's particularly necessary for younger founders to work long hours because they're probably not as efficient as they'll be later. Your second advantage, poverty, might not sound like an advantage, but it is a huge one.
在校期间创业的问题是,你有一个内置的逃生舱口。如果你在大三和大四之间的暑假创业,所有人会认为那只是一份暑期工作。所以如果创业失败了,也没什么大不了的;秋天你可以和其他大四学生一起返校;没人会认为你是失败者,因为你的身份是学生,而你在这一点上并没有失败。但如果你在毕业后仅仅一年才开始创业,只要秋天你没有去读研,所有人就会把创业视为你的职业。你现在是一名初创公司创始人,所以你必须做好这件事。
对几乎所有人来说,同龄人的看法是最强大的动力——甚至比大多数初创公司创始人的名义目标(致富)更强大。[1] 在每个融资周期开始大约一个月后,我们会举办一个名为“原型日”的活动,每家初创公司向其他公司展示他们目前的成果。你可能会觉得他们不需要更多的动力。他们正在研究自己酷炫的新想法;他们短期内不缺资金;而且他们玩的是一场只有两种结果的游戏:致富或失败。你会觉得这已经足够激励人了。然而,演示的前景还是会让大多数人陷入一阵忙碌。
即使你明确为了致富而创业,大部分时间里你可能赚到的钱看起来仍然相当抽象。每天驱动你的其实是不想显得糟糕。
Poverty implies you can live cheaply, and this is critically important for startups. Nearly every startup that fails, fails by running out of money. It's a little misleading to put it this way, because there's usually some other underlying cause. But regardless of the source of your problems, a low burn rate gives you more opportunity to recover from them. And since most startups make all kinds of mistakes at first, room to recover from mistakes is a valuable thing to have. Most startups end up doing something different than they planned. The way the successful ones find something that works is by trying things that don't. So the worst thing you can do in a startup is to have a rigid, pre-ordained plan and then start spending a lot of money to implement it. Better to operate cheaply and give your ideas time to evolve. Recent grads can live on practically nothing, and this gives you an edge over older founders, because the main cost in software startups is people. The guys with kids and mortgages are at a real disadvantage. This is one reason I'd bet on the 25 year old over the 32 year old. The 32 year old probably is a better programmer, but probably also has a much more expensive life. Whereas a 25 year old has some work experience (more on that later) but can live as cheaply as an undergrad. Robert Morris and I were 29 and 30 respectively when we started Viaweb, but fortunately we still lived like 23 year olds. We both had roughly zero assets. I would have loved to have a mortgage, since that would have meant I had a _house_. But in retrospect having nothing turned out to be convenient. I wasn't tied down and I was used to living cheaply. Even more important than living cheaply, though, is thinking cheaply. One reason the Apple II was so popular was that it was cheap. The computer itself was cheap, and it used cheap, off-the-shelf peripherals like a cassette tape recorder for data storage and a TV as a monitor.
你可能无法改变这一点。即使你能改变,我也不认为你会想改;一个真正完全不在乎同龄人看法的人,很可能是个精神病患者。所以你能做的最好的事,就是把这种力量视为一阵风,并据此调整你的船帆。如果你知道同龄人会把你推向某个方向,那就选择好的同伴,并调整自己的位置,让他们把你推向你喜欢的方向。
毕业会改变风向,而这会产生影响。创业非常艰难,即使对成功者来说也是千钧一发。无论一家初创公司现在飞得多高,它的起落架上可能还卡着几片从跑道尽头勉强擦过的树枝叶子。在这场势均力敌的比赛中,反对你的力量哪怕只是稍微增加一点点,也足以把你推过失败的边缘。
当我们刚开始 Y Combinator 时,我们鼓励人们在大学期间就创业。这部分是因为 Y Combinator 最初是一种暑期项目。我们保留了项目的形式——每周一次大家一起吃晚餐被证明是个好主意——但现在我们决定,官方立场应该是告诉人们等到毕业后再创业。
And you know why? Because Woz designed this computer for himself, and he couldn't afford anything more. We benefitted from the same phenomenon. Our prices were daringly low for the time. The top level of service was $300 a month, which was an order of magnitude below the norm. In retrospect this was a smart move, but we didn't do it because we were smart. $300 a month seemed like a lot of money to us. Like Apple, we created something inexpensive, and therefore popular, simply because we were poor. A lot of startups have that form: someone comes along and makes something for a tenth or a hundredth of what it used to cost, and the existing players can't follow because they don't even want to think about a world in which that's possible. Traditional long distance carriers, for example, didn't even want to think about VoIP. (It was coming, all the same.) Being poor helps in this game, because your own personal bias points in the same direction technology evolves in. The advantages of rootlessness are similar to those of poverty. When you're young you're more mobile—not just because you don't have a house or much stuff, but also because you're less likely to have serious relationships. This turns out to be important, because a lot of startups involve someone moving. The founders of Kiko, for example, are now en route to the Bay Area to start their next startup. It's a better place for what they want to do. And it was easy for them to decide to go, because neither as far as I know has a serious girlfriend, and everything they own will fit in one car—or more precisely, will either fit in one car or is crappy enough that they don't mind leaving it behind. They at least were in Boston. What if they'd been in Nebraska, like Evan Williams was at their age? Someone wrote recently that the drawback of Y Combinator was that you had to move to participate. It couldn't be any other way.
这是否意味着你不能在大学期间创业?完全不是。Loopt 的联合创始人 Sam Altman 在我们资助他们时刚刚读完大二,而 Loopt 可能是我们迄今为止资助过的最有前途的初创公司。但 Sam Altman 是个非常不寻常的人。在见到他的大约三分钟内,我记得自己想过:“啊,这就是比尔·盖茨19岁时的样子吧。”
如果大学期间创业可行,为什么我们要告诉人们不要这样做?原因和那个可能是杜撰的小提琴家的故事一样:每当有人请他评判别人的演奏时,他总是说他们没有足够的才华成为职业演奏家。成为成功的音乐家需要决心和才华,所以这个回答对所有人来说都是正确的建议。那些不确定的人会相信并放弃,而那些足够坚定的人会想:“去他的,我无论如何都会成功。”
The kind of conversations we have with founders, we have to have in person. We fund a dozen startups at a time, and we can't be in a dozen places at once. But even if we could somehow magically save people from moving, we wouldn't. We wouldn't be doing founders a favor by letting them stay in Nebraska. Places that aren't startup hubs are toxic to startups. You can tell that from indirect evidence. You can tell how hard it must be to start a startup in Houston or Chicago or Miami from the microscopically small number, per capita, that succeed there. I don't know exactly what's suppressing all the startups in these towns—probably a hundred subtle little things—but something must be. [2] Maybe this will change. Maybe the increasing cheapness of startups will mean they'll be able to survive anywhere, instead of only in the most hospitable environments. Maybe 37signals is the pattern for the future. But maybe not. Historically there have always been certain towns that were centers for certain industries, and if you weren't in one of them you were at a disadvantage. So my guess is that 37signals is an anomaly. We're looking at a pattern much older than "Web 2.0" here. Perhaps the reason more startups per capita happen in the Bay Area than Miami is simply that there are more founder-type people there. Successful startups are almost never started by one person. Usually they begin with a conversation in which someone mentions that something would be a good idea for a company, and his friend says, "Yeah, that is a good idea, let's try it." If you're missing that second person who says "let's try it," the startup never happens. And that is another area where undergrads have an edge. They're surrounded by people willing to say that. At a good college you're concentrated together with a lot of other ambitious and technically minded people—probably more concentrated than you'll ever be again.
所以我们现在官方政策是,只资助那些我们无法劝退的本科生。坦率地说,如果你不确定,你应该等待。并不是说如果你现在不创业,以后就再也没有机会了。也许你正在研究的某个想法的窗口期会关闭,但那不会是你最后一个想法。每当一个想法过时,新的想法就会变得可行。历史上,创业的机会只会随着时间的推移而增加。
既然如此,你可能会问,为什么不等待更长时间?为什么不先工作一段时间,或者读研究生,然后再创业?事实上,这可能是个好主意。如果非要我根据我们最希望看到的申请者来挑选创业者的最佳年龄,我会说大概是25岁左右。为什么?25岁的人比21岁的人有什么优势?为什么不是更大年纪?25岁的人能做到32岁的人做不到的事吗?这些问题值得探讨。
如果你大学毕业后不久就创业,按照现在的标准,你会是一名年轻的创始人,所以你应该知道年轻创始人的相对优势是什么。它们可能不是你想象的那样。作为一名年轻创始人,你的优势是:精力充沛、贫穷、无牵无挂、有同事、以及无知。
If your nucleus spits out a neutron, there's a good chance it will hit another nucleus. The number one question people ask us at Y Combinator is: Where can I find a co-founder? That's the biggest problem for someone starting a startup at 30. When they were in school they knew a lot of good co-founders, but by 30 they've either lost touch with them or these people are tied down by jobs they don't want to leave. Viaweb was an anomaly in this respect too. Though we were comparatively old, we weren't tied down by impressive jobs. I was trying to be an artist, which is not very constraining, and Robert, though 29, was still in grad school due to a little interruption in his academic career back in 1988. So arguably the Worm made Viaweb possible. Otherwise Robert would have been a junior professor at that age, and he wouldn't have had time to work on crazy speculative projects with me. Most of the questions people ask Y Combinator we have some kind of answer for, but not the co-founder question. There is no good answer. Co-founders really should be people you already know. And by far the best place to meet them is school. You have a large sample of smart people; you get to compare how they all perform on identical tasks; and everyone's life is pretty fluid. A lot of startups grow out of schools for this reason. Google, Yahoo, and Microsoft, among others, were all founded by people who met in school. (In Microsoft's case, it was high school.) Many students feel they should wait and get a little more experience before they start a company. All other things being equal, they should. But all other things are not quite as equal as they look. Most students don't realize how rich they are in the scarcest ingredient in startups, co-founders. If you wait too long, you may find that your friends are now involved in some project they don't want to abandon. The better they are, the more likely this is to happen.
精力充沛的重要性并不令人意外。如果你听说过关于初创公司的任何事,你可能听说过长时间工作。据我所知,这是普遍现象。我想不出任何成功的初创公司创始人是朝九晚五工作的。年轻创始人尤其需要长时间工作,因为他们可能没有以后那么高效。
你的第二个优势——贫穷——听起来可能不像优势,但它确实是一个巨大的优势。贫穷意味着你可以生活得很节俭,这对初创公司至关重要。几乎所有失败的初创公司都是因为资金耗尽而失败的。这种说法有点误导性,因为通常还有其他根本原因。但无论问题的根源是什么,低烧钱率都能给你更多机会从中恢复。由于大多数初创公司一开始都会犯各种错误,拥有从错误中恢复的空间是非常宝贵的。
One way to mitigate this problem might be to actively plan your startup while you're getting those n years of experience. Sure, go off and get jobs or go to grad school or whatever, but get together regularly to scheme, so the idea of starting a startup stays alive in everyone's brain. I don't know if this works, but it can't hurt to try. It would be helpful just to realize what an advantage you have as students. Some of your classmates are probably going to be successful startup founders; at a great technical university, that is a near certainty. So which ones? If I were you I'd look for the people who are not just smart, but incurable builders. Look for the people who keep starting projects, and finish at least some of them. That's what we look for. Above all else, above academic credentials and even the idea you apply with, we look for people who build things. The other place co-founders meet is at work. Fewer do than at school, but there are things you can do to improve the odds. The most important, obviously, is to work somewhere that has a lot of smart, young people. Another is to work for a company located in a startup hub. It will be easier to talk a co-worker into quitting with you in a place where startups are happening all around you. You might also want to look at the employment agreement you sign when you get hired. Most will say that any ideas you think of while you're employed by the company belong to them. In practice it's hard for anyone to prove what ideas you had when, so the line gets drawn at code. If you're going to start a startup, don't write any of the code while you're still employed. Or at least discard any code you wrote while still employed and start over. It's not so much that your employer will find out and sue you. It won't come to that; investors or acquirers or (if you're so lucky) underwriters will nail you first.
大多数初创公司最终做的事情与最初的计划不同。成功的初创公司找到可行方案的方法,就是尝试那些不可行的方案。所以在初创公司里你能做的最糟糕的事,就是制定一个僵化、预先确定的计划,然后开始花大量资金去实施它。更好的做法是低成本运营,给你的想法时间去演化。
刚毕业的学生几乎可以零成本生活,这让你比年长的创始人更有优势,因为软件初创公司的主要成本是人力。那些有孩子和房贷的人处于真正的劣势。这是我更愿意押注25岁而非32岁的人的原因之一。32岁的人可能是更好的程序员,但他的生活成本也高得多。而25岁的人有一些工作经验(稍后会详细讨论),但可以像本科生一样低成本生活。
Robert Morris 和我在创办 Viaweb 时分别是29岁和30岁,但幸运的是,我们仍然像23岁的人一样生活。我们俩的资产几乎为零。我当时很希望能有房贷,因为那意味着我有一栋房子。但回想起来,一无所有反而很方便。我没有束缚,而且习惯了节俭生活。
Between t = 0 and when you buy that yacht, _someone_ is going to ask if any of your code legally belongs to anyone else, and you need to be able to say no. [3] The most overreaching employee agreement I've seen so far is Amazon's. In addition to the usual clauses about owning your ideas, you also can't be a founder of a startup that has another founder who worked at Amazon—even if you didn't know them or even work there at the same time. I suspect they'd have a hard time enforcing this, but it's a bad sign they even try. There are plenty of other places to work; you may as well choose one that keeps more of your options open. Speaking of cool places to work, there is of course Google. But I notice something slightly frightening about Google: zero startups come out of there. In that respect it's a black hole. People seem to like working at Google too much to leave. So if you hope to start a startup one day, the evidence so far suggests you shouldn't work there. I realize this seems odd advice. If they make your life so good that you don't want to leave, why not work there? Because, in effect, you're probably getting a local maximum. You need a certain activation energy to start a startup. So an employer who's fairly pleasant to work for can lull you into staying indefinitely, even if it would be a net win for you to leave. [4] The best place to work, if you want to start a startup, is probably a startup. In addition to being the right sort of experience, one way or another it will be over quickly. You'll either end up rich, in which case problem solved, or the startup will get bought, in which case it it will start to suck to work there and it will be easy to leave, or most likely, the thing will blow up and you'll be free again. Your final advantage, ignorance, may not sound very useful. I deliberately used a controversial word for it; you might equally call it innocence. But it seems to be a powerful force.
不过,比节俭生活更重要的是节俭思维。Apple II 如此受欢迎的一个原因是它便宜。电脑本身便宜,而且使用廉价的现成外设,比如用盒式磁带录音机存储数据,用电视机当显示器。你知道为什么吗?因为 Woz 是为自己设计的这台电脑,而他买不起更贵的东西。
我们也受益于同样的现象。当时我们的价格低得惊人。最高级别的服务是每月300美元,比行业标准低一个数量级。回想起来,这是一个明智之举,但我们这样做并不是因为我们聪明。每月300美元对我们来说已经是一大笔钱了。和苹果一样,我们创造了一些便宜的东西,因此受欢迎,仅仅是因为我们穷。
许多初创公司都有这种模式:有人出现并以原来成本的十分之一或百分之一制造某样东西,而现有玩家无法跟进,因为他们甚至不愿想象一个这样的世界是可能的。例如,传统的长途电话公司甚至不愿考虑 VoIP。(但它还是来了。)贫穷在这场游戏中有所帮助,因为你个人的偏见与技术发展的方向一致。
My Y Combinator co-founder Jessica Livingston is just about to publish a book of interviews with startup founders, and I noticed a remarkable pattern in them. One after another said that if they'd known how hard it would be, they would have been too intimidated to start. Ignorance can be useful when it's a counterweight to other forms of stupidity. It's useful in starting startups because you're capable of more than you realize. Starting startups is harder than you expect, but you're also capable of more than you expect, so they balance out. Most people look at a company like Apple and think, how could I ever make such a thing? Apple is an institution, and I'm just a person. But every institution was at one point just a handful of people in a room deciding to start something. Institutions are made up, and made up by people no different from you. I'm not saying everyone could start a startup. I'm sure most people couldn't; I don't know much about the population at large. When you get to groups I know well, like hackers, I can say more precisely. At the top schools, I'd guess as many as a quarter of the CS majors could make it as startup founders if they wanted. That "if they wanted" is an important qualification—so important that it's almost cheating to append it like that—because once you get over a certain threshold of intelligence, which most CS majors at top schools are past, the deciding factor in whether you succeed as a founder is how much you want to. You don't have to be that smart. If you're not a genius, just start a startup in some unsexy field where you'll have less competition, like software for human resources departments. I picked that example at random, but I feel safe in predicting that whatever they have now, it wouldn't take genius to do better.
无牵无挂的优势与贫穷类似。年轻时你更灵活——不仅因为你没有房子或太多东西,还因为你不太可能有严肃的感情关系。这很重要,因为许多初创公司需要有人搬家。
例如,Kiko 的创始人现在正前往湾区创办他们的下一家初创公司。那里更适合他们想做的事。他们很容易做出搬家的决定,因为据我所知,他们都没有认真的女朋友,而且他们所有的东西都能装进一辆车——或者更准确地说,要么能装进一辆车,要么就是烂到他们不介意扔掉。
There are a lot of people out there working on boring stuff who are desperately in need of better software, so however short you think you fall of Larry and Sergey, you can ratchet down the coolness of the idea far enough to compensate. As well as preventing you from being intimidated, ignorance can sometimes help you discover new ideas. Steve Wozniak put this very strongly:.
他们至少是在波士顿。如果他们像 Evan Williams 在他们这个年纪时在内布拉斯加州呢?最近有人写道,Y Combinator 的缺点是你必须搬家才能参与。这是不可避免的。我们与创始人的那种对话必须面对面进行。我们一次资助十几家初创公司,不可能同时出现在十几个地方。但即使我们能以某种神奇的方式让人们免于搬家,我们也不会这样做。让创始人留在内布拉斯加并不是在帮他们。非创业中心的地方对初创公司是有害的。你可以从间接证据中看出这一点。从休斯顿、芝加哥或迈阿密等地人均极低的成功初创公司数量,你可以看出在那里创业有多难。我不完全知道是什么压制了这些城市的所有初创公司——可能是一百种微妙的小事——但肯定有什么东西在起作用。[2]
也许这会改变。也许初创公司成本的降低意味着它们可以在任何地方生存,而不仅仅是在最适宜的环境中。也许 37signals 是未来的模式。但也可能不是。历史上,某些行业总是集中在某些城市,如果你不在其中之一,你就会处于劣势。所以我猜 37signals 是个例外。我们在这里看到的是一种比“Web 2.0”古老得多的模式。
也许湾区人均初创公司比迈阿密多的原因仅仅是那里有更多创始人类型的人。成功的初创公司几乎从来不是由一个人创立的。通常它们始于一次对话,有人提到某个想法可以成为一家好公司,而他的朋友说:“是啊,那是个好主意,我们试试吧。”如果你缺少那个说“我们试试吧”的第二个人,初创公司就不会发生。这是本科生的另一个优势。他们周围有很多愿意说这句话的人。在一所好大学里,你和其他许多有抱负且技术头脑的人集中在一起——可能比你以后任何时候都更集中。如果你的核心释放出一个中子,它很有可能会击中另一个核心。
> All the best things that I did at Apple came from (a) not having money and (b) not having done it before, ever. Every single thing that we came out with that was really great, I'd never once done that thing in my life.
人们在 Y Combinator 问我们的头号问题是:我在哪里可以找到联合创始人?这对30岁创业的人来说是最大的问题。他们在学校时认识很多好的联合创始人,但到了30岁,他们要么失去了联系,要么这些人被不想放弃的工作束缚住了。
Viaweb 在这方面也是个例外。虽然我们相对年长,但我们没有被令人印象深刻的工作束缚住。我当时想成为一名艺术家,这没什么约束力,而 Robert 虽然29岁了,但由于1988年学术生涯中的一次小中断,他还在读研究生。所以可以说,蠕虫病毒让 Viaweb 成为可能。否则 Robert 在那个年纪会是一名初级教授,他不会有时间和我一起做疯狂且充满不确定性的项目。
人们对 Y Combinator 提出的问题,我们大多都有某种答案,但联合创始人问题除外。没有好的答案。联合创始人真的应该是你已经认识的人。而迄今为止最好的认识他们的地方是学校。你有大量聪明人的样本;你可以比较他们在相同任务上的表现;而且每个人的生活都很灵活。许多初创公司因此从学校中诞生。谷歌、雅虎和微软等公司都是由在学校认识的人创立的。(微软的案例中,是高中。)
When you know nothing, you have to reinvent stuff for yourself, and if you're smart your reinventions may be better than what preceded them. This is especially true in fields where the rules change. All our ideas about software were developed in a time when processors were slow, and memories and disks were tiny. Who knows what obsolete assumptions are embedded in the conventional wisdom? And the way these assumptions are going to get fixed is not by explicitly deallocating them, but by something more akin to garbage collection. Someone ignorant but smart will come along and reinvent everything, and in the process simply fail to reproduce certain existing ideas. Minus So much for the advantages of young founders. What about the disadvantages? I'm going to start with what goes wrong and try to trace it back to the root causes. What goes wrong with young founders is that they build stuff that looks like class projects. It was only recently that we figured this out ourselves. We noticed a lot of similarities between the startups that seemed to be falling behind, but we couldn't figure out how to put it into words. Then finally we realized what it was: they were building class projects. But what does that really mean? What's wrong with class projects? What's the difference between a class project and a real startup? If we could answer that question it would be useful not just to would-be startup founders but to students in general, because we'd be a long way toward explaining the mystery of the so-called real world. There seem to be two big things missing in class projects: (1) an iterative definition of a real problem and (2) intensity. The first is probably unavoidable. Class projects will inevitably solve fake problems. For one thing, real problems are rare and valuable.
许多学生觉得他们应该等待并积累更多经验后再创业。在其他条件相同的情况下,他们应该这样做。但其他条件并不像看起来那么平等。大多数学生没有意识到他们在初创公司最稀缺的资源——联合创始人——方面有多富有。如果你等得太久,你可能会发现你的朋友们现在都参与了一些他们不想放弃的项目。他们越优秀,这种情况就越有可能发生。
缓解这个问题的一种方法可能是在积累那几年经验的同时积极规划你的初创公司。当然,你可以去工作或读研究生或做其他事,但要定期聚在一起谋划,这样创业的想法在每个人的脑海中保持活跃。我不知道这是否有效,但试试也无妨。
If a professor wanted to have students solve real problems, he'd face the same paradox as someone trying to give an example of whatever "paradigm" might succeed the Standard Model of physics. There may well be something that does, but if you could think of an example you'd be entitled to the Nobel Prize. Similarly, good new problems are not to be had for the asking. In technology the difficulty is compounded by the fact that real startups tend to discover the problem they're solving by a process of evolution. Someone has an idea for something; they build it; and in doing so (and probably only by doing so) they realize the problem they should be solving is another one. Even if the professor let you change your project description on the fly, there isn't time enough to do that in a college class, or a market to supply evolutionary pressures. So class projects are mostly about implementation, which is the least of your problems in a startup. It's not just that in a startup you work on the idea as well as implementation. The very implementation is different. Its main purpose is to refine the idea. Often the only value of most of the stuff you build in the first six months is that it proves your initial idea was mistaken. And that's extremely valuable. If you're free of a misconception that everyone else still shares, you're in a powerful position. But you're not thinking that way about a class project. Proving your initial plan was mistaken would just get you a bad grade. Instead of building stuff to throw away, you tend to want every line of code to go toward that final goal of showing you did a lot of work. That leads to our second difference: the way class projects are measured. Professors will tend to judge you by the distance between the starting point and where you are now. If someone has achieved a lot, they should get a good grade.
只要意识到作为学生的优势就很有帮助。你的一些同学很可能会成为成功的初创公司创始人;在一所优秀的技术大学里,这几乎是肯定的。那么是谁呢?如果我是你,我会寻找那些不仅聪明,而且无可救药的建造者。寻找那些不断启动项目并至少完成其中一些的人。这就是我们寻找的。最重要的是,高于学术资历甚至你申请时的想法,我们寻找的是那些建造东西的人。
联合创始人相遇的另一个地方是工作场所。比在学校相遇的人少,但你可以做一些事情来提高几率。最重要的显然是去一家有很多聪明年轻人的公司工作。另一个是去位于创业中心的公司工作。在一个初创公司遍地的地方,说服同事和你一起辞职会更容易。
你可能还想看看入职时签署的雇佣协议。大多数协议会说,你在受雇期间想到的任何想法都属于公司。实际上,很难证明你在什么时候有过什么想法,所以界限划在代码上。如果你要创业,不要在受雇期间写任何代码。或者至少丢弃你在受雇期间写的所有代码并重新开始。这并不是说你的雇主会发现并起诉你。事情不会发展到那一步;投资者、收购方或(如果你足够幸运)承销商会先抓住你。在 t = 0 和你买游艇之间的某个时刻,某人会问你的代码是否在法律上属于其他人,你需要能够说不。[3]
But customers will judge you from the other direction: the distance remaining between where you are now and the features they need. The market doesn't give a shit how hard you worked. Users just want your software to do what they need, and you get a zero otherwise. That is one of the most distinctive differences between school and the real world: there is no reward for putting in a good effort. In fact, the whole concept of a "good effort" is a fake idea adults invented to encourage kids. It is not found in nature. Such lies seem to be helpful to kids. But unfortunately when you graduate they don't give you a list of all the lies they told you during your education. You have to get them beaten out of you by contact with the real world. And this is why so many jobs want work experience. I couldn't understand that when I was in college. I knew how to program. In fact, I could tell I knew how to program better than most people doing it for a living. So what was this mysterious "work experience" and why did I need it? Now I know what it is, and part of the confusion is grammatical. Describing it as "work experience" implies it's like experience operating a certain kind of machine, or using a certain programming language. But really what work experience refers to is not some specific expertise, but the elimination of certain habits left over from childhood. One of the defining qualities of kids is that they flake. When you're a kid and you face some hard test, you can cry and say "I can't" and they won't make you do it. Of course, no one can make you do anything in the grownup world either. What they do instead is fire you. And when motivated by that you find you can do a lot more than you realized. So one of the things employers expect from someone with "work experience" is the elimination of the flake reflex—the ability to get things done, with no excuses.
迄今为止我见过最霸道的雇佣协议是亚马逊的。除了通常的关于拥有你的想法的条款外,你还不能成为一家有其他亚马逊前员工联合创始人的初创公司的创始人——即使你不认识他们,甚至没有同时在那里工作过。我怀疑他们很难执行这一点,但他们甚至尝试这样做就是个不好的信号。还有很多其他地方可以工作;你不妨选择一个让你保留更多选择的地方。
说到工作的好地方,当然还有谷歌。但我注意到谷歌有一点令人不安:那里没有诞生任何初创公司。在这方面,它是个黑洞。人们似乎太喜欢在谷歌工作而不愿离开。所以如果你希望有一天创业,目前的证据表明你不应该在那里工作。
The other thing you get from work experience is an understanding of what work is, and in particular, how intrinsically horrible it is. Fundamentally the equation is a brutal one: you have to spend most of your waking hours doing stuff someone else wants, or starve. There are a few places where the work is so interesting that this is concealed, because what other people want done happens to coincide with what you want to work on. But you only have to imagine what would happen if they diverged to see the underlying reality. It's not so much that adults lie to kids about this as never explain it. They never explain what the deal is with money. You know from an early age that you'll have some sort of job, because everyone asks what you're going to "be" when you grow up. What they don't tell you is that as a kid you're sitting on the shoulders of someone else who's treading water, and that starting working means you get thrown into the water on your own, and have to start treading water yourself or sink. "Being" something is incidental; the immediate problem is not to drown. The relationship between work and money tends to dawn on you only gradually. At least it did for me. One's first thought tends to be simply "This sucks. I'm in debt. Plus I have to get up on monday and go to work." Gradually you realize that these two things are as tightly connected as only a market can make them. So the most important advantage 24 year old founders have over 20 year old founders is that they know what they're trying to avoid. To the average undergrad the idea of getting rich translates into buying Ferraris, or being admired. To someone who has learned from experience about the relationship between money and work, it translates to something way more important: it means you get to opt out of the brutal equation that governs the lives of 99.9% of people. Getting rich means you can stop treading water.
我意识到这听起来像奇怪的建议。如果他们让你的生活如此美好以至于你不想离开,为什么不在那里工作?因为实际上,你可能正在获得一个局部最大值。创业需要一定的激活能量。所以一个相当愉快的工作可能会让你无限期地留下来,即使离开对你来说是净收益。[4]
如果你想创业,最好的工作地点可能是另一家初创公司。除了是合适的经验外,无论如何它都会很快结束。你要么最终变得富有,问题解决;要么初创公司被收购,那时在那里工作会变得糟糕,离开会很容易;或者最有可能的是,公司倒闭,你又自由了。
你的最后一个优势——无知——听起来可能不太有用。我故意用了一个有争议的词;你也可以称之为天真。但它似乎是一种强大的力量。我的 Y Combinator 联合创始人 Jessica Livingston 即将出版一本关于初创公司创始人的访谈书,我在其中注意到一个显著的模式。一个接一个的创始人说,如果他们早知道创业有多难,他们会因为害怕而不敢开始。
Someone who gets this will work much harder at making a startup succeed—with the proverbial energy of a drowning man, in fact. But understanding the relationship between money and work also changes the way you work. You don't get money just for working, but for doing things other people want. Someone who's figured that out will automatically focus more on the user. And that cures the other half of the class-project syndrome. After you've been working for a while, you yourself tend to measure what you've done the same way the market does. Of course, you don't have to spend years working to learn this stuff. If you're sufficiently perceptive you can grasp these things while you're still in school. Sam Altman did. He must have, because Loopt is no class project. And as his example suggests, this can be valuable knowledge. At a minimum, if you get this stuff, you already have most of what you gain from the "work experience" employers consider so desirable. But of course if you really get it, you can use this information in a way that's more valuable to you than that. Now So suppose you think you might start a startup at some point, either when you graduate or a few years after. What should you do now? For both jobs and grad school, there are ways to prepare while you're in college. If you want to get a job when you graduate, you should get summer jobs at places you'd like to work. If you want to go to grad school, it will help to work on research projects as an undergrad. What's the equivalent for startups? How do you keep your options maximally open? One thing you can do while you're still in school is to learn how startups work. Unfortunately that's not easy. Few if any colleges have classes about startups. There may be business school classes on entrepreneurship, as they call it over there, but these are likely to be a waste of time.
当无知可以抵消其他形式的愚蠢时,它是有用的。它在创业中有用,因为你的能力比你意识到的更强。创业比你预期的更难,但你的能力也比你预期的更强,所以它们会相互抵消。
大多数人看着像苹果这样的公司会想,我怎么可能做出这样的东西?苹果是一个机构,而我仅仅是一个人。但每个机构都曾经只是房间里几个人决定开始做某事。机构是由人组成的,而这些人和你没什么不同。
我不是说每个人都能创业。我确信大多数人不能;我对大众了解不多。但对于我熟悉的群体,比如黑客,我可以更精确地说。在顶尖学校,我猜多达四分之一的计算机科学专业学生如果愿意,可以成为成功的初创公司创始人。
Business schools like to talk about startups, but philosophically they're at the opposite end of the spectrum. Most books on startups also seem to be useless. I've looked at a few and none get it right. Books in most fields are written by people who know the subject from experience, but for startups there's a unique problem: by definition the founders of successful startups don't need to write books to make money. As a result most books on the subject end up being written by people who don't understand it. So I'd be skeptical of classes and books. The way to learn about startups is by watching them in action, preferably by working at one. How do you do that as an undergrad? Probably by sneaking in through the back door. Just hang around a lot and gradually start doing things for them. Most startups are (or should be) very cautious about hiring. Every hire increases the burn rate, and bad hires early on are hard to recover from. However, startups usually have a fairly informal atmosphere, and there's always a lot that needs to be done. If you just start doing stuff for them, many will be too busy to shoo you away. You can thus gradually work your way into their confidence, and maybe turn it into an official job later, or not, whichever you prefer. This won't work for all startups, but it would work for most I've known. Number two, make the most of the great advantage of school: the wealth of co-founders. Look at the people around you and ask yourself which you'd like to work with. When you apply that test, you may find you get surprising results. You may find you'd prefer the quiet guy you've mostly ignored to someone who seems impressive but has an attitude to match. I'm not suggesting you suck up to people you don't really like because you think one day they'll be successful. Exactly the opposite, in fact: you should only start a startup with someone you like, because a startup will put your friendship through a stress test.
“如果愿意”是一个重要的限定条件——重要到几乎可以说是作弊——因为一旦你超过某个智力门槛(大多数顶尖学校的计算机科学专业学生都超过了),决定你能否成为成功创始人的因素就是你有多想成功。你不必那么聪明。如果你不是天才,就在一些不那么性感的领域创业,比如人力资源部门的软件,这样竞争会更少。我随机选了这个例子,但我可以安全地预测,无论他们现在有什么,做得更好并不需要天才。有很多人在做无聊的事情,他们迫切需要更好的软件,所以无论你认为自己比拉里和谢尔盖差多少,你都可以通过降低想法的酷炫程度来弥补。
除了防止你被吓倒,无知有时还能帮助你发现新想法。Steve Wozniak 对此说得非常明确:
I'm just saying you should think about who you really admire and hang out with them, instead of whoever circumstances throw you together with. Another thing you can do is learn skills that will be useful to you in a startup. These may be different from the skills you'd learn to get a job. For example, thinking about getting a job will make you want to learn programming languages you think employers want, like Java and C++. Whereas if you start a startup, you get to pick the language, so you have to think about which will actually let you get the most done. If you use that test you might end up learning Ruby or Python instead. But the most important skill for a startup founder isn't a programming technique. It's a knack for understanding users and figuring out how to give them what they want. I know I repeat this, but that's because it's so important. And it's a skill you can learn, though perhaps habit might be a better word. Get into the habit of thinking of software as having users. What do those users want? What would make them say wow? This is particularly valuable for undergrads, because the concept of users is missing from most college programming classes. The way you get taught programming in college would be like teaching writing as grammar, without mentioning that its purpose is to communicate something to an audience. Fortunately an audience for software is now only an http request away. So in addition to the programming you do for your classes, why not build some kind of website people will find useful? At the very least it will teach you how to write software with users.
我在苹果公司做过的最棒的事情都源于两点:(a) 没有钱,(b) 以前从未做过。我们推出的每一个真正伟大的产品,都是我人生中从未涉足过的领域。
当你一无所知时,就必须自己重新发明一切。如果你足够聪明,你的新发明可能比前人的更好。这在规则不断变化的领域尤为明显。我们所有关于软件的认知都形成于处理器缓慢、内存和磁盘微小的年代。谁知道传统智慧中隐藏着多少过时的假设?而这些假设的修正方式并非通过显式释放,而是更类似于垃圾回收机制——某个无知但聪明的人会重新发明一切,并在过程中自然淘汰某些现有观念。
劣势 年轻创始人的优势已如上述,那么劣势呢?我将从问题表象出发,追溯其根源。 年轻创始人常犯的错误是做出像课堂作业般的作品。我们近期才意识到这点:那些发展滞后的初创公司存在惊人相似性,却难以言明。最终我们明白——他们在制作课堂作业。 但这意味着什么?课堂作业的缺陷何在?与真实创业的本质区别是什么?若能解答,不仅对潜在创业者,对所有学生都意义重大,因为这直指所谓"真实世界"的核心谜题。 课堂作业缺失两大要素:(1)对真实问题的迭代定义;(2)极致投入。 前者或许不可避免。课堂作业必然解决虚假问题——真实问题本就稀缺珍贵。若教授要求学生解决真实问题,就会陷入类似"寻找超越标准模型的新物理范式案例"的悖论:真正的好问题无法轻易获得。 技术领域更因创业公司的进化特性而复杂化。创业者常通过演化过程发现真正该解决的问题:先有构想,实践后才发现应解决的是另一个问题。即便允许动态调整课题,大学课程也缺乏足够时间或市场压力来促成这种进化。因此课堂作业多聚焦实现环节——而这恰是创业中最次要的难题。 创业不仅需要构思与实现并行,其实现方式也截然不同——核心目的是打磨创意。初创公司前六个月的产出价值,往往仅在于证明初始想法的谬误。这种认知颠覆极具价值,当你能摆脱大众共有的错误认知时,就占据了优势地位。但课堂作业的思维截然不同:证明初始计划错误只会导致低分。你倾向于让每行代码都服务于"展示工作量"的终极目标,而非构建可废弃的中间产物。 这引出第二差异:评价标准。教授根据起点与现状的差距评分,而用户只关心现状与需求的剩余距离。市场毫不关心你付出多少努力——用户只要功能实现,否则价值归零。这正是校园与真实世界的本质区别:努力本身不产生回报。"尽力而为"根本是成人激励孩子的虚构概念,自然界本不存在。 这类善意谎言似乎对孩子有益。可悲的是毕业时没人会列出教育期间的所有谎言,你必须通过现实碰撞来破除迷思。这也解释了为何多数工作强调"工作经验"——大学时我无法理解:明明编程能力胜过许多从业者,为何还需要这种神秘经历? 如今我明白,部分困惑源于语法误导。"工作经验"听似某种机器操作或编程语言的熟练度,实则指代童年习性的祛除。 孩子的定义特征之一是易放弃。面对困难时,孩子可以哭喊"我做不到"而获得豁免。成人世界虽无人强迫,但代价是失业。在这种压力下,你会发现自己的潜力远超想象。因此雇主期待的"工作经验",本质是祛除逃避本能——培养无借口完成任务的能力。 工作经验的另一收获是理解工作本质,特别是其内在残酷性:必须用大部分清醒时间做他人要求之事,否则面临生存危机。少数幸运者能从事兴趣与生计重合的工作,但只需设想二者分离的情形,就能窥见底层真相。 成人并非刻意欺骗,而是从未解释金钱契约的实质。从小被问"长大后想成为什么",却无人告知:童年时你骑在他人肩上,而工作意味着被抛入水中独自挣扎。"成为什么"只是表象,首要问题是不被淹死。 工作与金钱的关系需要逐渐领悟。最初只会觉得"周一上班真痛苦,还有债务缠身",慢慢才意识到这两者被市场紧密捆绑。 因此24岁创始人相比20岁者的最大优势,在于清楚自己逃避的是什么。对普通本科生,"致富"意味着法拉利或崇拜;而对理解工作金钱关系的人,这代表挣脱99.9%人类受制的残酷等式——致富意味着停止踩水求生。 领悟者会以溺水者的求生欲拼命创业。这种认知还会改变工作方式:报酬不来自劳动本身,而来自满足他人需求。明白这点就会自动聚焦用户,从而治愈"课堂作业综合征"的另一半。工作一段时间后,你会自然采用市场的衡量标准。 当然,不必经年累月才能领悟。若洞察力足够,在校期间即可掌握——Sam Altman就是例证,否则Loopt不会超越课堂作业。如他所示,这种认知极具价值。至少,明白这些就获得了雇主推崇的"工作经验"之精髓。而若真正领悟,你能以此创造更大价值。
In the best case, it might not just be preparation for a startup, but the startup itself, like it was for Yahoo and Google. Notes [1] Even the desire to protect one's children seems weaker, judging from things people have historically done to their kids rather than risk their community's disapproval. (I assume we still do things that will be regarded in the future as barbaric, but historical abuses are easier for us to see.) [2] Worrying that Y Combinator makes founders move for 3 months also suggests one underestimates how hard it is to start a startup. You're going to have to put up with much greater inconveniences than that. [3] Most employee agreements say that any idea relating to the company's present or potential future business belongs to them. Often as not the second clause could include any possible startup, and anyone doing due diligence for an investor or acquirer will assume the worst. To be safe either (a) don't use code written while you were still employed in your previous job, or (b) get your employer to renounce, in writing, any claim to the code you write for your side project. Many will consent to (b) rather than lose a prized employee. The downside is that you'll have to tell them exactly what your project does. [4] Geshke and Warnock only founded Adobe because Xerox ignored them. If Xerox had used what they built, they would probably never have left PARC. Thanks to Jessica Livingston and Robert Morris for reading drafts of this, and to Jeff Arnold and the SIPB for inviting me to speak. [](http://reddit.com) Comment on this essay.
| Chinese Translation | | | Arabic Translation.
当下 若你考虑毕业后或数年内创业,现在该做什么?求职或读研都有明确准备路径:心仪公司的暑期实习,或本科参与科研项目。创业的等效准备是什么?如何最大化保持选择权? 在校期间可学习创业运作机制。可惜这并不容易——几乎没有高校开设创业课程。商学院所谓的" entrepreneurship"课程多半浪费时间,因其理念与创业本质相悖。多数创业书籍同样无用,成功创业者无需靠写书谋生,导致该领域书籍多由外行撰写。 建议对课程和书籍保持怀疑。了解创业的最佳方式是观察实践,最好是参与其中。本科生如何做到?不妨走后门:频繁出现并主动帮忙。初创公司(理当)对招聘极为谨慎——早期错误聘用代价沉重。但创业公司氛围松散且事务繁杂,若你持续贡献价值,多数团队无暇驱赶。由此逐步建立信任,未来或可转为正式成员。此策略对多数初创公司有效。 第二,善用学校的核心优势:联合创始人资源库。观察周围同学,自问愿与谁共事。这个测试可能带来意外发现——那个被忽视的安静者或许比傲慢的"明星"更合适。绝非建议讨好你认为会成功的人,恰恰相反:创业将考验友谊极限,必须选择真心喜爱的人合作。关键是主动选择真正钦佩的伙伴,而非被动接受随机社交圈。 第三,学习创业所需的特殊技能。这与求职技能可能不同:求职者会学Java/C++等"雇主需求"语言,而创业者需选择最高效的工具(如Ruby/Python)。 但创始人最重要的技能非编程技术,而是理解用户需求的本能。我反复强调这点,因其至关重要。这是可习得的技能(或更准确说是习惯):培养"软件必有用户"的思维惯性——用户要什么?什么会让他们惊叹? 这对本科生尤为珍贵,因为大学编程课普遍缺失"用户"概念。传统教学像只教语法不提沟通目的的写作课。幸运的是,如今软件受众仅需一次http请求即可触达。除了课程作业,何不构建真正有用的网站?至少能学习为用户写代码,最佳情况下可能直接成为创业项目——正如Yahoo和Google的起源。
注释 [1] 历史上人们为避社群非议甚至不惜伤害子女(当今必有未来视为野蛮的行为),可见保护子女的欲望也非绝对。 [2] 若嫌YC要求创始人搬迁三个月太苛刻,说明低估了创业难度——未来你要忍受更大不便。 [3] 多数雇佣协议声明:凡涉及公司现有/潜在业务的创意均归公司所有。投资者尽调时往往做最坏推定。 安全做法:a) 不使用离职前编写的代码;b) 获取雇主对副业代码的书面弃权声明。许多雇主会选择b)而非失去优秀员工,但需披露项目细节。 [4] Adobe的创立只因施乐忽视Geschke和Warnock的成果——若施乐采用他们的发明,二人可能永不会离开帕洛阿尔托研究中心。
致谢 Jessica Livingston和Robert Morris审阅本文草稿,Jeff Arnold及SIPB邀请演讲。
[](https://s.turbifycdn.com/aah/paulgraham/how-to-present-to-investors-11.gif) Want to start a startup? Get funded by Y Combinator.
August 2006, rev. April 2007, September 2010 In a few days it will be Demo Day, when the startups we funded this summer present to investors. Y Combinator funds startups twice a year, in January and June. Ten weeks later we invite all the investors we know to hear them present what they've built so far. Ten weeks is not much time. The average startup probably doesn't have much to show for itself after ten weeks. But the average startup fails. When you look at the ones that went on to do great things, you find a lot that began with someone pounding out a prototype in a week or two of nonstop work. Startups are a counterexample to the rule that haste makes waste. (Too much money seems to be as bad for startups as too much time, so we don't give them much money either.) A week before Demo Day, we have a dress rehearsal called Rehearsal Day. At other Y Combinator events we allow outside guests, but not at Rehearsal Day. No one except the other founders gets to see the rehearsals. The presentations on Rehearsal Day are often pretty rough. But this is to be expected. We try to pick founders who are good at building things, not ones who are slick presenters. Some of the founders are just out of college, or even still in it, and have never spoken to a group of people they didn't already know. So we concentrate on the basics. On Demo Day each startup will only get ten minutes, so we encourage them to focus on just two goals: (a) explain what you're doing, and (b) explain why users will want it. That might sound easy, but it's not when the speakers have no experience presenting, and they're explaining technical matters to an audience that's mostly non-technical.
This situation is constantly repeated when startups present to investors: people who are bad at explaining, talking to people who are bad at understanding. Practically every successful startup, including stars like Google, presented at some point to investors who didn't get it and turned them down. Was it because the founders were bad at presenting, or because the investors were obtuse? It's probably always some of both. At the most recent Rehearsal Day, we four Y Combinator partners found ourselves saying a lot of the same things we said at the last two. So at dinner afterward we collected all our tips about presenting to investors. Most startups face similar challenges, so we hope these will be useful to a wider audience. 1\. Explain what you're doing. Investors' main question when judging a very early startup is whether you've made a compelling product. Before they can judge whether you've built a good x, they have to understand what kind of x you've built. They will get very frustrated if instead of telling them what you do, you make them sit through some kind of preamble. Say what you're doing as soon as possible, preferably in the first sentence. "We're Jeff and Bob and we've built an easy to use web-based database. Now we'll show it to you and explain why people need this." If you're a great public speaker you may be able to violate this rule. Last year one founder spent the whole first half of his talk on a fascinating analysis of the limits of the conventional desktop metaphor. He got away with it, but unless you're a captivating speaker, which most hackers aren't, it's better to play it safe. 2\. Get rapidly to demo. _This section is now obsolete for YC founders presenting at Demo Day, because Demo Day presentations are now so short that they rarely include much if any demo.
They seem to work just as well without, however, which makes me think I was wrong to emphasize demos so much before._ A demo explains what you've made more effectively than any verbal description. The only thing worth talking about first is the problem you're trying to solve and why it's important. But don't spend more than a tenth of your time on that. Then demo. When you demo, don't run through a catalog of features. Instead start with the problem you're solving, and then show how your product solves it. Show features in an order driven by some kind of purpose, rather than the order in which they happen to appear on the screen. If you're demoing something web-based, assume that the network connection will mysteriously die 30 seconds into your presentation, and come prepared with a copy of the server software running on your laptop. 3\. Better a narrow description than a vague one. One reason founders resist describing their projects concisely is that, at this early stage, there are all kinds of possibilities. The most concise descriptions seem misleadingly narrow. So for example a group that has built an easy web-based database might resist calling their applicaton that, because it could be so much more. In fact, it could be anything... The problem is, as you approach (in the calculus sense) a description of something that could be anything, the content of your description approaches zero. If you describe your web-based database as "a system to allow people to collaboratively leverage the value of information," it will go in one investor ear and out the other. They'll just discard that sentence as meaningless boilerplate, and hope, with increasing impatience, that in the next sentence you'll actually explain what you've made. Your primary goal is not to describe everything your system might one day become, but simply to convince investors you're worth talking to further.
So approach this like an algorithm that gets the right answer by successive approximations. Begin with a description that's gripping but perhaps overly narrow, then flesh it out to the extent you can. It's the same principle as incremental development: start with a simple prototype, then add features, but at every point have working code. In this case, "working code" means a working description in the investor's head. 4\. Don't talk and drive. Have one person talk while another uses the computer. If the same person does both, they'll inevitably mumble downwards at the computer screen instead of talking clearly at the audience. As long as you're standing near the audience and looking at them, politeness (and habit) compel them to pay attention to you. Once you stop looking at them to fuss with something on your computer, their minds drift off to the errands they have to run later. 5\. Don't talk about secondary matters at length. If you only have a few minutes, spend them explaining what your product does and why it's great. Second order issues like competitors or resumes should be single slides you go through quickly at the end. If you have impressive resumes, just flash them on the screen for 15 seconds and say a few words. For competitors, list the top 3 and explain in one sentence each what they lack that you have. And put this kind of thing at the end, after you've made it clear what you've built. 6\. Don't get too deeply into business models. It's good to talk about how you plan to make money, but mainly because it shows you care about that and have thought about it. Don't go into detail about your business model, because (a) that's not what smart investors care about in a brief presentation, and (b) any business model you have at this point is probably wrong anyway. Recently a VC who came to speak at Y Combinator talked about a company he just invested in.
He said their business model was wrong and would probably change three times before they got it right. The founders were experienced guys who'd done startups before and who'd just succeeded in getting millions from one of the top VC firms, and even their business model was crap. (And yet he invested anyway, because he expected it to be crap at this stage.) If you're solving an important problem, you're going to sound a lot smarter talking about that than the business model. The business model is just a bunch of guesses, and guesses about stuff that's probably not your area of expertise. So don't spend your precious few minutes talking about crap when you could be talking about solid, interesting things you know a lot about: the problem you're solving and what you've built so far. As well as being a bad use of time, if your business model seems spectacularly wrong, that will push the stuff you want investors to remember out of their heads. They'll just remember you as the company with the boneheaded plan for making money, rather than the company that solved that important problem. 7\. Talk slowly and clearly at the audience. Everyone at Rehearsal Day could see the difference between the people who'd been out in the world for a while and had presented to groups, and those who hadn't. You need to use a completely different voice and manner talking to a roomful of people than you would in conversation. Everyday life gives you no practice in this. If you can't already do it, the best solution is to treat it as a consciously artificial trick, like juggling. However, that doesn't mean you should talk like some kind of announcer. Audiences tune that out. What you need to do is talk in this artificial way, and yet make it seem conversational. (Writing is the same. Good writing is an elaborate effort to seem spontaneous.) If you want to write out your whole presentation beforehand and memorize it, that's ok.
[](https://s.turbifycdn.com/aah/paulgraham/how-to-present-to-investors-11.gif) 想创业? 获得Y Combinator的资助。
2006年8月,2007年4月修订,2010年9月修订 再过几天就是演示日(Demo Day)了,这是我们今年夏天资助的初创公司向投资者展示成果的日子。Y Combinator每年一月和六月分两次资助初创公司。十周后,我们会邀请所有认识的投资者来听取他们的进展汇报。 十周时间并不长。普通初创公司在十周后可能拿不出多少成果。但普通初创公司往往会失败。当你观察那些最终取得巨大成功的公司时,会发现很多都是在创始人一两周不眠不休敲出原型后起步的。初创公司是"欲速则不达"这条规则的反例。 (过多的资金对初创公司来说似乎和过多的时间一样有害,所以我们也不会给他们太多钱。) 在演示日的前一周,我们会举行一次彩排,称为"排练日"(Rehearsal Day)。其他Y Combinator活动我们允许外部嘉宾参加,但排练日不行。除了其他创始人,没人能看到彩排。 排练日的演示往往相当粗糙。但这在意料之中。我们挑选的创始人擅长构建产品,而非擅长演讲。有些创始人刚大学毕业,甚至还在校读书,从未向一群陌生人发表过讲话。 因此我们专注于基础事项。演示日上每家初创公司只有十分钟时间,所以我们鼓励他们聚焦两个目标:(a) 解释你们在做什么;(b) 解释用户为什么需要它。 这听起来可能很简单,但当演讲者缺乏经验,且要向非技术背景的听众解释技术问题时,就并非易事了。 初创公司向投资者演示时,这种情况不断重演:不擅长解释的人向不擅长理解的人讲述。几乎所有成功的初创公司,包括谷歌这样的明星企业,都曾向不理解他们而拒绝投资的投资者做过演示。是因为创始人不擅长演讲,还是因为投资者愚钝?可能两方面原因都有。 在最近的排练日上,我们四位Y Combinator合伙人发现自己重复说了前两次说过的话。于是在之后的晚餐中,我们整理了所有关于向投资者演示的建议。大多数初创公司面临类似的挑战,因此我们希望这些建议对更广泛的受众有所帮助。 1. 解释你们在做什么 投资者评判早期初创公司时,主要问题是你们是否做出了令人信服的产品。在他们判断你们是否做出了一个好的x之前,他们需要先理解你们做的是哪种x。如果你们不直接告诉他们你们在做什么,而是让他们听完某种开场白,他们会非常沮丧。 尽快说明你们在做什么,最好在第一句话中就说明。"我们是Jeff和Bob,我们开发了一个易于使用的基于网络的数据库。现在我们将向您展示它,并解释人们为什么需要它。" 如果你是一位出色的公共演讲者,或许可以违反这条规则。去年有一位创始人花了演讲的前半部分时间,对传统桌面隐喻的局限性进行了引人入胜的分析。他成功了,但除非你是一位引人入胜的演讲者(大多数黑客都不是),否则最好稳妥行事。 2. 快速进入演示环节 _本节对在演示日演讲的YC创始人已过时,因为现在的演示日演讲时间非常短,很少包含大量演示内容。然而,没有演示似乎效果同样好,这让我觉得之前过分强调演示是错误的。_ 演示比任何口头描述都更能有效说明你们做出了什么。唯一值得先谈论的是你们试图解决的问题及其重要性。但不要在这上面花费超过十分之一的时间。然后开始演示。 演示时,不要逐一罗列功能。而是从你们解决的问题开始,然后展示你们的产品如何解决它。按照某种目的驱动的顺序展示功能,而不是按照它们恰好在屏幕上出现的顺序。 如果你们演示的是基于网络的产品,假设网络连接会在演讲开始30秒后神秘中断,并准备好笔记本电脑上运行的服务器软件副本。 3. 宁可描述得具体,也不要模糊 创始人抗拒简洁描述项目的一个原因是,在早期阶段,存在各种可能性。最简洁的描述似乎会误导性地显得过于狭窄。例如,一个开发了简易网络数据库的团队可能不愿这样称呼他们的应用,因为它可以做得更多。事实上,它可以是任何东西…… 问题是,当你(在数学意义上)趋近于描述一个可以是任何东西的东西时,描述的内容趋近于零。如果你将你们的网络数据库描述为"一个让人们协作利用信息价值的系统",投资者会左耳进右耳出。他们会认为这句话是毫无意义的套话,并越来越不耐烦地希望你们在下一句话中真正解释你们做出了什么。 你们的主要目标不是描述系统未来可能成为的一切,而是简单地说服投资者你们值得进一步交谈。因此,要像通过逐次逼近得到正确答案的算法一样处理这个问题。从一个引人注目但可能过于狭窄的描述开始,然后尽可能充实它。这与增量开发的原则相同:从一个简单的原型开始,然后添加功能,但在每一步都有可运行的代码。在这里,"可运行的代码"意味着投资者头脑中可运行的描述。 4. 不要边讲边操作 让一个人讲解,另一个人操作电脑。如果同一个人做这两件事,他们不可避免地会对着电脑屏幕含糊低语,而不是清晰地面对观众讲话。 只要你站在观众附近并看着他们,礼貌(和习惯)会迫使他们注意你。一旦你停止看他们,转而摆弄电脑上的东西,他们的思绪就会飘到之后要办的事情上。 5. 不要过多谈论次要事项 如果你们只有几分钟时间,就用它来解释你们的产品是什么以及它为什么很棒。竞争对手或简历等次要问题应该是最后快速浏览的单张幻灯片。如果你们的简历令人印象深刻,只需在屏幕上展示15秒并简单说几句。对于竞争对手,列出前三名,并用一句话分别说明他们缺少什么而你们拥有。将这类内容放在最后,在你们清楚地说明你们做出了什么之后。 6. 不要过于深入商业模式 谈论你们计划如何赚钱是好的,但主要是因为这表明你们关心这一点并思考过它。不要详细讨论你们的商业模式,因为(a) 聪明的投资者在简短演示中不关心这一点,(b) 你们此时的任何商业模式可能都是错的。 最近一位来Y Combinator演讲的风投谈到他刚投资的一家公司。他说他们的商业模式是错的,可能会在找到正确的之前改变三次。创始人是经验丰富的人,之前创过业,并成功从顶级风投公司之一获得了数百万资金,但即使他们的商业模式也很糟糕。(然而他还是投资了,因为他预计在这个阶段它是糟糕的。) 如果你们正在解决一个重要问题,谈论这个问题会比谈论商业模式显得聪明得多。商业模式只是一堆猜测,而且可能是关于你们专业领域之外的猜测。所以不要用宝贵的几分钟谈论糟糕的东西,而应该谈论你们了解的具体、有趣的事情:你们正在解决的问题以及你们目前做出的成果。 除了浪费时间外,如果你们的商业模式看起来明显错误,这会把你们希望投资者记住的内容挤出他们的脑海。他们只会记住你们是一家有愚蠢赚钱计划的公司,而不是一家解决了那个重要问题的公司。 7. 面向观众,缓慢清晰地讲话 排练日的每个人都看得出哪些人曾在外界打拼过并向群体演讲过,哪些人没有。 向满屋子的人讲话需要使用与对话完全不同的声音和方式。日常生活中你们没有这方面的练习。如果你们还不会这样做,最好的解决办法是将其视为一种有意识的人工技巧,就像杂耍一样。 然而,这并不意味着你们应该像某种播音员一样讲话。观众会忽略这种讲话。你们需要做的是以这种人工的方式讲话,同时让它显得像对话。(写作也是如此。好的写作是看似自然的精心努力。) 如果你们想事先写出整个演讲并记住它,那没问题。过去有些团队这样做过。但要确保写出听起来像自发、非正式演讲的内容,并以这种方式表达。 宁可讲得慢一些。在排练日,一位创始人提到演员使用的一条规则:如果你觉得自己讲得太慢,那么你的速度大概正合适。 8. 让一个人主讲 初创公司通常希望展示所有创始人都是平等的合伙人。这是一种好的本能;投资者不喜欢不平衡的团队。但试图通过分配演讲时间来展示这一点就过头了。这会分散注意力。你们可以通过更微妙的方式展示彼此的尊重。例如,当一组人在演示日演讲时,两位创始人中更外向的那位做了大部分讲解,但他称他的联合创始人是自己见过的最好的黑客,而且你能看出他是认真的。 挑选一位或最多两位最好的演讲者,让他们负责大部分讲解。 例外:如果一位创始人是某个特定技术领域的专家,让他们谈论这一分钟可能是好的。这种"专家证人"可以增加可信度,即使观众不理解所有细节。如果乔布斯和沃兹尼亚克有十分钟来展示Apple II,一个好的计划可能是乔布斯讲九分钟,沃兹在中间讲一分钟他在设计中实现的一些技术壮举。(当然,如果是他们两位,乔布斯会讲满十分钟。) 9. 显得自信 由于时间短暂且缺乏技术背景,观众中的许多人将难以评估你们在做什么。最初,最大的证据可能就是你们自己对它的信心。你们必须展示出对自己成果的印象深刻。 我的意思是展示,而不是告诉。永远不要说"我们充满激情"或"我们的产品很棒"。人们会忽略这种话——或者更糟,认为你们是胡说八道的人。这样的信息必须是隐含的。 你们绝不能显得紧张和歉意。如果你们真的做出了好东西,告诉他们是在帮他们的忙。如果你们不真心相信这一点,也许你们应该改变公司正在做的事情。如果你们不认为自己的初创公司有足够的潜力,以至于让他们投资是在帮他们的忙,那你们为什么要把时间投入其中? 10. 不要试图显得超出你们的实际 不要担心你们的公司才成立几个月还没有办公室,或者你们的创始人是没有商业经验的技术人员。谷歌曾经也是这样,他们后来发展得很好。聪明的投资者能看透这些表面缺陷。他们寻找的不是完美、流畅的演讲。他们寻找的是原始才华。你们需要说服他们的只是你们很聪明,并且正在做一件好事。如果你们过于努力地掩饰自己的不成熟——试图显得公司化,或假装了解你们不了解的东西——你们可能只会掩盖自己的才华。 你们可以坦率地承认尚未解决的问题。不要刻意提起(例如用一张幻灯片说明可能出错的地方),但也不要假装比实际进展更远。如果你们是黑客,向经验丰富的投资者演讲,他们可能比你们更擅长识破胡说八道。 11. 不要在幻灯片上放太多文字 当幻灯片上有大量文字时,人们会直接跳过阅读。所以检查你们的幻灯片,对每个词问"我可以划掉这个吗?"这包括多余的剪贴画。尽量将幻灯片控制在20个词以内。 不要读幻灯片。它们应该是你们面向观众讲话时的背景内容,而不是你们面对并读给坐在身后的观众的东西。 杂乱的网站在演示中效果不好,尤其是投影到屏幕上时。至少,将字体调大到所有文字都清晰可读。但杂乱的网站本身就不.
That has worked for some groups in the past. But make sure to write something that sounds like spontaneous, informal speech, and deliver it that way too. Err on the side of speaking slowly. At Rehearsal Day, one of the founders mentioned a rule actors use: if you feel you're speaking too slowly, you're speaking at about the right speed. 8\. Have one person talk. Startups often want to show that all the founders are equal partners. This is a good instinct; investors dislike unbalanced teams. But trying to show it by partitioning the presentation is going too far. It's distracting. You can demonstrate your respect for one another in more subtle ways. For example, when one of the groups presented at Demo Day, the more extroverted of the two founders did most of the talking, but he described his co-founder as the best hacker he'd ever met, and you could tell he meant it. Pick the one or at most two best speakers, and have them do most of the talking. Exception: If one of the founders is an expert in some specific technical field, it can be good for them to talk about that for a minute or so. This kind of "expert witness" can add credibility, even if the audience doesn't understand all the details. If Jobs and Wozniak had 10 minutes to present the Apple II, it might be a good plan to have Jobs speak for 9 minutes and have Woz speak for a minute in the middle about some of the technical feats he'd pulled off in the design. (Though of course if it were actually those two, Jobs would speak for the entire 10 minutes.) 9\. Seem confident. Between the brief time available and their lack of technical background, many in the audience will have a hard time evaluating what you're doing. Probably the single biggest piece of evidence, initially, will be your own confidence in it. You have to show you're impressed with what you've made. And I mean show, not tell.
Never say "we're passionate" or "our product is great." People just ignore that—or worse, write you off as bullshitters. Such messages must be implicit. What you must not do is seem nervous and apologetic. If you've truly made something good, you're doing investors a _favor_ by telling them about it. If you don't genuinely believe that, perhaps you ought to change what your company is doing. If you don't believe your startup has such promise that you'd be doing them a favor by letting them invest, why are you investing your time in it? 10\. Don't try to seem more than you are. Don't worry if your company is just a few months old and doesn't have an office yet, or your founders are technical people with no business experience. Google was like that once, and they turned out ok. Smart investors can see past such superficial flaws. They're not looking for finished, smooth presentations. They're looking for raw talent. All you need to convince them of is that you're smart and that you're onto something good. If you try too hard to conceal your rawness—by trying to seem corporate, or pretending to know about stuff you don't—you may just conceal your talent. You can afford to be candid about what you haven't figured out yet. Don't go out of your way to bring it up (e.g. by having a slide about what might go wrong), but don't try to pretend either that you're further along than you are. If you're a hacker and you're presenting to experienced investors, they're probably better at detecting bullshit than you are at producing it. 11\. Don't put too many words on slides. When there are a lot of words on a slide, people just skip reading it. So look at your slides and ask of each word "could I cross this out?" This includes gratuitous clip art. Try to get your slides under 20 words if you can. Don't read your slides.
They should be something in the background as you face the audience and talk to them, not something you face and read to an audience sitting behind you. Cluttered sites don't do well in demos, especially when they're projected onto a screen. At the very least, crank up the font size big enough to make all the text legible. But cluttered sites are bad anyway, so perhaps you should use this opportunity to make your design simpler. 12\. Specific numbers are good. If you have any kind of data, however preliminary, tell the audience. Numbers stick in people's heads. If you can claim that the median visitor generates 12 page views, that's great. But don't give them more than four or five numbers, and only give them numbers specific to you. You don't need to tell them the size of the market you're in. Who cares, really, if it's 500 million or 5 billion a year? Talking about that is like an actor at the beginning of his career telling his parents how much Tom Hanks makes. Yeah, sure, but first you have to become Tom Hanks. The important part is not whether he makes ten million a year or a hundred, but how you get there. 13\. Tell stories about users. The biggest fear of investors looking at early stage startups is that you've built something based on your own a priori theories of what the world needs, but that no one will actually want. So it's good if you can talk about problems specific users have and how you solve them. Greg Mcadoo said one thing Sequoia looks for is the "proxy for demand." What are people doing now, using inadequate tools, that shows they need what you're making? Another sign of user need is when people pay a lot for something. It's easy to convince investors there will be demand for a cheaper alternative to something popular, if you preserve the qualities that made it popular. The best stories about user needs are about your own.
A remarkable number of famous startups grew out of some need the founders had: Apple, Microsoft, Yahoo, Google. Experienced investors know that, so stories of this type will get their attention. The next best thing is to talk about the needs of people you know personally, like your friends or siblings. 14\. Make a soundbite stick in their heads. Professional investors hear a lot of pitches. After a while they all blur together. The first cut is simply to be one of those they remember. And the way to ensure that is to create a descriptive phrase about yourself that sticks in their heads. In Hollywood, these phrases seem to be of the form "x meets y." In the startup world, they're usually "the x of y" or "the x y." Viaweb's was "the Microsoft Word of ecommerce." Find one and launch it clearly (but apparently casually) in your talk, preferably near the beginning. It's a good exercise for you, too, to sit down and try to figure out how to describe your startup in one compelling phrase. If you can't, your plans may not be sufficiently focused.
| How to Fund a Startup | | | Hackers' Guide to Investors | Spanish Translation | | | Japanese Translation | Russian Translation.
Image: Casey Muller: Trevor Blackwell at Rehearsal Day, summer 2006
图片:Casey Muller:Trevor Blackwell在2006年夏季的排练日
[](https://s.turbifycdn.com/aah/paulgraham/copy-what-you-like-11.gif) July 2006 When I was in high school I spent a lot of time imitating bad writers. What we studied in English classes was mostly fiction, so I assumed that was the highest form of writing. Mistake number one. The stories that seemed to be most admired were ones in which people suffered in complicated ways. Anything funny or gripping was ipso facto suspect, unless it was old enough to be hard to understand, like Shakespeare or Chaucer. Mistake number two. The ideal medium seemed the short story, which I've since learned had quite a brief life, roughly coincident with the peak of magazine publishing. But since their size made them perfect for use in high school classes, we read a lot of them, which gave us the impression the short story was flourishing. Mistake number three. And because they were so short, nothing really had to happen; you could just show a randomly truncated slice of life, and that was considered advanced. Mistake number four. The result was that I wrote a lot of stories in which nothing happened except that someone was unhappy in a way that seemed deep. For most of college I was a philosophy major. I was very impressed by the papers published in philosophy journals. They were so beautifully typeset, and their tone was just captivating—alternately casual and buffer-overflowingly technical. A fellow would be walking along a street and suddenly modality qua modality would spring upon him. I didn't ever quite understand these papers, but I figured I'd get around to that later, when I had time to reread them more closely. In the meantime I tried my best to imitate them. This was, I can now see, a doomed undertaking, because they weren't really saying anything. No philosopher ever refuted another, for example, because no one said anything definite enough to refute. Needless to say, my imitations didn't say anything either.
[](https://s.turbifycdn.com/aah/paulgraham/copy-what-you-like-11.gif)
高中时,我花了大量时间模仿糟糕的作家。英语课上我们学的主要是小说,于是我认为那是写作的最高形式——这是第一个错误。那些最受推崇的故事,往往描写人物以复杂的方式受苦。任何有趣或引人入胜的内容反而会被质疑,除非它古老得难以理解,比如莎士比亚或乔叟的作品——这是第二个错误。理想的体裁似乎是短篇小说,后来我才知道这种形式寿命极短,大致与杂志出版的黄金时代重合。但由于其篇幅完美契合课堂使用,我们读了大量短篇,误以为这种文体正在蓬勃发展——这是第三个错误。又因为它们过于简短,故事根本无需真正展开;只需随意截取生活的片段,就被视为高级——这是第四个错误。结果我写了许多故事,其中除了某人陷入看似深刻的痛苦外,什么也没发生。
大学期间我主修哲学,曾被哲学期刊上的论文深深震撼。它们排版精美,语调迷人——时而随意,时而堆砌晦涩术语。比如某人走在街上,突然被"模态作为模态"的概念击中。我从未真正读懂这些论文,但总想着以后有空再细读。与此同时,我竭力模仿它们。如今看来这注定失败,因为它们实则言之无物。从未有哲学家真正驳倒过同行,因为没人提出明确到可被反驳的观点。自然,我的仿作也同样空洞。
研究生时期我仍在错误模仿上浪费时间。当时流行一种叫"专家系统"的程序,其核心是"推理引擎"。我看过功能后心想:"这玩意儿一千行代码就能写出来。"然而知名教授们为其著书立说,创业公司以年薪的价格售卖。我暗自窃喜:这些令人敬畏的东西对我如此简单,我必定天赋异禀——大错特错。这只是场风潮。教授们关于专家系统的著作早已无人问津,它们甚至未曾通向任何有趣的方向。而那些高价采购的客户,多半和花数千美元买螺丝刀与马桶座的政府机构是同一批人。
如何避免模仿错误对象?只模仿你真心喜爱的事物。这个原则本可挽救我所有三次失误。我不喜欢英语课要求的短篇小说,未从哲学论文中获得启发,自己也从未使用过专家系统。我推崇它们只因它们备受推崇。
In grad school I was still wasting time imitating the wrong things. There was then a fashionable type of program called an expert system, at the core of which was something called an inference engine. I looked at what these things did and thought "I could write that in a thousand lines of code." And yet eminent professors were writing books about them, and startups were selling them for a year's salary a copy. What an opportunity, I thought; these impressive things seem easy to me; I must be pretty sharp. Wrong. It was simply a fad. The books the professors wrote about expert systems are now ignored. They were not even on a _path_ to anything interesting. And the customers paying so much for them were largely the same government agencies that paid thousands for screwdrivers and toilet seats. How do you avoid copying the wrong things? Copy only what you genuinely like. That would have saved me in all three cases. I didn't enjoy the short stories we had to read in English classes; I didn't learn anything from philosophy papers; I didn't use expert systems myself. I believed these things were good because they were admired. It can be hard to separate the things you like from the things you're impressed with. One trick is to ignore presentation. Whenever I see a painting impressively hung in a museum, I ask myself: how much would I pay for this if I found it at a garage sale, dirty and frameless, and with no idea who painted it? If you walk around a museum trying this experiment, you'll find you get some truly startling results. Don't ignore this data point just because it's an outlier. Another way to figure out what you like is to look at what you enjoy as guilty pleasures. Many things people like, especially if they're young and ambitious, they like largely for the feeling of virtue in liking them. 99% of people reading _Ulysses_ are thinking "I'm reading _Ulysses_ " as they do it. A guilty pleasure is at least a pure one.
将个人喜好与外界推崇区分开并不容易。有个诀窍是忽略呈现形式。每当看见博物馆里隆重展出的画作,我就问自己:如果在车库拍卖会发现它脏兮兮无画框,也不知作者是谁,我愿出多少钱?在博物馆进行这个实验,结果常令人震惊。别因数据异常就忽视它。
另一种方法是审视那些带负罪感的快乐。人们——尤其是年轻野心家——喜欢的许多事物,其实只是享受"喜欢它们带来的道德优越感"。99%读《尤利西斯》的人,全程都在想"我正在读《尤利西斯》"。而带负罪感的喜好至少是纯粹的。当你不想表现得高尚时会读什么?哪种书会让你因只剩半本而遗憾,而非因读了一半而自豪?那才是你真正的热爱。
即使找到真正优秀的模仿对象,还需警惕另一个陷阱:要复制其精华而非缺陷。缺陷往往更易察觉,也更容易模仿。例如18-19世纪多数画家使用棕色调,他们模仿的是文艺复兴大师——当时那些画作因积尘已呈褐色。后来原画经清洗焕发出绚丽色彩,而模仿者的作品至今仍是棕色的。
说来讽刺,是绘画治愈了我模仿错误对象的毛病。读研中途我决定尝试当画家,而艺术圈赤裸裸的腐败终于扯断了我的轻信枷锁。这帮人让哲学教授看起来像数学家般严谨。要么创作好作品,要么当圈内人,界限如此分明令我无法回避。几乎所有领域都存在这种分野,只是我此前一直逃避面对。
这是绘画教给我最宝贵的经验:你必须自行判断何为优秀。不能相信权威,他们在此事上必定撒谎。
What do you read when you don't feel up to being virtuous? What kind of book do you read and feel sad that there's only half of it left, instead of being impressed that you're half way through? That's what you really like. Even when you find genuinely good things to copy, there's another pitfall to be avoided. Be careful to copy what makes them good, rather than their flaws. It's easy to be drawn into imitating flaws, because they're easier to see, and of course easier to copy too. For example, most painters in the eighteenth and nineteenth centuries used brownish colors. They were imitating the great painters of the Renaissance, whose paintings by that time were brown with dirt. Those paintings have since been cleaned, revealing brilliant colors; their imitators are of course still brown. It was painting, incidentally, that cured me of copying the wrong things. Halfway through grad school I decided I wanted to try being a painter, and the art world was so manifestly corrupt that it snapped the leash of credulity. These people made philosophy professors seem as scrupulous as mathematicians. It was so clearly a choice of doing good work xor being an insider that I was forced to see the distinction. It's there to some degree in almost every field, but I had till then managed to avoid facing it. That was one of the most valuable things I learned from painting: you have to figure out for yourself what's good. You can't trust authorities. They'll lie to you on this one. [](http://reddit.com) Comment on this essay.
| Chinese Translation | | | Romanian Translation | Spanish Translation | | | Russian Translation.
[](https://s.turbifycdn.com/aah/paulgraham/the-island-test-11.gif) July 2006 I've discovered a handy test for figuring out what you're addicted to. Imagine you were going to spend the weekend at a friend's house on a little island off the coast of Maine. There are no shops on the island and you won't be able to leave while you're there. Also, you've never been to this house before, so you can't assume it will have more than any house might. What, besides clothes and toiletries, do you make a point of packing? That's what you're addicted to. For example, if you find yourself packing a bottle of vodka (just in case), you may want to stop and think about that. For me the list is four things: books, earplugs, a notebook, and a pen. There are other things I might bring if I thought of it, like music, or tea, but I can live without them. I'm not so addicted to caffeine that I wouldn't risk the house not having any tea, just for a weekend. Quiet is another matter. I realize it seems a bit eccentric to take earplugs on a trip to an island off the coast of Maine. If anywhere should be quiet, that should. But what if the person in the next room snored? What if there was a kid playing basketball? (Thump, thump, thump... thump.) Why risk it? Earplugs are small. Sometimes I can think with noise. If I already have momentum on some project, I can work in noisy places. I can edit an essay or debug code in an airport. But airports are not so bad: most of the noise is whitish. I couldn't work with the sound of a sitcom coming through the wall, or a car in the street playing thump-thump music. And of course there's another kind of thinking, when you're starting something new, that requires complete quiet. You never know when this will strike. It's just as well to carry plugs. The notebook and pen are professional equipment, as it were.
[](https://s.turbifycdn.com/aah/paulgraham/the-island-test-11.gif)
我发现了一个判断自己沉迷何物的实用测试。想象你要去缅因州海岸外一座小岛上的朋友家度周末。岛上没有商店,期间你无法离开。而且你从未去过这栋房子,不能预设它比普通住宅具备更多物品。
除了衣物和洗漱用品,你会特意打包什么?那就是你上瘾的东西。例如,如果你发现自己塞了一瓶伏特加(以防万一),或许该停下来反思一下。
我的清单有四样:书籍、耳塞、笔记本和钢笔。
其他如音乐或茶叶等物品,想到时我也会带上,但没有也能应付。我对咖啡因的依赖还没到为区区周末就担心房子缺茶叶的地步。
Though actually there is something druglike about them, in the sense that their main purpose is to make me feel better. I hardly ever go back and read stuff I write down in notebooks. It's just that if I can't write things down, worrying about remembering one idea gets in the way of having the next. Pen and paper wick ideas. The best notebooks I've found are made by a company called Miquelrius. I use their smallest size, which is about 2.5 x 4 in. The secret to writing on such narrow pages is to break words only when you run out of space, like a Latin inscription. I use the cheapest plastic Bic ballpoints, partly because their gluey ink doesn't seep through pages, and partly so I don't worry about losing them. I only started carrying a notebook about three years ago. Before that I used whatever scraps of paper I could find. But the problem with scraps of paper is that they're not ordered. In a notebook you can guess what a scribble means by looking at the pages around it. In the scrap era I was constantly finding notes I'd written years before that might say something I needed to remember, if I could only figure out what. As for books, I know the house would probably have something to read. On the average trip I bring four books and only read one of them, because I find new books to read en route. Really bringing books is insurance. I realize this dependence on books is not entirely good—that what I need them for is distraction. The books I bring on trips are often quite virtuous, the sort of stuff that might be assigned reading in a college class. But I know my motives aren't virtuous. I bring books because if the world gets boring I need to be able to slip into another distilled by some writer. It's like eating jam when you know you should be eating fruit. There is a point where I'll do without books.
安静则是另一回事。我明白去缅因外岛旅行还带耳塞显得古怪——那种地方本该静谧。但万一隔壁有人打鼾?万一有孩子打篮球?(砰、砰、砰...砰)何必冒险?耳塞又不占地方。
有时我能在噪音中思考。若已进入工作状态,我可以在嘈杂场所修改文章或调试代码。机场还好,多数噪音属白噪音。但情景喜剧的穿透声或街头汽车的动次打次音乐绝对不行。
而开启新项目时需要的深度思考,必须绝对安静。这种时刻难以预料,随身带耳塞总没错。
笔记本和钢笔算是职业装备,不过它们确有药物般的功效——主要作用是让我安心。我几乎从不重读笔记内容,但若无法记录,对遗忘的担忧会阻碍新灵感诞生。纸笔能吸附思绪。
我最爱Miquelrius品牌的最小尺寸笔记本(约6.4x10厘米)。在窄页书写的秘诀是像拉丁碑文那样,仅当空间不足时才断词。我用最便宜的Bic塑料圆珠笔,既因黏性墨水不易渗纸,也因丢了不心疼。
三年前我才开始随身带笔记本,此前都用零散纸片。但纸片无法按序排列,笔记本却能通过上下文推测潦草字迹的含义。纸片时代我总发现多年前写下的笔记,内容可能很重要——如果能破译的话。
I was walking in some steep mountains once, and decided I'd rather just think, if I was bored, rather than carry a single unnecessary ounce. It wasn't so bad. I found I could entertain myself by having ideas instead of reading other people's. If you stop eating jam, fruit starts to taste better. So maybe I'll try not bringing books on some future trip. They're going to have to pry the plugs out of my cold, dead ears, however.
| Spanish Translation | | | Japanese Translation.
Want to start a startup? Get funded by Y Combinator.
June 2006 _(This essay is derived from talks at Usenix 2006 and Railsconf 2006.)_ A couple years ago my friend Trevor and I went to look at the Apple garage. As we stood there, he said that as a kid growing up in Saskatchewan he'd been amazed at the dedication Jobs and Wozniak must have had to work in a garage. "Those guys must have been freezing!" That's one of California's hidden advantages: the mild climate means there's lots of marginal space. In cold places that margin gets trimmed off. There's a sharper line between outside and inside, and only projects that are officially sanctioned — by organizations, or parents, or wives, or at least by oneself — get proper indoor space. That raises the activation energy for new ideas. You can't just tinker. You have to justify. Some of Silicon Valley's most famous companies began in garages: Hewlett-Packard in 1938, Apple in 1976, Google in 1998. In Apple's case the garage story is a bit of an urban legend. Woz says all they did there was assemble some computers, and that he did all the actual design of the Apple I and Apple II in his apartment or his cube at HP. [1] This was apparently too marginal even for Apple's PR people. By conventional standards, Jobs and Wozniak were marginal people too. Obviously they were smart, but they can't have looked good on paper. They were at the time a pair of college dropouts with about three years of school between them, and hippies to boot. Their previous business experience consisted of making "blue boxes" to hack into the phone system, a business with the rare distinction of being both illegal and unprofitable. Outsiders Now a startup operating out of a garage in Silicon Valley would feel part of an exalted tradition, like the poet in his garret, or the painter who can't afford to heat his studio and thus has to wear a beret indoors.
想创业吗? 获得Y Combinator的资助。
(本文源自2006年Usenix大会和Railsconf大会的演讲。)
几年前,我和朋友特雷弗去参观苹果公司的车库旧址。站在那儿时,他提到自己从小在萨斯喀彻温省长大,一直惊叹于乔布斯和沃兹尼亚克竟能在车库里坚持工作。
But in 1976 it didn't seem so cool. The world hadn't yet realized that starting a computer company was in the same category as being a writer or a painter. It hadn't been for long. Only in the preceding couple years had the dramatic fall in the cost of hardware allowed outsiders to compete. In 1976, everyone looked down on a company operating out of a garage, including the founders. One of the first things Jobs did when they got some money was to rent office space. He wanted Apple to seem like a real company. They already had something few real companies ever have: a fabulously well designed product. You'd think they'd have had more confidence. But I've talked to a lot of startup founders, and it's always this way. They've built something that's going to change the world, and they're worried about some nit like not having proper business cards. That's the paradox I want to explore: great new things often come from the margins, and yet the people who discover them are looked down on by everyone, including themselves. It's an old idea that new things come from the margins. I want to examine its internal structure. Why do great ideas come from the margins? What kind of ideas? And is there anything we can do to encourage the process? Insiders One reason so many good ideas come from the margin is simply that there's so much of it. There have to be more outsiders than insiders, if insider means anything. If the number of outsiders is huge it will always seem as if a lot of ideas come from them, even if few do per capita. But I think there's more going on than this. There are real disadvantages to being an insider, and in some kinds of work they can outweigh the advantages. Imagine, for example, what would happen if the government decided to commission someone to write an official Great American Novel. First there'd be a huge ideological squabble over who to choose.
"那两位肯定冻坏了!"
这就是加州隐藏的优势之一:温和的气候意味着这里存在大量边缘空间。在寒冷地区,这种边缘会被削减。室内外的界限更加分明,只有那些得到官方认可——无论是组织、父母、妻子,至少是自己认可——的项目才能获得像样的室内空间。这提高了新想法的启动门槛。你不能只是随便捣鼓,必须给出正当理由。
硅谷许多著名公司都始于车库:惠普(1938年)、苹果(1976年)、谷歌(1998年)。苹果的车库故事某种程度上是个都市传说。沃兹说他们只是在那儿组装了几台电脑,而Apple I和Apple II的实际设计工作都是在他自己的公寓或惠普的工位上完成的。[1] 显然,这对苹果的公关人员来说都太过边缘了。
按传统标准,乔布斯和沃兹尼亚克也是边缘人。他们当然聪明,但纸面履历肯定不好看。当时他们是两个大学辍学生,加起来只上过三年大学,还是嬉皮士。之前的商业经验是制作盗打电话的"蓝盒子"——这种生意罕见地同时具备违法和不赚钱两大特点。
Most of the best writers would be excluded for having offended one side or the other. Of the remainder, the smart ones would refuse such a job, leaving only a few with the wrong sort of ambition. The committee would choose one at the height of his career — that is, someone whose best work was behind him — and hand over the project with copious free advice about how the book should show in positive terms the strength and diversity of the American people, etc, etc. The unfortunate writer would then sit down to work with a huge weight of expectation on his shoulders. Not wanting to blow such a public commission, he'd play it safe. This book had better command respect, and the way to ensure that would be to make it a tragedy. Audiences have to be enticed to laugh, but if you kill people they feel obliged to take you seriously. As everyone knows, America plus tragedy equals the Civil War, so that's what it would have to be about. When finally completed twelve years later, the book would be a 900-page pastiche of existing popular novels — roughly _Gone with the Wind_ plus _Roots_. But its bulk and celebrity would make it a bestseller for a few months, until blown out of the water by a talk-show host's autobiography. The book would be made into a movie and thereupon forgotten, except by the more waspish sort of reviewers, among whom it would be a byword for bogusness like Milli Vanilli or _Battlefield Earth_. Maybe I got a little carried away with this example. And yet is this not at each point the way such a project would play out? The government knows better than to get into the novel business, but in other fields where they have a natural monopoly, like nuclear waste dumps, aircraft carriers, and regime change, you'd find plenty of projects isomorphic to this one — and indeed, plenty that were less successful.
如今,在硅谷车库里创业会让人感觉身处崇高传统之中,就像阁楼里的诗人或买不起暖气只能戴贝雷帽在室内作画的画家。但在1976年,这并不酷。世界尚未意识到创办计算机公司与成为作家或画家属于同一类别。这种认知转变时间不长:就在此前几年,硬件成本的暴跌才让局外人有了竞争机会。
1976年时,所有人都看不起车库公司,包括创始人自己。乔布斯拿到第一笔钱后,最先做的事之一就是租办公室。他希望苹果看起来像家正经公司。
其实他们已拥有绝大多数正经公司梦寐以求的东西:设计惊艳的产品。你会以为他们该更有信心。但我和许多创业者聊过,发现他们总是如此:明明做出了能改变世界的东西,却为没有正规名片这种琐事焦虑。
This little thought experiment suggests a few of the disadvantages of insider projects: the selection of the wrong kind of people, the excessive scope, the inability to take risks, the need to seem serious, the weight of expectations, the power of vested interests, the undiscerning audience, and perhaps most dangerous, the tendency of such work to become a duty rather than a pleasure. Tests A world with outsiders and insiders implies some kind of test for distinguishing between them. And the trouble with most tests for selecting elites is that there are two ways to pass them: to be good at what they try to measure, and to be good at hacking the test itself. So the first question to ask about a field is how honest its tests are, because this tells you what it means to be an outsider. This tells you how much to trust your instincts when you disagree with authorities, whether it's worth going through the usual channels to become one yourself, and perhaps whether you want to work in this field at all. Tests are least hackable when there are consistent standards for quality, and the people running the test really care about its integrity. Admissions to PhD programs in the hard sciences are fairly honest, for example. The professors will get whoever they admit as their own grad students, so they try hard to choose well, and they have a fair amount of data to go on. Whereas undergraduate admissions seem to be much more hackable. One way to tell whether a field has consistent standards is the overlap between the leading practitioners and the people who teach the subject in universities. At one end of the scale you have fields like math and physics, where nearly all the teachers are among the best practitioners. In the middle are medicine, law, history, architecture, and computer science, where many are.
这就是我想探讨的矛盾现象:伟大的新事物往往来自边缘,但发现它们的人却被所有人(包括他们自己)看不起。
新事物来自边缘是个古老观点。我想剖析其内在逻辑:为何伟大创意源于边缘?是哪些类型的创意?我们能做些什么来促进这个过程?
好创意多来自边缘的一个简单原因是:边缘本身就很广阔。如果"局内人"真有特定含义,那么局外人必然更多。当局外人基数庞大时,即使人均产出不高,也会显得有很多创意来自他们。但我认为不止如此。成为局内人确有实实在在的劣势,在某些领域这些劣势会超过优势。
试想如果政府决定委托某人撰写官方版《伟大的美国小说》会怎样。首先会就人选爆发巨大意识形态争论,多数优秀作家会因冒犯某一方被排除。剩下的人里,聪明的会拒绝这种差事,只留下几个野心用错地方的。委员会将选择处于事业巅峰的作家——即最佳作品已成过往的人——然后交付项目并附赠大量"指导意见":这本书应该如何正面展现美国人民的力量与多样性等等。
At the bottom are business, literature, and the visual arts, where there's almost no overlap between the teachers and the leading practitioners. It's this end that gives rise to phrases like "those who can't do, teach." Incidentally, this scale might be helpful in deciding what to study in college. When I was in college the rule seemed to be that you should study whatever you were most interested in. But in retrospect you're probably better off studying something moderately interesting with someone who's good at it than something very interesting with someone who isn't. You often hear people say that you shouldn't major in business in college, but this is actually an instance of a more general rule: don't learn things from teachers who are bad at them. How much you should worry about being an outsider depends on the quality of the insiders. If you're an amateur mathematician and think you've solved a famous open problem, better go back and check. When I was in grad school, a friend in the math department had the job of replying to people who sent in proofs of Fermat's last theorem and so on, and it did not seem as if he saw it as a valuable source of tips — more like manning a mental health hotline. Whereas if the stuff you're writing seems different from what English professors are interested in, that's not necessarily a problem. Anti-Tests Where the method of selecting the elite is thoroughly corrupt, most of the good people will be outsiders. In art, for example, the image of the poor, misunderstood genius is not just one possible image of a great artist: it's the _standard_ image. I'm not saying it's correct, incidentally, but it is telling how well this image has stuck.
这位不幸的作家将背负沉重期待开始工作。为避免搞砸高调委托,他会选择稳妥路线。这本书必须赢得尊重,而确保这点的方式就是写成悲剧。逗笑观众需要技巧,但死人情节能强制获得严肃对待。众所周知,美国加悲剧等于南北战争,所以主题必然如此。十二年后完稿时,这本书会成为900页的流行小说拼贴——大致是《乱世佳人》加《根》。但其厚重与名头会让它畅销数月,直到被脱口秀主持人的自传挤下榜单。小说会被改编成电影然后被遗忘,除了尖刻的评论家会把它当作虚假的代名词,就像米利·瓦尼利或《地球战场》。
这个例子或许夸张了些。但这类项目不正是按这种逻辑发展的吗?政府明智地不涉足小说领域,但在其天然垄断的其他领域(如核废料处理、航空母舰、政权更迭),你会发现大量类似项目——且确实有很多更不成功。
这个小实验揭示了局内人项目的若干劣势:选错人、摊子铺太大、不敢冒险、需要显得正经、期待压力、既得利益、缺乏鉴别力的观众,而最危险的或许是这类工作容易变成义务而非乐趣。
You couldn't make a rap like that stick to math or medicine. [2] If it's corrupt enough, a test becomes an anti-test, filtering out the people it should select by making them to do things only the wrong people would do. Popularity in high school seems to be such a test. There are plenty of similar ones in the grownup world. For example, rising up through the hierarchy of the average big company demands an attention to politics few thoughtful people could spare. [3] Someone like Bill Gates can grow a company under him, but it's hard to imagine him having the patience to climb the corporate ladder at General Electric — or Microsoft, actually. It's kind of strange when you think about it, because lord-of-the-flies schools and bureaucratic companies are both the default. There are probably a lot of people who go from one to the other and never realize the whole world doesn't work this way. I think that's one reason big companies are so often blindsided by startups. People at big companies don't realize the extent to which they live in an environment that is one large, ongoing test for the wrong qualities. If you're an outsider, your best chances for beating insiders are obviously in fields where corrupt tests select a lame elite. But there's a catch: if the tests are corrupt, your victory won't be recognized, at least in your lifetime. You may feel you don't need that, but history suggests it's dangerous to work in fields with corrupt tests. You may beat the insiders, and yet not do as good work, on an absolute scale, as you would in a field that was more honest. Standards in art, for example, were almost as corrupt in the first half of the eighteenth century as they are today. This was the era of those fluffy idealized portraits of countesses with their lapdogs. Chardin decided to skip all that and paint ordinary things as he saw them.
局外人与局内人的分野意味着某种筛选测试。多数精英选拔机制的问题在于,通过测试有两种方式:真正擅长测试内容,或擅长钻测试空子。
因此评估一个领域首先要看其测试是否诚实,因为这决定了"局外人"意味着什么。它能告诉你在与权威意见相左时该多相信直觉,是否值得通过正规渠道成为局内人,甚至这个领域是否值得投入。
当存在明确质量标准且主考者真正在乎测试公正性时,测试最难被钻空子。例如硬科学领域的博士录取相当公正:教授要对录取的学生负责,因此竭力择优,且有充分数据参考。而本科录取似乎更容易钻空子。
判断领域是否有稳定标准的方法之一,是看顶尖从业者与大学教师的交集程度。最顶端是数学、物理等领域,几乎所有教师都是顶尖实践者。中间层是医学、法律、历史、建筑和计算机科学,部分教师是。最底层是商科、文学和视觉艺术,教师与顶尖从业者几乎无交集。正是这一端催生了"不会做的人就去教书"的说法。
He's now considered the best of that period — and yet not the equal of Leonardo or Bellini or Memling, who all had the additional encouragement of honest standards. It can be worth participating in a corrupt contest, however, if it's followed by another that isn't corrupt. For example, it would be worth competing with a company that can spend more than you on marketing, as long as you can survive to the next round, when customers compare your actual products. Similarly, you shouldn't be discouraged by the comparatively corrupt test of college admissions, because it's followed immediately by less hackable tests. [4] Risk Even in a field with honest tests, there are still advantages to being an outsider. The most obvious is that outsiders have nothing to lose. They can do risky things, and if they fail, so what? Few will even notice. The eminent, on the other hand, are weighed down by their eminence. Eminence is like a suit: it impresses the wrong people, and it constrains the wearer. Outsiders should realize the advantage they have here. Being able to take risks is hugely valuable. Everyone values safety too much, both the obscure and the eminent. No one wants to look like a fool. But it's very useful to be able to. If most of your ideas aren't stupid, you're probably being too conservative. You're not bracketing the problem. Lord Acton said we should judge talent at its best and character at its worst. For example, if you write one great book and ten bad ones, you still count as a great writer — or at least, a better writer than someone who wrote eleven that were merely good. Whereas if you're a quiet, law-abiding citizen most of the time but occasionally cut someone up and bury them in your backyard, you're a bad guy. Almost everyone makes the mistake of treating ideas as if they were indications of character rather than talent — as if having a stupid idea made you stupid.
顺便说,这个尺度或许有助于选择大学专业。我上大学时流行说法是应该选最感兴趣的领域。但回头看,跟着优秀的人学中等兴趣的内容,可能比跟着平庸的人学非常感兴趣的内容更好。常有人说大学不该主修商科,其实这是更普适规则的实例:别向不擅长某事的人学习。
该多担心自己是局外人取决于局内人的水平。如果你是业余数学家且认为自己解决了著名开放问题,最好再检查几遍。我在研究生院时,数学系有位朋友负责回复那些提交费马大定理证明的人,他显然不把这视为宝贵线索来源——更像是值守心理健康热线。而如果你写的东西与英语教授的兴趣不同,未必是问题。
当精英选拔机制彻底腐败时,多数优秀者会成为局外人。例如在艺术领域,贫穷被误解的天才形象不仅是伟大艺术家的可能形象之一,更是标准形象。顺便说,我并非认为这正确,但这个形象的顽固程度很能说明问题。你没法把这种说唱形象套在数学或医学领域。[2]
当腐败到一定程度,测试会变成逆向筛选,通过要求只有错误人选才会做的事来排除本该选中的人。高中人气就是这种测试。成人世界也有许多类似机制。例如在普通大公司爬梯子需要投入的政治注意力,是多数有思想的人不愿付出的。[3] 像比尔·盖茨这样的人能让公司在他手下成长,但很难想象他有耐心在通用电气——其实微软也是——慢慢爬梯子。
There's a huge weight of tradition advising us to play it safe. "Even a fool is thought wise if he keeps silent," says the Old Testament (Proverbs 17:28). Well, that may be fine advice for a bunch of goatherds in Bronze Age Palestine. There conservatism would be the order of the day. But times have changed. It might still be reasonable to stick with the Old Testament in political questions, but materially the world now has a lot more state. Tradition is less of a guide, not just because things change faster, but because the space of possibilities is so large. The more complicated the world gets, the more valuable it is to be willing to look like a fool. Delegation And yet the more successful people become, the more heat they get if they screw up — or even seem to screw up. In this respect, as in many others, the eminent are prisoners of their own success. So the best way to understand the advantages of being an outsider may be to look at the disadvantages of being an insider. If you ask eminent people what's wrong with their lives, the first thing they'll complain about is the lack of time. A friend of mine at Google is fairly high up in the company and went to work for them long before they went public. In other words, he's now rich enough not to have to work. I asked him if he could still endure the annoyances of having a job, now that he didn't have to. And he said that there weren't really any annoyances, except — and he got a wistful look when he said this — that he got _so much email_. The eminent feel like everyone wants to take a bite out of them. The problem is so widespread that people pretending to be eminent do it by pretending to be overstretched. The lives of the eminent become scheduled, and that's not good for thinking. One of the great advantages of being an outsider is long, uninterrupted blocks of time.
细想很奇妙,因为弱肉强食的学校和官僚化公司都是默认状态。可能很多人从一个转到另一个,却从未意识到世界本不该如此运作。
我认为这是大公司常被创业公司突袭的原因之一。大公司员工没意识到自己生活在持续筛选错误特质的环境中。
如果你是局外人,击败局内人的最佳机会显然在那些腐败测试选出平庸精英的领域。但有陷阱:如果测试腐败,你的胜利可能不被承认(至少在你生前)。或许你觉得无所谓,但历史表明在腐败测试的领域工作很危险。你或许能击败局内人,但绝对标准下,成果可能不如在更诚实领域能达到的水平。
That's what I remember about grad school: apparently endless supplies of time, which I spent worrying about, but not writing, my dissertation. Obscurity is like health food — unpleasant, perhaps, but good for you. Whereas fame tends to be like the alcohol produced by fermentation. When it reaches a certain concentration, it kills off the yeast that produced it. The eminent generally respond to the shortage of time by turning into managers. They don't have time to work. They're surrounded by junior people they're supposed to help or supervise. The obvious solution is to have the junior people do the work. Some good stuff happens this way, but there are problems it doesn't work so well for: the kind where it helps to have everything in one head. For example, it recently emerged that the famous glass artist Dale Chihuly hasn't actually blown glass for 27 years. He has assistants do the work for him. But one of the most valuable sources of ideas in the visual arts is the resistance of the medium. That's why oil paintings look so different from watercolors. In principle you could make any mark in any medium; in practice the medium steers you. And if you're no longer doing the work yourself, you stop learning from this. So if you want to beat those eminent enough to delegate, one way to do it is to take advantage of direct contact with the medium. In the arts it's obvious how: blow your own glass, edit your own films, stage your own plays. And in the process pay close attention to accidents and to new ideas you have on the fly. This technique can be generalized to any sort of work: if you're an outsider, don't be ruled by plans. Planning is often just a weakness forced on those who delegate. Is there a general rule for finding problems best solved in one head? Well, you can manufacture them by taking any project usually done by multiple people and trying to do it all yourself.
例如18世纪上半叶的艺术标准几乎和今天一样腐败。那是伯爵夫人与宠物犬的蓬松理想化肖像时代。夏尔丹决定跳过这些,按所见描绘寻常事物。他现在被视为那个时期的最佳画家——但仍不及达芬奇、贝利尼或梅姆林,这些人都受益于诚实的标准。
但如果后续有不腐败的测试,参与腐败竞赛仍可能值得。例如与营销预算更雄厚的公司竞争就有价值,只要你能活到客户比较实际产品的下一轮。同样,你不该被相对腐败的大学录取标准打击,因为它后面紧跟着更难钻空子的测试。[4]
即使在测试诚实的领域,局外人仍有优势。最明显的是他们没什么可失去的。可以冒险尝试,失败又如何?甚至没多少人会注意到。
而名人被名气所累。名气就像西装:能打动错误的人,也会束缚穿着者。
Wozniak's work was a classic example: he did everything himself, hardware and software, and the result was miraculous. He claims not one bug was ever found in the Apple II, in either hardware or software. Another way to find good problems to solve in one head is to focus on the grooves in the chocolate bar — the places where tasks are divided when they're split between several people. If you want to beat delegation, focus on a vertical slice: for example, be both writer and editor, or both design buildings and construct them. One especially good groove to span is the one between tools and things made with them. For example, programming languages and applications are usually written by different people, and this is responsible for a lot of the worst flaws in programming languages. I think every language should be designed simultaneously with a large application written in it, the way C was with Unix. Techniques for competing with delegation translate well into business, because delegation is endemic there. Instead of avoiding it as a drawback of senility, many companies embrace it as a sign of maturity. In big companies software is often designed, implemented, and sold by three separate types of people. In startups one person may have to do all three. And though this feels stressful, it's one reason startups win. The needs of customers and the means of satisfying them are all in one head. Focus The very skill of insiders can be a weakness. Once someone is good at something, they tend to spend all their time doing that. This kind of focus is very valuable, actually. Much of the skill of experts is the ability to ignore false trails. But focus has drawbacks: you don't learn from other fields, and when a new approach arrives, you may be the last to notice. For outsiders this translates into two ways to win. One is to work on a variety of things.
局外人应意识到自己的优势。能冒险非常宝贵。无论无名小卒还是名流大腕,人人都过分看重安全。没人想显得愚蠢。但能承受这点非常有用。如果你的多数想法都不蠢,可能说明你太保守了。你没有全面探索问题空间。
阿克顿勋爵说我们该以最佳表现评判才华,以最差表现评判品格。例如你写过一本杰作和十本烂书,仍算优秀作家——至少比写过十一本平庸之作的人强。而如果你多数时候是安静守法的公民,只是偶尔杀人埋尸后院,那你就是坏人。
几乎每个人都错误地把想法当作品格而非才华的体现——仿佛有个蠢想法就说明你蠢。传统的重压教导我们谨慎行事。《旧约》说:"愚昧人若静默不言,也可算为智慧。"(箴言17:28)
Since you can't derive as much benefit (yet) from a narrow focus, you may as well cast a wider net and derive what benefit you can from similarities between fields. Just as you can compete with delegation by working on larger vertical slices, you can compete with specialization by working on larger horizontal slices — by both writing and illustrating your book, for example. The second way to compete with focus is to see what focus overlooks. In particular, new things. So if you're not good at anything yet, consider working on something so new that no one else is either. It won't have any prestige yet, if no one is good at it, but you'll have it all to yourself. The potential of a new medium is usually underestimated, precisely because no one has yet explored its possibilities. Before Durer tried making engravings, no one took them very seriously. Engraving was for making little devotional images — basically fifteenth century baseball cards of saints. Trying to make masterpieces in this medium must have seemed to Durer's contemporaries the way that, say, making masterpieces in comics might seem to the average person today. In the computer world we get not new mediums but new platforms: the minicomputer, the microprocessor, the web-based application. At first they're always dismissed as being unsuitable for real work. And yet someone always decides to try anyway, and it turns out you can do more than anyone expected. So in the future when you hear people say of a new platform: yeah, it's popular and cheap, but not ready yet for real work, jump on it. As well as being more comfortable working on established lines, insiders generally have a vested interest in perpetuating them. The professor who made his reputation by discovering some new idea is not likely to be the one to discover its replacement.
好吧,这对青铜时代巴勒斯坦的牧羊人可能是好建议。那时保守本是常态。但时代变了。在政治问题上遵循《旧约》或许仍有道理,但物质世界已复杂得多。传统越来越不适用,不仅因为变化加速,更因为可能性空间大幅扩展。世界越复杂,越需要敢于显得愚蠢。
然而人越成功,搞砸时(或看似搞砸时)承受的压力就越大。在这方面,名流和其他方面一样是自己成功的囚徒。因此理解局外人优势的最佳方式或许是审视局内人的劣势。
若问名流生活中有什么困扰,他们首先会抱怨时间不够。我在谷歌的一位朋友职位颇高,在公司上市前就加入了。换句话说,他现在富到不必工作。我问他既然财务自由为何还忍受工作烦恼。他说其实没什么烦恼,除了——说这话时他露出惆怅表情——要处理的邮件实在太多。
名流感觉人人都想咬他们一口。这现象如此普遍,以至于假装有名的人会假装自己忙到透支。
This is particularly true with companies, who have not only skill and pride anchoring them to the status quo, but money as well. The Achilles heel of successful companies is their inability to cannibalize themselves. Many innovations consist of replacing something with a cheaper alternative, and companies just don't want to see a path whose immediate effect is to cut an existing source of revenue. So if you're an outsider you should actively seek out contrarian projects. Instead of working on things the eminent have made prestigious, work on things that could steal that prestige. The really juicy new approaches are not the ones insiders reject as impossible, but those they ignore as undignified. For example, after Wozniak designed the Apple II he offered it first to his employer, HP. They passed. One of the reasons was that, to save money, he'd designed the Apple II to use a TV as a monitor, and HP felt they couldn't produce anything so declasse. Less Wozniak used a TV as a monitor for the simple reason that he couldn't afford a monitor. Outsiders are not merely free but compelled to make things that are cheap and lightweight. And both are good bets for growth: cheap things spread faster, and lightweight things evolve faster. The eminent, on the other hand, are almost forced to work on a large scale. Instead of garden sheds they must design huge art museums. One reason they work on big things is that they can: like our hypothetical novelist, they're flattered by such opportunities. They also know that big projects will by their sheer bulk impress the audience. A garden shed, however lovely, would be easy to ignore; a few might even snicker at it. You can't snicker at a giant museum, no matter how much you dislike it. And finally, there are all those people the eminent have working for them; they have to choose projects that can keep them all busy. Outsiders are free of all this.
名流的生活被日程填满,这对思考不利。局外人的一大优势是拥有大块不间断时间。这就是我对研究生院的记忆:似乎无限的时间供应,我花在担心论文上的时间比写作还多。默默无闻像健康食品——或许不美味但对你有益。而名声则像发酵产生的酒精,浓度达到一定水平就会杀死产生它的酵母。
名流通常通过转型管理者应对时间短缺。他们没时间工作,周围是需要指导或监督的年轻人。显然的解决方案是让年轻人干活。这种方式能产生些好东西,但对某些问题效果不佳——那些需要所有信息都在一个头脑中的问题。
例如最近爆出著名玻璃艺术家戴尔·奇胡利其实27年没吹制过玻璃,全是助手代劳。但视觉艺术最宝贵的创意来源之一正是材质的抵抗性。油画与水彩的差异正源于此。理论上任何材质都能实现任何效果,实际上材质会引导你。若不再亲手操作,就失去了这种学习机会。
They can work on small things, and there's something very pleasing about small things. Small things can be perfect; big ones always have something wrong with them. But there's a magic in small things that goes beyond such rational explanations. All kids know it. Small things have more personality. Plus making them is more fun. You can do what you want; you don't have to satisfy committees. And perhaps most important, small things can be done fast. The prospect of seeing the finished project hangs in the air like the smell of dinner cooking. If you work fast, maybe you could have it done tonight. Working on small things is also a good way to learn. The most important kinds of learning happen one project at a time. ("Next time, I won't...") The faster you cycle through projects, the faster you'll evolve. Plain materials have a charm like small scale. And in addition there's the challenge of making do with less. Every designer's ears perk up at the mention of that game, because it's a game you can't lose. Like the JV playing the varsity, if you even tie, you win. So paradoxically there are cases where fewer resources yield better results, because the designers' pleasure at their own ingenuity more than compensates. [5] So if you're an outsider, take advantage of your ability to make small and inexpensive things. Cultivate the pleasure and simplicity of that kind of work; one day you'll miss it. Responsibility When you're old and eminent, what will you miss about being young and obscure? What people seem to miss most is the lack of responsibilities. Responsibility is an occupational disease of eminence. In principle you could avoid it, just as in principle you could avoid getting fat as you get old, but few do. I sometimes suspect that responsibility is a trap and that the most virtuous route would be to shirk it, but regardless it's certainly constraining.
因此要击败那些名到可以授权的人,方法之一是利用与材质的直接接触。艺术领域很明显:自己吹玻璃、自己剪电影、自己排戏剧。在此过程中密切留意意外效果和即兴想法。这种技术可推广到任何领域:如果你是局外人,别被计划束缚。计划常是被迫授权者的弱点。
是否存在判断哪些问题适合单人解决的通用法则?你可以把通常多人合作的项目拿来自行完成来制造这类问题。沃兹尼亚克的工作就是经典案例:他包揽硬件软件所有工作,结果堪称奇迹。他声称Apple II的硬件和软件中从未发现一个bug。
另一种寻找适合单人解决的好问题的方法是关注"巧克力棒的凹槽"——任务在多人间分配时的接缝处。要击败授权机制,就专注垂直切片:比如同时当作家和编辑,或既设计建筑又建造它。
特别值得跨越的是工具与用工具制造之物间的鸿沟。例如编程语言和应用通常由不同人编写,这导致编程语言许多最糟糕的缺陷。我认为每种语言都应像C语言与Unix那样,与用其编写的大型应用同步设计。
When you're an outsider you're constrained too, of course. You're short of money, for example. But that constrains you in different ways. How does responsibility constrain you? The worst thing is that it allows you not to focus on real work. Just as the most dangerous forms of procrastination are those that seem like work, the danger of responsibilities is not just that they can consume a whole day, but that they can do it without setting off the kind of alarms you'd set off if you spent a whole day sitting on a park bench. A lot of the pain of being an outsider is being aware of one's own procrastination. But this is actually a good thing. You're at least close enough to work that the smell of it makes you hungry. As an outsider, you're just one step away from getting things done. A huge step, admittedly, and one that most people never seem to make, but only one step. If you can summon up the energy to get started, you can work on projects with an intensity (in both senses) that few insiders can match. For insiders work turns into a duty, laden with responsibilities and expectations. It's never so pure as it was when they were young. Work like a dog being taken for a walk, instead of an ox being yoked to the plow. That's what they miss. Audience A lot of outsiders make the mistake of doing the opposite; they admire the eminent so much that they copy even their flaws. Copying is a good way to learn, but copy the right things. When I was in college I imitated the pompous diction of famous professors. But this wasn't what _made_ them eminent — it was more a flaw their eminence had allowed them to sink into. Imitating it was like pretending to have gout in order to seem rich. Half the distinguishing qualities of the eminent are actually disadvantages. Imitating these is not only a waste of time, but will make you seem a fool to your models, who are often well aware of it.
对抗授权机制的技术很容易转化到商业领域,因为授权在那里无处不在。许多公司不仅不将其视为衰老的弊端,反而当作成熟的标志。大公司的软件常由三类人分别设计、实现和销售。创业公司可能一人包办三者。虽然压力大,但这就是创业公司能赢的原因之一。客户需求与满足手段全在一个头脑中。
局内人的专业技能本身可能成为弱点。当某人擅长某事,往往会将所有时间投入其中。这种专注其实很有价值。专家的大部分技能正是忽略错误路径的能力。但专注有代价:你无法从其他领域学习,当新方法出现时,你可能最后才注意到。
对局外人而言这转化为两种取胜方式。一是同时研究多样事物。既然(还)无法从狭窄专注中获得最大收益,不妨撒网更广,从领域相似性中获取可能收益。就像可以通过处理更大垂直切片来对抗授权机制,你也可以通过更大水平切片对抗专业化——比如同时写作和绘制插图。
第二种对抗专注的方式是关注被专注者忽略的事物,特别是新事物。所以如果你还不擅长任何事,考虑研究新到没人在行的领域。既然没人在行,它自然还没声望,但你能独占整个领域。
What are the genuine advantages of being an insider? The greatest is an audience. It often seems to outsiders that the great advantage of insiders is money — that they have the resources to do what they want. But so do people who inherit money, and that doesn't seem to help, not as much as an audience. It's good for morale to know people want to see what you're making; it draws work out of you. If I'm right that the defining advantage of insiders is an audience, then we live in exciting times, because just in the last ten years the Internet has made audiences a lot more liquid. Outsiders don't have to content themselves anymore with a proxy audience of a few smart friends. Now, thanks to the Internet, they can start to grow themselves actual audiences. This is great news for the marginal, who retain the advantages of outsiders while increasingly being able to siphon off what had till recently been the prerogative of the elite. Though the Web has been around for more than ten years, I think we're just beginning to see its democratizing effects. Outsiders are still learning how to steal audiences. But more importantly, audiences are still learning how to be stolen — they're still just beginning to realize how much deeper bloggers can dig than journalists, how much more interesting a democratic news site can be than a front page controlled by editors, and how much funnier a bunch of kids with webcams can be than mass-produced sitcoms. The big media companies shouldn't worry that people will post their copyrighted material on YouTube. They should worry that people will post their own stuff on YouTube, and audiences will watch that instead. Hacking If I had to condense the power of the marginal into one sentence it would be: just try hacking something together.
新媒介的潜力常被低估,正因为无人探索其可能性。在丢勒尝试版画前,没人认真看待它。版画只是制作小型宗教图像——基本上是15世纪的圣徒棒球卡。试图用这种媒介创作杰作,在丢勒同代人眼中大概就像今天普通人对用漫画创作杰作的看法。
计算机领域我们获得的是新平台而非新媒介:小型机、微处理器、基于网络的应用程序。起初它们总被认为不适合正经工作。但总有人决定尝试,结果总能超出预期。所以未来当你听人说某个新平台"虽然流行便宜但还不适合正经工作"时,赶紧抓住它。
除了更习惯既定路线,局内人通常还有维持现状的既得利益。因发现某个新理论成名的教授,不太可能是发现其替代者的人。公司尤其如此,不仅有技能和骄傲将其锚定在现状上,还有金钱因素。成功公司的阿喀琉斯之踵就是无法自我蚕食。许多创新在于用更廉价的方案替代现有事物,而公司就是不愿看到会立即削减现有收入的路径。
That phrase draws in most threads I've mentioned here. Hacking something together means deciding what to do as you're doing it, not a subordinate executing the vision of his boss. It implies the result won't be pretty, because it will be made quickly out of inadequate materials. It may work, but it won't be the sort of thing the eminent would want to put their name on. Something hacked together means something that barely solves the problem, or maybe doesn't solve the problem at all, but another you discovered en route. But that's ok, because the main value of that initial version is not the thing itself, but what it leads to. Insiders who daren't walk through the mud in their nice clothes will never make it to the solid ground on the other side. The word "try" is an especially valuable component. I disagree here with Yoda, who said there is no try. There is try. It implies there's no punishment if you fail. You're driven by curiosity instead of duty. That means the wind of procrastination will be in your favor: instead of avoiding this work, this will be what you do as a way of avoiding other work. And when you do it, you'll be in a better mood. The more the work depends on imagination, the more that matters, because most people have more ideas when they're happy. If I could go back and redo my twenties, that would be one thing I'd do more of: just try hacking things together. Like many people that age, I spent a lot of time worrying about what I should do. I also spent some time trying to build stuff. I should have spent less time worrying and more time building. If you're not sure what to do, make something. Raymond Chandler's advice to thriller writers was "When in doubt, have a man come through a door with a gun in his hand." He followed that advice. Judging from his books, he was often in doubt. But though the result is occasionally cheesy, it's never boring. In life, as in books, action is underrated.
所以如果你是局外人,应该积极寻找逆向项目。别研究那些名流已使其有声望的事物,研究那些可能偷走这种声望的东西。
真正多汁的新方法不是局内人认为不可能的,而是他们觉得不够格关注的。例如沃兹尼亚克设计出Apple II后,首先提供给雇主惠普。他们拒绝了。原因之一是他为省钱设计成用电视机当显示器,惠普觉得不能生产这么掉价的东西。
沃兹用电视机当显示器很简单:他买不起显示器。局外人不仅自由,而且被迫制作廉价轻量的东西。这两者都是增长的好赌注:便宜的东西传播更快,轻量的东西进化更快。
而名流几乎被迫大操大办。他们必须设计巨型艺术博物馆而非花园小屋。选择大项目的一个原因是他们有能力:就像我们假设的小说家,他们被这种机会奉承。他们也清楚庞大体积会给观众留下印象。花园小屋再可爱也容易被忽视,甚至可能被嘲笑。但没人会嘲笑巨型博物馆,无论多讨厌它。最后,名流手下有那么多员工,必须选择能让他们都忙起来的项目。
Fortunately the number of things you can just hack together keeps increasing. People fifty years ago would be astonished that one could just hack together a movie, for example. Now you can even hack together distribution. Just make stuff and put it online. Inappropriate If you really want to score big, the place to focus is the margin of the margin: the territories only recently captured from the insiders. That's where you'll find the juiciest projects still undone, either because they seemed too risky, or simply because there were too few insiders to explore everything. This is why I spend most of my time writing essays lately. The writing of essays used to be limited to those who could get them published. In principle you could have written them and just shown them to your friends; in practice that didn't work. [6] An essayist needs the resistance of an audience, just as an engraver needs the resistance of the plate. Up till a few years ago, writing essays was the ultimate insider's game. Domain experts were allowed to publish essays about their field, but the pool allowed to write on general topics was about eight people who went to the right parties in New York. Now the reconquista has overrun this territory, and, not surprisingly, found it sparsely cultivated. There are so many essays yet unwritten. They tend to be the naughtier ones; the insiders have pretty much exhausted the motherhood and apple pie topics. This leads to my final suggestion: a technique for determining when you're on the right track. You're on the right track when people complain that you're unqualified, or that you've done something inappropriate. If people are complaining, that means you're doing something rather than sitting around, which is the first step. And if they're driven to such empty forms of complaint, that means you've probably done something good.
局外人没有这些束缚。他们可以研究小事物,而小事物有种特别的魅力。小事物可以完美;大事物总有缺陷。但小事物的魔力超越理性解释。所有孩子都知道这点。小事物更有性格。
而且制作它们更有趣。你可以为所欲为,不必满足委员会。或许最重要的是,小事物能快速完成。完成项目的期待像烹饪的香气般弥漫。如果动作快,或许今晚就能搞定。
研究小事物也是很好的学习方式。最重要的学习往往一次一个项目发生。("下次我不会……")项目周期越快,进化就越快。
If you make something and people complain that it doesn't _work_ , that's a problem. But if the worst thing they can hit you with is your own status as an outsider, that implies that in every other respect you've succeeded. Pointing out that someone is unqualified is as desperate as resorting to racial slurs. It's just a legitimate sounding way of saying: we don't like your type around here. But the best thing of all is when people call what you're doing inappropriate. I've been hearing this word all my life and I only recently realized that it is, in fact, the sound of the homing beacon. "Inappropriate" is the null criticism. It's merely the adjective form of "I don't like it." So that, I think, should be the highest goal for the marginal. Be inappropriate. When you hear people saying that, you're golden. And they, incidentally, are busted. Notes [1] The facts about Apple's early history are from an interview with Steve Wozniak in Jessica Livingston's _Founders at Work_. [2] As usual the popular image is several decades behind reality. Now the misunderstood artist is not a chain-smoking drunk who pours his soul into big, messy canvases that philistines see and say "that's not art" because it isn't a picture of anything. The philistines have now been trained that anything hung on a wall is art. Now the misunderstood artist is a coffee-drinking vegan cartoonist whose work they see and say "that's not art" because it looks like stuff they've seen in the Sunday paper. [3] In fact this would do fairly well as a definition of politics: what determines rank in the absence of objective tests. [4] In high school you're led to believe your whole future depends on where you go to college, but it turns out only to buy you a couple years.
朴素材料像小规模一样有魅力。此外还有"因陋就简"的挑战。每个设计师听到这个游戏都会竖起耳朵,因为这是场不会输的比赛。就像校队对阵职业队,只要不输就是赢。因此矛盾的是,有时资源越少结果越好,因为设计者因自己的机智获得的快乐足以弥补。[5]
所以如果你是局外人,利用你能制作小巧廉价物品的优势。培养这种工作的简单乐趣;总有一天你会怀念它。
当你年老成名时,会怀念年轻无名的什么?人们最怀念的似乎是缺乏责任。
责任是名气的职业病。理论上你可以避免,就像理论上可以避免年老发福,但极少人做到。我有时怀疑责任是陷阱,最道德的做法或许是逃避它,但无论如何它确实束缚人。
By your mid-twenties the people worth impressing already judge you more by what you've done than where you went to school. [5] Managers are presumably wondering, how can I make this miracle happen? How can I make the people working for me do more with less? Unfortunately the constraint probably has to be self-imposed. If you're _expected_ to do more with less, then you're being starved, not eating virtuously. [6] Without the prospect of publication, the closest most people come to writing essays is to write in a journal. I find I never get as deeply into subjects as I do in proper essays. As the name implies, you don't go back and rewrite journal entries over and over for two weeks. Thanks to Sam Altman, Trevor Blackwell, Paul Buchheit, Sarah Harlin, Jessica Livingston, Jackie McDonough, Robert Morris, Olin Shivers, and Chris Small for reading drafts of this, and to Chris Small and Chad Fowler for inviting me to speak.
| Japanese Translation | | | Chinese Translation.
当然局外人也有束缚。比如缺钱。但这种束缚方向不同。责任如何束缚你?最糟的是它让你不必专注真正的工作。就像最危险的拖延是那些看似工作的拖延,责任的危险不仅在于可能消耗一整天,还在于它消耗时不会触发警报——如果你在公园长椅坐一整天,警报早响了。
局外人的许多痛苦源于意识到自己在拖延。但这其实是好事。你至少离工作足够近,能闻到它的气息而饥渴。
作为局外人,你离完成事物只差一步。诚然是巨大的一步,多数人似乎永远跨不出的一步,但毕竟只是一步。如果能鼓起勇气开始,你就能以(两种意义上的)强度工作,这种强度是多数局内人无法匹敌的。对局内人而言,工作变成背负责任与期待的苦差。它再也不像年轻时那般纯粹。
像被遛的狗那样工作,而非套犁的牛。这就是他们怀念的。
May 2006 _(This essay is derived from a keynote at Xtech.)_ Startups happen in clusters. There are a lot of them in Silicon Valley and Boston, and few in Chicago or Miami. A country that wants startups will probably also have to reproduce whatever makes these clusters form. I've claimed that the recipe is a great university near a town smart people like. If you set up those conditions within the US, startups will form as inevitably as water droplets condense on a cold piece of metal. But when I consider what it would take to reproduce Silicon Valley in another country, it's clear the US is a particularly humid environment. Startups condense more easily here. It is by no means a lost cause to try to create a silicon valley in another country. There's room not merely to equal Silicon Valley, but to surpass it. But if you want to do that, you have to understand the advantages startups get from being in America. 1\. The US Allows Immigration. For example, I doubt it would be possible to reproduce Silicon Valley in Japan, because one of Silicon Valley's most distinctive features is immigration. Half the people there speak with accents. And the Japanese don't like immigration. When they think about how to make a Japanese silicon valley, I suspect they unconsciously frame it as how to make one consisting only of Japanese people. This way of framing the question probably guarantees failure. A silicon valley has to be a mecca for the smart and the ambitious, and you can't have a mecca if you don't let people into it. Of course, it's not saying much that America is more open to immigration than Japan. Immigration policy is one area where a competitor could do better. 2\. The US Is a Rich Country. I could see India one day producing a rival to Silicon Valley. Obviously they have the right people: you can tell that by the number of Indians in the current Silicon Valley.
The problem with India itself is that it's still so poor. In poor countries, things we take for granted are missing. A friend of mine visiting India sprained her ankle falling down the steps in a railway station. When she turned to see what had happened, she found the steps were all different heights. In industrialized countries we walk down steps our whole lives and never think about this, because there's an infrastructure that prevents such a staircase from being built. The US has never been so poor as some countries are now. There have never been swarms of beggars in the streets of American cities. So we have no data about what it takes to get from the swarms-of-beggars stage to the silicon-valley stage. Could you have both at once, or does there have to be some baseline prosperity before you get a silicon valley? I suspect there is some speed limit to the evolution of an economy. Economies are made out of people, and attitudes can only change a certain amount per generation. [1] 3\. The US Is Not (Yet) a Police State. Another country I could see wanting to have a silicon valley is China. But I doubt they could do it yet either. China still seems to be a police state, and although present rulers seem enlightened compared to the last, even enlightened despotism can probably only get you part way toward being a great economic power. It can get you factories for building things designed elsewhere. Can it get you the designers, though? Can imagination flourish where people can't criticize the government? Imagination means having odd ideas, and it's hard to have odd ideas about technology without also having odd ideas about politics. And in any case, many technical ideas do have political implications. So if you squash dissent, the back pressure will propagate into technical fields. [2] Singapore would face a similar problem. Singapore seems very aware of the importance of encouraging startups.
But while energetic government intervention may be able to make a port run efficiently, it can't coax startups into existence. A state that bans chewing gum has a long way to go before it could create a San Francisco. Do you need a San Francisco? Might there not be an alternate route to innovation that goes through obedience and cooperation instead of individualism? Possibly, but I'd bet not. Most imaginative people seem to share a certain prickly independence, whenever and wherever they lived. You see it in Diogenes telling Alexander to get out of his light and two thousand years later in Feynman breaking into safes at Los Alamos. [3] Imaginative people don't want to follow or lead. They're most productive when everyone gets to do what they want. Ironically, of all rich countries the US has lost the most civil liberties recently. But I'm not too worried yet. I'm hoping once the present administration is out, the natural openness of American culture will reassert itself. 4\. American Universities Are Better. You need a great university to seed a silicon valley, and so far there are few outside the US. I asked a handful of American computer science professors which universities in Europe were most admired, and they all basically said "Cambridge" followed by a long pause while they tried to think of others. There don't seem to be many universities elsewhere that compare with the best in America, at least in technology. In some countries this is the result of a deliberate policy. The German and Dutch governments, perhaps from fear of elitism, try to ensure that all universities are roughly equal in quality. The downside is that none are especially good. The best professors are spread out, instead of being concentrated as they are in the US. This probably makes them less productive, because they don't have good colleagues to inspire them.
It also means no one university will be good enough to act as a mecca, attracting talent from abroad and causing startups to form around it. The case of Germany is a strange one. The Germans invented the modern university, and up till the 1930s theirs were the best in the world. Now they have none that stand out. As I was mulling this over, I found myself thinking: "I can understand why German universities declined in the 1930s, after they excluded Jews. But surely they should have bounced back by now." Then I realized: maybe not. There are few Jews left in Germany and most Jews I know would not want to move there. And if you took any great American university and removed the Jews, you'd have some pretty big gaps. So maybe it would be a lost cause trying to create a silicon valley in Germany, because you couldn't establish the level of university you'd need as a seed. [4] It's natural for US universities to compete with one another because so many are private. To reproduce the quality of American universities you probably also have to reproduce this. If universities are controlled by the central government, log-rolling will pull them all toward the mean: the new Institute of X will end up at the university in the district of a powerful politician, instead of where it should be. 5\. You Can Fire People in America. I think one of the biggest obstacles to creating startups in Europe is the attitude toward employment. The famously rigid labor laws hurt every company, but startups especially, because startups have the least time to spare for bureaucratic hassles. The difficulty of firing people is a particular problem for startups because they have no redundancy. Every person has to do their job well. But the problem is more than just that some startup might have a problem firing someone they needed to. Across industries and countries, there's a strong inverse correlation between performance and job security.
Actors and directors are fired at the end of each film, so they have to deliver every time. Junior professors are fired by default after a few years unless the university chooses to grant them tenure. Professional athletes know they'll be pulled if they play badly for just a couple games. At the other end of the scale (at least in the US) are auto workers, New York City schoolteachers, and civil servants, who are all nearly impossible to fire. The trend is so clear that you'd have to be willfully blind not to see it. Performance isn't everything, you say? Well, are auto workers, schoolteachers, and civil servants _happier_ than actors, professors, and professional athletes? European public opinion will apparently tolerate people being fired in industries where they really care about performance. Unfortunately the only industry they care enough about so far is soccer. But that is at least a precedent. 6\. In America Work Is Less Identified with Employment. The problem in more traditional places like Europe and Japan goes deeper than the employment laws. More dangerous is the attitude they reflect: that an employee is a kind of servant, whom the employer has a duty to protect. It used to be that way in America too. In 1970 you were still supposed to get a job with a big company, for whom ideally you'd work your whole career. In return the company would take care of you: they'd try not to fire you, cover your medical expenses, and support you in old age. Gradually employment has been shedding such paternalistic overtones and becoming simply an economic exchange. But the importance of the new model is not just that it makes it easier for startups to grow. More important, I think, is that it it makes it easier for people to _start_ startups. Even in the US most kids graduating from college still think they're supposed to get jobs, as if you couldn't be productive without being someone's employee.
But the less you identify work with employment, the easier it becomes to start a startup. When you see your career as a series of different types of work, instead of a lifetime's service to a single employer, there's less risk in starting your own company, because you're only replacing one segment instead of discarding the whole thing. The old ideas are so powerful that even the most successful startup founders have had to struggle against them. A year after the founding of Apple, Steve Wozniak still hadn't quit HP. He still planned to work there for life. And when Jobs found someone to give Apple serious venture funding, on the condition that Woz quit, he initially refused, arguing that he'd designed both the Apple I and the Apple II while working at HP, and there was no reason he couldn't continue. 7\. America Is Not Too Fussy. If there are any laws regulating businesses, you can assume larval startups will break most of them, because they don't know what the laws are and don't have time to find out. For example, many startups in America begin in places where it's not really legal to run a business. Hewlett-Packard, Apple, and Google were all run out of garages. Many more startups, including ours, were initially run out of apartments. If the laws against such things were actually enforced, most startups wouldn't happen. That could be a problem in fussier countries. If Hewlett and Packard tried running an electronics company out of their garage in Switzerland, the old lady next door would report them to the municipal authorities. But the worst problem in other countries is probably the effort required just to start a company. A friend of mine started a company in Germany in the early 90s, and was shocked to discover, among many other regulations, that you needed $20,000 in capital to incorporate. That's one reason I'm not typing this on an Apfel laptop.
Jobs and Wozniak couldn't have come up with that kind of money in a company financed by selling a VW bus and an HP calculator. We couldn't have started Viaweb either. [5] Here's a tip for governments that want to encourage startups: read the stories of existing startups, and then try to simulate what would have happened in your country. When you hit something that would have killed Apple, prune it off. _Startups aremarginal._ They're started by the poor and the timid; they begin in marginal space and spare time; they're started by people who are supposed to be doing something else; and though businesses, their founders often know nothing about business. Young startups are fragile. A society that trims its margins sharply will kill them all. 8\. America Has a Large Domestic Market. What sustains a startup in the beginning is the prospect of getting their initial product out. The successful ones therefore make the first version as simple as possible. In the US they usually begin by making something just for the local market. This works in America, because the local market is 300 million people. It wouldn't work so well in Sweden. In a small country, a startup has a harder task: they have to sell internationally from the start. The EU was designed partly to simulate a single, large domestic market. The problem is that the inhabitants still speak many different languages. So a software startup in Sweden is still at a disadvantage relative to one in the US, because they have to deal with internationalization from the beginning. It's significant that the most famous recent startup in Europe, Skype, worked on a problem that was intrinsically international. However, for better or worse it looks as if Europe will in a few decades speak a single language. When I was a student in Italy in 1990, few Italians spoke English. Now all educated people seem to be expected to-- and Europeans do not like to seem uneducated.
This is presumably a taboo subject, but if present trends continue, French and German will eventually go the way of Irish and Luxembourgish: they'll be spoken in homes and by eccentric nationalists. 9\. America Has Venture Funding. Startups are easier to start in America because funding is easier to get. There are now a few VC firms outside the US, but startup funding doesn't only come from VC firms. A more important source, because it's more personal and comes earlier in the process, is money from individual angel investors. Google might never have got to the point where they could raise millions from VC funds if they hadn't first raised a hundred thousand from Andy Bechtolsheim. And he could help them because he was one of the founders of Sun. This pattern is repeated constantly in startup hubs. It's this pattern that _makes_ them startup hubs. The good news is, all you have to do to get the process rolling is get those first few startups successfully launched. If they stick around after they get rich, startup founders will almost automatically fund and encourage new startups. The bad news is that the cycle is slow. It probably takes five years, on average, before a startup founder can make angel investments. And while governments _might_ be able to set up local VC funds by supplying the money themselves and recruiting people from existing firms to run them, only organic growth can produce angel investors. Incidentally, America's private universities are one reason there's so much venture capital. A lot of the money in VC funds comes from their endowments. So another advantage of private universities is that a good chunk of the country's wealth is managed by enlightened investors. 10\. America Has Dynamic Typing for Careers. Compared to other industrialized countries the US is disorganized about routing people into careers.
For example, in America people often don't decide to go to medical school till they've finished college. In Europe they generally decide in high school. The European approach reflects the old idea that each person has a single, definite occupation-- which is not far from the idea that each person has a natural "station" in life. If this were true, the most efficient plan would be to discover each person's station as early as possible, so they could receive the training appropriate to it. In the US things are more haphazard. But that turns out to be an advantage as an economy gets more liquid, just as dynamic typing turns out to work better than static for ill-defined problems. This is particularly true with startups. "Startup founder" is not the sort of career a high school student would choose. If you ask at that age, people will choose conservatively. They'll choose well-understood occupations like engineer, or doctor, or lawyer. Startups are the kind of thing people don't plan, so you're more likely to get them in a society where it's ok to make career decisions on the fly. For example, in theory the purpose of a PhD program is to train you to do research. But fortunately in the US this is another rule that isn't very strictly enforced. In the US most people in CS PhD programs are there simply because they wanted to learn more. They haven't decided what they'll do afterward. So American grad schools spawn a lot of startups, because students don't feel they're failing if they don't go into research. Those worried about America's "competitiveness" often suggest spending more on public schools. But perhaps America's lousy public schools have a hidden advantage. Because they're so bad, the kids adopt an attitude of waiting for college. I did; I knew I was learning so little that I wasn't even learning what the choices were, let alone which to choose. This is demoralizing, but it does at least make you keep an open mind.
Certainly if I had to choose between bad high schools and good universities, like the US, and good high schools and bad universities, like most other industrialized countries, I'd take the US system. Better to make everyone feel like a late bloomer than a failed child prodigy. Attitudes There's one item conspicuously missing from this list: American attitudes. Americans are said to be more entrepreneurial, and less afraid of risk. But America has no monopoly on this. Indians and Chinese seem plenty entrepreneurial, perhaps more than Americans. Some say Europeans are less energetic, but I don't believe it. I think the problem with Europe is not that they lack balls, but that they lack examples. Even in the US, the most successful startup founders are often technical people who are quite timid, initially, about the idea of starting their own company. Few are the sort of backslapping extroverts one thinks of as typically American. They can usually only summon up the activation energy to start a startup when they meet people who've done it and realize they could too. I think what holds back European hackers is simply that they don't meet so many people who've done it. You see that variation even within the US. Stanford students are more entrepreneurial than Yale students, but not because of some difference in their characters; the Yale students just have fewer examples. I admit there seem to be different attitudes toward ambition in Europe and the US. In the US it's ok to be overtly ambitious, and in most of Europe it's not. But this can't be an intrinsically European quality; previous generations of Europeans were as ambitious as Americans. What happened? My hypothesis is that ambition was discredited by the terrible things ambitious people did in the first half of the twentieth century.
Now swagger is out. (Even now the image of a very ambitious German presses a button or two, doesn't it?) It would be surprising if European attitudes weren't affected by the disasters of the twentieth century. It takes a while to be optimistic after events like that. But ambition is human nature. Gradually it will re-emerge. [6] How To Do Better I don't mean to suggest by this list that America is the perfect place for startups. It's the best place so far, but the sample size is small, and "so far" is not very long. On historical time scales, what we have now is just a prototype. So let's look at Silicon Valley the way you'd look at a product made by a competitor. What weaknesses could you exploit? How could you make something users would like better? The users in this case are those critical few thousand people you'd like to move to your silicon valley. To start with, Silicon Valley is too far from San Francisco. Palo Alto, the original ground zero, is about thirty miles away, and the present center more like forty. So people who come to work in Silicon Valley face an unpleasant choice: either live in the boring sprawl of the valley proper, or live in San Francisco and endure an hour commute each way. The best thing would be if the silicon valley were not merely closer to the interesting city, but interesting itself. And there is a lot of room for improvement here. Palo Alto is not so bad, but everything built since is the worst sort of strip development. You can measure how demoralizing it is by the number of people who will sacrifice two hours a day commuting rather than live there. Another area in which you could easily surpass Silicon Valley is public transportation. There is a train running the length of it, and by American standards it's not bad. Which is to say that to Japanese or Europeans it would seem like something out of the third world.
The kind of people you want to attract to your silicon valley like to get around by train, bicycle, and on foot. So if you want to beat America, design a town that puts cars last. It will be a while before any American city can bring itself to do that. Capital Gains There are also a couple things you could do to beat America at the national level. One would be to have lower capital gains taxes. It doesn't seem critical to have the lowest _income_ taxes, because to take advantage of those, people have to move. [7] But if capital gains rates vary, you move assets, not yourself, so changes are reflected at market speeds. The lower the rate, the cheaper it is to buy stock in growing companies as opposed to real estate, or bonds, or stocks bought for the dividends they pay. So if you want to encourage startups you should have a low rate on capital gains. Politicians are caught between a rock and a hard place here, however: make the capital gains rate low and be accused of creating "tax breaks for the rich," or make it high and starve growing companies of investment capital. As Galbraith said, politics is a matter of choosing between the unpalatable and the disastrous. A lot of governments experimented with the disastrous in the twentieth century; now the trend seems to be toward the merely unpalatable. Oddly enough, the leaders now are European countries like Belgium, which has a capital gains tax rate of zero. Immigration The other place you could beat the US would be with smarter immigration policy. There are huge gains to be made here. Silicon valleys are made of people, remember. Like a company whose software runs on Windows, those in the current Silicon Valley are all too aware of the shortcomings of the INS, but there's little they can do about it. They're hostages of the platform. America's immigration system has never been well run, and since 2001 there has been an additional admixture of paranoia.
What fraction of the smart people who want to come to America can even get in? I doubt even half. Which means if you made a competing technology hub that let in all smart people, you'd immediately get more than half the world's top talent, for free. US immigration policy is particularly ill-suited to startups, because it reflects a model of work from the 1970s. It assumes good technical people have college degrees, and that work means working for a big company. If you don't have a college degree you can't get an H1B visa, the type usually issued to programmers. But a test that excludes Steve Jobs, Bill Gates, and Michael Dell can't be a good one. Plus you can't get a visa for working on your own company, only for working as an employee of someone else's. And if you want to apply for citizenship you daren't work for a startup at all, because if your sponsor goes out of business, you have to start over. American immigration policy keeps out most smart people, and channels the rest into unproductive jobs. It would be easy to do better. Imagine if, instead, you treated immigration like recruiting-- if you made a conscious effort to seek out the smartest people and get them to come to your country. A country that got immigration right would have a huge advantage. At this point you could become a mecca for smart people simply by having an immigration system that let them in. A Good Vector If you look at the kinds of things you have to do to create an environment where startups condense, none are great sacrifices. Great universities? Livable towns? Civil liberties? Flexible employment laws? Immigration policies that let in smart people? Tax laws that encourage growth? It's not as if you have to risk destroying your country to get a silicon valley; these are all good things in their own right.
And then of course there's the question, can you afford not to? I can imagine a future in which the default choice of ambitious young people is to start their own company rather than work for someone else's. I'm not sure that will happen, but it's where the trend points now. And if that is the future, places that don't have startups will be a whole step behind, like those that missed the Industrial Revolution. Notes [1] On the verge of the Industrial Revolution, England was already the richest country in the world. As far as such things can be compared, per capita income in England in 1750 was higher than India's in 1960. Deane, Phyllis, _The First Industrial Revolution_ , Cambridge University Press, 1965. [2] This has already happened once in China, during the Ming Dynasty, when the country turned its back on industrialization at the command of the court. One of Europe's advantages was that it had no government powerful enough to do that. [3] Of course, Feynman and Diogenes were from adjacent traditions, but Confucius, though more polite, was no more willing to be told what to think. [4] For similar reasons it might be a lost cause to try to establish a silicon valley in Israel. Instead of no Jews moving there, only Jews would move there, and I don't think you could build a silicon valley out of just Jews any more than you could out of just Japanese. (This is not a remark about the qualities of these groups, just their sizes. Japanese are only about 2% of the world population, and Jews about .2%.) [5] According to the World Bank, the initial capital requirement for German companies is 47.6% of the per capita income. Doh. World Bank, _Doing Business in 2006_ , http://doingbusiness.org [6] For most of the twentieth century, Europeans looked back on the summer of 1914 as if they'd been living in a dream world.
It seems more accurate (or at least, as accurate) to call the years after 1914 a nightmare than to call those before a dream. A lot of the optimism Europeans consider distinctly American is simply what they too were feeling in 1914. [7] The point where things start to go wrong seems to be about 50%. Above that people get serious about tax avoidance. The reason is that the payoff for avoiding tax grows hyperexponentially (x/1-x for 0 < x < 1). If your income tax rate is 10%, moving to Monaco would only give you 11% more income, which wouldn't even cover the extra cost. If it's 90%, you'd get ten times as much income. And at 98%, as it was briefly in Britain in the 70s, moving to Monaco would give you fifty times as much income. It seems quite likely that European governments of the 70s never drew this curve. Thanks to Trevor Blackwell, Matthias Felleisen, Jessica Livingston, Robert Morris, Neil Rimer, Hugues Steinier, Brad Templeton, Fred Wilson, and Stephen Wolfram for reading drafts of this, and to Ed Dumbill for inviting me to speak.
| French Translation | | | Russian Translation | Japanese Translation | | | Arabic Translation.
2006年5月 (本文源自Xtech大会的主题演讲) 初创企业往往集群而生。硅谷和波士顿遍地皆是,芝加哥或迈阿密却寥寥无几。一个国家若想培育初创企业,很可能需要复刻促成这些集群形成的条件。 我曾提出秘诀在于:在聪明人喜爱的城镇附近建立顶尖大学。若在美国境内营造这些条件,初创企业就会如冷凝水珠般自然涌现。但当我思考如何在其他国家复刻硅谷时,显然美国具备独特的"湿润环境"——这里更易催生初创企业。 在其他国家打造硅谷并非毫无希望。不仅有可能与之比肩,更可能实现超越。但要做到这点,必须理解美国赋予初创企业的优势。 1. 美国允许移民 例如,我认为日本难以复刻硅谷,因为硅谷最鲜明的特征就是移民文化。这里半数人口带着异国口音。而日本并不欢迎移民。当日本人思考如何打造本土硅谷时,我猜他们潜意识里设定的命题是"如何建立纯日本人组成的硅谷"。这种思维框架注定失败。 硅谷必须是智慧与野心家的圣地,若拒绝外人进入,就永远无法成为圣地。 当然,美国比日本开放移民这点不足为奇。移民政策正是竞争对手可以超越的领域。 2. 美国是富裕国家 我认为印度未来可能孕育硅谷的竞争者。印度显然不缺人才——现有硅谷中的印度裔数量就是明证。问题在于印度自身仍太贫穷。 在贫困国家,我们习以为常的事物往往缺失。我朋友造访印度时,曾在火车站台阶扭伤脚踝。当她回头查看,发现台阶高度参差不齐。在工业化国家,我们行走台阶一辈子都不会注意这点,因为基础设施杜绝了这种设计缺陷。 美国从未像某些国家现今这般贫困。美国城市街头从未出现过成群乞丐。因此我们无从得知:从乞丐成群到硅谷林立需要哪些条件?能否同步实现?还是需要先达到某种基础繁荣水平? 我猜测经济发展存在速度极限。经济由人构成,而观念迭代需要代际更替。[1] 3. 美国(尚)非警察国家 另一个可能渴望硅谷的国家是中国。但我认为他们也尚未具备条件。中国仍像是个警察国家,尽管当前统治者比前任开明,但即便开明专制恐怕也只能实现经济强国目标的部分路径。 它能建立代工厂生产他国设计的产品。但它能培育设计师吗?在禁止批评政府的地方,想象力能繁荣吗?想象力意味着离经叛道的思想,而技术上的奇思妙想往往伴随政治上的异见。更何况,许多技术理念确实具有政治意涵。压制异议的反作用力终将蔓延至技术领域。[2] 新加坡面临类似问题。新加坡政府似乎深知鼓励初创企业的重要性。但政府强力干预能让港口高效运转,却无法孕育初创企业。一个禁止口香糖的国家,距离创造旧金山这样的城市还很遥远。 是否需要旧金山式的城市?是否存在通过服从与合作(而非个人主义)实现创新的另类路径?或许有,但我敢打赌不存在。古往今来,最具想象力的人似乎都带有某种桀骜的独立性——从第欧根尼让亚历山大大帝别挡住阳光,到两千年后费曼在洛斯阿拉莫斯撬保险柜,莫不如此。[3]富有想象力的人既不愿追随也不愿领导。当每个人都能做自己想做的事时,他们最具创造力。 讽刺的是,在所有富裕国家中,美国近年来丧失的公民自由最多。但我并不太担忧。我希望现政府下台后,美国文化天然的开放性将自我修复。 4. 美国大学更优秀 孕育硅谷需要顶尖大学,而美国之外这样的学府屈指可数。我询问数位美国计算机科学教授欧洲最受推崇的大学,他们基本都回答"剑桥",然后陷入漫长停顿试图想出其他名字。至少在科技领域,其他国家似乎少有能与美国顶尖大学比肩者。 某些国家这是刻意政策的结果。德荷政府或许出于反精英主义,竭力确保所有大学质量相当。代价就是没有特别出众者。最优秀的教授分散各处,而非像美国那样高度集中。这可能导致产出降低,因为他们缺乏激发灵感的优秀同僚。这也意味着没有哪所大学能成为吸引全球人才的圣地,进而形成初创企业集群。 德国情况尤为奇特。德国人发明了现代大学体系,直至1930年代其大学仍冠绝全球。如今却无一突出。当我思考此事时,不禁自问:"我能理解1930年代排斥犹太人后德国大学的衰落。但理应当已恢复。"随即我意识到:或许不能。德国犹太人所剩无几,而我认识的犹太人多不愿移居德国。若从任何美国顶尖大学移除犹太群体,都将留下巨大空白。因此在德国打造硅谷或许是徒劳,因为你无法建立所需水平的种子大学。[4] 美国大学自然相互竞争,因为多数是私立院校。要复刻美国大学质量,很可能也需复刻这点。若大学由中央政府控制,政治分肥将使其趋于平庸:新建的X研究院终将落户某权贵政客的选区,而非应处之地。 5. 美国可以解雇员工 我认为欧洲创建初创企业的最大障碍之一是对雇佣关系的态度。著名的僵化劳动法伤害所有公司,对初创企业尤甚,因为它们最经不起官僚程序的折腾。 解雇困难对初创企业特别棘手,因为它们没有冗余编制。每个人都必须胜任工作。 但问题不止于某个初创企业可能难解雇必要人员。纵观各行业与国家,绩效与职业保障呈强烈负相关。演员和导演每部电影结束后都可能被"解雇",因此必须每次都有表现。助理教授数年后默认解聘,除非大学授予终身教职。职业运动员知道只要几场表现不佳就会被换下。天平另一端(至少在美国)是汽车工人、纽约市教师和公务员——这些人几乎不可能被解雇。趋势如此明显,只有刻意视而不见才会忽略。 你说绩效不是全部?那么汽车工人、教师和公务员比演员、教授和职业运动员更快乐吗? 欧洲舆论显然能接受他们真正在乎绩效的行业解雇人。遗憾的是目前他们足够在乎的只有足球。但这至少是个先例。 6. 美国不将工作等同于雇佣 欧洲和日本等更传统地区的问题比雇佣法更深刻。更危险的是其反映的态度:雇员是某种仆人,雇主有义务保护。美国也曾如此。1970年人们仍应进入大公司工作,理想是奉献整个职业生涯。作为回报,公司会照顾你:尽量不解雇,支付医疗费用,养老保障。 逐渐地,雇佣关系褪去这种家长制色彩,变成单纯的经济交换。但新模型的重要性不仅在于更易让初创企业成长。更重要的是,我认为它让人更易创立初创企业。 即使在美国,多数大学毕业生仍认为应该找工作,仿佛不成为雇员就无法创造价值。但工作与雇佣的等同性越弱,创立初创企业就越容易。当把职业生涯视为一系列不同类型的工作,而非对单一雇主的终身服务时,创立自己公司的风险更小,因为你只是替换一个片段而非抛弃整体。 旧观念如此强大,连最成功的初创企业创始人都不得不与之斗争。苹果创立一年后,沃兹尼亚克仍未辞去惠普工作。他仍计划终身效力惠普。当乔布斯找到人为苹果提供严肃风险投资,条件是他辞职时,他最初拒绝,辩称自己在惠普工作时既设计了Apple I也设计了Apple II,没理由不能继续。 7. 美国不拘小节 若有任何商业法规,你可以假定初创雏形会违反其中多数,因为它们既不知道这些法规,也没时间了解。 例如,美国许多初创企业始于本不合法经营的地方。惠普、苹果和谷歌都始于车库。更多初创企业(包括我们)最初在公寓运营。若这些禁令严格执行,多数初创企业不会诞生。 这在挑剔的国家可能成为问题。若休利特和帕卡德在瑞士车库运营电子公司,隔壁老太太会向市政当局举报他们。 但其他国家最糟的问题或许是开公司本身所需努力。我朋友1990年代初在德国创业,震惊地发现(除众多规定外)需要2万美元资本金注册。这就是为何我不是在Apfel笔记本上打字。乔布斯和沃兹尼亚克靠卖大众面包车和HP计算器筹资的公司拿不出这笔钱。我们也不可能创立Viaweb。[5] 给想鼓励初创企业的政府一个建议:阅读现有初创企业的故事,然后模拟在贵国会发生什么。当遇到会扼杀苹果公司的因素时,就修剪掉。 初创企业是边缘性的。它们由穷人和胆怯者创立;始于边缘空间和业余时间;由本应做其他事的人创立;尽管是企业,其创始人常对商业一无所知。年轻初创企业很脆弱。一个严苛修剪边缘的社会会扼杀它们全部。 8. 美国拥有庞大国内市场 初创企业初期靠推出初始产品的期望维系。因此成功者会把第一版做得尽可能简单。在美国,它们通常先为本地市场打造产品。 这在美国可行,因为本地市场有3亿人。在瑞典就行不通。小国的初创企业任务更艰巨:必须从一开始就国际销售。 欧盟设计部分是为模拟单一庞大国内市场。问题在于居民仍说多种语言。因此瑞典的软件初创企业相对美国处于劣势,因为它们必须从一开始就处理国际化问题。值得注意的是欧洲最近最著名的初创企业Skype,解决的是本质国际性的问题。 然而,无论好坏,欧洲似乎几十年后将通用一种语言。1990年我在意大利求学时,少有意大利人说英语。如今所有受教育者似乎都被要求掌握——而欧洲人不愿显得没文化。这大概是个禁忌话题,但若当前趋势持续,法语和德语终将如爱尔兰语和卢森堡语:只在家庭和古怪民族主义者中使用。 9. 美国拥有风险投资 初创企业在美国更易创立,因为融资更便利。美国之外现在也有少数风投公司,但初创资金不仅来自风投。更重要来源(因更个人化且介入更早)是天使投资人的资金。若非先获得安迪·贝托尔斯海姆的十万美元,谷歌可能永远达不到从风投融资数百万的阶段。而他能帮助他们,因为他是Sun公司创始人。这种模式在初创枢纽不断重演。正是这种模式造就了初创枢纽。 好消息是,要启动这个过程,只需成功推出最初几家初创企业。如果致富后他们留在当地,初创企业创始人几乎会自动资助和鼓励新初创企业。 坏消息是这个循环很慢。初创企业创始人平均需要五年才能进行天使投资。尽管政府或许能通过注资和从现有公司招募人员建立本地风投基金,但只有有机增长能产生天使投资人。 顺便说,美国私立大学是风险资本充裕的原因之一。风投基金大量资金来自大学捐赠基金。因此私立大学的另一优势是国家大量财富由开明的投资者管理。 10. 美国对职业采用动态类型 相比其他工业化国家,美国在职业引导方面更无组织。例如在美国,人们常到大学毕业才决定读医学院。在欧洲通常高中就决定。 欧洲方式反映旧观念:每人有单一明确职业——这与人生而有其自然"位置"的观念相去不远。若真如此,最有效方案就是尽早发现每人位置,以便接受相应训练。 在美国事情更随机。但随着经济流动性增强,这反成优势,正如动态类型对模糊问题比静态类型更有效。对初创企业尤其如此。"初创企业创始人"不是高中生会选择的职业。若在那个年龄询问,人们会选择保守。他们会选择工程师、医生或律师等熟知的职业。 初创企业是人们不去计划的事物,因此在允许随时决定职业的社会更可能出现。 例如,理论上博士项目的目的是训练研究能力。但幸运的是在美国,这条规则执行也不严格。美国多数计算机科学博士生就读只因想学更多。他们尚未决定之后做什么。因此美国研究生院催生许多初创企业,因为学生不觉得不从事研究就是失败。 那些担忧美国"竞争力"的人常建议增加公立学校投入。但或许美国糟糕的公立学校有个隐藏优势。正因太差,孩子们养成了等待大学的态度。我就是;我知道自己学得太少,甚至不了解选择项,更谈不上选择。这令人沮丧,但至少让你保持开放心态。 当然,若必须在"差高中+好大学"(如美国)和"好高中+差大学"(如多数其他工业化国家)间选择,我会选美国体系。让所有人感觉是大器晚成者,好过是失败的神童。 态度 这个清单明显漏掉一项:美国态度。据说美国人更具创业精神,更不惧风险。但美国对此并无垄断。印度人和中国人似乎很有创业精神,或许超过美国人。 有人说欧洲人缺乏活力,但我不信。我认为欧洲的问题不是缺乏胆量,而是缺乏榜样。 即使在美国,最成功的初创企业创始人常是技术出身,最初对创业想法相当胆怯。少有我们印象中典型美国式的拍背外向者。通常只有遇到做过的人并意识到自己也能行时,他们才能积聚起创业的活化能。 我认为阻碍欧洲黑客的只是他们没遇到那么多做过的人。即使在美国内部也能看到这种差异。斯坦福学生比耶鲁学生更具创业精神,但非因性格差异;耶鲁学生只是榜样更少。 我承认欧美对野心的态度似乎不同。在美国公开有野心没问题,在欧洲多数地方则不然。但这不可能是欧洲固有特质;前几代欧洲人和美国人一样野心勃勃。发生了什么?我的假设是野心因二十世纪上半叶野心家所做的可怕事情而声名狼藉。如今虚张声势过时了。(即使现在,一个极度野心勃勃的德国人形象不也会按下某些按钮吗?) 若欧洲态度未受二十世纪灾难影响才奇怪。经历那些事件后需要时间恢复乐观。但野心是人性。它会逐渐重现。[6] 如何做得更好 我列此清单并非暗示美国是初创企业的完美之地。它是目前最佳,但样本量小,且"目前"时间不长。在历史尺度上,现有成果只是原型。 因此让我们像审视竞争对手产品那样看硅谷。你能利用哪些弱点?如何做出用户更喜爱的产品?此处的用户是那些你希望吸引至硅谷的关键数千人。 首先,硅谷离旧金山太远。最初爆心投影点帕洛阿尔托约30英里,现今中心更达40英里。因此来硅谷工作的人面临痛苦选择:要么住在硅谷本地的无聊郊区,要么住在旧金山忍受单程一小时通勤。 最佳情况是硅谷不仅离有趣城市更近,本身也很有趣。这方面大有改进空间。帕洛阿尔托还不错,但之后建造的全是最糟糕的带状开发区。其令人沮丧的程度可用宁愿每天牺牲两小时通勤也不住那里的人数衡量。 另一个容易超越硅谷的领域是公共交通。硅谷沿线有火车,按美国标准不算差。即对日本或欧洲人而言像第三世界产物。 你想吸引至硅谷的那类人喜欢乘火车、骑自行车和步行。因此若要超越美国,就设计一个汽车优先级最低的城镇。美国城市要下决心这么做还需时日。 资本利得 在国家层面也有几件事可超越美国。其一是实行更低资本利得税。拥有最低所得税似乎不关键,因为要利用这点人们必须搬迁。[7]但若资本利得税率不同,你移动的是资产而非自身,因此变化会以市场速度反映。税率越低,购买成长型企业股票(相对于房地产、债券或为股息购买的股票)就越便宜。 因此若要鼓励初创企业,应设定低资本利得税率。但政客在此左右为难:降低税率被指责"为富人减税",提高税率又让成长型企业缺乏投资资本。如加尔布雷斯所言,政治是在难以下咽和灾难性间选择。二十世纪许多政府尝试了灾难性;如今趋势似乎是转向仅难以下咽。 奇怪的是,如今领先的是比利时等欧洲国家,其资本利得税率为零。 移民 另一个可超越美国之处是更明智的移民政策。这里收益巨大。记住,硅谷由人构成。 就像软件运行在Windows上的公司,现有硅谷企业对移民局的缺陷心知肚明却无能为力。他们是平台的"人质"。 美国移民系统从未良好运行,2001年后更添偏执。想赴美的聪明人有多少能成功入境?我怀疑不到半数。这意味着若建立允许所有聪明人进入的竞争性技术中心,你将立即免费获得超半数世界顶尖人才。 美国移民政策特别不适合初创企业,因为它反映1970年代的工作模式。它假定优秀技术人才拥有大学学位,且工作意味着为大公司效力。 若无大学学位,就无法获得通常签发给程序员的H1B签证。但一个将乔布斯、盖茨和戴尔拒之门外的测试不可能是好测试。此外,你无法为自己公司工作获得签证,只能为他人公司打工。若想申请公民身份,你根本不敢为初创企业工作,因为若担保公司倒闭,你必须重头再来。 美国移民政策将多数聪明人挡在门外,并将其余引向低效工作。要做得更好很容易。想象一下,若你把移民当作招聘——若你有意识地努力寻找最聪明的人并吸引他们来你的国家。 移民政策正确的国家将具巨大优势。当前,仅凭允许聪明人入境的移民系统,你就能成为他们的圣地。 优质载体 若要创造初创企业凝聚的环境,所需措施无一需要巨大牺牲。顶尖大学?宜居城镇?公民自由?弹性雇佣法?允许聪明人入境的移民政策?鼓励增长的税法?要获得硅谷,你不必冒险摧毁国家;这些本就是好东西。 当然还有问题:你能承受不这样做的代价吗?我能想象未来雄心勃勃的年轻人默认选择是创立自己的公司而非为他人工作。我不确定这会发生,但这是当前趋势所指。若那是未来,没有初创企业的地方将如错过工业革命者般落后整整一步。 注释 [1] 工业革命前夕,英格兰已是全球最富裕国家。就可比性而言,1750年英格兰人均收入高于1960年的印度。 迪恩,菲利斯,《第一次工业革命》,剑桥大学出版社,1965年。 [2] 这在中国明代已发生过一次,当时朝廷命令国家背弃工业化。欧洲的优势之一就是没有足够强大的政府这么做。 [3] 当然,费曼和第欧根尼来自相邻传统,.
May 2006 _(This essay is derived from a keynote at Xtech.)_ Could you reproduce Silicon Valley elsewhere, or is there something unique about it? It wouldn't be surprising if it were hard to reproduce in other countries, because you couldn't reproduce it in most of the US either. What does it take to make a silicon valley even here? What it takes is the right people. If you could get the right ten thousand people to move from Silicon Valley to Buffalo, Buffalo would become Silicon Valley. [1] That's a striking departure from the past. Up till a couple decades ago, geography was destiny for cities. All great cities were located on waterways, because cities made money by trade, and water was the only economical way to ship. Now you could make a great city anywhere, if you could get the right people to move there. So the question of how to make a silicon valley becomes: who are the right people, and how do you get them to move? Two Types I think you only need two kinds of people to create a technology hub: rich people and nerds. They're the limiting reagents in the reaction that produces startups, because they're the only ones present when startups get started. Everyone else will move. Observation bears this out: within the US, towns have become startup hubs if and only if they have both rich people and nerds. Few startups happen in Miami, for example, because although it's full of rich people, it has few nerds. It's not the kind of place nerds like. Whereas Pittsburgh has the opposite problem: plenty of nerds, but no rich people. The top US Computer Science departments are said to be MIT, Stanford, Berkeley, and Carnegie-Mellon. MIT yielded Route 128. Stanford and Berkeley yielded Silicon Valley. But Carnegie-Mellon? The record skips at that point. Lower down the list, the University of Washington yielded a high-tech community in Seattle, and the University of Texas at Austin yielded one in Austin.
(本文源自Xtech大会的主题演讲。)
能否在其他地方复制硅谷,还是它拥有某种独特性?
若在其他国家难以复制硅谷并不令人惊讶,因为在美国大部分地区同样无法复制。即便在美国本土,打造硅谷需要哪些条件?
关键在于聚集对的人。如果能促使一万名硅谷的核心人群迁居布法罗市,布法罗就会蜕变为新的硅谷。[1]
这与历史形成鲜明对比。直至二十年前,地理位置仍决定城市命运。所有伟大城市都依水而建,因为城市通过贸易获利,而水运曾是唯一经济的运输方式。
But what happened in Pittsburgh? And in Ithaca, home of Cornell, which is also high on the list? I grew up in Pittsburgh and went to college at Cornell, so I can answer for both. The weather is terrible, particularly in winter, and there's no interesting old city to make up for it, as there is in Boston. Rich people don't want to live in Pittsburgh or Ithaca. So while there are plenty of hackers who could start startups, there's no one to invest in them. Not Bureaucrats Do you really need the rich people? Wouldn't it work to have the government invest in the nerds? No, it would not. Startup investors are a distinct type of rich people. They tend to have a lot of experience themselves in the technology business. This (a) helps them pick the right startups, and (b) means they can supply advice and connections as well as money. And the fact that they have a personal stake in the outcome makes them really pay attention. Bureaucrats by their nature are the exact opposite sort of people from startup investors. The idea of them making startup investments is comic. It would be like mathematicians running _Vogue_ \-- or perhaps more accurately, _Vogue_ editors running a math journal. [2] Though indeed, most things bureaucrats do, they do badly. We just don't notice usually, because they only have to compete against other bureaucrats. But as startup investors they'd have to compete against pros with a great deal more experience and motivation. Even corporations that have in-house VC groups generally forbid them to make their own investment decisions. Most are only allowed to invest in deals where some reputable private VC firm is willing to act as lead investor. Not Buildings If you go to see Silicon Valley, what you'll see are buildings. But it's the people that make it Silicon Valley, not the buildings.
如今,只要吸引对的人才,任何地方都能崛起为伟大城市。因此"如何打造硅谷"的问题可转化为:谁是核心人群?如何吸引他们迁移?
我认为构建科技中心只需两类人:富人和极客。他们是催生初创企业的关键要素,因为初创阶段仅有这两类人参与,其他角色会随之而来。
现实印证了这点:美国城市要成为创业中心,必须同时拥有富人和极客。例如迈阿密虽富人云集却缺乏极客,因而创业稀少——这里不符合极客的审美。
匹兹堡则面临相反困境:极客众多但缺少富人。美国顶尖计算机院系公认是MIT、斯坦福、伯克利和卡内基梅隆。MIT孕育了128号公路,斯坦福与伯克利造就了硅谷。但卡内基梅隆呢?历史在此留下空白。榜单下游,华盛顿大学孕育了西雅图的高科技生态,德州大学奥斯汀分校助力奥斯汀崛起。而匹兹堡和康奈尔大学所在的伊萨卡又发生了什么?
作为在匹兹堡长大、康奈尔求学的亲历者,我可以解答:两地冬季气候恶劣,又缺乏波士顿式的历史底蕴,富人无意定居。因此尽管技术人才充足,却缺乏投资力量。
I read occasionally about attempts to set up "technology parks" in other places, as if the active ingredient of Silicon Valley were the office space. An article about Sophia Antipolis bragged that companies there included Cisco, Compaq, IBM, NCR, and Nortel. Don't the French realize these aren't startups? Building office buildings for technology companies won't get you a silicon valley, because the key stage in the life of a startup happens before they want that kind of space. The key stage is when they're three guys operating out of an apartment. Wherever the startup is when it gets funded, it will stay. The defining quality of Silicon Valley is not that Intel or Apple or Google have offices there, but that they were _started_ there. So if you want to reproduce Silicon Valley, what you need to reproduce is those two or three founders sitting around a kitchen table deciding to start a company. And to reproduce that you need those people. Universities The exciting thing is, _all_ you need are the people. If you could attract a critical mass of nerds and investors to live somewhere, you could reproduce Silicon Valley. And both groups are highly mobile. They'll go where life is good. So what makes a place good to them? What nerds like is other nerds. Smart people will go wherever other smart people are. And in particular, to great universities. In theory there could be other ways to attract them, but so far universities seem to be indispensable. Within the US, there are no technology hubs without first-rate universities-- or at least, first-rate computer science departments. So if you want to make a silicon valley, you not only need a university, but one of the top handful in the world. It has to be good enough to act as a magnet, drawing the best people from thousands of miles away. And that means it has to stand up to existing magnets like MIT and Stanford. This sounds hard.
富人真是必需的吗?政府直接投资极客是否可行?答案是否定的。初创投资者是特殊的富人群体,通常具备科技行业深厚经验:这既帮助他们甄选优质项目,又能提供资金外的专业指导与人脉。个人利益关联更驱使他们全心投入。
官僚本质与风投家截然相反。设想官僚主导投资如同让数学家主编《Vogue》,或让时尚编辑运营数学期刊般荒诞。[2]
官僚体系多数事务都处理拙劣,只是通常在与同类对比时不显。但作为投资者,他们将面对经验与动力都远超自己的专业对手。
即便设立内部风投部门的企业,也多禁止其自主决策,通常只允许跟投知名风投领投的项目。
硅谷的表象是建筑群,但灵魂在于人。偶见其他地方筹建"科技园区"的报道,仿佛硅谷的精髓在于办公空间。某篇关于索菲亚科技园的文章夸耀入驻企业包括思科、康柏、IBM等——法国人难道不明白这些都不是初创公司?
Actually it might be easy. My professor friends, when they're deciding where they'd like to work, consider one thing above all: the quality of the other faculty. What attracts professors is good colleagues. So if you managed to recruit, en masse, a significant number of the best young researchers, you could create a first-rate university from nothing overnight. And you could do that for surprisingly little. If you paid 200 people hiring bonuses of $3 million apiece, you could put together a faculty that would bear comparison with any in the world. And from that point the chain reaction would be self-sustaining. So whatever it costs to establish a mediocre university, for an additional half billion or so you could have a great one. [3] Personality However, merely creating a new university would not be enough to start a silicon valley. The university is just the seed. It has to be planted in the right soil, or it won't germinate. Plant it in the wrong place, and you just create Carnegie-Mellon. To spawn startups, your university has to be in a town that has attractions other than the university. It has to be a place where investors want to live, and students want to stay after they graduate. The two like much the same things, because most startup investors are nerds themselves. So what do nerds look for in a town? Their tastes aren't completely different from other people's, because a lot of the towns they like most in the US are also big tourist destinations: San Francisco, Boston, Seattle. But their tastes can't be quite mainstream either, because they dislike other big tourist destinations, like New York, Los Angeles, and Las Vegas. There has been a lot written lately about the "creative class." The thesis seems to be that as wealth derives increasingly from ideas, cities will prosper only if they attract those who have them. That is certainly true; in fact it was the basis of Amsterdam's prosperity 400 years ago.
为科技公司建造办公楼无法孕育硅谷,因为初创企业的关键成长阶段发生在公寓里的三人团队时期。获得融资时企业所在的位置,就是其扎根之地。硅谷的本质不在于英特尔、苹果或谷歌的入驻,而在于它们在此诞生。
因此复制硅谷,实质是复制厨房餐桌旁两三位创始人决心创业的场景。而复制这一场景,需要复制那群人。
激动人心的是:你只需要人。若能吸引足够数量的极客与投资者聚居,就能复制硅谷。这两类群体流动性极强,会主动选择宜居之地。什么构成他们的理想居所?
极客渴望同类。聪明人会追随聪明人的聚集地,尤其是一流大学。理论上或有其他吸引方式,但迄今大学仍不可替代。美国所有科技中心都依托顶尖大学——至少是顶尖计算机院系。
因此打造硅谷不仅需要大学,更需要世界顶级学府。它必须足够卓越,能吸引千里之外的顶尖人才,这意味着要与MIT、斯坦福等现有磁极比肩。
A lot of nerd tastes they share with the creative class in general. For example, they like well-preserved old neighborhoods instead of cookie-cutter suburbs, and locally-owned shops and restaurants instead of national chains. Like the rest of the creative class, they want to live somewhere with personality. What exactly is personality? I think it's the feeling that each building is the work of a distinct group of people. A town with personality is one that doesn't feel mass-produced. So if you want to make a startup hub-- or any town to attract the "creative class"-- you probably have to ban large development projects. When a large tract has been developed by a single organization, you can always tell. [4] Most towns with personality are old, but they don't have to be. Old towns have two advantages: they're denser, because they were laid out before cars, and they're more varied, because they were built one building at a time. You could have both now. Just have building codes that ensure density, and ban large scale developments. A corollary is that you have to keep out the biggest developer of all: the government. A government that asks "How can we build a silicon valley?" has probably ensured failure by the way they framed the question. You don't build a silicon valley; you let one grow. Nerds If you want to attract nerds, you need more than a town with personality. You need a town with the right personality. Nerds are a distinct subset of the creative class, with different tastes from the rest. You can see this most clearly in New York, which attracts a lot of creative people, but few nerds. [5] What nerds like is the kind of town where people walk around smiling. This excludes LA, where no one walks at all, and also New York, where people walk, but not smiling. When I was in grad school in Boston, a friend came to visit from New York.
这看似艰难,实则可能容易。教授朋友们择业时最看重同事水平。吸引学者的正是优秀同行。若能集中招募大批顶尖青年研究者,一夜之间就能创建世界级大学。所需成本出人意料:若以每人300万美元招募200人,就能组建媲美全球任何名校的师资。此后链式反应将自我维持。因此,在建设普通大学的基础上,追加约5亿美元即可打造顶尖学府。[3]
但仅创建新大学不足以孕育硅谷。大学只是种子,需要适宜的土壤才能发芽。选址错误只会再造一个卡内基梅隆。
要培育初创企业,大学所在城市必须拥有超越校园的吸引力——既要让投资者愿意定居,也要让学生毕业后选择留下。
两类人群的偏好高度重合,因为多数投资者本身也是极客。极客青睐怎样的城市?他们的品味与大众并非完全相左:旧金山、波士顿、西雅图既是极客圣地也是旅游热点。但又不尽相同:他们厌恶纽约、洛杉矶、拉斯维加斯等主流旅游地。
近来关于"创意阶层"的讨论颇多。核心论点是:当财富日益源于创意时,城市繁荣取决于能否吸引创意人才。这千真万确——四百年前阿姆斯特丹的繁荣正是基于此。
On the subway back from the airport she asked "Why is everyone smiling?" I looked and they weren't smiling. They just looked like they were compared to the facial expressions she was used to. If you've lived in New York, you know where these facial expressions come from. It's the kind of place where your mind may be excited, but your body knows it's having a bad time. People don't so much enjoy living there as endure it for the sake of the excitement. And if you like certain kinds of excitement, New York is incomparable. It's a hub of glamour, a magnet for all the shorter half-life isotopes of style and fame. Nerds don't care about glamour, so to them the appeal of New York is a mystery. People who like New York will pay a fortune for a small, dark, noisy apartment in order to live in a town where the cool people are really cool. A nerd looks at that deal and sees only: pay a fortune for a small, dark, noisy apartment. Nerds _will_ pay a premium to live in a town where the smart people are really smart, but you don't have to pay as much for that. It's supply and demand: glamour is popular, so you have to pay a lot for it. Most nerds like quieter pleasures. They like cafes instead of clubs; used bookshops instead of fashionable clothing shops; hiking instead of dancing; sunlight instead of tall buildings. A nerd's idea of paradise is Berkeley or Boulder. Youth It's the young nerds who start startups, so it's those specifically the city has to appeal to. The startup hubs in the US are all young-feeling towns. This doesn't mean they have to be new. Cambridge has the oldest town plan in America, but it feels young because it's full of students. What you can't have, if you want to create a silicon valley, is a large, existing population of stodgy people. It would be a waste of time to try to reverse the fortunes of a declining industrial town like Detroit or Philadelphia by trying to encourage startups.
极客与广义创意阶层有许多共同偏好:他们钟爱保存完好的历史街区而非千篇一律的郊区,青睐本地特色商铺而非连锁品牌。与其他创意人一样,他们追求有性格的居所。
何为城市性格?我认为是每栋建筑都彰显独特群体印记的感觉。有性格的城市拒绝流水线生产。因此要打造创业中心(或任何吸引创意阶层的城市),或许需要禁止大型开发项目——单一机构开发的片区总带着标准化痕迹。[4]
多数有性格的城市历史悠久,但非必然。老城具备两大优势:汽车时代前规划的高密度,以及渐进建设形成的多样性。现代城市通过建筑法规确保密度,禁止大规模开发,同样可以实现。
由此引申:必须排除最大的开发商——政府。当政府询问"如何建设硅谷"时,其提问方式已预示失败。硅谷无法被建造,只能任其生长。
要吸引极客,仅有个性城市不够,还需契合其独特品味。极客是创意阶层的子集,在纽约表现最明显:这里吸引大量创意人却少有极客。[5]
Those places have too much momentum in the wrong direction. You're better off starting with a blank slate in the form of a small town. Or better still, if there's a town young people already flock to, that one. The Bay Area was a magnet for the young and optimistic for decades before it was associated with technology. It was a place people went in search of something new. And so it became synonymous with California nuttiness. There's still a lot of that there. If you wanted to start a new fad-- a new way to focus one's "energy," for example, or a new category of things not to eat-- the Bay Area would be the place to do it. But a place that tolerates oddness in the search for the new is exactly what you want in a startup hub, because economically that's what startups are. Most good startup ideas seem a little crazy; if they were obviously good ideas, someone would have done them already. (How many people are going to want computers in their _houses_? What, _another_ search engine?) That's the connection between technology and liberalism. Without exception the high-tech cities in the US are also the most liberal. But it's not because liberals are smarter that this is so. It's because liberal cities tolerate odd ideas, and smart people by definition have odd ideas. Conversely, a town that gets praised for being "solid" or representing "traditional values" may be a fine place to live, but it's never going to succeed as a startup hub. The 2004 presidential election, though a disaster in other respects, conveniently supplied us with a county-by-county map of such places. [6] To attract the young, a town must have an intact center. In most American cities the center has been abandoned, and the growth, if any, is in the suburbs. Most American cities have been turned inside out. But none of the startup hubs has: not San Francisco, or Boston, or Seattle.
极客向往人们微笑漫步的城市。这排除了无人步行的洛杉矶,也排除了行人冷漠的纽约。我在波士顿读研时,纽约访友曾在地铁上问:"为什么人人都在笑?"实际上他们只是比她习惯的表情更放松。
纽约客的面部表情源自何处?在这里,心灵可能兴奋,身体却诚实地抗拒。人们为都市刺激忍受生活不便。若追求特定类型的兴奋感,纽约无与伦比——它是魅力中心,吸引所有短暂闪耀的风格与名声。
极客不慕浮华,因此纽约魅力对他们成谜。热衷者愿为阴暗嘈杂的小公寓支付高价,只为与真正酷的人为邻;极客眼中这交易只剩:高价换取糟糕居住条件。
极客确实愿为聪明人聚集地支付溢价,但成本低得多——这是供需关系:魅力需求旺盛导致高价,而智力聚集地溢价较低。
多数极客偏爱安静乐趣:咖啡馆而非夜店,二手书店而非时装店,远足而非舞会,阳光而非摩天楼。伯克利或博尔德才是极客天堂。
They all have intact centers. [7] My guess is that no city with a dead center could be turned into a startup hub. Young people don't want to live in the suburbs. Within the US, the two cities I think could most easily be turned into new silicon valleys are Boulder and Portland. Both have the kind of effervescent feel that attracts the young. They're each only a great university short of becoming a silicon valley, if they wanted to. Time A great university near an attractive town. Is that all it takes? That was all it took to make the original Silicon Valley. Silicon Valley traces its origins to William Shockley, one of the inventors of the transistor. He did the research that won him the Nobel Prize at Bell Labs, but when he started his own company in 1956 he moved to Palo Alto to do it. At the time that was an odd thing to do. Why did he? Because he had grown up there and remembered how nice it was. Now Palo Alto is suburbia, but then it was a charming college town-- a charming college town with perfect weather and San Francisco only an hour away. The companies that rule Silicon Valley now are all descended in various ways from Shockley Semiconductor. Shockley was a difficult man, and in 1957 his top people-- "the traitorous eight"-- left to start a new company, Fairchild Semiconductor. Among them were Gordon Moore and Robert Noyce, who went on to found Intel, and Eugene Kleiner, who founded the VC firm Kleiner Perkins. Forty-two years later, Kleiner Perkins funded Google, and the partner responsible for the deal was John Doerr, who came to Silicon Valley in 1974 to work for Intel. So although a lot of the newest companies in Silicon Valley don't make anything out of silicon, there always seem to be multiple links back to Shockley. There's a lesson here: startups beget startups. People who work for startups start their own. People who get rich from startups fund new ones.
初创企业多由年轻极客创立,因此城市需特别吸引他们。美国所有创业中心都充满年轻气息。这不要求城市年轻——剑桥市拥有美国最古老规划,却因学生云集而朝气蓬勃。
若要打造硅谷,绝不能有大量顽固守旧人群。试图通过创业振兴底特律、费城等衰败工业城纯属徒劳——这些地方惯性太强。不如从白纸状态的小城起步,或直接选择已受年轻人追捧的城镇。
湾区在成为科技代名词前数十年,就已是年轻乐观者的磁石。人们来此追寻新事物,这里遂成加州怪诞精神的象征。这种特质至今犹存——若要发起新潮流(比如新型"能量聚焦法"或新禁食类别),湾区仍是理想试验场。而这种对新奇事物的包容,正是创业中心的本质:因为经济层面,初创企业就是新奇事物。优秀创业点子往往显得疯狂——若显而易见,早被他人实现。
(有多少人需要家用电脑?什么,又一家搜索引擎?)
这解释了科技与自由主义的关联。美国所有高科技城市无一例外高度自由。非因自由派更聪明,而是自由城市包容怪异想法——而聪明人本质就是想法怪异者。
I suspect this kind of organic growth is the only way to produce a startup hub, because it's the only way to grow the expertise you need. That has two important implications. The first is that you need time to grow a silicon valley. The university you could create in a couple years, but the startup community around it has to grow organically. The cycle time is limited by the time it takes a company to succeed, which probably averages about five years. The other implication of the organic growth hypothesis is that you can't be somewhat of a startup hub. You either have a self-sustaining chain reaction, or not. Observation confirms this too: cities either have a startup scene, or they don't. There is no middle ground. Chicago has the third largest metropolitan area in America. As a source of startups it's negligible compared to Seattle, number 15. The good news is that the initial seed can be quite small. Shockley Semiconductor, though itself not very successful, was big enough. It brought a critical mass of experts in an important new technology together in a place they liked enough to stay. Competing Of course, a would-be silicon valley faces an obstacle the original one didn't: it has to compete with Silicon Valley. Can that be done? Probably. One of Silicon Valley's biggest advantages is its venture capital firms. This was not a factor in Shockley's day, because VC funds didn't exist. In fact, Shockley Semiconductor and Fairchild Semiconductor were not startups at all in our sense. They were subsidiaries-- of Beckman Instruments and Fairchild Camera and Instrument respectively. Those companies were apparently willing to establish subsidiaries wherever the experts wanted to live. Venture investors, however, prefer to fund startups within an hour's drive. For one, they're more likely to notice startups nearby. But when they do notice startups in other towns they prefer them to move.
反之,被赞誉为"稳重"或代表"传统价值"的城市或许宜居,但永难成为创业中心。2004年总统大选虽在其他方面堪称灾难,却为我们提供了一份此类地区的详尽郡县地图。[6]
吸引年轻人需要完整的城市中心。多数美国城市中心已荒废,增长(若有)发生在郊区,形成"内外翻转"格局。但所有创业中心——旧金山、波士顿、西雅图——都保持完整中心区。[7] 我推测没有活力中心的城市不可能成为创业中心,年轻人拒绝郊区生活。
在美国,我认为最易转型为硅谷的城市是博尔德和波特兰。两者都拥有吸引年轻人的活力特质,只差一所顶尖大学就能蜕变——只要它们愿意。
名校毗邻魅力城镇就是全部条件?这正是原始硅谷的诞生配方。硅谷起源可追溯至晶体管发明者之一威廉·肖克利。他在贝尔实验室完成诺奖研究,但1956年创业时却选择帕洛阿尔托——当时此举颇为反常。为何?因为这是他记忆中的美好故乡。如今帕洛阿尔托已成郊区,当年却是气候宜人、距旧金山仅一小时车程的迷人大学城。
现今统治硅谷的企业都直接或间接源于肖克利半导体。肖克利性情乖戾,1957年八位核心员工("叛逆八人帮")离职创立仙童半导体,其中包括后来创建英特尔的戈登·摩尔与罗伯特·诺伊斯,以及创立凯鹏华盈的尤金·克莱纳。42年后,凯鹏华盈投资谷歌,主导该交易的约翰·多尔正是1974年为英特尔来到硅谷。
They don't want to have to travel to attend board meetings, and in any case the odds of succeeding are higher in a startup hub. The centralizing effect of venture firms is a double one: they cause startups to form around them, and those draw in more startups through acquisitions. And although the first may be weakening because it's now so cheap to start some startups, the second seems as strong as ever. Three of the most admired "Web 2.0" companies were started outside the usual startup hubs, but two of them have already been reeled in through acquisitions. Such centralizing forces make it harder for new silicon valleys to get started. But by no means impossible. Ultimately power rests with the founders. A startup with the best people will beat one with funding from famous VCs, and a startup that was sufficiently successful would never have to move. So a town that could exert enough pull over the right people could resist and perhaps even surpass Silicon Valley. For all its power, Silicon Valley has a great weakness: the paradise Shockley found in 1956 is now one giant parking lot. San Francisco and Berkeley are great, but they're forty miles away. Silicon Valley proper is soul-crushing suburban sprawl. It has fabulous weather, which makes it significantly better than the soul-crushing sprawl of most other American cities. But a competitor that managed to avoid sprawl would have real leverage. All a city needs is to be the kind of place the next traitorous eight look at and say "I want to stay here," and that would be enough to get the chain reaction started. Notes [1] It's interesting to consider how low this number could be made. I suspect five hundred would be enough, even if they could bring no assets with them.
因此尽管现今许多硅谷企业已不涉足硅技术,但总能追溯至肖克利的血脉。这揭示了一条规律:初创企业孕育初创企业。初创员工自立门户,初创获利者投资新项目。我怀疑这种有机生长是培育创业中心的唯一途径,因为唯有如此才能积累必要经验。
这引出两个重要推论:首先,培育硅谷需要时间。大学可数年建成,但周边创业生态必须有机生长。生长周期受企业成功时间限制,平均约需五年。
其次,创业中心没有中间状态——要么形成自持链式反应,要么没有。现实印证此点:城市要么拥有创业生态,要么空白。芝加哥作为美国第三大都会区,其创业产出与第十五位的西雅图相比微不足道。
好消息是初始种子可以很小。肖克利半导体虽自身不成功,却足以将重要新技术的专家群体聚集在他们愿意扎根的地方。
当然,潜在硅谷面临原始硅谷未曾有的障碍:必须与硅谷竞争。这可能吗?或许。
Probably just thirty, if I could pick them, would be enough to turn Buffalo into a significant startup hub. [2] Bureaucrats manage to allocate research funding moderately well, but only because (like an in-house VC fund) they outsource most of the work of selection. A professor at a famous university who is highly regarded by his peers will get funding, pretty much regardless of the proposal. That wouldn't work for startups, whose founders aren't sponsored by organizations, and are often unknowns. [3] You'd have to do it all at once, or at least a whole department at a time, because people would be more likely to come if they knew their friends were. And you should probably start from scratch, rather than trying to upgrade an existing university, or much energy would be lost in friction. [4] Hypothesis: Any plan in which multiple independent buildings are gutted or demolished to be "redeveloped" as a single project is a net loss of personality for the city, with the exception of the conversion of buildings not previously public, like warehouses. [5] A few startups get started in New York, but less than a tenth as many per capita as in Boston, and mostly in less nerdy fields like finance and media. [6] Some blue counties are false positives (reflecting the remaining power of Democractic party machines), but there are no false negatives.
硅谷最大优势之一是风投机构。这在肖克利时代不存在——当时尚无风投基金。实际上肖克利半导体与仙童半导体按现代标准都不算初创企业,它们分别是贝克曼仪器和仙童照相器材的子公司。这些母公司显然愿意在专家选择的任何地点设立分支机构。
而现代风投偏好一小时车程内的项目:既更容易发现本地初创,也会要求外地项目搬迁。他们不愿奔波参与董事会,且创业中心的成功率本就更高。
风投的双重集聚效应:既促使初创企业围绕其聚集,又通过收购吸引更多企业。虽然第一点因创业成本降低而减弱,但第二点依然强劲。三家最受瞩目的Web 2.0公司中,两家已通过收购被纳入传统创业中心。
这种集聚力增加了新硅谷的诞生难度,但绝非不可能。最终决定权在创始人手中:顶级人才的初创总能击败知名风投支持的项目,足够成功的企业也无需搬迁。因此若能对核心人群形成足够吸引力,城市就有可能抗衡甚至超越硅谷。
尽管实力雄厚,硅谷存在致命弱点:肖克利1956年发现的天堂如今已成巨型停车场。旧金山与伯克利虽好,但远在40英里外。真正的硅谷是令人窒息的郊区蔓延——虽因气候优于美国多数同类区域。若能避免这种蔓延,竞争者将获得真正优势。城市只需成为新一代"叛逆八人帮"愿意扎根的地方,便足以启动链式反应。
You can safely write off all the red counties. [7] Some "urban renewal" experts took a shot at destroying Boston's in the 1960s, leaving the area around city hall a bleak wasteland, but most neighborhoods successfully resisted them. Thanks to Chris Anderson, Trevor Blackwell, Marc Hedlund, Jessica Livingston, Robert Morris, Greg Mcadoo, Fred Wilson, and Stephen Wolfram for reading drafts of this, and to Ed Dumbill for inviting me to speak. (The second part of this talk became Why Startups Condense in America.)
| VC Deals by Region | | | Startup Jobs by Region | They Would Be Gods | | | Interview: Richard Hodgson | Santa Clara Valley, 1971 | | | Scattered Abroad | Russian Translation | | | Spanish Translation | Japanese Translation | | | Portuguese Translation | Arabic Translation.
[1] 探讨这个数字的下限很有趣。我认为五百人足够,即使不带资产;若精挑细选,或许三十人就能使布法罗成为重要创业中心。
[2] 官僚能较好分配科研资金,只因(如企业内部风投)将筛选工作外包。著名大学中受同行尊敬的教授总能获得资助,几乎无关提案内容。这不适用于初创企业——其创始人无机构背书,常是无名之辈。
[3] 必须一次性行动(至少整院系),因为人们更愿随朋友迁移。最好从零开始而非升级现有大学,避免内耗损耗能量。
[4] 假设:任何将多栋独立建筑"再开发"为单一项目的计划都会净损失城市个性,仓库等原非公共建筑的改造除外。
[5] 纽约有少量初创企业,但人均不足波士顿十分之一,且多集中于金融、媒体等极客色彩淡薄的领域。
If you liked this, you may also like _Hackers & Painters_.
[6] 部分蓝郡是假阳性(反映民主党机器的残余力量),但红郡绝无假阴性——可安全排除所有红郡。
[7] 1960年代"城市更新"专家曾试图摧毁波士顿市中心,导致市政厅周边沦为荒原,但多数街区成功抵抗。
致谢克里斯·安德森、特雷弗·布莱克韦尔、马克·赫德伦、杰西卡·利文斯顿、罗伯特·莫里斯、格雷格·麦卡杜、弗雷德·威尔逊、史蒂芬·沃尔夫拉姆阅读初稿,埃德·邓比尔邀请演讲。
(演讲第二部分形成《为何初创企业在美国集聚》)
如果你喜欢这篇文章,可能也会喜欢《黑客与画家》。
April 2006 _(This essay is derived from a talk at the 2006Startup School.)_ The startups we've funded so far are pretty quick, but they seem quicker to learn some lessons than others. I think it's because some things about startups are kind of counterintuitive. We've now invested in enough companies that I've learned a trick for determining which points are the counterintuitive ones: they're the ones I have to keep repeating. So I'm going to number these points, and maybe with future startups I'll be able to pull off a form of Huffman coding. I'll make them all read this, and then instead of nagging them in detail, I'll just be able to say: _number four!_ 1\. Release Early. The thing I probably repeat most is this recipe for a startup: get a version 1 out fast, then improve it based on users' reactions. By "release early" I don't mean you should release something full of bugs, but that you should release something minimal. Users hate bugs, but they don't seem to mind a minimal version 1, if there's more coming soon. There are several reasons it pays to get version 1 done fast. One is that this is simply the right way to write software, whether for a startup or not. I've been repeating that since 1993, and I haven't seen much since to contradict it. I've seen a lot of startups die because they were too slow to release stuff, and none because they were too quick. [1] One of the things that will surprise you if you build something popular is that you won't know your users. Reddit now has almost half a million unique visitors a month. Who are all those people? They have no idea. No web startup does. And since you don't know your users, it's dangerous to guess what they'll like. Better to release something and let them tell you. Wufoo took this to heart and released their form-builder before the underlying database.
You can't even drive the thing yet, but 83,000 people came to sit in the driver's seat and hold the steering wheel. And Wufoo got valuable feedback from it: Linux users complained they used too much Flash, so they rewrote their software not to. If they'd waited to release everything at once, they wouldn't have discovered this problem till it was more deeply wired in. Even if you had no users, it would still be important to release quickly, because for a startup the initial release acts as a shakedown cruise. If anything major is broken-- if the idea's no good, for example, or the founders hate one another-- the stress of getting that first version out will expose it. And if you have such problems you want to find them early. Perhaps the most important reason to release early, though, is that it makes you work harder. When you're working on something that isn't released, problems are intriguing. In something that's out there, problems are alarming. There is a lot more urgency once you release. And I think that's precisely why people put it off. They know they'll have to work a lot harder once they do. [2] 2\. Keep Pumping Out Features. Of course, "release early" has a second component, without which it would be bad advice. If you're going to start with something that doesn't do much, you better improve it fast. What I find myself repeating is "pump out features." And this rule isn't just for the initial stages. This is something all startups should do for as long as they want to be considered startups. I don't mean, of course, that you should make your application ever more complex. By "feature" I mean one unit of hacking-- one quantum of making users' lives better. As with exercise, improvements beget improvements. If you run every day, you'll probably feel like running tomorrow. But if you skip running for a couple weeks, it will be an effort to drag yourself out.
"尽早发布"并非指发布充满漏洞的产品,而是推出最小可行版本。用户厌恶漏洞,但只要后续更新及时,他们通常能接受简陋的1.0版本。
快速完成1.0版本意义重大:首先这是软件开发的基本准则,无论是否创业。自1993年以来我始终秉持这一理念,现实不断验证其正确性。我见证过无数因动作迟缓而夭折的初创公司,却从未见过因行动过快而失败的案例[1]。
当你打造出受欢迎的产品时,最令人惊讶的发现是:你根本不了解用户。Reddit月活用户已近50万,但创始团队坦言他们完全不知道这些用户是谁——所有网络初创公司都面临同样困境。既然无法预知用户喜好,不如尽早发布产品让他们亲自告诉你。
Wufoo深谙此道,他们在底层数据库尚未完成时就发布了表单构建器。这个"无法驾驶的汽车"吸引了83,000人试坐体验,并收获关键反馈:Linux用户抗议Flash过度使用,团队立即重写了代码。若等所有功能完备再发布,这个隐患将深植系统。
即便没有用户,快速发布依然重要,因为首版产品就是初创公司的试航。任何重大缺陷——比如核心概念错误或团队内讧——都会在版本发布的高压中暴露。而这些问题越早发现越好。
但最重要的原因或许是:发布倒逼效率提升。未发布时,问题只是有趣的谜题;已发布后,问题就成了警报。这种紧迫感正是人们拖延发布的原因——他们清楚发布后将面临更艰巨的工作[2]。
So it is with hacking: the more ideas you implement, the more ideas you'll have. You should make your system better at least in some small way every day or two. This is not just a good way to get development done; it is also a form of marketing. Users love a site that's constantly improving. In fact, users expect a site to improve. Imagine if you visited a site that seemed very good, and then returned two months later and not one thing had changed. Wouldn't it start to seem lame? [3] They'll like you even better when you improve in response to their comments, because customers are used to companies ignoring them. If you're the rare exception-- a company that actually listens-- you'll generate fanatical loyalty. You won't need to advertise, because your users will do it for you. This seems obvious too, so why do I have to keep repeating it? I think the problem here is that people get used to how things are. Once a product gets past the stage where it has glaring flaws, you start to get used to it, and gradually whatever features it happens to have become its identity. For example, I doubt many people at Yahoo (or Google for that matter) realized how much better web mail could be till Paul Buchheit showed them. I think the solution is to assume that anything you've made is far short of what it could be. Force yourself, as a sort of intellectual exercise, to keep thinking of improvements. Ok, sure, what you have is perfect. But if you had to change something, what would it be? If your product seems finished, there are two possible explanations: (a) it is finished, or (b) you lack imagination. Experience suggests (b) is a thousand times more likely. 3\. Make Users Happy. Improving constantly is an instance of a more general rule: make users happy. One thing all startups have in common is that they can't force anyone to do anything. They can't force anyone to use their software, and they can't force anyone to do deals with them.
2. 持续迭代功能
"尽早发布"必须配合第二条准则,否则就是馊主意:既然首发版本功能简陋,就必须快速迭代。
我不断强调"持续输出功能",这不仅适用于初期阶段,而是初创公司整个生命周期都应遵循的法则。
当然,这并非指无节制堆砌功能。所谓"功能"是指能切实改善用户体验的最小开发单元。
如同锻炼身体,改进会引发更多改进。每日跑步的人第二天会自觉继续,但停跑两周后重启就异常艰难。编程同理:实现的想法越多,新灵感就越多。至少每两天要让系统有所提升。
这不仅是高效的开发方式,更是绝妙的营销策略。用户热爱持续进化的产品,事实上他们对此早有期待。设想访问某个优质网站,两月后竟毫无变化——难道不会觉得它已落伍?[3]
A startup has to sing for its supper. That's why the successful ones make great things. They have to, or die. When you're running a startup you feel like a little bit of debris blown about by powerful winds. The most powerful wind is users. They can either catch you and loft you up into the sky, as they did with Google, or leave you flat on the pavement, as they do with most startups. Users are a fickle wind, but more powerful than any other. If they take you up, no competitor can keep you down. As a little piece of debris, the rational thing for you to do is not to lie flat, but to curl yourself into a shape the wind will catch. I like the wind metaphor because it reminds you how impersonal the stream of traffic is. The vast majority of people who visit your site will be casual visitors. It's them you have to design your site for. The people who really care will find what they want by themselves. The median visitor will arrive with their finger poised on the Back button. Think about your own experience: most links you follow lead to something lame. Anyone who has used the web for more than a couple weeks has been _trained_ to click on Back after following a link. So your site has to say "Wait! Don't click on Back. This site isn't lame. Look at this, for example." There are two things you have to do to make people pause. The most important is to explain, as concisely as possible, what the hell your site is about. How often have you visited a site that seemed to assume you already knew what they did? For example, the corporate site that says the company makes > enterprise content management solutions for business that enable organizations to unify people, content and processes to minimize business risk, accelerate time-to-value and sustain lower total cost of ownership..
若根据用户反馈改进,效果更佳。因为消费者早已习惯被企业忽视,若你成为罕见的倾听者,将收获狂热忠诚。届时口碑传播会取代广告投放。
道理看似简单,为何仍需反复强调?问题在于人们容易安于现状。当产品超越漏洞百出的阶段后,团队会逐渐将现有功能视为产品本质。比如在Paul Buchheit展示Gmail之前,雅虎(甚至谷歌)员工都未意识到邮箱服务还能如此革新。
解决方案是:永远假设产品远未完善。强迫自己进行思维训练,持续构思改进方案。当然,现有版本看似完美,但若必须改变,你会选择哪里?
若觉得产品已完工,只有两种可能:(a)确实完美 (b)缺乏想象力。经验表明(b)的可能性高出千倍。
3. 取悦用户
持续改进是更普世准则的体现:让用户快乐。所有初创公司的共同点在于——它们无法强迫任何人做任何事。既不能强制使用软件,也无法胁迫他人合作。初创公司必须靠实力赢得生存,这正是成功者创造伟大产品的原因:要么卓越,要么消亡。
经营初创公司就像狂风中的微尘,而用户是最强劲的气流。他们既能如托起谷歌般送你上青云,也会像对待多数创业公司那样任你跌落尘埃。用户虽善变,却是最强大的力量。若得他们青睐,任何对手都无法将你击倒。
An established company may get away with such an opaque description, but no startup can. A startup should be able to explain in one or two sentences exactly what it does. [4] And not just to users. You need this for everyone: investors, acquirers, partners, reporters, potential employees, and even current employees. You probably shouldn't even start a company to do something that can't be described compellingly in one or two sentences. The other thing I repeat is to give people everything you've got, right away. If you have something impressive, try to put it on the front page, because that's the only one most visitors will see. Though indeed there's a paradox here: the more you push the good stuff toward the front, the more likely visitors are to explore further. [5] In the best case these two suggestions get combined: you tell visitors what your site is about by _showing_ them. One of the standard pieces of advice in fiction writing is "show, don't tell." Don't say that a character's angry; have him grind his teeth, or break his pencil in half. Nothing will explain what your site does so well as using it. The industry term here is "conversion." The job of your site is to convert casual visitors into users-- whatever your definition of a user is. You can measure this in your growth rate. Either your site is catching on, or it isn't, and you must know which. If you have decent growth, you'll win in the end, no matter how obscure you are now. And if you don't, you need to fix something. 4\. Fear the Right Things. Another thing I find myself saying a lot is "don't worry." Actually, it's more often "don't worry about this; worry about that instead." Startups are right to be paranoid, but they sometimes fear the wrong things. Most visible disasters are not so alarming as they seem.
作为微尘,理性的做法不是躺平,而是调整姿态御风而行。
这个比喻提醒我们:流量本质上是非人格化的。绝大多数访客都是匆匆过客,你正需要为这些群体设计产品。真正在乎的用户自会找到所需。
典型访客的手指始终悬停在返回按钮上。回想自身经历:多数链接导向平庸内容。任何上网两周以上的人都被训练出"点击链接→立即返回"的条件反射。因此你的网站必须高喊:"等等!别急着返回。我们与众不同。看看这个..."
要留住用户需做到两点:最关键是用最简练的语言阐明网站价值。多少网站默认访客已了解其业务?比如某企业官网宣称:
> 为企业提供统一人员、内容与流程的企业内容管理解决方案,助力降低商业风险、加速价值实现、维持更低总体拥有成本。
以下是Paul Graham文章《创业公司最难掌握的教训》第2部分(共3部分)的中文翻译:
Disasters are normal in a startup: a founder quits, you discover a patent that covers what you're doing, your servers keep crashing, you run into an insoluble technical problem, you have to change your name, a deal falls through-- these are all par for the course. They won't kill you unless you let them. Nor will most competitors. A lot of startups worry "what if Google builds something like us?" Actually big companies are not the ones you have to worry about-- not even Google. The people at Google are smart, but no smarter than you; they're not as motivated, because Google is not going to go out of business if this one product fails; and even at Google they have a lot of bureaucracy to slow them down. What you should fear, as a startup, is not the established players, but other startups you don't know exist yet. They're way more dangerous than Google because, like you, they're cornered animals. Looking just at existing competitors can give you a false sense of security. You should compete against what someone else _could_ be doing, not just what you can see people doing. A corollary is that you shouldn't relax just because you have no visible competitors yet. No matter what your idea, there's someone else out there working on the same thing. That's the downside of it being easier to start a startup: more people are doing it. But I disagree with Caterina Fake when she says that makes this a bad time to start a startup. More people are starting startups, but not as many more as could. Most college graduates still think they have to get a job. The average person can't ignore something that's been beaten into their head since they were three just because serving web pages recently got a lot cheaper. And in any case, competitors are not the biggest threat. Way more startups hose themselves than get crushed by competitors. There are a lot of ways to do it, but the three main ones are internal disputes, inertia, and ignoring users.
老牌公司或许能用模糊描述蒙混过关,但创业公司绝不能。初创企业必须能用一两句话清晰说明自己的业务。[4] 而且不仅要对用户解释清楚——你需要向所有人阐明:投资人、收购方、合作伙伴、记者、潜在员工,甚至现有员工。如果一件事无法用一两句话生动描述,你或许根本不该为此创业。
我常强调的另一件事是:第一时间展示全部实力。如果有令人印象深刻的功能,尽量放在首页——因为多数访客只会看这一页。这里存在悖论:你把亮点推得越靠前,访客越可能深入探索。[5]
最理想的情况是将这两点结合:通过直接演示向访客说明网站价值。小说创作的经典建议"展示而非讲述"同样适用。不要说角色很愤怒,要写他咬牙切齿或折断铅笔。没有什么比亲身体验更能说明产品价值。
行业术语称之为"转化率"。网站的任务是将随意浏览者转化为用户(无论你如何定义用户)。这反映在增长率上:要么势头正盛,要么停滞不前,你必须清楚现状。只要保持可观增长,终将成功,无论当下多么默默无闻;反之则必须调整。
4. 恐惧正确的事物
我常说的另一句话是"别担心",更准确说是"别担心这个,该担心那个"。创业者的偏执有理,但有时用错了方向。
Each is, by itself, enough to kill you. But if I had to pick the worst, it would be ignoring users. If you want a recipe for a startup that's going to die, here it is: a couple of founders who have some great idea they know everyone is going to love, and that's what they're going to build, no matter what. Almost everyone's initial plan is broken. If companies stuck to their initial plans, Microsoft would be selling programming languages, and Apple would be selling printed circuit boards. In both cases their customers told them what their business should be-- and they were smart enough to listen. As Richard Feynman said, the imagination of nature is greater than the imagination of man. You'll find more interesting things by looking at the world than you could ever produce just by thinking. This principle is very powerful. It's why the best abstract painting still falls short of Leonardo, for example. And it applies to startups too. No idea for a product could ever be so clever as the ones you can discover by smashing a beam of prototypes into a beam of users. 5\. Commitment Is a Self-Fulfilling Prophecy. I now have enough experience with startups to be able to say what the most important quality is in a startup founder, and it's not what you might think. The most important quality in a startup founder is determination. Not intelligence-- determination. This is a little depressing. I'd like to believe Viaweb succeeded because we were smart, not merely determined. A lot of people in the startup world want to believe that. Not just founders, but investors too. They like the idea of inhabiting a world ruled by intelligence. And you can tell they really believe this, because it affects their investment decisions. Time after time VCs invest in startups founded by eminent professors. This may work in biotech, where a lot of startups simply commercialize existing research, but in software you want to invest in students, not professors.
多数可见灾难没看起来那么可怕。初创企业遭遇危机很正常:联合创始人退出、发现专利冲突、服务器频繁崩溃、遇到无解技术难题、被迫更名、交易告吹——这些都是家常便饭。除非你主动放弃,否则它们杀不死你。
大多数竞争对手也不足为惧。许多创业者担心"如果谷歌做同类产品怎么办?"其实大公司并不可怕——包括谷歌。谷歌员工虽聪明,但不会比你更聪明;他们动力不足,因为单个产品失败不会让谷歌倒闭;即便在谷歌,官僚主义也会拖慢进度。
初创企业真正该害怕的,是那些尚未知晓的其他创业公司。它们比谷歌危险得多——因为和你一样,都是困兽之斗。
只关注现有竞争者会带来虚假安全感。你的竞争对象应该是别人可能做出的产品,而不仅是眼前所见。由此可得:没有可见竞争对手时更不该松懈。无论你的创意多独特,世上总有人在默默做着同样的事。
创业门槛降低的副作用就是参与者增多。但我不同意Caterina Fake"现在不适合创业"的观点。虽然创业者增多,但远未饱和。多数毕业生仍认为必须找工作。普通人不可能仅因建站成本下降,就推翻三岁起被灌输的观念。
况且竞争对手并非最大威胁。死于内耗的初创企业远多于被对手消灭的。死法多样,但主要三种:内部分裂、惯性僵化、忽视用户。任一都足以致命。若必须选最致命的,当属忽视用户。若要设计必死创业公式,那就是:几个创始人坚信某个伟大创意必定受欢迎,于是不顾一切闭门造车。
Microsoft, Yahoo, and Google were all founded by people who dropped out of school to do it. What students lack in experience they more than make up in dedication. Of course, if you want to get rich, it's not enough merely to be determined. You have to be smart too, right? I'd like to think so, but I've had an experience that convinced me otherwise: I spent several years living in New York. You can lose quite a lot in the brains department and it won't kill you. But lose even a little bit in the commitment department, and that will kill you very rapidly. Running a startup is like walking on your hands: it's possible, but it requires extraordinary effort. If an ordinary employee were asked to do the things a startup founder has to, he'd be very indignant. Imagine if you were hired at some big company, and in addition to writing software ten times faster than you'd ever had to before, they expected you to answer support calls, administer the servers, design the web site, cold-call customers, find the company office space, and go out and get everyone lunch. And to do all this not in the calm, womb-like atmosphere of a big company, but against a backdrop of constant disasters. That's the part that really demands determination. In a startup, there's always some disaster happening. So if you're the least bit inclined to find an excuse to quit, there's always one right there. But if you lack commitment, chances are it will have been hurting you long before you actually quit. Everyone who deals with startups knows how important commitment is, so if they sense you're ambivalent, they won't give you much attention. If you lack commitment, you'll just find that for some mysterious reason good things happen to your competitors but not to you. If you lack commitment, it will seem to you that you're unlucky. Whereas if you're determined to stick around, people will pay attention to you, because odds are they'll have to deal with you later.
几乎所有初始计划都是错的。如果公司死守最初方案,微软现在该卖编程语言,苹果该卖电路板。这两家都是客户指明了方向——而他们足够聪明,愿意倾听。
正如费曼所言:自然的想象力远超人类。观察世界发现的奥秘,永远比空想更有价值。这个原则威力巨大——例如最好的抽象画仍不及达芬奇。创业亦然。任何产品构思都比不上将原型砸向用户群体获得的真知。
5. 决心是自我实现的预言
如今我有足够经验断言:创业者最重要的品质并非你以为的那样。不是智力,而是决心。
这有点令人沮丧。我宁愿相信Viaweb成功靠的是聪明才智而非单纯坚持。创业圈很多人都渴望相信这点——不仅是创始人,投资人也如此。他们向往智力主导的世界。从投资决策能看出他们真心相信这点。
风投屡屡投资知名教授创立的公司。这在生物技术领域或许可行(许多初创公司只是将现有研究商业化),但在软件领域,你该投资的是学生而非教授。微软、雅虎、谷歌的创始人都为创业辍学。学生用专注弥补了经验不足。
当然,仅靠决心不足以致富,还得聪明对吧?我愿如此认为,但纽约生活经历让我醒悟:即使智商大打折扣也不会致命,但决心稍有松懈就会迅速灭亡。
You're a local, not just a tourist, so everyone has to come to terms with you. At Y Combinator we sometimes mistakenly fund teams who have the attitude that they're going to give this startup thing a shot for three months, and if something great happens, they'll stick with it-- "something great" meaning either that someone wants to buy them or invest millions of dollars in them. But if this is your attitude, "something great" is very unlikely to happen to you, because both acquirers and investors judge you by your level of commitment. If an acquirer thinks you're going to stick around no matter what, they'll be more likely to buy you, because if they don't and you stick around, you'll probably grow, your price will go up, and they'll be left wishing they'd bought you earlier. Ditto for investors. What really motivates investors, even big VCs, is not the hope of good returns, but the fear of missing out. [6] So if you make it clear you're going to succeed no matter what, and the only reason you need them is to make it happen a little faster, you're much more likely to get money. You can't fake this. The only way to convince everyone that you're ready to fight to the death is actually to be ready to. You have to be the right kind of determined, though. I carefully chose the word determined rather than stubborn, because stubbornness is a disastrous quality in a startup. You have to be determined, but flexible, like a running back. A successful running back doesn't just put his head down and try to run through people. He improvises: if someone appears in front of him, he runs around them; if someone tries to grab him, he spins out of their grip; he'll even run in the wrong direction briefly if that will help. The one thing he'll never do is stand still. [7] 6\. There Is Always Room. I was talking recently to a startup founder about whether it might be good to add a social component to their software.
经营创业公司如同倒立行走:可行但需非凡努力。若让普通员工承担创始人的职责,他们会勃然大怒。想象某大公司要求你:以十倍速度编程的同时,还要接客服电话、维护服务器、设计网站、cold call客户、寻找办公场地、给大家买午餐。
而且不是在安稳的大公司环境,而是在灾难频发的背景下完成。这才是真正考验决心之处。初创企业永远灾祸不断,只要稍想放弃,借口唾手可得。
但缺乏决心早在真正放弃前就会伤害你。所有与初创企业打交道的人都重视决心,若察觉你犹豫不决,便不会关注你。缺乏决心时,你会神秘地发现:好事总发生在竞争对手身上。你会觉得自己运气差。
反之若坚定留守,人们就会重视你——因为他们迟早要与你打交道。你是本地居民而非游客,所有人都必须与你达成共识。
Y Combinator有时会误投这样的团队:他们打算"试水"三个月,若有"大好事"就继续——"大好事"指收购或巨额投资。但持此态度时,"大好事"几乎不会发生,因为收购方和投资人都会评估你的决心。
若收购方认定你会坚持到底,就更可能收购你——因为若不收购,你壮大后价格会上涨,他们将后悔没早点下手。投资人也同理。真正驱动投资人(包括大VC)的不是回报预期,而是害怕错过。[6] 所以若明确传达"无论是否融资都会成功,融资只为加速",获得资金的可能性将大增。
He said he didn't think so, because the whole social thing was tapped out. Really? So in a hundred years the only social networking sites will be the Facebook, MySpace, Flickr, and Del.icio.us? Not likely. There is always room for new stuff. At every point in history, even the darkest bits of the dark ages, people were discovering things that made everyone say "why didn't anyone think of that before?" We know this continued to be true up till 2004, when the Facebook was founded-- though strictly speaking someone else did think of that. The reason we don't see the opportunities all around us is that we adjust to however things are, and assume that's how things have to be. For example, it would seem crazy to most people to try to make a better search engine than Google. Surely that field, at least, is tapped out. Really? In a hundred years-- or even twenty-- are people still going to search for information using something like the current Google? Even Google probably doesn't think that. In particular, I don't think there's any limit to the number of startups. Sometimes you hear people saying "All these guys starting startups now are going to be disappointed. How many little startups are Google and Yahoo going to buy, after all?" That sounds cleverly skeptical, but I can prove it's mistaken. No one proposes that there's some limit to the number of people who can be employed in an economy consisting of big, slow-moving companies with a couple thousand people each. Why should there be any limit to the number who could be employed by small, fast-moving companies with ten each? It seems to me the only limit would be the number of people who want to work that hard. The limit on the number of startups is not the number that can get acquired by Google and Yahoo-- though it seems even that should be unlimited, if the startups were actually worth buying-- but the amount of wealth that can be created.
这无法伪装。让众人相信你会死战到底的唯一方法,就是真正做好准备。
但决心需用对方向。我刻意选用"决心"而非"固执",因为固执对初创企业是灾难性品质。你要像跑卫般既坚定又灵活:成功跑卫不会埋头硬冲,而是随机应变——有人拦截就绕行,有人擒抱就旋转挣脱,必要时甚至短暂反向跑动。唯一不会做的就是静止不动。[7]
6. 永远存在机会
最近与某创始人讨论是否该为软件添加社交功能。他认为社交领域已无机会。真的吗?难道百年后社交网站仍只有Facebook、MySpace、Flickr和Del.icio.us?显然不会。
新事物永远有空间。历史上每个时期(包括黑暗时代最黑暗的阶段),都有人做出让世人惊叹"为何无人早想到"的发明。我们知道这持续到2004年Facebook成立——严格说来前人已有类似构想。
我们看不见周围机会,是因为适应现状后便认为理应如此。例如多数人觉得挑战谷歌搜索引擎近乎疯狂——这个领域肯定饱和了吧?果真如此吗?百年后(甚至二十年后),人们还会用类似谷歌的方式搜索信息?恐怕谷歌自己都不信。
And I don't think there's any limit on that, except cosmological ones. So for all practical purposes, there is no limit to the number of startups. Startups make wealth, which means they make things people want, and if there's a limit on the number of things people want, we are nowhere near it. I still don't even have a flying car. 7\. Don't Get Your Hopes Up. This is another one I've been repeating since long before Y Combinator. It was practically the corporate motto at Viaweb. Startup founders are naturally optimistic. They wouldn't do it otherwise. But you should treat your optimism the way you'd treat the core of a nuclear reactor: as a source of power that's also very dangerous. You have to build a shield around it, or it will fry you. The shielding of a reactor is not uniform; the reactor would be useless if it were. It's pierced in a few places to let pipes in. An optimism shield has to be pierced too. I think the place to draw the line is between what you expect of yourself, and what you expect of other people. It's ok to be optimistic about what you can do, but assume the worst about machines and other people. This is particularly necessary in a startup, because you tend to be pushing the limits of whatever you're doing. So things don't happen in the smooth, predictable way they do in the rest of the world. Things change suddenly, and usually for the worse. Shielding your optimism is nowhere more important than with deals. If your startup is doing a deal, just assume it's not going to happen. The VCs who say they're going to invest in you aren't. The company that says they're going to buy you isn't. The big customer who wants to use your system in their whole company won't. Then if things work out you can be pleasantly surprised. The reason I warn startups not to get their hopes up is not to save them from being _disappointed_ when things fall through.
尤其我认为创业公司数量没有上限。常听人说:"现在创业的人都会失望。谷歌雅虎能收购多少小公司?"这种怀疑论看似聪明,但我能证明其谬误。没人认为由数千人组成的缓慢大公司构成的经济体存在就业人数上限,那么为何由十人组成的敏捷小公司会有上限?在我看来唯一限制是愿拼命工作的人数。
创业公司的限制不在于能被谷歌雅虎收购的数量(如果真有价值,收购数量本应无限),而在于能创造的财富总量——除宇宙限制外,我认为这没有上限。
因此实际意义上,创业公司数量无限。创业创造财富,即创造人们需要的东西。如果人类需求存在上限,我们离它还很远——我连飞行汽车都还没坐上呢。
7. 别抱太高期望
这是Y Combinator成立前我就常重复的原则,几乎是Viaweb的座右铭。
创业者天生乐观,否则不会创业。但应像对待核反应堆堆芯那样对待乐观:它是动力源,也极度危险。必须建立防护罩,否则会毁了你。
It's for a more practical reason: to prevent them from leaning their company against something that's going to fall over, taking them with it. For example, if someone says they want to invest in you, there's a natural tendency to stop looking for other investors. That's why people proposing deals seem so positive: they _want_ you to stop looking. And you want to stop too, because doing deals is a pain. Raising money, in particular, is a huge time sink. So you have to consciously force yourself to keep looking. Even if you ultimately do the first deal, it will be to your advantage to have kept looking, because you'll get better terms. Deals are dynamic; unless you're negotiating with someone unusually honest, there's not a single point where you shake hands and the deal's done. There are usually a lot of subsidiary questions to be cleared up after the handshake, and if the other side senses weakness-- if they sense you need this deal-- they will be very tempted to screw you in the details. VCs and corp dev guys are professional negotiators. They're trained to take advantage of weakness. [8] So while they're often nice guys, they just can't help it. And as pros they do this more than you. So don't even try to bluff them. The only way a startup can have any leverage in a deal is genuinely not to need it. And if you don't believe in a deal, you'll be less likely to depend on it. So I want to plant a hypnotic suggestion in your heads: when you hear someone say the words "we want to invest in you" or "we want to acquire you," I want the following phrase to appear automatically in your head: _don't get your hopes up._ Just continue running your company as if this deal didn't exist. Nothing is more likely to make it close.
反应堆防护罩并非完全封闭(那会使其失效),而是留有管道接口。乐观屏障也需留孔。我认为分界线在于:对自身保持乐观,对机器和他人做最坏打算。
这对初创企业尤为必要,因为你总在突破极限。事情不会像常规世界那样平稳可预测,突变总在发生——通常往坏的方向。
在交易中防护乐观尤为重要。只要涉及交易,就假设它不会成真:说投资的风投不会投,说要收购的公司不会买,说要全公司采用你们系统的大客户不会用。这样若真成功,反而是惊喜。
我警告创业者别抱期望,不是为避免失望,而是出于更实际的原因:防止公司倚靠终将倒塌的支柱。
例如当有人说要投资时,你自然想停止寻找其他投资人。交易提议者表现得积极正因如此——他们希望你停止寻找。你也想停止,因为谈判很痛苦,尤其融资极其耗时。所以必须强迫自己继续寻找。
即使最终与最初那家成交,持续寻找也会让你获得更好条款。交易是动态的:除非对方异常诚实,否则没有握手即定的交易。握手后通常还有大量细节问题,若对方察觉你依赖这笔交易,就会在细节上压榨你。
风投和企业发展部人士是专业谈判者,受过利用弱点的训练。[8] 尽管他们可能是好人,但职业使然。作为专业人士,他们比你更精于此道。别妄想唬住他们。初创企业在交易中掌握筹码的唯一方式,是真正不需要这笔交易。若不相信某笔交易能成,你就不会依赖它。
The way to succeed in a startup is to focus on the goal of getting lots of users, and keep walking swiftly toward it while investors and acquirers scurry alongside trying to wave money in your face. Speed, not Money The way I've described it, starting a startup sounds pretty stressful. It is. When I talk to the founders of the companies we've funded, they all say the same thing: I knew it would be hard, but I didn't realize it would be this hard. So why do it? It would be worth enduring a lot of pain and stress to do something grand or heroic, but just to make money? Is making money really that important? No, not really. It seems ridiculous to me when people take business too seriously. I regard making money as a boring errand to be got out of the way as soon as possible. There is nothing grand or heroic about starting a startup per se. So why do I spend so much time thinking about startups? I'll tell you why. Economically, a startup is best seen not as a way to get rich, but as a way to work faster. You have to make a living, and a startup is a way to get that done quickly, instead of letting it drag on through your whole life. [9] We take it for granted most of the time, but human life is fairly miraculous. It is also palpably short. You're given this marvellous thing, and then poof, it's taken away. You can see why people invent gods to explain it. But even to people who don't believe in gods, life commands respect. There are times in most of our lives when the days go by in a blur, and almost everyone has a sense, when this happens, of wasting something precious. As Ben Franklin said, if you love life, don't waste time, because time is what life is made of. So no, there's nothing particularly grand about making money. That's not what makes startups worth the trouble. What's important about startups is the speed.
所以我想给你们植入催眠指令:当听到"我们想投资"或"我们想收购"时,脑中要自动浮现"别抱期望"。继续运营公司就当这笔交易不存在——这反而最可能促成交易。
创业成功之道在于紧盯获取大量用户的目标稳步前进,让投资人和收购方追着你挥舞钞票。
按我的描述,创业听起来压力巨大。确实如此。与我们投资的创始人交谈时,他们都说:我知道会很难,但没想到这么难。
那为何还要创业?若为伟大或崇高事业,承受痛苦压力或许值得,但只为赚钱?赚钱真那么重要?
不,并非如此。把商业看得太重在我看来很可笑。我把赚钱视为应尽快解决的乏味差事。创业本身并无崇高可言。
那我为何花大量时间思考创业?原因在于:从经济学角度,创业不应被视为致富手段,而是加速工作的方式。人总要谋生,而创业能快速解决这个问题,而非让谋生耗尽一生。[9]
By compressing the dull but necessary task of making a living into the smallest possible time, you show respect for life, and there is something grand about that. Notes [1] Startups can die from releasing something full of bugs, and not fixing them fast enough, but I don't know of any that died from releasing something stable but minimal very early, then promptly improving it. [2] I know this is why I haven't released Arc. The moment I do, I'll have people nagging me for features. [3] A web site is different from a book or movie or desktop application in this respect. Users judge a site not as a single snapshot, but as an animation with multiple frames. Of the two, I'd say the rate of improvement is more important to users than where you currently are. [4] It should not always tell this to users, however. For example, MySpace is basically a replacement mall for mallrats. But it was wiser for them, initially, to pretend that the site was about bands. [5] Similarly, don't make users register to try your site. Maybe what you have is so valuable that visitors should gladly register to get at it. But they've been trained to expect the opposite. Most of the things they've tried on the web have sucked-- and probably especially those that made them register. [6] VCs have rational reasons for behaving this way. They don't make their money (if they make money) off their median investments. In a typical fund, half the companies fail, most of the rest generate mediocre returns, and one or two "make the fund" by succeeding spectacularly. So if they miss just a few of the most promising opportunities, it could hose the whole fund. [7] The attitude of a running back doesn't translate to soccer.
我们常视为理所当然,但生命实属奇迹,同时也明显短暂。你被赐予这奇妙之物,转瞬又被夺走。难怪人们创造神灵来解释。但即使无神论者也会敬畏生命。多数人生命中都有浑噩度日的阶段,此时几乎所有人都感到在浪费珍宝。正如富兰克林所言:若热爱生命,别浪费时间,因为生命正是由时间构成。
所以赚钱并无特别崇高之处,这并非创业的价值所在。重要的是速度——通过将谋生这项必要但乏味的任务压缩至极短时间,你展现出对生命的尊重,这才具有崇高意义。
[1] 初创企业可能因发布漏洞百出的产品且未及时修复而死亡,但我没见过哪个因过早发布精简稳定产品并快速迭代而死。
[2] 这就是我未发布Arc语言的原因。一旦发布,就会有人不断索要新功能。
[3] 网站与书籍、电影或桌面应用不同。用户评判网站不是看静态快照,而是多帧动画。两者间,改进速度比当前状态更重要。
[4] 但不必总对用户直言。例如MySpace本质是商场文化的线上替代品,但初期假装成音乐人网站更明智。
Though it looks great when a forward dribbles past multiple defenders, a player who persists in trying such things will do worse in the long term than one who passes. [8] The reason Y Combinator never negotiates valuations is that we're not professional negotiators, and don't want to turn into them. [9] There are two ways to do work you love: (a) to make money, then work on what you love, or (b) to get a job where you get paid to work on stuff you love. In practice the first phases of both consist mostly of unedifying schleps, and in (b) the second phase is less secure. Thanks to Sam Altman, Trevor Blackwell, Beau Hartshorne, Jessica Livingston, and Robert Morris for reading drafts of this.
| Romanian Translation | | | Russian Translation | French Translation | | | Japanese Translation.
[5] 同理,别让用户注册才能试用。或许你的产品值得注册获取,但用户已被训练出相反预期。他们试过的大多数网站都很糟——尤其是那些要求注册的。
[6] 风投这样行事有理性原因。他们(如果赚钱)不是靠中等回报的投资。典型基金中半数公司失败,其余多数回报平庸,仅一两家惊人成功"支撑整个基金"。因此若错过几个最有潜力的机会,可能毁掉整个基金。
[7] 跑卫的态度不适用于足球。虽然前锋连过数人很精彩,但长期来看,执着于此的球员表现不如善传球的球员。
[8] Y Combinator从不谈判估值,因为我们不是专业谈判者,也不想变成那样。
[9] 做热爱的工作有两种方式:(a)先赚钱再做热爱的事;(b)找份能获得报酬做热爱之事的工作。实践中两者第一阶段多是枯燥苦差,而(b)的第二阶段更不稳定。
致谢 Sam Altman、Trevor Blackwell、Beau Hartshorne、Jessica Livingston和Robert Morris阅读了本文草稿。
April 2006, rev August 2009 Plato quotes Socrates as saying "the unexamined life is not worth living." Part of what he meant was that the proper role of humans is to think, just as the proper role of anteaters is to poke their noses into anthills. A lot of ancient philosophy had the quality — and I don't mean this in an insulting way — of the kind of conversations freshmen have late at night in common rooms: > What is our purpose? Well, we humans are as conspicuously different from other animals as the anteater. In our case the distinguishing feature is the ability to reason. So obviously that is what we should be doing, and a human who doesn't is doing a bad job of being human — is no better than an animal.
2006年4月,2009年8月修订
Now we'd give a different answer. At least, someone Socrates's age would. We'd ask why we even suppose we have a "purpose" in life. We may be better adapted for some things than others; we may be happier doing things we're adapted for; but why assume purpose? The history of ideas is a history of gradually discarding the assumption that it's all about us. No, it turns out, the earth is not the center of the universe — not even the center of the solar system. No, it turns out, humans are not created by God in his own image; they're just one species among many, descended not merely from apes, but from microorganisms. Even the concept of "me" turns out to be fuzzy around the edges if you examine it closely. The idea that we're the center of things is difficult to discard. So difficult that there's probably room to discard more. Richard Dawkins made another step in that direction only in the last several decades, with the idea of the selfish gene. No, it turns out, we're not even the protagonists: we're just the latest model vehicle our genes have constructed to travel around in. And having kids is our genes heading for the lifeboats. Reading that book snapped my brain out of its previous way of thinking the way Darwin's must have when it first appeared. (Few people can experience now what Darwin's contemporaries did when _The Origin of Species_ was first published, because everyone now is raised either to take evolution for granted, or to regard it as a heresy. No one encounters the idea of natural selection for the first time as an adult.) So if you want to discover things that have been overlooked till now, one really good place to look is in our blind spot: in our natural, naive belief that it's all about us. And expect to encounter ferocious opposition if you do. Conversely, if you have to choose between two theories, prefer the one that doesn't center on you.
柏拉图引用苏格拉底的话说:"未经省察的人生不值得过。"他部分想表达的是,人类恰当的职责是思考,就像食蚁兽恰当的职责是把鼻子探进蚁穴一样。
许多古代哲学都带有一种特质——我这么说并非不敬——就像大一新生深夜在公共休息室里进行的那些对话:
This principle isn't only for big ideas. It works in everyday life, too. For example, suppose you're saving a piece of cake in the fridge, and you come home one day to find your housemate has eaten it. Two possible theories:.
> 我们的目的是什么?嗯,人类与其它动物的显著差异,就像食蚁兽那样明显。对我们来说,区别性特征就是理性能力。所以显然这就是我们应该做的事,不这样做的人就是在糟糕地履行人类的职责——与动物无异。
如今我们会给出不同的答案。至少,像苏格拉底这样年纪的人会。我们会问,为什么我们甚至假设生活中有一个"目的"。我们可能更适合做某些事而非其它;做我们适应的事可能更快乐;但为什么要假设目的?
> a) Your housemate did it deliberately to upset you. He _knew_ you were saving that piece of cake. > > b) Your housemate was hungry.
思想的历史就是逐渐抛弃"一切以我们为中心"这一假设的历史。不,事实证明,地球不是宇宙的中心——甚至不是太阳系的中心。不,事实证明,人类不是上帝按自己的形象创造的;他们只是众多物种之一,不仅从猿类进化而来,而且源自微生物。甚至"自我"这个概念,如果仔细审视,边缘也是模糊的。
我们是万物中心这一观念很难摒弃。如此之难,以至于可能还有更多可以摒弃的空间。理查德·道金斯在最近几十年才在这个方向上又迈出了一步,提出了自私的基因的概念。不,事实证明,我们甚至不是主角:我们只是我们的基因为了四处活动而建造的最新模型载体。而生孩子是我们的基因奔向救生艇。读那本书让我的大脑摆脱了以前的思维方式,就像达尔文的书第一次出现时那样。
I say pick b. No one knows who said "never attribute to malice what can be explained by incompetence," but it is a powerful idea. Its more general version is our answer to the Greeks:
(现在很少有人能体验到达尔文同时代的人在《物种起源》首次出版时的感受,因为现在每个人要么认为进化是理所当然的,要么将其视为异端邪说。没有人会在成年后第一次遇到自然选择的概念。)
> Don't see purpose where there isn't.
因此,如果你想发现迄今为止被忽视的东西,一个非常好的地方就是我们的盲点:在我们天然的、天真的信念中,即一切以我们为中心。而且如果你这样做,预计会遇到激烈的反对。
相反,如果你必须在两种理论之间做出选择,倾向于不以你为中心的那个。
Or better still, the positive version:
这个原则不仅适用于大思想。它在日常生活中也适用。例如,假设你在冰箱里保存了一块蛋糕,有一天你回到家发现你的室友把它吃了。有两种可能的理论:
a) 你的室友是故意惹你生气。他_知道_你在留着那块蛋糕。 b) 你的室友只是饿了。
> See randomness.
我选b。虽然没人知道“能用愚蠢解释的事就别归咎于恶意”这句话是谁说的,但这个观点很有力。它更普遍的版本就是我们给希腊人的答案:
> 不要在没有目的的地方寻找目的。
March 2006, rev August 2009 Yesterday one of the founders we funded asked me why we started Y Combinator. Or more precisely, he asked if we'd started YC mainly for fun. Kind of, but not quite. It is enormously fun to be able to work with Rtm and Trevor again. I missed that after we sold Viaweb, and for all the years after I always had a background process running, looking for something we could do together. There is definitely an aspect of a band reunion to Y Combinator. Every couple days I slip and call it "Viaweb." Viaweb we started very explicitly to make money. I was sick of living from one freelance project to the next, and decided to just work as hard as I could till I'd made enough to solve the problem once and for all. Viaweb was sometimes fun, but it wasn't designed for fun, and mostly it wasn't. I'd be surprised if any startup is. All startups are mostly schleps. The real reason we started Y Combinator is neither selfish nor virtuous. We didn't start it mainly to make money; we have no idea what our average returns might be, and won't know for years. Nor did we start YC mainly to help out young would-be founders, though we do like the idea, and comfort ourselves occasionally with the thought that if all our investments tank, we will thus have been doing something unselfish. (It's oddly nondeterministic.) The real reason we started Y Combinator is one probably only a hacker would understand. We did it because it seems such a great hack. There are thousands of smart people who could start companies and don't, and with a relatively small amount of force applied at just the right place, we can spring on the world a stream of new startups that might otherwise not have existed. In a way this is virtuous, because I think startups are a good thing.
But really what motivates us is the completely amoral desire that would motivate any hacker who looked at some complex device and realized that with a tiny tweak he could make it run more efficiently. In this case, the device is the world's economy, which fortunately happens to be open source..
2006年3月,2009年8月修订 昨天,一位我们资助的创始人问我为什么要创办Y Combinator。更准确地说,他问我们创办YC是否主要是为了乐趣。 某种程度上是的,但不完全是。能够再次与Rtm和Trevor共事非常有趣。在卖掉Viaweb后,我一直怀念这种感觉,之后的这些年里,我总有一个后台进程在运行,寻找我们可以一起做的事情。Y Combinator确实有一种乐队重聚的感觉。每隔几天,我就会不小心把它叫做“Viaweb”。 我们创办Viaweb时非常明确是为了赚钱。我厌倦了从一个自由职业项目到另一个的生活,决定拼命工作,直到赚够钱一劳永逸地解决问题。Viaweb有时很有趣,但它不是为了乐趣而设计的,大多数时候并非如此。如果任何初创公司主要是为了乐趣,我会感到惊讶。所有初创公司大多都是苦差事。 我们创办Y Combinator的真正原因既不自私也不高尚。我们创办它主要不是为了赚钱;我们不知道平均回报可能是多少,而且多年内都不会知道。我们创办YC主要也不是为了帮助年轻的潜在创始人,尽管我们确实喜欢这个想法,并偶尔安慰自己,如果我们所有的投资都失败了,那么我们就是在做一件无私的事情。(这奇怪地具有不确定性。) 我们创办Y Combinator的真正原因可能只有黑客才能理解。我们这样做是因为它看起来是一个伟大的黑客行为。有成千上万的聪明人可以创办公司却没有这样做,通过在正确的地方施加相对较小的力量,我们可以向世界推出一系列新的初创公司,否则这些公司可能不会存在。 从某种意义上说,这是高尚的,因为我认为初创公司是好事。但真正激励我们的是完全无关道德的动力,这种动力会激励任何黑客看到某个复杂设备时,意识到只需微调就能让它运行得更高效。在这种情况下,这个设备就是世界经济,幸运的是,它恰好是开源的。
March 2006 _(This essay is derived from a talk at Google.)_ A few weeks ago I found to my surprise that I'd been granted four patents. This was all the more surprising because I'd only applied for three. The patents aren't mine, of course. They were assigned to Viaweb, and became Yahoo's when they bought us. But the news set me thinking about the question of software patents generally. Patents are a hard problem. I've had to advise most of the startups we've funded about them, and despite years of experience I'm still not always sure I'm giving the right advice. One thing I do feel pretty certain of is that if you're against software patents, you're against patents in general. Gradually our machines consist more and more of software. Things that used to be done with levers and cams and gears are now done with loops and trees and closures. There's nothing special about physical embodiments of control systems that should make them patentable, and the software equivalent not. Unfortunately, patent law is inconsistent on this point. Patent law in most countries says that algorithms aren't patentable. This rule is left over from a time when "algorithm" meant something like the Sieve of Eratosthenes. In 1800, people could not see as readily as we can that a great many patents on mechanical objects were really patents on the algorithms they embodied. Patent lawyers still have to pretend that's what they're doing when they patent algorithms. You must not use the word "algorithm" in the title of a patent application, just as you must not use the word "essays" in the title of a book. If you want to patent an algorithm, you have to frame it as a computer system executing that algorithm. Then it's mechanical; phew. The default euphemism for algorithm is "system and method." Try a patent search for that phrase and see how many results you get.
(本文改编自在谷歌的一次演讲。)
几周前,我惊讶地发现自己被授予了四项专利。更令人意外的是,我当初只申请了三项。当然,这些专利并不属于我个人。它们最初归属于Viaweb,后来随着公司被收购而成为雅虎的资产。但这一消息让我开始深入思考软件专利的普遍问题。
专利问题复杂难解。多年来,我不得不为大多数我们投资过的初创公司提供专利方面的建议,但即便经验丰富,我仍不确定自己给出的建议是否总是正确。
有一点我非常确定:如果你反对软件专利,那么你本质上反对的是所有专利。如今,我们的机器越来越依赖软件运作。过去由杠杆、凸轮和齿轮完成的工作,现在被循环、树结构和闭包所替代。控制系统的物理实现并无特殊之处使其应受专利保护,而软件实现也不该被排除在外。
Since software patents are no different from hardware patents, people who say "software patents are evil" are saying simply "patents are evil." So why do so many people complain about software patents specifically? I think the problem is more with the patent office than the concept of software patents. Whenever software meets government, bad things happen, because software changes fast and government changes slow. The patent office has been overwhelmed by both the volume and the novelty of applications for software patents, and as a result they've made a lot of mistakes. The most common is to grant patents that shouldn't be granted. To be patentable, an invention has to be more than new. It also has to be non-obvious. And this, especially, is where the USPTO has been dropping the ball. Slashdot has an icon that expresses the problem vividly: a knife and fork with the words "patent pending" superimposed. The scary thing is, this is the _only_ icon they have for patent stories. Slashdot readers now take it for granted that a story about a patent will be about a bogus patent. That's how bad the problem has become. The problem with Amazon's notorious one-click patent, for example, is not that it's a software patent, but that it's obvious. Any online store that kept people's shipping addresses would have implemented this. The reason Amazon did it first was not that they were especially smart, but because they were one of the earliest sites with enough clout to force customers to log in before they could buy something. [1] We, as hackers, know the USPTO is letting people patent the knives and forks of our world. The problem is, the USPTO are not hackers. They're probably good at judging new inventions for casting steel or grinding lenses, but they don't understand software yet. At this point an optimist would be tempted to add "but they will eventually." Unfortunately that might not be true.
遗憾的是,专利法在这一问题上并不一致。多数国家的专利法规定算法不可专利化。这一规则源于“算法”还仅指类似埃拉托斯特尼筛法的时代。在1800年,人们无法像我们一样清晰地认识到,许多机械物体的专利本质上是对其背后算法的保护。
专利律师在为算法申请专利时,仍不得不假装自己在保护其他内容。专利标题中绝不能出现“算法”一词,就像书名不能直接叫“散文集”。若想为算法申请专利,必须将其包装成“执行该算法的计算机系统”——这样它就摇身一变成了机械发明,问题迎刃而解。算法的默认委婉说法是“系统与方法”。用这个词组做专利搜索,结果数量会令人瞠目。
既然软件专利与硬件专利并无本质区别,那些声称“软件专利是邪恶的”的人,实际上是在说“所有专利都是邪恶的”。那么,为何如此多人专门抨击软件专利?
我认为问题更多出在专利局而非软件专利本身。每当软件与政府体系碰撞,结果往往不尽如人意——软件迭代迅速,而政府变革迟缓。面对软件专利申请的数量与新颖性,专利局已不堪重负,因而犯下诸多错误。
最常见的错误是授予了本不该通过的专利。一项发明要获得专利,不仅要新颖,还必须具备非显而易见性。而美国专利商标局(USPTO)尤其在此环节频频失守。Slashdot网站用一个图标生动呈现这个问题:刀叉图案上叠加着“专利待批”字样。
The problem with software patents is an instance of a more general one: the patent office takes a while to understand new technology. If so, this problem will only get worse, because the rate of technological change seems to be increasing. In thirty years, the patent office may understand the sort of things we now patent as software, but there will be other new types of inventions they understand even less. Applying for a patent is a negotiation. You generally apply for a broader patent than you think you'll be granted, and the examiners reply by throwing out some of your claims and granting others. So I don't really blame Amazon for applying for the one-click patent. The big mistake was the patent office's, for not insisting on something narrower, with real technical content. By granting such an over-broad patent, the USPTO in effect slept with Amazon on the first date. Was Amazon supposed to say no? Where Amazon went over to the dark side was not in applying for the patent, but in enforcing it. A lot of companies (Microsoft, for example) have been granted large numbers of preposterously over-broad patents, but they keep them mainly for defensive purposes. Like nuclear weapons, the main role of big companies' patent portfolios is to threaten anyone who attacks them with a counter-suit. Amazon's suit against Barnes & Noble was thus the equivalent of a nuclear first strike. That suit probably hurt Amazon more than it helped them. Barnes & Noble was a lame site; Amazon would have crushed them anyway. To attack a rival they could have ignored, Amazon put a lasting black mark on their own reputation. Even now I think if you asked hackers to free-associate about Amazon, the one-click patent would turn up in the first ten topics. Google clearly doesn't feel that merely holding patents is evil. They've applied for a lot of them.
可怕的是,这是他们报道专利新闻时使用的唯一图标。Slashdot读者如今已默认专利新闻必然涉及虚假专利——问题严重性可见一斑。
以亚马逊臭名昭著的“一键下单”专利为例,问题不在于它是软件专利,而在于其显而易见的特性。任何保存用户收货地址的网店都会自然实现此功能。亚马逊能抢先并非因为格外聪明,而是他们作为早期电商巨头,有实力强制用户登录后才能购物。[1]
作为黑客,我们清楚USPTO正在放任人们给常识性创新申请专利。问题在于,USPTO审查员并非黑客。他们或许擅长评判炼钢或透镜研磨领域的新发明,但对软件仍缺乏理解。
乐观主义者或许会补充“但他们终将进步”。遗憾的是,这可能不会实现。软件专利问题折射出更普遍的困境:专利局理解新技术总需要时间。若果真如此,这一问题只会恶化,因为技术变革的速度似乎在加快。三十年后,专利局或许能理解我们现在申请的软件专利,但届时又会出现更让他们困惑的新发明类型。
专利申请本质上是场谈判。申请人通常会提出比预期更宽泛的权利要求,审查员则通过驳回部分条款、批准其他条款来回应。因此我并不责怪亚马逊申请“一键下单”专利。重大失误在于专利局未能坚持要求更具技术实质的窄范围专利。通过授予如此宽泛的专利,USPTO相当于初次约会就与亚马逊“共度良宵”——难道该指望亚马逊主动拒绝吗?
Are they hypocrites? Are patents evil? There are really two variants of that question, and people answering it often aren't clear in their own minds which they're answering. There's a narrow variant: is it bad, given the current legal system, to apply for patents? and also a broader one: is it bad that the current legal system allows patents? These are separate questions. For example, in preindustrial societies like medieval Europe, when someone attacked you, you didn't call the police. There were no police. When attacked, you were supposed to fight back, and there were conventions about how to do it. Was this wrong? That's two questions: was it wrong to take justice into your own hands, and was it wrong that you had to? We tend to say yes to the second, but no to the first. If no one else will defend you, you have to defend yourself. [2] The situation with patents is similar. Business is a kind of ritualized warfare. Indeed, it evolved from actual warfare: most early traders switched on the fly from merchants to pirates depending on how strong you seemed. In business there are certain rules describing how companies may and may not compete with one another, and someone deciding that they're going to play by their own rules is missing the point. Saying "I'm not going to apply for patents just because everyone else does" is not like saying "I'm not going to lie just because everyone else does." It's more like saying "I'm not going to use TCP/IP just because everyone else does." Oh yes you are. A closer comparison might be someone seeing a hockey game for the first time, realizing with shock that the players were _deliberately_ bumping into one another, and deciding that one would on no account be so rude when playing hockey oneself. Hockey allows checking. It's part of the game. If your team refuses to do it, you simply lose. So it is in business. Under the present rules, patents are part of the game.
亚马逊真正堕入黑暗面的行为不是申请专利,而是强制执行它。许多公司(如微软)持有大量荒谬的宽泛专利,但主要将其用于防御。就像核武器,大公司的专利组合主要用于威慑——谁敢起诉,就反诉谁。而亚马逊起诉巴诺书店,无异于发动核打击首袭。
这场诉讼对亚马逊的伤害可能远超收益。巴诺网站本就孱弱,亚马逊本可轻松碾压。为打击一个本可忽视的对手,亚马逊给自己的声誉烙上永久污点。即便现在,若让黑客自由联想亚马逊,“一键下单专利”仍会位列前十话题。
谷歌显然不认为持有专利是邪恶的。他们申请了大量专利。这是虚伪吗?专利本身邪恶吗?
这个问题实际包含两个层面,而回答者往往混淆不清:狭义层面是“在现行法律体系下申请专利是否错误?”;广义层面则是“现行法律允许专利存在是否错误?”
What does that mean in practice? We tell the startups we fund not to worry about infringing patents, because startups rarely get sued for patent infringement. There are only two reasons someone might sue you: for money, or to prevent you from competing with them. Startups are too poor to be worth suing for money. And in practice they don't seem to get sued much by competitors, either. They don't get sued by other startups because (a) patent suits are an expensive distraction, and (b) since the other startups are as young as they are, their patents probably haven't issued yet. [3] Nor do startups, at least in the software business, seem to get sued much by established competitors. Despite all the patents Microsoft holds, I don't know of an instance where they sued a startup for patent infringement. Companies like Microsoft and Oracle don't win by winning lawsuits. That's too uncertain. They win by locking competitors out of their sales channels. If you do manage to threaten them, they're more likely to buy you than sue you. When you read of big companies filing patent suits against smaller ones, it's usually a big company on the way down, grasping at straws. For example, Unisys's attempts to enforce their patent on LZW compression. When you see a big company threatening patent suits, sell. When a company starts fighting over IP, it's a sign they've lost the real battle, for users. A company that sues competitors for patent infringement is like a defender who has been beaten so thoroughly that he turns to plead with the referee. You don't do that if you can still reach the ball, even if you genuinely believe you've been fouled. So a company threatening patent suits is a company in trouble. When we were working on Viaweb, a bigger company in the e-commerce business was granted a patent on online ordering, or something like that. I got a call from a VP there asking if we'd like to license it.
这是两个独立问题。以中世纪欧洲等前工业社会为例:当遭受攻击时,人们无法报警(因为不存在警察),只能自卫并遵循特定惯例。这错误吗?需分两点回答:自行伸张正义是否错误?以及不得不这样做是否错误?我们通常对后者说“是”,对前者说“否”——当无人保护你时,自卫是必然选择。[2]
专利现状与之相似。商业是种仪式化的战争,甚至就是从真实战争演化而来:早期商旅常根据对方实力在商人与海盗身份间切换。商业竞争存在既定规则,拒绝遵守者实则误解了游戏本质。声称“我不申请专利只因其他人都申请”,不同于说“我不撒谎只因其他人都撒谎”,而更像宣称“我不使用TCP/IP协议只因其他人都用”——不,你终究会用。
更贴切的类比或许是:初次观看冰球比赛的人震惊于球员故意冲撞,遂决定自己打球时绝不如此粗鲁。
但冲撞本就是冰球规则的一部分。拒绝冲撞的球队必输无疑。商业亦是如此。现行规则下,专利是游戏组成部分。
实践中这意味着什么?我们建议投资的初创公司不必担心专利侵权,因为初创企业很少因此被诉。起诉动机无非两种:谋利或阻止竞争。初创公司太穷,不值得为钱起诉;实践中也鲜见竞争对手起诉——其他初创公司不会起诉,因为(a)专利诉讼昂贵且干扰业务;(b)同龄初创公司的专利可能尚未获批。[3] 即便是软件行业的成熟巨头,也极少起诉初创公司。尽管微软持有大量专利,我未见其起诉初创公司侵权的案例。微软、甲骨文等公司制胜靠的是封锁竞争对手的销售渠道,而非诉讼这种不确定手段。若你真构成威胁,他们更可能收购而非起诉你。
I replied that I thought the patent was completely bogus, and would never hold up in court. "Ok," he replied. "So, are you guys hiring?" If your startup grows big enough, however, you'll start to get sued, no matter what you do. If you go public, for example, you'll be sued by multiple patent trolls who hope you'll pay them off to go away. More on them later. In other words, no one will sue you for patent infringement till you have money, and once you have money, people will sue you whether they have grounds to or not. So I advise fatalism. Don't waste your time worrying about patent infringement. You're probably violating a patent every time you tie your shoelaces. At the start, at least, just worry about making something great and getting lots of users. If you grow to the point where anyone considers you worth attacking, you're doing well. We do advise the companies we fund to apply for patents, but not so they can sue competitors. Successful startups either get bought or grow into big companies. If a startup wants to grow into a big company, they should apply for patents to build up the patent portfolio they'll need to maintain an armed truce with other big companies. If they want to get bought, they should apply for patents because patents are part of the mating dance with acquirers. Most startups that succeed do it by getting bought, and most acquirers care about patents. Startup acquisitions are usually a build-vs-buy decision for the acquirer. Should we buy this little startup or build our own? And two things, especially, make them decide not to build their own: if you already have a large and rapidly growing user base, and if you have a fairly solid patent application on critical parts of your software. There's a third reason big companies should prefer buying to building: that if they built their own, they'd screw it up. But few big companies are smart enough yet to admit this to themselves.
当大公司起诉小公司专利侵权时,通常是衰败中的垂死挣扎。例如Unisys试图强制执行其LZW压缩专利。看到大公司威胁专利诉讼时,抛售其股票才是明智之举——当企业开始争夺知识产权,往往意味着已输掉真正的用户之战。
以专利侵权起诉竞争对手的公司,就像被彻底击败的防守队员转向哀求裁判。只要还能触球,即使确信对方犯规,你也不会这样做。因此,威胁专利诉讼的公司往往深陷困境。
Viaweb时期,某电商巨头获得了“在线订购”之类的专利。其副总裁来电询问我们是否愿意授权。我直言该专利完全无效,法庭绝不会支持。他竟回应:“好吧……你们招人吗?”
然而,若初创公司壮大到一定程度,无论做什么都难免被诉。例如上市时,专利流氓会轮番起诉,指望你花钱消灾。关于他们后文再述。
简言之,没钱时无人起诉你;有钱后,无论有无依据都会有人起诉。因此我建议采取宿命论态度:别浪费时间担忧专利侵权。系鞋带都可能侵权。初创阶段只需专注打造伟大产品、获取海量用户。若有人觉得你值得起诉,说明你已成功。
It's usually the acquirer's engineers who are asked how hard it would be for the company to build their own, and they overestimate their abilities. [4] A patent seems to change the balance. It gives the acquirer an excuse to admit they couldn't copy what you're doing. It may also help them to grasp what's special about your technology. Frankly, it surprises me how small a role patents play in the software business. It's kind of ironic, considering all the dire things experts say about software patents stifling innovation, but when one looks closely at the software business, the most striking thing is how little patents seem to matter. In other fields, companies regularly sue competitors for patent infringement. For example, the airport baggage scanning business was for many years a cozy duopoly shared between two companies, InVision and L-3. In 2002 a startup called Reveal appeared, with new technology that let them build scanners a third the size. They were sued for patent infringement before they'd even released a product. You rarely hear that kind of story in our world. The one example I've found is, embarrassingly enough, Yahoo, which filed a patent suit against a gaming startup called Xfire in 2005. Xfire doesn't seem to be a very big deal, and it's hard to say why Yahoo felt threatened. Xfire's VP of engineering had worked at Yahoo on similar stuff-- in fact, he was listed as an inventor on the patent Yahoo sued over-- so perhaps there was something personal about it. My guess is that someone at Yahoo goofed. At any rate they didn't pursue the suit very vigorously. Why do patents play so small a role in software? I can think of three possible reasons. One is that software is so complicated that patents by themselves are not worth very much.
我们确实建议被投公司申请专利,但目的不是起诉竞争对手。成功的初创公司要么被收购,要么成长为巨头。若选择后者,需建立专利组合以与其他巨头维持武装和平;若选择前者,专利则是与收购方“求偶舞蹈”的重要环节。
多数成功初创通过被收购退出,而收购方普遍重视专利。对收购方而言,决策常简化为“自建还是收购”。两类因素尤其促使其选择收购:(1)你已拥有快速增长的用户群;(2)你在核心技术上有扎实的专利申请。
还有第三类因素本应促使大公司选择收购:自建很可能会搞砸。但鲜有大公司足够清醒地承认这点。通常由收购方的工程师评估自建难度,而他们往往高估自身能力。[4] 专利能改变天平——它给收购方一个台阶,承认无法复制你的成果,同时帮助其理解你技术的独特之处。
坦白说,专利在软件行业的作用之小令我惊讶。考虑到专家们关于软件专利扼杀创新的可怕预言,颇具讽刺意味的是:细察软件行业,最突出的恰恰是专利的无足轻重。
其他领域常见专利侵权诉讼。例如机场行李扫描行业曾长期由InVision和L-3两家公司舒适垄断。2002年初创公司Reveal携新技术入场,能制造体积仅三分之一的扫描仪。产品未及面世就被诉专利侵权。
I may be maligning other fields here, but it seems that in most types of engineering you can hand the details of some new technique to a group of medium-high quality people and get the desired result. For example, if someone develops a new process for smelting ore that gets a better yield, and you assemble a team of qualified experts and tell them about it, they'll be able to get the same yield. This doesn't seem to work in software. Software is so subtle and unpredictable that "qualified experts" don't get you very far. That's why we rarely hear phrases like "qualified expert" in the software business. What that level of ability can get you is, say, to make your software compatible with some other piece of software-- in eight months, at enormous cost. To do anything harder you need individual brilliance. If you assemble a team of qualified experts and tell them to make a new web-based email program, they'll get their asses kicked by a team of inspired nineteen year olds. Experts can implement, but they can't design. Or rather, expertise in implementation is the only kind most people, including the experts themselves, can measure. [5] But design is a definite skill. It's not just an airy intangible. Things always seem intangible when you don't understand them. Electricity seemed an airy intangible to most people in 1800. Who knew there was so much to know about it? So it is with design. Some people are good at it and some people are bad at it, and there's something very tangible they're good or bad at. The reason design counts so much in software is probably that there are fewer constraints than on physical things. Building physical things is expensive and dangerous. The space of possible choices is smaller; you tend to have to work as part of a larger group; and you're subject to a lot of regulations. You don't have any of that if you and a couple friends decide to create a new web-based application.
这类故事在软件界极为罕见。我找到的唯一案例(颇为尴尬)是雅虎2005年起诉游戏初创公司Xfire。Xfire规模有限,雅虎的威胁感知令人费解。可能因Xfire工程副总裁曾任职雅虎类似项目——事实上他正是雅虎诉讼所涉专利的发明人之一——或许涉及个人恩怨。我猜是雅虎某位人士犯了糊涂。无论如何他们未强力推进诉讼。
为何专利在软件领域作用微弱?我认为有三个原因:
首先,软件过于复杂,专利本身价值有限。其他工程领域,将新技术细节交给中等偏上团队通常能复现成果。例如新冶炼工艺若能提升产量,专家团队按方案操作即可达成。但软件截然不同——其微妙性与不可预测性使得“合格专家”难以奏效。
这正是软件业罕提“合格专家”的原因。这种能力级别或许能实现软件兼容性——但需耗时八月、耗资巨大。要突破创新,需要的是个体天赋。若组建专家团队开发网页邮箱,他们会被一群19岁天才少年碾压。
Because there's so much scope for design in software, a successful application tends to be way more than the sum of its patents. What protects little companies from being copied by bigger competitors is not just their patents, but the thousand little things the big company will get wrong if they try. The second reason patents don't count for much in our world is that startups rarely attack big companies head-on, the way Reveal did. In the software business, startups beat established companies by transcending them. Startups don't build desktop word processing programs to compete with Microsoft Word. [6] They build Writely. If this paradigm is crowded, just wait for the next one; they run pretty frequently on this route. Fortunately for startups, big companies are extremely good at denial. If you take the trouble to attack them from an oblique angle, they'll meet you half-way and maneuver to keep you in their blind spot. To sue a startup would mean admitting it was dangerous, and that often means seeing something the big company doesn't want to see. IBM used to sue its mainframe competitors regularly, but they didn't bother much about the microcomputer industry because they didn't want to see the threat it posed. Companies building web based apps are similarly protected from Microsoft, which even now doesn't want to imagine a world in which Windows is irrelevant. The third reason patents don't seem to matter very much in software is public opinion-- or rather, hacker opinion. In a recent interview, Steve Ballmer coyly left open the possibility of attacking Linux on patent grounds. But I doubt Microsoft would ever be so stupid. They'd face the mother of all boycotts. And not just from the technical community in general; a lot of their own people would rebel. Good hackers care a lot about matters of principle, and they are highly mobile.
专家精于实施,却拙于设计。或者说,实施能力是包括专家本人在内的大多数人唯一可衡量的维度。[5]
但设计确实是种明确技能,绝非虚无缥缈。1800年电对多数人同样神秘莫测——谁能预见其中蕴含如此多知识?设计亦然。有人擅长有人拙劣,这种能力差异真实存在。
设计在软件中至关重要的原因,或许是约束条件远少于物理世界。制造实体物品成本高昂且危险,可能性空间较小,常需团队协作并受诸多法规限制。而开发网络应用则全无这些束缚。
正因软件设计的广阔空间,成功应用的价值远超其专利总和。保护小公司不被大公司复制的不仅是专利,更是大公司尝试时必然犯下的无数小错误。
第二,软件初创公司很少像Reveal那样正面攻击巨头,而是通过升维超越。初创公司不会开发对标微软Word的文字处理程序,[6] 而是创造Writely。若当前范式拥挤,只需等待下个技术浪潮——这条赛道迭代极快。
If a company starts misbehaving, smart people won't work there. For some reason this seems to be more true in software than other businesses. I don't think it's because hackers have intrinsically higher principles so much as that their skills are easily transferrable. Perhaps we can split the difference and say that mobility gives hackers the luxury of being principled. Google's "don't be evil" policy may for this reason be the most valuable thing they've discovered. It's very constraining in some ways. If Google does do something evil, they get doubly whacked for it: once for whatever they did, and again for hypocrisy. But I think it's worth it. It helps them to hire the best people, and it's better, even from a purely selfish point of view, to be constrained by principles than by stupidity. (I wish someone would get this point across to the present administration.) I'm not sure what the proportions are of the preceding three ingredients, but the custom among the big companies seems to be not to sue the small ones, and the startups are mostly too busy and too poor to sue one another. So despite the huge number of software patents there's not a lot of suing going on. With one exception: patent trolls. Patent trolls are companies consisting mainly of lawyers whose whole business is to accumulate patents and threaten to sue companies who actually make things. Patent trolls, it seems safe to say, are evil. I feel a bit stupid saying that, because when you're saying something that Richard Stallman and Bill Gates would both agree with, you must be perilously close to tautologies. The CEO of Forgent, one of the most notorious patent trolls, says that what his company does is "the American way." Actually that's not true. The American way is to make money by creating wealth, not by suing people. [7] What companies like Forgent do is actually the proto-industrial way.
幸运的是,大公司极其善于自我欺骗。若你以迂回方式进攻,他们会配合地保持盲区姿态。起诉初创公司意味着承认其威胁性,这常需直面大公司不愿看到的现实。IBM曾定期起诉主机竞争对手,却忽视微机行业——因其拒绝正视威胁。基于网络的应用程序开发者同样受此保护:即便今日,微软仍不愿想象Windows无关紧要的世界。
第三是舆论压力——确切说是黑客舆论。史蒂夫·鲍尔默近期访谈中暧昧提及可能以专利攻击Linux。但我怀疑微软真会如此愚蠢——他们将面临史上最强抵制,不仅来自技术社区,许多自家员工也会反抗。
优秀黑客极为重视原则,且高度流动。公司行为不端,聪明人便拒绝效力。软件行业这一特点尤为突出。非因黑客道德更高尚,而是其技能可轻松迁移。或许可以说:流动性赋予黑客坚守原则的奢侈。
谷歌“不作恶”信条或许因此成为其最有价值的发现。这虽在某些方面形成约束(作恶将遭双重打击:行为本身+伪善罪名),但利大于弊——既能吸引顶尖人才,从自私角度看,被原则约束也远胜被愚蠢束缚。
(但愿有人能让现任政府明白这点。)
In the period just before the industrial revolution, some of the greatest fortunes in countries like England and France were made by courtiers who extracted some lucrative right from the crown-- like the right to collect taxes on the import of silk-- and then used this to squeeze money from the merchants in that business. So when people compare patent trolls to the mafia, they're more right than they know, because the mafia too are not merely bad, but bad specifically in the sense of being an obsolete business model. Patent trolls seem to have caught big companies by surprise. In the last couple years they've extracted hundreds of millions of dollars from them. Patent trolls are hard to fight precisely because they create nothing. Big companies are safe from being sued by other big companies because they can threaten a counter-suit. But because patent trolls don't make anything, there's nothing they can be sued for. I predict this loophole will get closed fairly quickly, at least by legal standards. It's clearly an abuse of the system, and the victims are powerful. [8] But evil as patent trolls are, I don't think they hamper innovation much. They don't sue till a startup has made money, and by that point the innovation that generated it has already happened. I can't think of a startup that avoided working on some problem because of patent trolls. So much for hockey as the game is played now. What about the more theoretical question of whether hockey would be a better game without checking? Do patents encourage or discourage innovation? This is a very hard question to answer in the general case. People write whole books on the topic. One of my main hobbies is the history of technology, and even though I've studied the subject for years, it would take me several weeks of research to be able to say whether patents have in general been a net win.
尽管前述三因素比例难定,但大公司似乎形成不诉小公司的惯例,而初创公司则忙于生存无暇互诉。因此尽管软件专利数量庞大,诉讼却不多——除专利流氓外。
专利流氓是由律师主导的公司,专事积累专利并威胁实体企业。可以说,专利流氓是邪恶的。此言近乎废话——当理查德·斯托曼与比尔·盖茨罕见达成共识时,你显然在陈述不证自明之理。
最臭名昭著的专利流氓之一Forgent的CEO称其行为是“美国方式”。实则谬误。美国精神应是通过创造财富获利,而非诉讼勒索。[7] Forgent之流实为前工业化时代的遗毒。工业革命前夕,英法等国部分巨富通过向王室购买征税权(如丝绸进口税)盘剥商人敛财。将专利流氓比作黑手党甚至不够准确——因黑手党不仅是恶势力,更是过时商业模式的代表。
专利流氓似乎令大公司措手不及,近年已勒索数亿美元。其难以反击 precisely because they create nothing. 大公司间因可相互制衡而免于诉讼,但专利流氓因不事生产,无把柄可抓。我预测此漏洞将较快(以法律标准而言)被填补——这明显是制度滥用,且受害者实力雄厚。[8]
尽管专利流氓邪恶,但我不认为其严重阻碍创新。他们只在初创公司盈利后才起诉,此时创新早已发生。我想不出有初创公司因忌惮专利流氓而放弃某个领域。
One thing I can say is that 99.9% of the people who express opinions on the subject do it not based on such research, but out of a kind of religious conviction. At least, that's the polite way of putting it; the colloquial version involves speech coming out of organs not designed for that purpose. Whether they encourage innovation or not, patents were at least intended to. You don't get a patent for nothing. In return for the exclusive right to use an idea, you have to _publish_ it, and it was largely to encourage such openness that patents were established. Before patents, people protected ideas by keeping them secret. With patents, central governments said, in effect, if you tell everyone your idea, we'll protect it for you. There is a parallel here to the rise of civil order, which happened at roughly the same time. Before central governments were powerful enough to enforce order, rich people had private armies. As governments got more powerful, they gradually compelled magnates to cede most responsibility for protecting them. (Magnates still have bodyguards, but no longer to protect them from other magnates.) Patents, like police, are involved in many abuses. But in both cases the default is something worse. The choice is not "patents or freedom?" any more than it is "police or freedom?" The actual questions are respectively "patents or secrecy?" and "police or gangs?" As with gangs, we have some idea what secrecy would be like, because that's how things used to be. The economy of medieval Europe was divided up into little tribes, each jealously guarding their privileges and secrets. In Shakespeare's time, "mystery" was synonymous with "craft." Even today we can see an echo of the secrecy of medieval guilds, in the now pointless secrecy of the Masons. The most memorable example of medieval industrial secrecy is probably Venice, which forbade glassblowers to leave the city, and sent assassins after those who tried.
以上是当前“冰球比赛”的实况。更理论的问题是:若取消冲撞,比赛会更好吗?专利究竟促进还是阻碍创新?
这问题在普遍情况下极难回答。相关专著汗牛充栋。作为科技史爱好者,即便研究多年,我也需数周调研才能判断专利是否整体有利。
可以确定的是,99.9%的讨论者并非基于研究,而是出于某种宗教式信念。委婉地说——若直白表述,恐怕要用到非发音器官的隐喻。
无论专利是否促进创新,其初衷确是如此。专利非无偿授予——作为垄断使用权的交换,你必须公开创意,而鼓励公开正是专利制度建立的初衷。
We might like to think we wouldn't go so far, but the movie industry has already tried to pass laws prescribing three year prison terms just for putting movies on public networks. Want to try a frightening thought experiment? If the movie industry could have any law they wanted, where would they stop? Short of the death penalty, one assumes, but how close would they get? Even worse than the spectacular abuses might be the overall decrease in efficiency that would accompany increased secrecy. As anyone who has dealt with organizations that operate on a "need to know" basis can attest, dividing information up into little cells is terribly inefficient. The flaw in the "need to know" principle is that you don't _know_ who needs to know something. An idea from one area might spark a great discovery in another. But the discoverer doesn't know he needs to know it. If secrecy were the only protection for ideas, companies wouldn't just have to be secretive with other companies; they'd have to be secretive internally. This would encourage what is already the worst trait of big companies. I'm not saying secrecy would be worse than patents, just that we couldn't discard patents for free. Businesses would become more secretive to compensate, and in some fields this might get ugly. Nor am I defending the current patent system. There is clearly a lot that's broken about it. But the breakage seems to affect software less than most other fields. In the software business I know from experience whether patents encourage or discourage innovation, and the answer is the type that people who like to argue about public policy least like to hear: they don't affect innovation much, one way or the other. Most innovation in the software business happens in startups, and startups should simply ignore other companies' patents. At least, that's what we advise, and we bet money on that advice.
专利出现前,人们通过保密保护创意。专利制度相当于中央政府承诺:“若公开创意,我们为你保护。”这与公民秩序的兴起并行——政府强大后,迫使权贵解散私军(虽保留保镖,但不再用于对抗同级权贵)。
专利如警察,存在诸多滥用。但两者的默认替代方案更糟。问题并非“要专利还是自由?”正如不是“要警察还是自由?”,实际选择是“要专利还是保密?”与“要警察还是黑帮?”。
关于保密,我们有所了解——那正是中世纪的经济形态。欧洲经济被割据为小部落,各自严防特权与秘密。莎士比亚时代,“mystery”(奥秘)与“craft”(技艺)同义。即便今日,共济会无意义的保密传统仍折射着中世纪行会的影子。
中世纪工业保密最著名的案例当属威尼斯——禁止玻璃工匠离城,并派刺客追杀叛逃者。我们或许自认不会如此极端,但电影业已试图推动法律将电影上传公共网络的行为判处三年监禁。来做思想实验:若电影业能制定任何法律,底线会在哪?虽不至于死刑,但会多接近?
比极端案例更严重的是伴随保密而来的整体效率下降。任何与“需知 basis”组织打过交道的人都明白:信息割据效率极低。“需知”原则的致命缺陷在于你无法预知谁需要知晓——某个领域的创意可能点燃另一领域的革命,但发现者并不自知需要它。
The only real role of patents, for most startups, is as an element of the mating dance with acquirers. There patents do help a little. And so they do encourage innovation indirectly, in that they give more power to startups, which is where, pound for pound, the most innovation happens. But even in the mating dance, patents are of secondary importance. It matters more to make something great and get a lot of users. Notes [1] You have to be careful here, because a great discovery often seems obvious in retrospect. One-click ordering, however, is not such a discovery. [2] "Turn the other cheek" skirts the issue; the critical question is not how to deal with slaps, but sword thrusts. [3] Applying for a patent is now very slow, but it might actually be bad if that got fixed. At the moment the time it takes to get a patent is conveniently just longer than the time it takes a startup to succeed or fail. [4] Instead of the canonical "could you build this?" maybe the corp dev guys should be asking "will you build this?" or even "why haven't you already built this?" [5] Design ability is so hard to measure that you can't even trust the design world's internal standards. You can't assume that someone with a degree in design is any good at design, or that an eminent designer is any better than his peers. If that worked, any company could build products as good as Apple's just by hiring sufficiently qualified designers. [6] If anyone wanted to try, we'd be interested to hear from them. I suspect it's one of those things that's not as hard as everyone assumes. [7] Patent trolls can't even claim, like speculators, that they "create" liquidity. [8] If big companies don't want to wait for the government to take action, there is a way to fight back themselves. For a long time I thought there wasn't, because there was nothing to grab onto. But there is one resource patent trolls need: lawyers.
若保密成为保护创意的唯一手段,公司不仅需对外保密,内部也将信息割裂。这会加剧大公司最糟糕的特质。
我并非断言保密比专利更糟,而是强调废除专利并非无代价。企业将转向更严密的保密措施,某些领域可能因此恶化。我也并非为现行专利制度辩护——它显然存在诸多缺陷——但软件领域受其负面影响似乎小于其他行业。
就软件行业而言,凭经验我能断言专利对创新的影响——这恰恰是政策辩论者最不愿听的答案:无论促进或抑制,影响都微乎其微。软件业的创新主要来自初创公司,而初创公司只需无视他人专利。至少这是我们给出的建议,并以真金白银押注于此。
对多数初创公司而言,专利的唯一实际价值在于提升被收购时的议价能力。这方面专利确有助益,因此间接鼓励创新——它们赋予初创公司更多力量,而后者正是创新密度最高的领域。但即便在收购谈判中,专利也非首要因素。打造伟大产品、获取海量用户才至关重要。
[1] 需谨慎判断,因为伟大发现在事后总显得显而易见。但一键下单绝非此类发现。
Big technology companies between them generate a lot of legal business. If they agreed among themselves never to do business with any firm employing anyone who had worked for a patent troll, either as an employee or as outside counsel, they could probably starve the trolls of the lawyers they need. Thanks to Dan Bloomberg, Paul Buchheit, Sarah Harlin, Jessica Livingston, and Peter Norvig for reading drafts of this, to Joel Lehrer and Peter Eng for answering my questions about patents, and to Ankur Pansari for inviting me to speak.
[2] “转过另一边脸”回避了核心问题——关键不在于如何应对掌掴,而是如何面对利剑穿胸。
[3] 当前专利申请极慢,但这或许是好事——专利获批时间恰巧长于初创公司成败周期。
[4] 企业开发部门或许不该问“能否构建这个?”,而该问“你们会构建吗?”或更尖锐:“为何你们尚未构建?”
[5] 设计能力难以量化,甚至设计界的内部标准也不可靠。设计学位不保证能力,著名设计师未必优于同行。若标准有效,任何公司只需雇佣“合格设计师”就能做出苹果水准的产品。
[6] 若有志尝试,我们愿闻其详。我怀疑这事没大众想象
March 2006, rev August 2009 A couple days ago I found to my surprise that I'd been granted a patent. It issued in 2003, but no one told me. I wouldn't know about it now except that a few months ago, while visiting Yahoo, I happened to run into a Big Cheese I knew from working there in the late nineties. He brought up something called Revenue Loop, which Viaweb had been working on when they bought us. The idea is basically that you sort search results not in order of textual "relevance" (as search engines did then) nor in order of how much advertisers bid (as Overture did) but in order of the bid times the number of transactions. Ordinarily you'd do this for shopping searches, though in fact one of the features of our scheme is that it automatically detects which searches are shopping searches. If you just order the results in order of bids, you can make the search results useless, because the first results could be dominated by lame sites that had bid the most. But if you order results by bid multiplied by transactions, far from selling out, you're getting a _better_ measure of relevance. What could be a better sign that someone was satisfied with a search result than going to the site and buying something? And, of course, this algorithm automatically maximizes the revenue of the search engine. Everyone is focused on this type of approach now, but few were in 1998\. In 1998 it was all about selling banner ads. We didn't know that, so we were pretty excited when we figured out what seemed to us the optimal way of doing shopping searches. When Yahoo was thinking of buying us, we had a meeting with Jerry Yang in New York.
2006年3月,2009年8月修订
几天前我惊讶地发现,自己竟被授予了一项专利。这项专利早在2003年就已获批,却无人告知。若非几个月前在雅虎偶遇一位九十年代末共事过的高管,我至今仍被蒙在鼓里。他提起当年收购我们时Viaweb正在研发的"收益循环"系统。
其核心理念是:搜索结果的排序既不依据文本"相关性"(当时搜索引擎的做法),也不按广告主出价(如Overture的模式),而是以出价乘以交易量为序。这套机制本用于购物搜索——事实上我们方案的亮点之一,就是能自动识别哪些搜索属于购物场景。
若单纯按出价排序,搜索结果可能毫无价值,因为排名靠前的或许是那些出价最高但质量低劣的网站。但若以出价乘以交易量为序,非但不会牺牲公正性,反而能获得更精准的相关性衡量标准——还有什么比用户点击网站并完成购买更能证明搜索结果令人满意呢?
For him, I now realize, this was supposed to be one of those meetings when you check out a company you've pretty much decided to buy, just to make sure they're ok guys. We weren't expected to do more than chat and seem smart and reasonable. He must have been dismayed when I jumped up to the whiteboard and launched into a presentation of our exciting new technology. I was just as dismayed when he didn't seem to care at all about it. At the time I thought, "boy, is this guy poker-faced. We present to him what has to be the optimal way of sorting product search results, and he's not even curious." I didn't realize till much later why he didn't care. In 1998, advertisers were overpaying enormously for ads on web sites. In 1998, if advertisers paid the maximum that traffic was worth to them, Yahoo's revenues would have _decreased._ Things are different now, of course. Now this sort of thing is all the rage. So when I ran into the Yahoo exec I knew from the old days in the Yahoo cafeteria a few months ago, the first thing he remembered was not (fortunately) all the fights I had with him, but Revenue Loop. "Well," I said, "I think we actually applied for a patent on it. I'm not sure what happened to the application after I left." "Really? That would be an important patent." So someone investigated, and sure enough, that patent application had continued in the pipeline for several years after, and finally issued in 2003. The main thing that struck me on reading it, actually, is that lawyers at some point messed up my nice clear writing. Some clever person with a spell checker reduced one section to Zen-like incomprehensibility: > Also, common spelling errors will tend to get fixed.
当然,这套算法也天然实现了搜索引擎收益的最大化。
如今这类方法已成行业焦点,但在1998年却鲜有人问津。那时横幅广告才是王道。我们当时懵懂无知,自认为发现了购物搜索的最佳解决方案,为此兴奋不已。
雅虎考虑收购我们时,曾在纽约与杨致远会面。如今我才明白,对他而言那不过是例行公事的收购前摸底——只需确认我们这群人靠谱就行。本应只是展现聪明才智的闲谈,我却突然跳起来在白板前演示这项激动人心的新技术,想必让他措手不及。
当他表现得毫无兴趣时,我同样错愕。当时心想:"这家伙真是喜怒不形于色。我们展示了产品搜索排序的最佳方案,他居然连好奇心都没有。"多年后我才明白其中缘由:1998年广告主正为网络广告支付巨额溢价,若按实际流量价值收费,雅虎的收入反而会缩水。
For example, if users searching for "compact disc player" end up spending considerable money at sites offering compact disc players, then those pages will have a higher relevance for that search phrase, even though the phrase "compact disc player" is not present on those pages..
如今时过境迁,这类技术已成主流。所以当我在雅虎餐厅偶遇旧识时,他首先想起的(幸好)不是当年争执,而是"收益循环"。
"其实,"我说,"我们为此申请过专利。只是不确定离职后进展如何。"
"真的?那将是项重要专利。"
经查证,这项专利申请在流程中辗转数年,最终于2003年获批。
(That "compat disc player" wasn't a typo, guys.) For the fine prose of the original, see the provisional application of February 1998, back when we were still Viaweb and couldn't afford to pay lawyers to turn every "a lot of" into "considerable."
重读专利文件时,最令我愕然的是律师们糟蹋了我原本清晰的表述。某位"聪明人"用拼写检查工具将某段改得禅意十足、晦涩难明:
> 常见拼写错误也将自动修正。例如当用户搜索"compact disc player"后在某网站完成大额消费,即便该页面未出现"compact disc player"字样,其与该搜索词的相关性评分仍将提升。
(那个“兼容光盘播放器”可不是打错了,伙计们。)
想欣赏原文的优美文笔,请参阅1998年2月的临时申请文件,那时候我们还叫Viaweb,也请不起律师把每个“很多”都改成“相当数量”。
Want to start a startup? Get funded by Y Combinator.
January 2006 To do something well you have to like it. That idea is not exactly novel. We've got it down to four words: "Do what you love." But it's not enough just to tell people that. Doing what you love is complicated. The very idea is foreign to what most of us learn as kids. When I was a kid, it seemed as if work and fun were opposites by definition. Life had two states: some of the time adults were making you do things, and that was called work; the rest of the time you could do what you wanted, and that was called playing. Occasionally the things adults made you do were fun, just as, occasionally, playing wasn't — for example, if you fell and hurt yourself. But except for these few anomalous cases, work was pretty much defined as not-fun. And it did not seem to be an accident. School, it was implied, was tedious _because_ it was preparation for grownup work. The world then was divided into two groups, grownups and kids. Grownups, like some kind of cursed race, had to work. Kids didn't, but they did have to go to school, which was a dilute version of work meant to prepare us for the real thing. Much as we disliked school, the grownups all agreed that grownup work was worse, and that we had it easy. Teachers in particular all seemed to believe implicitly that work was not fun. Which is not surprising: work wasn't fun for most of them. Why did we have to memorize state capitals instead of playing dodgeball? For the same reason they had to watch over a bunch of kids instead of lying on a beach. You couldn't just do what you wanted. I'm not saying we should let little kids do whatever they want. They may have to be made to work on certain things.
想创业吗? 获得 Y Combinator 的资助。
2006年1月 要做好一件事,你必须喜欢它。这个想法并不新鲜。我们把它浓缩成四个字:“做你所爱。”但仅仅告诉人们这一点是不够的。做你所爱是复杂的。 这一理念与我们大多数人从小接受的教育背道而驰。小时候,工作和乐趣似乎从定义上就是对立的。生活有两种状态:一部分时间大人们强迫你做事,这被称为工作;剩下的时间你可以做自己想做的事,这被称为玩耍。偶尔大人让你做的事也有趣,就像偶尔玩耍也会无趣——比如你摔倒受伤时。但除了这些少数例外,工作几乎被定义为“不有趣”。 而且这似乎并非偶然。人们暗示,学校之所以乏味,是因为它是为成年后的工作做准备。 那时世界分为两类人:成年人和孩子。成年人像某种被诅咒的种族,不得不工作。孩子不用工作,但他们必须上学,这是工作的稀释版,旨在为真正的工作做准备。尽管我们讨厌学校,但大人们一致认为成年后的工作更糟,而我们过得轻松多了。 尤其是老师们,似乎都默认工作不是有趣的。这并不奇怪:对他们大多数人来说,工作确实无趣。为什么我们必须背诵州首府而不是玩躲避球?就像他们必须看管一群孩子而不是躺在海滩上一样。你不能只做自己想做的事。 我并不是说应该让孩子为所欲为。他们可能需要被迫完成某些任务。但如果让孩子做枯燥的事,明智的做法是告诉他们:乏味并非工作的本质,现在做枯燥的事是为了将来能做更有趣的事。[1] 大约9、10岁时,父亲曾告诉我,长大后我可以成为任何想成为的人,只要我喜欢。我至今记得这句话,因为它显得如此反常。就像被告知要使用“干水”一样。无论我当时如何理解,我都不认为他是在说工作真的可以像玩耍一样有趣。我花了很多年才明白这一点。 工作 到了高中,真正的工作已近在眼前。有时成年人会来向我们介绍他们的工作,或者我们去参观他们的工作场所。大家总是默认他们喜欢自己的工作。回想起来,可能有一个人是真的喜欢:那位私人飞机驾驶员。但我不认为银行经理真的喜欢。 他们表现得喜欢工作的主要原因,大概是中上阶层的惯例要求如此。公开表示厌恶自己的工作不仅对职业不利,还是社交失礼。 为什么假装喜欢工作是惯例?本文第一句话就解释了这一点。如果做好一件事需要喜欢它,那么最成功的人都会喜欢自己的工作。这就是中上阶层传统的来源。就像全美各地的房子里摆满了椅子,主人们甚至不知道这些椅子是对250年前为法国国王设计的椅子的第N度模仿;关于工作的传统态度,主人们同样不自知地模仿着那些取得伟大成就者的态度。 这是多么严重的疏离感啊。等到孩子们开始思考自己想做什么时,大多数人已被彻底误导了对“热爱工作”的理解。学校训练他们将工作视为痛苦的义务。据说工作比学业更令人厌烦。然而所有成年人都声称喜欢自己的工作。难怪孩子们会想:“我和这些人不一样;我不适合这个世界。” 实际上他们被灌输了三个谎言:学校里被教导视为“工作”的事并非真正的工作;成年人的工作未必比学业更糟;周围许多成年人说自己喜欢工作时是在撒谎。 最危险的撒谎者可能是孩子的父母。如果你像许多人一样,为让家人过上高标准生活而从事乏味的工作,你可能会让孩子感染“工作很无聊”的观念。[2] 或许在这种情况下,父母不那么无私反而对孩子更好。一个以热爱工作为榜样的父母,可能比一栋昂贵的房子对孩子更有帮助。[3] 直到大学,我才将“工作”与“谋生”的概念分开。那时重要的问题不再是如何赚钱,而是该从事什么工作。理想情况下两者重合,但一些极端案例(比如专利局里的爱因斯坦)证明它们并非同一件事。 现在我对工作的定义是:为世界做出原创贡献,同时避免饿死。但多年习惯使然,我仍认为工作包含大量痛苦成分。工作似乎仍需要自律,因为只有难题才能带来伟大成果,而难题不可能真的有趣。肯定得强迫自己去做。 如果你认为某件事本该痛苦,就不太容易注意到自己做错了。这大致总结了我的研究生经历。 边界 你该多喜欢自己的工作?除非知道这一点,否则你不知道何时该停止寻找。如果像大多数人一样低估了喜欢的程度,你会过早停止寻找。最终你会做父母为你选择的事,或为赚钱、声望——或纯粹出于惯性。 上限是:“做你所爱”不意味着“做此刻最想做的事”。即使是爱因斯坦,可能也有想喝咖啡却告诉自己先完成手头工作的时候。 读到有人热爱自己的工作到“别无他求”时,我曾感到困惑。似乎没有任何工作能让我喜欢到那种程度。如果选择(a)接下来一小时工作或(b)瞬间传送到罗马闲逛一小时,我会选哪种工作?老实说,没有。 但事实是,几乎任何人在任何时刻,都会选择在加勒比海漂浮、做爱或享用美食,而非解决难题。“做你所爱”的规则预设了时间跨度。它不是指“让你此刻最快乐的事”,而是“在更长周期(比如一周或一月)里让你最快乐的事”。 无意义的快乐终会乏味。在沙滩躺久了你也会厌倦。想保持快乐,你必须做点什么。 下限是:你必须比无意义的快乐更喜欢你的工作。你必须喜欢到“空闲时间”这个概念显得荒谬。这不是说你必须一直工作。过度工作会导致疲劳和失误,这时你想做点别的——哪怕是无聊的事。但你不该把这些时间视为奖赏,而将工作时间视为换取奖赏的痛苦。 设定下限是出于实际原因。如果工作不是你最喜欢的事,你会严重拖延。你将不得不强迫自己工作,而这种状态下的成果明显更差。 我认为要获得快乐,你必须从事不仅享受而且钦佩的事。结束时你能说“哇,这太酷了”。这不一定要创造实物。如果你学会滑翔伞或流利掌握一门外语,至少短期内你会觉得“哇,这太酷了”。关键是要有检验标准。 我认为读书勉强达不到标准。除了数学和硬科学类书籍,读书没有检验标准,这就是为什么单纯读书不太像工作。你必须对读过的内容有所输出,才能感到成效。 我认为最好的检验标准是Gino Lee教我的:做让朋友惊叹“哇”的事。但这可能要到22岁左右才有效,因为此前大多数人没有足够样本量来选择朋友。 诱惑 我认为你不该在意朋友以外任何人的看法。不该关心声望。声望是其他人的看法。当你能询问尊重之人的意见时,考虑陌生人的看法有何意义?[4] 这条建议说起来容易做起来难,尤其对年轻人而言。[5]声望像强力磁铁,甚至扭曲你对喜好的认知。它让你从事你以为会喜欢而非真正喜欢的事。 比如,这导致人们尝试写小说。他们喜欢读小说,注意到小说家能获诺贝尔奖。他们想:还有什么比成为小说家更棒呢?但喜欢“成为小说家”这个想法不够;要写好小说,你必须喜欢小说创作的实际工作——喜欢编造精细的谎言。 声望只是固化的灵感。如果你把任何事做到极致,你就能让它变得有声望。许多现在有声望的事物最初并非如此。爵士乐就是个例子——几乎所有成熟艺术形式都是。所以只管做你喜欢的事,让声望自然形成。 声望对雄心勃勃者尤其危险。想让有抱负的人浪费时间跑腿?用声望当诱饵就行。这是让人们发表演讲、撰写序言、加入委员会、担任部门主管等的秘诀。或许简单规则是避开任何有声望的任务。如果它不糟糕,人们就不必赋予它声望。 同理,如果你同样欣赏两种工作,其中一种更有声望,你或许该选另一种。你对“值得钦佩”的判断总会受声望影响,所以如果两者看起来同等,你对声望较低的那个可能怀有更真实的欣赏。 另一个让人迷失的强大力量是金钱。金钱本身并不那么危险。当某件事报酬丰厚但受人轻视(如电话推销、卖淫或人身伤害诉讼)时,有抱负的人不会被诱惑。这类工作最终由“只为谋生”的人完成。(提示:避开从业者说这种话的领域。)危险的是金钱与声望结合,比如公司法或医学。对尚未认真思考自己真正喜欢什么的年轻人来说,这种相对安全、富裕且自带声望的职业极具诱惑力。 检验人们是否热爱工作的标准是:即使没有报酬,他们是否仍愿意做——甚至需要另谋生计也坚持。有多少公司律师会在免费兼职做当前工作、同时靠当服务员维生的情况下继续工作? 这一检验对选择学术领域特别有帮助,因为不同领域差异巨大。多数优秀数学家即使没有教授职位也会研究数学;而光谱另一端的院系中,教职机会才是驱动力:人们宁愿当英语教授也不愿去广告公司工作,发表论文是竞争这类职位的方式。没有数学系,数学仍会存在;但正是英语专业学生(及相应的教职)的存在,催生了成千上万关于康拉德小说中性别与身份的沉闷论文。没人会为乐趣做那种研究。 父母的建议往往偏向金钱。可以确定,想当小说生而父母希望他们当医生的本科生,比想当医生而父母希望他们当作家的多。孩子认为父母“物质”。未必。所有父母对孩子的选择总比对自己的更保守,仅仅因为他们作为父母分担风险多于分享回报。如果你8岁的儿子想爬高树,或青春期的女儿想和本地坏小子约会,你分享不到兴奋,但如果儿子摔下或女儿怀孕,你得承担后果。 自律 在这些强大力量的误导下,发现自己喜欢的工作如此困难并不奇怪。多数人在童年就被“工作=痛苦”的公理注定命运。逃脱这一点的人,几乎都被声望或金钱引诱触礁。有多少人真正发现自己热爱的工作?也许几十亿人中只有几十万。 找到热爱的工作很难;如果这么少人做到,那一定很难。所以别低估这个任务。如果还没成功,也别难过。事实上,承认自己不满足,你已经比大多数仍在否认的人领先一步。如果周围同事声称喜欢你觉得可鄙的工作,很可能他们在自欺。不一定,但很可能。 尽管做伟大工作需要.
But if we make kids work on dull stuff, it might be wise to tell them that tediousness is not the defining quality of work, and indeed that the reason they have to work on dull stuff now is so they can work on more interesting stuff later. [1] Once, when I was about 9 or 10, my father told me I could be whatever I wanted when I grew up, so long as I enjoyed it. I remember that precisely because it seemed so anomalous. It was like being told to use dry water. Whatever I thought he meant, I didn't think he meant work could _literally_ be fun — fun like playing. It took me years to grasp that. Jobs By high school, the prospect of an actual job was on the horizon. Adults would sometimes come to speak to us about their work, or we would go to see them at work. It was always understood that they enjoyed what they did. In retrospect I think one may have: the private jet pilot. But I don't think the bank manager really did. The main reason they all acted as if they enjoyed their work was presumably the upper-middle class convention that you're supposed to. It would not merely be bad for your career to say that you despised your job, but a social faux-pas. Why is it conventional to pretend to like what you do? The first sentence of this essay explains that. If you have to like something to do it well, then the most successful people will all like what they do. That's where the upper-middle class tradition comes from. Just as houses all over America are full of chairs that are, without the owners even knowing it, nth-degree imitations of chairs designed 250 years ago for French kings, conventional attitudes about work are, without the owners even knowing it, nth-degree imitations of the attitudes of people who've done great things. What a recipe for alienation.
有机路径:随着你越来越出色,逐渐增加工作中你喜欢的部分,减少不喜欢的部分。
双轨路径:做你不喜欢的工作来赚钱,以便从事你喜欢的事情。
By the time they reach an age to think about what they'd like to do, most kids have been thoroughly misled about the idea of loving one's work. School has trained them to regard work as an unpleasant duty. Having a job is said to be even more onerous than schoolwork. And yet all the adults claim to like what they do. You can't blame kids for thinking "I am not like these people; I am not suited to this world." Actually they've been told three lies: the stuff they've been taught to regard as work in school is not real work; grownup work is not (necessarily) worse than schoolwork; and many of the adults around them are lying when they say they like what they do. The most dangerous liars can be the kids' own parents. If you take a boring job to give your family a high standard of living, as so many people do, you risk infecting your kids with the idea that work is boring. [2] Maybe it would be better for kids in this one case if parents were not so unselfish. A parent who set an example of loving their work might help their kids more than an expensive house. [3] It was not till I was in college that the idea of work finally broke free from the idea of making a living. Then the important question became not how to make money, but what to work on. Ideally these coincided, but some spectacular boundary cases (like Einstein in the patent office) proved they weren't identical. The definition of work was now to make some original contribution to the world, and in the process not to starve. But after the habit of so many years my idea of work still included a large component of pain. Work still seemed to require discipline, because only hard problems yielded grand results, and hard problems couldn't literally be fun. Surely one had to force oneself to work on them. If you think something's supposed to hurt, you're less likely to notice if you're doing it wrong.
有机路径更为常见。任何工作出色的人都会自然走上这条路。年轻的建筑师不得不接手任何能接到的项目,但如果表现出色,他将逐渐能够挑选自己感兴趣的工作。这种路径的缺点是进展缓慢且充满不确定性。即便是终身教职也并非真正的自由。
That about sums up my experience of graduate school. Bounds _How much_ are you supposed to like what you do? Unless you know that, you don't know when to stop searching. And if, like most people, you underestimate it, you'll tend to stop searching too early. You'll end up doing something chosen for you by your parents, or the desire to make money, or prestige — or sheer inertia. Here's an upper bound: Do what you love doesn't mean, do what you would like to do most _this second_. Even Einstein probably had moments when he wanted to have a cup of coffee, but told himself he ought to finish what he was working on first. It used to perplex me when I read about people who liked what they did so much that there was nothing they'd rather do. There didn't seem to be any sort of work I liked _that_ much. If I had a choice of (a) spending the next hour working on something or (b) be teleported to Rome and spend the next hour wandering about, was there any sort of work I'd prefer? Honestly, no. But the fact is, almost anyone would rather, at any given moment, float about in the Carribbean, or have sex, or eat some delicious food, than work on hard problems. The rule about doing what you love assumes a certain length of time. It doesn't mean, do what will make you happiest this second, but what will make you happiest over some longer period, like a week or a month. Unproductive pleasures pall eventually. After a while you get tired of lying on the beach. If you want to stay happy, you have to do something. As a lower bound, you have to like your work more than any unproductive pleasure. You have to like what you do enough that the concept of "spare time" seems mistaken. Which is not to say you have to spend all your time working. You can only work so much before you get tired and start to screw up. Then you want to do something else — even something mindless.
双轨路径则根据你为金钱工作的时间长短分为几种变体。最极端的是"日常兼职"——用固定时间从事赚钱的工作,在业余时间追求所爱之事。另一个极端则是先通过某种工作积累足够财富,从此不再为金钱工作。
双轨路径比有机路径少见,因为它需要主动选择,同时也更危险。随着年龄增长,生活成本往往水涨船高,很容易陷入比预期更长的赚钱工作中。更糟的是,任何工作都会改变你。长期从事枯燥工作会腐蚀心智,而高薪工作往往最危险,因为它们需要你全神贯注。
But you don't regard this time as the prize and the time you spend working as the pain you endure to earn it. I put the lower bound there for practical reasons. If your work is not your favorite thing to do, you'll have terrible problems with procrastination. You'll have to force yourself to work, and when you resort to that the results are distinctly inferior. To be happy I think you have to be doing something you not only enjoy, but admire. You have to be able to say, at the end, wow, that's pretty cool. This doesn't mean you have to make something. If you learn how to hang glide, or to speak a foreign language fluently, that will be enough to make you say, for a while at least, wow, that's pretty cool. What there has to be is a test. So one thing that falls just short of the standard, I think, is reading books. Except for some books in math and the hard sciences, there's no test of how well you've read a book, and that's why merely reading books doesn't quite feel like work. You have to do something with what you've read to feel productive. I think the best test is one Gino Lee taught me: to try to do things that would make your friends say wow. But it probably wouldn't start to work properly till about age 22, because most people haven't had a big enough sample to pick friends from before then. Sirens What you should not do, I think, is worry about the opinion of anyone beyond your friends. You shouldn't worry about prestige. Prestige is the opinion of the rest of the world. When you can ask the opinions of people whose judgement you respect, what does it add to consider the opinions of people you don't even know? [4] This is easy advice to give. It's hard to follow, especially when you're young. [5] Prestige is like a powerful magnet that warps even your beliefs about what you enjoy. It causes you to work not on what you like, but what you'd like to like. That's what leads people to try to write novels, for example.
双轨路径的优势在于能帮你跨越障碍。职业版图并非平坦——不同工作间竖立着高度不等的围墙。[7]通过最大化工作中喜欢的部分,你或许能从建筑转向产品设计,但恐怕难以跨入音乐领域。若通过某工作赚钱再追求另一事业,你将拥有更大选择自由。
They like reading novels. They notice that people who write them win Nobel prizes. What could be more wonderful, they think, than to be a novelist? But liking the idea of being a novelist is not enough; you have to like the actual work of novel-writing if you're going to be good at it; you have to like making up elaborate lies. Prestige is just fossilized inspiration. If you do anything well enough, you'll _make_ it prestigious. Plenty of things we now consider prestigious were anything but at first. Jazz comes to mind — though almost any established art form would do. So just do what you like, and let prestige take care of itself. Prestige is especially dangerous to the ambitious. If you want to make ambitious people waste their time on errands, the way to do it is to bait the hook with prestige. That's the recipe for getting people to give talks, write forewords, serve on committees, be department heads, and so on. It might be a good rule simply to avoid any prestigious task. If it didn't suck, they wouldn't have had to make it prestigious. Similarly, if you admire two kinds of work equally, but one is more prestigious, you should probably choose the other. Your opinions about what's admirable are always going to be slightly influenced by prestige, so if the two seem equal to you, you probably have more genuine admiration for the less prestigious one. The other big force leading people astray is money. Money by itself is not that dangerous. When something pays well but is regarded with contempt, like telemarketing, or prostitution, or personal injury litigation, ambitious people aren't tempted by it. That kind of work ends up being done by people who are "just trying to make a living." (Tip: avoid any field whose practitioners say this.) The danger is when money is combined with prestige, as in, say, corporate law, or medicine.
该如何选择?这取决于:你对目标有多明确、对服从指令的适应度、风险承受能力,以及你追求的事业在你有生之年获得报酬的可能性。若你确信目标领域且该领域有变现可能,有机路径更为可取。但若方向不明或厌恶被指挥,在能承受风险的前提下,双轨路径或许更适合。
别过早做决定。早早确立目标的孩子看似令人钦佩,就像比其他学生更快解出数学题。他们确实有了答案,但多半是错的。
A comparatively safe and prosperous career with some automatic baseline prestige is dangerously tempting to someone young, who hasn't thought much about what they really like. The test of whether people love what they do is whether they'd do it even if they weren't paid for it — even if they had to work at another job to make a living. How many corporate lawyers would do their current work if they had to do it for free, in their spare time, and take day jobs as waiters to support themselves? This test is especially helpful in deciding between different kinds of academic work, because fields vary greatly in this respect. Most good mathematicians would work on math even if there were no jobs as math professors, whereas in the departments at the other end of the spectrum, the availability of teaching jobs is the driver: people would rather be English professors than work in ad agencies, and publishing papers is the way you compete for such jobs. Math would happen without math departments, but it is the existence of English majors, and therefore jobs teaching them, that calls into being all those thousands of dreary papers about gender and identity in the novels of Conrad. No one does that kind of thing for fun. The advice of parents will tend to err on the side of money. It seems safe to say there are more undergrads who want to be novelists and whose parents want them to be doctors than who want to be doctors and whose parents want them to be novelists. The kids think their parents are "materialistic." Not necessarily. All parents tend to be more conservative for their kids than they would for themselves, simply because, as parents, they share risks more than rewards.
我的一位非常成功的医生朋友总在抱怨工作。当医学院申请者向她求教时,她真想摇晃他们大喊"别学医!"(但她从未这样做)她为何陷入这般境地?高中时她就立志从医,凭借惊人的抱负与毅力,她克服了所有障碍——包括不幸的事实:她并不喜欢这份职业。
If your eight year old son decides to climb a tall tree, or your teenage daughter decides to date the local bad boy, you won't get a share in the excitement, but if your son falls, or your daughter gets pregnant, you'll have to deal with the consequences. Discipline With such powerful forces leading us astray, it's not surprising we find it so hard to discover what we like to work on. Most people are doomed in childhood by accepting the axiom that work = pain. Those who escape this are nearly all lured onto the rocks by prestige or money. How many even discover something they love to work on? A few hundred thousand, perhaps, out of billions. It's hard to find work you love; it must be, if so few do. So don't underestimate this task. And don't feel bad if you haven't succeeded yet. In fact, if you admit to yourself that you're discontented, you're a step ahead of most people, who are still in denial. If you're surrounded by colleagues who claim to enjoy work that you find contemptible, odds are they're lying to themselves. Not necessarily, but probably. Although doing great work takes less discipline than people think — because the way to do great work is to find something you like so much that you don't have to force yourself to do it — _finding_ work you love does usually require discipline. Some people are lucky enough to know what they want to do when they're 12, and just glide along as if they were on railroad tracks. But this seems the exception. More often people who do great things have careers with the trajectory of a ping-pong ball. They go to school to study A, drop out and get a job doing B, and then become famous for C after taking it up on the side. Sometimes jumping from one sort of work to another is a sign of energy, and sometimes it's a sign of laziness. Are you dropping out, or boldly carving a new path? You often can't tell yourself.
如今她被高中时的自己决定了人生轨迹。
年轻时我们总被灌输这样的观念:在做每个选择前都会获得充分信息。但职业选择绝非如此。当你决定人生方向时,只能在极度有限的信息下操作。即便在大学阶段,你对各类工作的认知也极为匮乏。至多通过几段实习窥见一斑——但并非所有职业都提供实习机会,而那些提供的,能教给你的也不过如同棒球童对职业棒球的了解。
Plenty of people who will later do great things seem to be disappointments early on, when they're trying to find their niche. Is there some test you can use to keep yourself honest? One is to try to do a good job at whatever you're doing, even if you don't like it. Then at least you'll know you're not using dissatisfaction as an excuse for being lazy. Perhaps more importantly, you'll get into the habit of doing things well. Another test you can use is: always produce. For example, if you have a day job you don't take seriously because you plan to be a novelist, are you producing? Are you writing pages of fiction, however bad? As long as you're producing, you'll know you're not merely using the hazy vision of the grand novel you plan to write one day as an opiate. The view of it will be obstructed by the all too palpably flawed one you're actually writing. "Always produce" is also a heuristic for finding the work you love. If you subject yourself to that constraint, it will automatically push you away from things you think you're supposed to work on, toward things you actually like. "Always produce" will discover your life's work the way water, with the aid of gravity, finds the hole in your roof. Of course, figuring out what you like to work on doesn't mean you get to work on it. That's a separate question. And if you're ambitious you have to keep them separate: you have to make a conscious effort to keep your ideas about what you want from being contaminated by what seems possible. [6] It's painful to keep them apart, because it's painful to observe the gap between them. So most people pre-emptively lower their expectations. For example, if you asked random people on the street if they'd like to be able to draw like Leonardo, you'd find most would say something like "Oh, I can't draw." This is more a statement of intention than fact; it means, I'm not going to try.
如同大多数设计工作,人生设计也需要弹性媒介。因此除非你非常明确目标,最佳策略或许是选择能兼容有机或双轨路径的职业。这可能正是我选择计算机领域的原因——你可以成为教授,可以赚大钱,也可以转型为无数其他职业。
早期选择能接触多元事务的工作也很明智,这能加速你对各类工作的认知。相反,极端版的双轨路径很危险,因为它几乎不提供关于喜好的反馈。若你为成为债券交易员奋斗十年,计划攒够钱就辞职写小说,当你真的辞职后却发现根本不喜欢写小说怎么办?
Because the fact is, if you took a random person off the street and somehow got them to work as hard as they possibly could at drawing for the next twenty years, they'd get surprisingly far. But it would require a great moral effort; it would mean staring failure in the eye every day for years. And so to protect themselves people say "I can't." Another related line you often hear is that not everyone can do work they love — that someone has to do the unpleasant jobs. Really? How do you make them? In the US the only mechanism for forcing people to do unpleasant jobs is the draft, and that hasn't been invoked for over 30 years. All we can do is encourage people to do unpleasant work, with money and prestige. If there's something people still won't do, it seems as if society just has to make do without. That's what happened with domestic servants. For millennia that was the canonical example of a job "someone had to do." And yet in the mid twentieth century servants practically disappeared in rich countries, and the rich have just had to do without. So while there may be some things someone has to do, there's a good chance anyone saying that about any particular job is mistaken. Most unpleasant jobs would either get automated or go undone if no one were willing to do them. Two Routes There's another sense of "not everyone can do work they love" that's all too true, however. One has to make a living, and it's hard to get paid for doing work you love. There are two routes to that destination:.
多数人会说我愿意面对这种烦恼——给我百万美元我自有打算。但这比想象中困难。约束赋予人生形状。当束缚消失时,大多数人反而不知所措:看看那些彩票中奖者或遗产继承者的遭遇吧。尽管人人都渴望财务自由,但最幸福的并非拥有财富的人,而是热爱工作的人。因此以迷失方向为代价换取自由的计划,未必如表面那般美好。
> The organic route: as you become more eminent, gradually to increase the parts of your job that you like at the expense of those you don't. > > The two-job route: to work at things you don't like to get money to work on things you do.
无论选择哪条路,请准备好奋斗。寻找热爱的事业极其困难,多数人都会失败。即使成功,能在三四十岁前自由追逐所爱之人也属凤毛麟角。但若你已望见目的地,抵达的可能性就会大增。若你确信自己能够热爱工作,就已进入最后冲刺;若你更清楚自己热爱何种工作,几乎就已触手可及。
[1] 当前我们的做法恰恰相反:当让孩子完成算术练习等枯燥任务时,我们不坦承其无趣性,反而用花哨装饰加以掩饰。
The organic route is more common. It happens naturally to anyone who does good work. A young architect has to take whatever work he can get, but if he does well he'll gradually be in a position to pick and choose among projects. The disadvantage of this route is that it's slow and uncertain. Even tenure is not real freedom. The two-job route has several variants depending on how long you work for money at a time. At one extreme is the "day job," where you work regular hours at one job to make money, and work on what you love in your spare time. At the other extreme you work at something till you make enough not to have to work for money again. The two-job route is less common than the organic route, because it requires a deliberate choice. It's also more dangerous. Life tends to get more expensive as you get older, so it's easy to get sucked into working longer than you expected at the money job. Worse still, anything you work on changes you. If you work too long on tedious stuff, it will rot your brain. And the best paying jobs are most dangerous, because they require your full attention. The advantage of the two-job route is that it lets you jump over obstacles. The landscape of possible jobs isn't flat; there are walls of varying heights between different kinds of work. [7] The trick of maximizing the parts of your job that you like can get you from architecture to product design, but not, probably, to music. If you make money doing one thing and then work on another, you have more freedom of choice. Which route should you take? That depends on how sure you are of what you want to do, how good you are at taking orders, how much risk you can stand, and the odds that anyone will pay (in your lifetime) for what you want to do. If you're sure of the general area you want to work in and it's something people are likely to pay you for, then you should probably take the organic route.
[2] 一位父亲告诉我相关现象:他发现自己会向家人隐瞒对工作的热爱。当他想在周六加班时,说"不得不去"比承认"宁愿工作也不愿待在家"更容易被接受。
But if you don't know what you want to work on, or don't like to take orders, you may want to take the two-job route, if you can stand the risk. Don't decide too soon. Kids who know early what they want to do seem impressive, as if they got the answer to some math question before the other kids. They have an answer, certainly, but odds are it's wrong. A friend of mine who is a quite successful doctor complains constantly about her job. When people applying to medical school ask her for advice, she wants to shake them and yell "Don't do it!" (But she never does.) How did she get into this fix? In high school she already wanted to be a doctor. And she is so ambitious and determined that she overcame every obstacle along the way — including, unfortunately, not liking it. Now she has a life chosen for her by a high-school kid. When you're young, you're given the impression that you'll get enough information to make each choice before you need to make it. But this is certainly not so with work. When you're deciding what to do, you have to operate on ridiculously incomplete information. Even in college you get little idea what various types of work are like. At best you may have a couple internships, but not all jobs offer internships, and those that do don't teach you much more about the work than being a batboy teaches you about playing baseball. In the design of lives, as in the design of most other things, you get better results if you use flexible media. So unless you're fairly sure what you want to do, your best bet may be to choose a type of work that could turn into either an organic or two-job career. That was probably part of the reason I chose computers. You can be a professor, or make a lot of money, or morph it into any number of other kinds of work. It's also wise, early on, to seek jobs that let you do many different things, so you can learn faster what various kinds of work are like.
[3] 郊区也存在类似现象。父母为给孩子安全环境搬至郊区,但郊区如此乏味做作,以至于孩子十五岁时就认定整个世界都无聊透顶。
[4] 我并非主张朋友应成为作品的唯一受众。能帮助的人越多越好,但朋友应作为你的指南针。
Conversely, the extreme version of the two-job route is dangerous because it teaches you so little about what you like. If you work hard at being a bond trader for ten years, thinking that you'll quit and write novels when you have enough money, what happens when you quit and then discover that you don't actually like writing novels? Most people would say, I'd take that problem. Give me a million dollars and I'll figure out what to do. But it's harder than it looks. Constraints give your life shape. Remove them and most people have no idea what to do: look at what happens to those who win lotteries or inherit money. Much as everyone thinks they want financial security, the happiest people are not those who have it, but those who like what they do. So a plan that promises freedom at the expense of knowing what to do with it may not be as good as it seems. Whichever route you take, expect a struggle. Finding work you love is very difficult. Most people fail. Even if you succeed, it's rare to be free to work on what you want till your thirties or forties. But if you have the destination in sight you'll be more likely to arrive at it. If you know you can love work, you're in the home stretch, and if you know what work you love, you're practically there. Notes [1] Currently we do the opposite: when we make kids do boring work, like arithmetic drills, instead of admitting frankly that it's boring, we try to disguise it with superficial decorations. [2] One father told me about a related phenomenon: he found himself concealing from his family how much he liked his work. When he wanted to go to work on a saturday, he found it easier to say that it was because he "had to" for some reason, rather than admitting he preferred to work than stay home with them. [3] Something similar happens with suburbs.
[5] 唐纳德·霍尔认为年轻诗人过度关注发表是种谬误。但你可以想象24岁诗人作品登上《纽约客》的影响——在派对相遇者眼中他成了真正的诗人。实际上他的水平并无变化,但对缺乏判断力的群体而言,官方权威的认可就是天壤之别。这比霍尔意识到的更复杂。年轻人如此看重声望,正因他们想打动的人缺乏鉴赏力。
Parents move to suburbs to raise their kids in a safe environment, but suburbs are so dull and artificial that by the time they're fifteen the kids are convinced the whole world is boring. [4] I'm not saying friends should be the only audience for your work. The more people you can help, the better. But friends should be your compass. [5] Donald Hall said young would-be poets were mistaken to be so obsessed with being published. But you can imagine what it would do for a 24 year old to get a poem published in _The New Yorker_. Now to people he meets at parties he's a real poet. Actually he's no better or worse than he was before, but to a clueless audience like that, the approval of an official authority makes all the difference. So it's a harder problem than Hall realizes. The reason the young care so much about prestige is that the people they want to impress are not very discerning. [6] This is isomorphic to the principle that you should prevent your beliefs about how things are from being contaminated by how you wish they were. Most people let them mix pretty promiscuously.
[6] 这与"防止现实认知被愿望污染"的原则同构。多数人任由二者混杂,宗教的持续流行就是最显著例证。
[7] 更准确的比喻是:职业关系图的连通性很差。
The continuing popularity of religion is the most visible index of that. [7] A more accurate metaphor would be to say that the graph of jobs is not very well connected. Thanks to Trevor Blackwell, Dan Friedman, Sarah Harlin, Jessica Livingston, Jackie McDonough, Robert Morris, Peter Norvig, David Sloo, and Aaron Swartz for reading drafts of this.
| Hebrew Translation | | | Japanese Translation | Chinese Translation | | | Russian Translation | Slovak Translation | | | Italian Translation | German Translation | | | Spanish Translation | French Translation | | | Hungarian Translation | Portuguese Translation | | | Serbian Translation | Greek Translation | | | Vietnamese Translation.
December 2005 The most impressive people I know are all terrible procrastinators. So could it be that procrastination isn't always bad? Most people who write about procrastination write about how to cure it. But this is, strictly speaking, impossible. There are an infinite number of things you could be doing. No matter what you work on, you're not working on everything else. So the question is not how to avoid procrastination, but how to procrastinate well. There are three variants of procrastination, depending on what you do instead of working on something: you could work on (a) nothing, (b) something less important, or (c) something more important. That last type, I'd argue, is good procrastination. That's the "absent-minded professor," who forgets to shave, or eat, or even perhaps look where he's going while he's thinking about some interesting question. His mind is absent from the everyday world because it's hard at work in another. That's the sense in which the most impressive people I know are all procrastinators. They're type-C procrastinators: they put off working on small stuff to work on big stuff. What's "small stuff?" Roughly, work that has zero chance of being mentioned in your obituary. It's hard to say at the time what will turn out to be your best work (will it be your magnum opus on Sumerian temple architecture, or the detective thriller you wrote under a pseudonym?), but there's a whole class of tasks you can safely rule out: shaving, doing your laundry, cleaning the house, writing thank-you notes—anything that might be called an errand. Good procrastination is avoiding errands to do real work. Good in a sense, at least. The people who want you to do the errands won't think it's good. But you probably have to annoy them if you want to get anything done. The mildest seeming people, if they want to do real work, all have a certain degree of ruthlessness when it comes to avoiding errands.
我所认识的最令人印象深刻的人都是严重的拖延症患者。那么拖延症是否并非总是坏事?
大多数关于拖延症的文章都在讨论如何治愈它。但严格来说,这是不可能的。你永远有无数件事可以做。无论你选择做什么,都意味着你放弃了其他所有事。因此问题不在于如何避免拖延,而在于如何聪明地拖延。
拖延可分为三种类型,取决于你拖延正事时在做什么:(a)什么都不做,(b)做不太重要的事,或(c)做更重要的事。我认为最后一种拖延是良性的。
Some errands, like replying to letters, go away if you ignore them (perhaps taking friends with them). Others, like mowing the lawn, or filing tax returns, only get worse if you put them off. In principle it shouldn't work to put off the second kind of errand. You're going to have to do whatever it is eventually. Why not (as past-due notices are always saying) do it now? The reason it pays to put off even those errands is that real work needs two things errands don't: big chunks of time, and the right mood. If you get inspired by some project, it can be a net win to blow off everything you were supposed to do for the next few days to work on it. Yes, those errands may cost you more time when you finally get around to them. But if you get a lot done during those few days, you will be net more productive. In fact, it may not be a difference in degree, but a difference in kind. There may be types of work that can only be done in long, uninterrupted stretches, when inspiration hits, rather than dutifully in scheduled little slices. Empirically it seems to be so. When I think of the people I know who've done great things, I don't imagine them dutifully crossing items off to-do lists. I imagine them sneaking off to work on some new idea. Conversely, forcing someone to perform errands synchronously is bound to limit their productivity. The cost of an interruption is not just the time it takes, but that it breaks the time on either side in half. You probably only have to interrupt someone a couple times a day before they're unable to work on hard problems at all. I've wondered a lot about why startups are most productive at the very beginning, when they're just a couple guys in an apartment. The main reason may be that there's no one to interrupt them yet. In theory it's good when the founders finally get enough money to hire people to do some of the work for them. But it may be better to be overworked than interrupted.
这就是所谓的"心不在焉的教授"——他因为思考某个有趣的问题而忘记刮胡子、吃饭,甚至走路时都不看路。他的心思游离于日常世界之外,因为正全神贯注于另一个领域。
我认识的那些杰出人士正是这样的C类拖延者:他们推迟处理琐事,专注于重要工作。
什么是"琐事"?大致来说,就是那些绝无可能出现在你讣告里的工作。虽然很难预判什么会成为你最重要的成就(是关于苏美尔神庙建筑的巨著,还是用笔名发表的侦探小说?),但有一整类事务可以明确排除:刮胡子、洗衣服、打扫房间、写感谢信——任何可被归类为"杂务"的事情。
Once you dilute a startup with ordinary office workers—with type-B procrastinators—the whole company starts to resonate at their frequency. They're interrupt-driven, and soon you are too. Errands are so effective at killing great projects that a lot of people use them for that purpose. Someone who has decided to write a novel, for example, will suddenly find that the house needs cleaning. People who fail to write novels don't do it by sitting in front of a blank page for days without writing anything. They do it by feeding the cat, going out to buy something they need for their apartment, meeting a friend for coffee, checking email. "I don't have time to work," they say. And they don't; they've made sure of that. (There's also a variant where one has no place to work. The cure is to visit the places where famous people worked, and see how unsuitable they were.) I've used both these excuses at one time or another. I've learned a lot of tricks for making myself work over the last 20 years, but even now I don't win consistently. Some days I get real work done. Other days are eaten up by errands. And I know it's usually my fault: I _let_ errands eat up the day, to avoid facing some hard problem. The most dangerous form of procrastination is unacknowledged type-B procrastination, because it doesn't feel like procrastination. You're "getting things done." Just the wrong things. Any advice about procrastination that concentrates on crossing things off your to-do list is not only incomplete, but positively misleading, if it doesn't consider the possibility that the to-do list is itself a form of type-B procrastination. In fact, possibility is too weak a word. Nearly everyone's is. Unless you're working on the biggest things you could be working on, you're type-B procrastinating, no matter how much you're getting done.
良性拖延就是通过逃避杂务来完成真正有价值的工作。
至少从某个角度看是良性的。那些指望你处理杂务的人可不这么认为。但要想有所成就,你恐怕不得不惹恼他们。即使最温和的人,若要从事真正有意义的工作,在回避杂务时都不得不展现出某种程度的决绝。
有些杂务(比如回信)会因你的忽视而消失(可能连同朋友一起消失)。另一些(比如修剪草坪或报税)拖延只会让情况更糟。理论上不该拖延后者——反正迟早都得做,为何不(像逾期通知总说的那样)现在就做?
In his famous essay You and Your Research (which I recommend to anyone ambitious, no matter what they're working on), Richard Hamming suggests that you ask yourself three questions: 1. What are the most important problems in your field?.
但即便这类杂务也值得拖延,因为真正的工作需要两大要素(而杂务不需要):大块时间和正确心境。如果某个项目让你灵感迸发,为此搁置接下来几天所有计划反而可能带来净收益。没错,这些被拖延的杂务最终可能耗费更多时间。但若在那几天里收获颇丰,你的整体效率仍是提升的。
这或许不仅是程度差异,更是本质区别。有些工作只能在灵感来临时通过长时间不间断投入完成,而非按部就班地分段进行。经验证明确实如此。当我想到那些做出伟大成就的人,脑海中浮现的绝非他们按待办清单逐项打勾的画面,而是他们偷偷钻研新想法的身影。
相反,强制要求某人同步处理杂务注定会限制其创造力。打断的代价不仅是所耗时间,更在于它将前后时间都切割成碎片。每天只需打断某人几次,他们就完全无法处理复杂问题了。
2. Are you working on one of them?
我常思考为何创业公司在起步阶段(仅有三两人在公寓办公时)效率最高。主要原因或许就是无人打扰。理论上当创始人获得足够资金雇人分担工作时是好事,但过度工作可能仍优于频繁打断。一旦普通职员(B类拖延者)加入创业团队,整个公司就会开始与他们同频共振——他们是被打断驱动的,很快你也会如此。
杂务对伟大项目的扼杀效果如此显著,以至于许多人将其用作逃避手段。比如决心写小说的人会突然发现房子急需打扫。那些未能完成小说的人,并非因为盯着空白稿纸数日写不出一个字,而是通过喂猫、采购日用品、与朋友喝咖啡、查邮件等方式逃避。"我没时间写作"——他们确实没有,因为这本就是他们刻意营造的结果。
(还有个变体是声称没有合适的工作场所。解决方法就是去看看那些名人当年创作的环境有多简陋。)
3. Why not?
这些借口我都用过。过去20年我学会许多督促自己工作的技巧,但至今仍无法始终如一。有些日子我能完成真正的工作,另一些日子则被杂务吞噬。而我知道这通常是我的错——我放任杂务吞噬时间,以逃避棘手问题。
最危险的拖延是未被察觉的B类拖延,因为它看起来不像拖延。你确实在"完成任务",只是那些错误的任务。
任何关于拖延的建议若只关注待办清单的完成度,不仅不完整,更是种误导——除非它考虑到待办清单本身可能就是B类拖延的形式。实际上"可能"这个词都太温和了,几乎所有人的清单都是如此。除非你正在处理你所能触及的最重要事项,否则无论完成多少任务,你都在进行B类拖延。
理查德·汉明在其著名文章《你与你的研究》(我推荐给所有怀有抱负的人,无论其研究领域)中建议我们自问三个问题:
Hamming was at Bell Labs when he started asking such questions. In principle anyone there ought to have been able to work on the most important problems in their field. Perhaps not everyone can make an equally dramatic mark on the world; I don't know; but whatever your capacities, there are projects that stretch them. So Hamming's exercise can be generalized to:
1. 你所在领域最重要的问题是什么?
2. 你正在处理其中一项吗?
汉明在贝尔实验室工作时开始提出这些问题。原则上,那里的每个人都应该能够从事其领域最重要问题的研究。也许并非每个人都能对世界产生同样惊人的影响;我不确定;但无论你的能力如何,总有一些项目能让你全力以赴。因此,汉明的思考可以推广为:
> What's the best thing you could be working on, and why aren't you?
> 你现在能做的最重要的事是什么?为什么你还没做?
绝大多数人会回避这个问题。我自己也回避它;当我看到它出现在纸上时,会立刻跳到下一句话。汉明当年四处向人提出这个问题,结果并不受欢迎。但这是每个有抱负的人都应该直面的问题。
麻烦在于,这个诱饵可能会让你钓到一条超乎想象的大鱼。要做好工作,光找到好项目是不够的。找到之后,你还得说服自己投入其中——这往往才是最困难的。问题越重大,就越难让自己动手解决。
Most people will shy away from this question. I shy away from it myself; I see it there on the page and quickly move on to the next sentence. Hamming used to go around actually asking people this, and it didn't make him popular. But it's a question anyone ambitious should face. The trouble is, you may end up hooking a very big fish with this bait. To do good work, you need to do more than find good projects. Once you've found them, you have to get yourself to work on them, and that can be hard. The bigger the problem, the harder it is to get yourself to work on it. Of course, the main reason people find it difficult to work on a particular problem is that they don't enjoy it. When you're young, especially, you often find yourself working on stuff you don't really like-- because it seems impressive, for example, or because you've been assigned to work on it. Most grad students are stuck working on big problems they don't really like, and grad school is thus synonymous with procrastination. But even when you like what you're working on, it's easier to get yourself to work on small problems than big ones. Why? Why is it so hard to work on big problems? One reason is that you may not get any reward in the forseeable future. If you work on something you can finish in a day or two, you can expect to have a nice feeling of accomplishment fairly soon. If the reward is indefinitely far in the future, it seems less real. Another reason people don't work on big projects is, ironically, fear of wasting time. What if they fail? Then all the time they spent on it will be wasted. (In fact it probably won't be, because work on hard projects almost always leads somewhere.) But the trouble with big problems can't be just that they promise no immediate reward and might cause you to waste a lot of time. If that were all, they'd be no worse than going to visit your in-laws. There's more to it than that. Big problems are _terrifying_.
当然,人们觉得某个问题难以攻克的首要原因是不喜欢。年轻时尤其如此:你常会发现自己埋头于并不真正热爱的课题——或许因为它看起来光鲜,又或许只是被分配的任务。多数研究生都困在自己不感兴趣的重大课题里,因此"读研"成了"拖延"的同义词。
但即便面对热爱的工作,解决小问题也比大问题更容易启动。为什么?为何重大课题如此令人却步?一个原因是短期内看不到回报。若能在一两天内完成某项工作,你很快就能收获成就感;而当回报遥遥无期时,这种满足感就显得虚无缥缈。
讽刺的是,另一个阻碍人们投入重大项目的理由正是害怕浪费时间。万一失败呢?所有心血不就白费了?(实际上不会白费,攻坚克难的过程总会带来收获。)
There's an almost physical pain in facing them. It's like having a vacuum cleaner hooked up to your imagination. All your initial ideas get sucked out immediately, and you don't have any more, and yet the vacuum cleaner is still sucking. You can't look a big problem too directly in the eye. You have to approach it somewhat obliquely. But you have to adjust the angle just right: you have to be facing the big problem directly enough that you catch some of the excitement radiating from it, but not so much that it paralyzes you. You can tighten the angle once you get going, just as a sailboat can sail closer to the wind once it gets underway. If you want to work on big things, you seem to have to trick yourself into doing it. You have to work on small things that could grow into big things, or work on successively larger things, or split the moral load with collaborators. It's not a sign of weakness to depend on such tricks. The very best work has been done this way. When I talk to people who've managed to make themselves work on big things, I find that all blow off errands, and all feel guilty about it. I don't think they should feel guilty. There's more to do than anyone could. So someone doing the best work they can is inevitably going to leave a lot of errands undone. It seems a mistake to feel bad about that. I think the way to "solve" the problem of procrastination is to let delight pull you instead of making a to-do list push you.
但重大课题的棘手之处不止于回报延迟和潜在的时间浪费——若仅是如此,它们和拜访岳父母也没什么区别。更深层的原因在于:大问题令人恐惧。直面它们时会产生近乎生理性的痛苦,就像有台吸尘器正对着你的想象力猛吸。所有初始灵感瞬间被抽空,而真空吸力仍在持续。
你不能直勾勾地盯着大问题看。必须采取迂回策略——但角度要精准:既要足够直面问题以捕捉其散发的吸引力,又不能过度直视导致瘫痪。一旦启动后便可缩小角度,就像帆船启航后能更贴近风向行驶。
想要攻克重大课题,似乎必须自我欺骗。要么从可能发展壮大的小项目入手,要么循序渐进处理越来越大的问题,或是与协作者分担精神负荷。依赖这类技巧并非软弱——最杰出的工作正是这样诞生的。
Work on an ambitious project you really enjoy, and sail as close to the wind as you can, and you'll leave the right things undone. Thanks to Trevor Blackwell, Jessica Livingston, and Robert Morris for reading drafts of this.
| Romanian Translation | | | Russian Translation | Hebrew Translation | | | German Translation | Portuguese Translation | | | Italian Translation | Japanese Translation | | | Spanish Translation.
November 2005 In the next few years, venture capital funds will find themselves squeezed from four directions. They're already stuck with a seller's market, because of the huge amounts they raised at the end of the Bubble and still haven't invested. This by itself is not the end of the world. In fact, it's just a more extreme version of the norm in the VC business: too much money chasing too few deals. Unfortunately, those few deals now want less and less money, because it's getting so cheap to start a startup. The four causes: open source, which makes software free; Moore's law, which makes hardware geometrically closer to free; the Web, which makes promotion free if you're good; and better languages, which make development a lot cheaper. When we started our startup in 1995, the first three were our biggest expenses. We had to pay $5000 for the Netscape Commerce Server, the only software that then supported secure http connections. We paid $3000 for a server with a 90 MHz processor and 32 meg of memory. And we paid a PR firm about $30,000 to promote our launch. Now you could get all three for nothing. You can get the software for free; people throw away computers more powerful than our first server; and if you make something good you can generate ten times as much traffic by word of mouth online than our first PR firm got through the print media. And of course another big change for the average startup is that programming languages have improved-- or rather, the median language has. At most startups ten years ago, software development meant ten programmers writing code in C++. Now the same work might be done by one or two using Python or Ruby. During the Bubble, a lot of people predicted that startups would outsource their development to India. I think a better model for the future is David Heinemeier Hansson, who outsourced his development to a more powerful language instead.
未来几年,风险投资基金将面临来自四个方向的挤压。由于泡沫末期筹集的大量资金仍未投出,他们已深陷卖方市场。这本身并非世界末日,实际上只是风投行业常态的极端版本:过多资金追逐过少项目。
更糟的是,如今这些少数项目所需的资金越来越少,因为创业成本正急剧下降。四大推手是:让软件免费的开源运动、使硬件成本呈几何级数下降的摩尔定律、让优质产品获得免费推广的互联网,以及大幅降低开发成本的先进编程语言。
1995年我们创业时,前三点是最大开支。当时必须花费5000美元购买唯一支持安全http连接的Netscape商业服务器,花费3000美元购置90MHz处理器/32MB内存的服务器,还要支付3万美元给公关公司进行推广。
如今这三项成本皆为零:软件可免费获取;被丢弃的电脑性能都远超我们当年的服务器;优秀产品通过线上口碑获得的流量,是当年纸质媒体推广效果的十倍。
此外,编程语言的进化(或者说中位数语言的提升)也带来巨变。十年前大多数创业公司需要十名C++程序员完成的工作,现在一两名使用Python或Ruby的开发者就能胜任。
A lot of well-known applications are now, like BaseCamp, written by just one programmer. And one guy is more than 10x cheaper than ten, because (a) he won't waste any time in meetings, and (b) since he's probably a founder, he can pay himself nothing. Because starting a startup is so cheap, venture capitalists now often want to give startups more money than the startups want to take. VCs like to invest several million at a time. But as one VC told me after a startup he funded would only take about half a million, "I don't know what we're going to do. Maybe we'll just have to give some of it back." Meaning give some of the fund back to the institutional investors who supplied it, because it wasn't going to be possible to invest it all. Into this already bad situation comes the third problem: Sarbanes-Oxley. Sarbanes-Oxley is a law, passed after the Bubble, that drastically increases the regulatory burden on public companies. And in addition to the cost of compliance, which is at least two million dollars a year, the law introduces frightening legal exposure for corporate officers. An experienced CFO I know said flatly: "I would not want to be CFO of a public company now." You might think that responsible corporate governance is an area where you can't go too far. But you can go too far in any law, and this remark convinced me that Sarbanes-Oxley must have. This CFO is both the smartest and the most upstanding money guy I know. If Sarbanes-Oxley deters people like him from being CFOs of public companies, that's proof enough that it's broken. Largely because of Sarbanes-Oxley, few startups go public now. For all practical purposes, succeeding now equals getting bought. Which means VCs are now in the business of finding promising little 2-3 man startups and pumping them up into companies that cost $100 million to acquire. They didn't mean to be in this business; it's just what their business has evolved into.
泡沫时期许多人预测创业公司会将开发外包至印度。但未来更可能效仿David Heinemeier Hansson的模式——将开发"外包"给更高效的语言。如今许多知名应用(如BaseCamp)仅由一名程序员开发。单人团队成本不及十人团队的十分之一,因为:(a)无需会议耗时,(b)创始人可暂不支薪。
由于创业成本骤降,风投常面临初创公司拒绝超额融资的窘境。某风投人士在被投企业仅接受50万美元后坦言:"我们可能得退回部分基金。"因为资金已无法全额投放。
雪上加霜的是第三重问题:《萨班斯-奥克斯利法案》。这部后泡沫时代出台的法律大幅增加上市公司合规成本(年耗至少200万美元),更令高管面临可怕的法律风险。一位资深CFO直言:"我现在绝不愿担任上市公司财务官。"
你或许认为公司治理严苛无妨,但任何法律都可能矫枉过正。这位我认识的最睿智正直的财务专家的话让我确信:该法案已产生负面效应。若连他都拒绝出任上市公司CFO,足证法案存在严重缺陷。
受此影响,如今初创企业鲜少上市。实际意义上的成功几乎等同于被收购。这意味着风投业已演变为:培育2-3人团队的小型初创公司,直至其估值达1亿美元。这并非风投初衷,却是行业进化结果。
Hence the fourth problem: the acquirers have begun to realize they can buy wholesale. Why should they wait for VCs to make the startups they want more expensive? Most of what the VCs add, acquirers don't want anyway. The acquirers already have brand recognition and HR departments. What they really want is the software and the developers, and that's what the startup is in the early phase: concentrated software and developers. Google, typically, seems to have been the first to figure this out. "Bring us your startups early," said Google's speaker at the Startup School. They're quite explicit about it: they like to acquire startups at just the point where they would do a Series A round. (The Series A round is the first round of real VC funding; it usually happens in the first year.) It is a brilliant strategy, and one that other big technology companies will no doubt try to duplicate. Unless they want to have still more of their lunch eaten by Google. Of course, Google has an advantage in buying startups: a lot of the people there are rich, or expect to be when their options vest. Ordinary employees find it very hard to recommend an acquisition; it's just too annoying to see a bunch of twenty year olds get rich when you're still working for salary. Even if it's the right thing for your company to do. The Solution(s) Bad as things look now, there is a way for VCs to save themselves. They need to do two things, one of which won't surprise them, and another that will seem an anathema. Let's start with the obvious one: lobby to get Sarbanes-Oxley loosened. This law was created to prevent future Enrons, not to destroy the IPO market. Since the IPO market was practically dead when it passed, few saw what bad effects it would have. But now that technology has recovered from the last bust, we can see clearly what a bottleneck Sarbanes-Oxley has become. Startups are fragile plants—seedlings, in fact.
由此引发第四重危机:收购方开始意识到可以"批发采购"。为何要等风投抬价?收购方本就不需要风投附加的大多数资源——他们已具备品牌影响力和HR部门,真正需要的是初创企业早期核心:软件与开发团队。
谷歌率先洞悉此道。其在创业学校明确表示:"尽早把初创公司带给我们",专挑本应进行A轮融资的阶段收购(A轮通常发生在首年)。这一精妙策略必将被其他科技巨头效仿——除非他们甘愿被谷歌抢占更多先机。
当然,谷歌收购初创企业具备独特优势:大量员工已实现财富自由或期权待变现。普通企业员工很难推荐收购案——看着20多岁的年轻人暴富,而自己仍在挣薪水,这种心理落差难以克服,即便收购对公司有利。
尽管形势严峻,风投仍有自救之法。他们需做两件事:其一意料之中,其二则可能被视为大逆不道。
首先是显而易见之举:游说放宽《萨班斯-奥克斯利法案》。该法案本为防范安然事件而生,而非扼杀IPO市场。由于法案通过时IPO市场已近乎停滞,其负面影响未被预见。如今科技业复苏,该法案已成为明显瓶颈。
These seedlings are worth protecting, because they grow into the trees of the economy. Much of the economy's growth is their growth. I think most politicians realize that. But they don't realize just how fragile startups are, and how easily they can become collateral damage of laws meant to fix some other problem. Still more dangerously, when you destroy startups, they make very little noise. If you step on the toes of the coal industry, you'll hear about it. But if you inadvertantly squash the startup industry, all that happens is that the founders of the next Google stay in grad school instead of starting a company. My second suggestion will seem shocking to VCs: let founders cash out partially in the Series A round. At the moment, when VCs invest in a startup, all the stock they get is newly issued and all the money goes to the company. They could buy some stock directly from the founders as well. Most VCs have an almost religious rule against doing this. They don't want founders to get a penny till the company is sold or goes public. VCs are obsessed with control, and they worry that they'll have less leverage over the founders if the founders have any money. This is a dumb plan. In fact, letting the founders sell a little stock early would generally be better for the company, because it would cause the founders' attitudes toward risk to be aligned with the VCs'. As things currently work, their attitudes toward risk tend to be diametrically opposed: the founders, who have nothing, would prefer a 100% chance of $1 million to a 20% chance of $10 million, while the VCs can afford to be "rational" and prefer the latter. Whatever they say, the reason founders are selling their companies early instead of doing Series A rounds is that they get paid up front. That first million is just worth so much more than the subsequent ones. If founders could sell a little stock early, they'd be happy to take VC money and bet the rest on a bigger outcome.
初创企业如同经济生态中的幼苗,这些终将长成参天大树的新苗值得保护——经济增长很大程度上源自它们的成长。多数政客明白这点,却未意识到初创企业的脆弱性,以及它们如何轻易成为其他领域法规的牺牲品。
更危险的是,初创企业的消亡往往悄无声息。煤炭业受挫会引发强烈抗议,但若初创生态遭破坏,唯一的变化只是"下一个谷歌"的创始人选择留在研究生院而非创业。
我的第二项建议会让风投震惊:允许创始人在A轮融资时部分套现。目前风投入资时,所有股份均为新发,资金全归公司所有。他们完全可以同步向创始人直接购买部分股权。
多数风投对此有近乎宗教般的禁忌——坚持创始人在公司出售或上市前分文不取。源于对控制权的执念,他们担心创始人获得资金后会削弱掌控力。
这是愚蠢的策略。事实上,允许创始人早期少量套现通常更有利公司发展,因其能使创始人与风投的风险偏好趋于一致。现行模式下双方风险态度完全对立:一无所有的创始人宁愿选择100%概率的100万美元,而非20%概率的1000万美元;而风投则可"理性"选择后者。
So why not let the founders have that first million, or at least half million? The VCs would get same number of shares for the money. So what if some of the money would go to the founders instead of the company? Some VCs will say this is unthinkable—that they want all their money to be put to work growing the company. But the fact is, the huge size of current VC investments is dictated by the structure of VC funds, not the needs of startups. Often as not these large investments go to work destroying the company rather than growing it. The angel investors who funded our startup let the founders sell some stock directly to them, and it was a good deal for everyone. The angels made a huge return on that investment, so they're happy. And for us founders it blunted the terrifying all-or-nothingness of a startup, which in its raw form is more a distraction than a motivator. If VCs are frightened at the idea of letting founders partially cash out, let me tell them something still more frightening: you are now competing directly with Google. Thanks to Trevor Blackwell, Sarah Harlin, Jessica Livingston, and Robert Morris for reading drafts of this.
| Romanian Translation | | | Hebrew Translation | Japanese Translation.
无论表面说辞如何,创始人选择提前出售公司的根本原因就是即时变现。第一个100万美元的价值远超后续收益。若能早期套现部分股权,创始人会更乐意接受风投资金,用剩余股权搏取更大回报。
为何不让创始人先获得这100万(或至少50万)?风投以同等金额获取的股权不变。部分资金流向创始人而非公司,又有何妨?
某些风投会坚称此举不可想象——要求所有资金必须用于公司发展。但事实是,当前风投的巨额投资规模由基金结构决定,而非初创企业真实需求。这些大额资金往往毁掉公司而非助其成长。
当年投资我们的天使投资人允许直接购买创始人部分股权,最终实现多赢:天使投资获得巨额回报,而我们创始人则缓解了创业"不成功便成仁"的极端压力——这种压力本就更像干扰而非动力。
若风投对创始人部分套现感到恐惧,请容我告知更可怕的事实:你们现在正与谷歌直接竞争。
If you liked this, you may also like _Hackers & Painters_.
Want to start a startup? Get funded by Y Combinator.
November 2005 Does "Web 2.0" mean anything? Till recently I thought it didn't, but the truth turns out to be more complicated. Originally, yes, it was meaningless. Now it seems to have acquired a meaning. And yet those who dislike the term are probably right, because if it means what I think it does, we don't need it. I first heard the phrase "Web 2.0" in the name of the Web 2.0 conference in 2004. At the time it was supposed to mean using "the web as a platform," which I took to refer to web-based applications. [1] So I was surprised at a conference this summer when Tim O'Reilly led a session intended to figure out a definition of "Web 2.0." Didn't it already mean using the web as a platform? And if it didn't already mean something, why did we need the phrase at all? Origins Tim says the phrase "Web 2.0" first arose in "a brainstorming session between O'Reilly and Medialive International." What is Medialive International? "Producers of technology tradeshows and conferences," according to their site. So presumably that's what this brainstorming session was about. O'Reilly wanted to organize a conference about the web, and they were wondering what to call it. I don't think there was any deliberate plan to suggest there was a new _version_ of the web. They just wanted to make the point that the web mattered again. It was a kind of semantic deficit spending: they knew new things were coming, and the "2.0" referred to whatever those might turn out to be. And they were right. New things were coming. But the new version number led to some awkwardness in the short term. In the process of developing the pitch for the first conference, someone must have decided they'd better take a stab at explaining what that "2.0" referred to.
想创业吗? 获得Y Combinator的资助。
2005年11月 “Web 2.0”是否有意义?直到最近我还认为它毫无意义,但真相其实更复杂。最初,这个词确实空洞无物。如今它似乎获得了某种含义。然而那些厌恶这个词的人或许是对的——因为如果它真如我所理解的那样,我们根本不需要它。 我第一次听到“Web 2.0”这个词是在2004年的Web 2.0大会上。当时它被解释为“将网络作为平台”,我认为这指的是基于网络的应用。[1] 因此在今年夏天的一场会议上,当蒂姆·奥莱利主持讨论试图定义“Web 2.0”时,我感到十分惊讶。这个词不是已经有“将网络作为平台”的含义了吗?如果它原本没有明确含义,我们又为何需要这个词? 起源 蒂姆称“Web 2.0”一词最早诞生于“奥莱利与Medialive国际公司的头脑风暴会议”。Medialive国际是什么?其官网显示为“科技行业展会与会议承办商”。因此这场头脑风暴的目的显而易见——奥莱利想举办一场关于网络的会议,而他们在斟酌会议名称。 我认为他们并非刻意暗示网络出现了新版本,只是想强调网络重新变得重要。这是一种语义上的赤字开支:他们知道新事物即将涌现,“2.0”指代的就是那些尚未成形的东西。 他们是对的。新事物确实正在到来。但这个新版本号短期内引发了尴尬。在为第一届会议筹备宣传时,肯定有人觉得必须尝试解释“2.0”的含义。“将网络作为平台”这个说法至少不会限制太多可能性。 “Web 2.0即网络作为平台”的说法在第一届会议后就鲜少被提及。到第二届会议时,“Web 2.0”似乎更多与民主相关——至少网络文章如此描述。会议本身却不太草根:2800美元的票价使得只有风投和大公司员工才能参加。 然而吊诡的是,瑞安·辛格尔在《连线》杂志的会议报道中竟提到“成群极客”。当我朋友向瑞安求证时,他本人也感到意外。他解释最初写的是“成群风投和商务人士”,后来简化为“成群”,估计又被编辑扩展为“成群极客”——毕竟Web 2.0会议本该极客云集,不是吗? 事实并非如此。现场极客不超过7人。连蒂姆·奥莱利都穿着西装,这陌生景象让我一时没认出来。我指着路过的人对奥莱利员工说:“那人好像蒂姆。”“那就是蒂姆,他买了套西装。”追上去确认后,他解释这是在泰国刚买的。 2005年的Web 2.0大会让我想起泡沫时期的互联网展会——到处都是寻找下个热门项目的风投。那种“绝不能错过”的集体焦虑如出一辙。错过什么?他们不知道。总之是即将发生的、终将被定义为Web 2.0的任何事。 我不愿仅因风投重现热情就称之为“泡沫2.0”。互联网确实举足轻重,此前的崩盘与繁荣同样属于过度反应。就像大萧条前暴涨的行业总会强劲复苏,我们走出低谷后必然迎来巨大增长。 这次不会重蹈泡沫覆辙,因为IPO市场已消失。风险投资者的驱动力是退出策略。90年代末他们投资荒谬项目,是希望转手给轻信的散户投资者,笑着去银行兑现。如今这条路已断。现在默认退出策略是被收购,而收购方比IPO投资者理性得多。最接近泡沫估值的案例是默多克5.8亿美元收购Myspace,这也不过偏离了十倍左右。 1.
Ajax “Web 2.0”是否已超越会议名称获得实质含义?尽管不愿承认,但确实如此。如今当人们说“Web 2.0”时,我能理解其指代。这个我既厌恶又理解的短语开始承载意义,正是其获得实质的最佳证明。 其含义之一无疑是Ajax(我仍难以忍受不用引号提及这个词)。本质上,“Ajax”意味着“JavaScript现在可用了”,进而说明网络应用如今能更像桌面软件运作。 此刻正有大批新软件为利用Ajax而诞生,这是自微机出现以来最大规模的应用浪潮。连微软都察觉到了,却只能通过泄露“内部”文件假装紧跟潮流,实质已无力应对。 事实上新软件浪潮发展太快,微软连引导都做不到,更别说自主开发。他们现在唯一的希望是在谷歌之前收购所有优质Ajax初创公司。但这也很困难——谷歌在收购微型初创公司上的先发优势,正如几年前它在搜索领域的优势。毕竟典范级Ajax应用Google Maps就是收购初创公司的成果。 讽刺的是,Web 2.0大会最初的描述部分正确:基于网络的应用确实是Web 2.0的重要组成部分。但我确信这是歪打正着——Ajax浪潮直到2005年初Google Maps出现、“Ajax”术语被创造后才兴起。 2. 民主 Web 2.0的第二大要素是民主。现有多个案例证明,业余爱好者在合适的系统引导下能超越专业人士。维基百科或许最著名。专家对维基百科评价中庸,但他们忽略了关键:它足够好用,而且免费——这意味着人们真的会使用。在网络上,付费内容如同不存在。即便你愿意付费阅读,也无法分享链接,它们被排除在对话之外。 民主的另一胜利是新闻判定。如今除了Reddit我几乎不看任何新闻网站。[2]我知道任何重大事件或精彩文章都会出现在那里。何必再查看特定报纸杂志的头版?Reddit像是整个网络的RSS订阅源,附带质量过滤器。类似网站还有科技新闻站Digg(人气正快速逼近Slashdot),以及掀起“标签”运动的协作书签网络del.icio.us。如果说维基百科的核心优势是“够用且免费”,这些网站则证明大众筛选显著优于人工编辑。 Web 2.0民主最惊人的例证不在观点筛选,而在内容生产。我早就注意到个人网站上的文章质量不亚于甚至优于报刊杂志。现在有独立证据:Reddit热门链接多为个人网站而非杂志文章或新闻报道。 我的撰稿经历暗示了原因:编辑。他们控制选题,并常重写稿件,结果消弭了锋芒。编辑加工产生95分位的内容——95%的文章因此提升,但5%被拉低。5%的情况下你会得到“成群极客”这种表述。 在网络上,人们可以自由发布内容。绝大多数质量不及经过编辑打磨的印刷品。但创作者基数极其庞大。当基数足够大时,未经打磨反而意味着最优秀的网络作品应超越印刷品。[3]如今网络已演化出优质内容筛选机制,整体上更胜一筹。选择胜过打磨,正如市场经济胜过计划经济。 连初创公司也不同以往。它们与泡沫时期初创公司的关系,如同博主与传统媒体的关系。泡沫时期的初创公司指由MBA领导、挥霍数百万风投资金“快速扩张”的企业;现在则指更小型、更年轻、更技术化的团队,他们只想做出伟大产品。是否寻求风投规模的资金?日后再说。即便接受投资,也要按自己的条件。 3. 善待用户 我想所有人都会同意民主和Ajax是“Web 2.0”的要素。我还看到第三点:不虐待用户。泡沫时期许多热门网站对用户相当专横——不仅是强制注册或烦人广告这类明显方式,90年代末网站的平均设计本身就是一种冒犯。大多数热门网站充斥着 intrusive branding,加载缓慢,仿佛在宣告:这是我们的地盘,不是你的。(类似笔记本电脑上贴着的英特尔和微软贴纸。) 我认为根源在于网站觉得在免费提供服务——而直到最近,免费服务的公司都可以相当专横。有时甚至演变成经济虐待狂:网站主认为给用户制造的痛苦越多,自己获益就越大。这种模式最极端的残余或许是salon.com——你可以阅读文章开头,但想继续就得先看完一段视频。 在Y Combinator,我们建议所有资助的初创公司永远不要凌驾于用户之上:除非必要,绝不要求注册;若必须注册,绝不要求邮件确认链接(事实上除非确有必要,连邮箱都不该索要);不问任何非必要问题;未经明确许可绝不发送邮件;不嵌套或强制新窗口打开链接页面;免费版功能不应过度受限;当犹豫“是否允许用户做X?”时,答案永远是“是”。宁滥勿缺。 在《如何创业》中,我建议初创公司永远不要被任何人“低空飞行”——即永远不要让其他公司提供更廉价、更便捷的解决方案。另一种低空飞行方式是赋予用户更多权力。允许用户为所欲为。如果你不这么做而竞争对手做了,你就麻烦了。 从这个角度看,iTunes具有Web 2.0特质——终于能单曲购买而非整张专辑。唱片业憎恶这个点子并竭力抵制,但用户需求显而易见,于是苹果实现了“低空飞行”。[4]不过严格来说iTunes更像是Web 1.5——真正的Web 2.0音乐模式应该是乐队直接发布无DRM限制的免费单曲。 善待用户的终极方式是免费提供竞争对手收费的服务。90年代许多人可能以为我们现在已有一套可行的微支付系统。事实却相反——最成功的网站都是那些找到新方式免费提供服务的人。Craigslist几乎摧毁了90年代的分类广告网站,OkCupid也可能对上一代交友网站做同样的事。 提供网页服务的成本极低。只要每页浏览能赚取几分之一美分,就能盈利。广告定位技术也在持续改进。十年后eBay被广告支持的freeBay(或更可能是gBay)取代,我也不会惊讶。 听起来或许奇怪,但我们告诉初创公司要尽可能少赚钱。如果你能把十亿美元规模的产业变成五千万规模的产业(且这五千万全归你),那就更好了。不过事实上,降低成本往往最终带来更多收益,就像自动化常创造更多就业机会。 终极目标是微软。当有人提供基于网络的免费Office替代品戳破这个气球时,那声响将多么惊人。[5]会是谁?谷歌?他们似乎不紧不慢。我怀疑会是两个20岁的黑客——他们天真到不会被这个想法吓倒。(能有多难呢?) 共同主线 Ajax、民主、善待用户。它们的共同点是什么?直到最近我才意识到它们存在关联,这也是我如此厌恶“Web 2.0”一词的原因之一——它似乎只是用来标签任何新事物,缺乏预测性。 但确实存在共同主线。Web 2.0意味着以网络本该有的方式使用网络。我们看到的“趋势”只是网络从泡沫时期强加的错误模型下显现出的本质。 读到Excite联合创始人乔·克劳斯的访谈时,我明白了这一点。[6].
Whatever it meant, "the web as a platform" was at least not too constricting. The story about "Web 2.0" meaning the web as a platform didn't live much past the first conference. By the second conference, what "Web 2.0" seemed to mean was something about democracy. At least, it did when people wrote about it online. The conference itself didn't seem very grassroots. It cost $2800, so the only people who could afford to go were VCs and people from big companies. And yet, oddly enough, Ryan Singel's article about the conference in _Wired News_ spoke of "throngs of geeks." When a friend of mine asked Ryan about this, it was news to him. He said he'd originally written something like "throngs of VCs and biz dev guys" but had later shortened it just to "throngs," and that this must have in turn been expanded by the editors into "throngs of geeks." After all, a Web 2.0 conference would presumably be full of geeks, right? Well, no. There were about 7. Even Tim O'Reilly was wearing a suit, a sight so alien I couldn't parse it at first. I saw him walk by and said to one of the O'Reilly people "that guy looks just like Tim." "Oh, that's Tim. He bought a suit." I ran after him, and sure enough, it was. He explained that he'd just bought it in Thailand. The 2005 Web 2.0 conference reminded me of Internet trade shows during the Bubble, full of prowling VCs looking for the next hot startup. There was that same odd atmosphere created by a large number of people determined not to miss out. Miss out on what? They didn't know. Whatever was going to happen—whatever Web 2.0 turned out to be. I wouldn't quite call it "Bubble 2.0" just because VCs are eager to invest again. The Internet is a genuinely big deal. The bust was as much an overreaction as the boom.
Excite公司其实从未真正找准商业模式。我们陷入了经典困境:每当新媒体出现时,总会先套用旧媒体的运营方式、内容模式和商业模式——这些终将失败,之后更合适的模式才会逐渐成型。
泡沫破裂后的那些年,表面看似波澜不惊。但回望过去,变革正在发生:互联网正在寻找其自然平衡点。以民主化组件为例——这并非人为制造的创新,而是网络与生俱来的特质。
It's to be expected that once we started to pull out of the bust, there would be a lot of growth in this area, just as there was in the industries that spiked the sharpest before the Depression. The reason this won't turn into a second Bubble is that the IPO market is gone. Venture investors are driven by exit strategies. The reason they were funding all those laughable startups during the late 90s was that they hoped to sell them to gullible retail investors; they hoped to be laughing all the way to the bank. Now that route is closed. Now the default exit strategy is to get bought, and acquirers are less prone to irrational exuberance than IPO investors. The closest you'll get to Bubble valuations is Rupert Murdoch paying $580 million for Myspace. That's only off by a factor of 10 or so. 1\. Ajax Does "Web 2.0" mean anything more than the name of a conference yet? I don't like to admit it, but it's starting to. When people say "Web 2.0" now, I have some idea what they mean. And the fact that I both despise the phrase and understand it is the surest proof that it has started to mean something. One ingredient of its meaning is certainly Ajax, which I can still only just bear to use without scare quotes. Basically, what "Ajax" means is "Javascript now works." And that in turn means that web-based applications can now be made to work much more like desktop ones. As you read this, a whole new generation of software is being written to take advantage of Ajax. There hasn't been such a wave of new applications since microcomputers first appeared. Even Microsoft sees it, but it's too late for them to do anything more than leak "internal" documents designed to give the impression they're on top of this new trend.
通过网络交付类桌面应用的理念同样如此。这个构想几乎与互联网同龄。但它最初被Sun公司截取,于是我们得到了Java小程序。后来Java被改造成C++的通用替代品,但在1996年,Java被包装成软件新范式——取代桌面应用的将是从服务器分发的Java"小程序"。
这个计划因自身臃肿而崩塌。微软推波助澜,但即便没有干预也注定失败。黑客群体根本不买账。当你发现公关公司鼓吹某事物是下一代开发平台时,基本可以判定它不是。若真是如此,根本不需要公关造势,因为黑客们早就会自发在其上开发应用,就像Busmonster等网站在谷歌官方表态前,就已将谷歌地图当作开发平台那样。
In fact the new generation of software is being written way too fast for Microsoft even to channel it, let alone write their own in house. Their only hope now is to buy all the best Ajax startups before Google does. And even that's going to be hard, because Google has as big a head start in buying microstartups as it did in search a few years ago. After all, Google Maps, the canonical Ajax application, was the result of a startup they bought. So ironically the original description of the Web 2.0 conference turned out to be partially right: web-based applications are a big component of Web 2.0. But I'm convinced they got this right by accident. The Ajax boom didn't start till early 2005, when Google Maps appeared and the term "Ajax" was coined. 2\. Democracy The second big element of Web 2.0 is democracy. We now have several examples to prove that amateurs can surpass professionals, when they have the right kind of system to channel their efforts. Wikipedia may be the most famous. Experts have given Wikipedia middling reviews, but they miss the critical point: it's good enough. And it's free, which means people actually read it. On the web, articles you have to pay for might as well not exist. Even if you were willing to pay to read them yourself, you can't link to them. They're not part of the conversation. Another place democracy seems to win is in deciding what counts as news. I never look at any news site now except Reddit. [2] I know if something major happens, or someone writes a particularly interesting article, it will show up there. Why bother checking the front page of any specific paper or magazine? Reddit's like an RSS feed for the whole web, with a filter for quality.
Ajax成为热门平台的证据在于:成千上万黑客已自发以其为基础进行开发。市场用脚投票。
Web 2.0三大要素还有另一个共同点。试想以下创业计划向投资人提案时的场景:
Similar sites include Digg, a technology news site that's rapidly approaching Slashdot in popularity, and del.icio.us, the collaborative bookmarking network that set off the "tagging" movement. And whereas Wikipedia's main appeal is that it's good enough and free, these sites suggest that voters do a significantly better job than human editors. The most dramatic example of Web 2.0 democracy is not in the selection of ideas, but their production. I've noticed for a while that the stuff I read on individual people's sites is as good as or better than the stuff I read in newspapers and magazines. And now I have independent evidence: the top links on Reddit are generally links to individual people's sites rather than to magazine articles or news stories. My experience of writing for magazines suggests an explanation. Editors. They control the topics you can write about, and they can generally rewrite whatever you produce. The result is to damp extremes. Editing yields 95th percentile writing—95% of articles are improved by it, but 5% are dragged down. 5% of the time you get "throngs of geeks." On the web, people can publish whatever they want. Nearly all of it falls short of the editor-damped writing in print publications. But the pool of writers is very, very large. If it's large enough, the lack of damping means the best writing online should surpass the best in print. [3] And now that the web has evolved mechanisms for selecting good stuff, the web wins net. Selection beats damping, for the same reason market economies beat centrally planned ones. Even the startups are different this time around. They are to the startups of the Bubble what bloggers are to the print media. During the Bubble, a startup meant a company headed by an MBA that was blowing through several million dollars of VC money to "get big fast" in the most literal sense.
> del.icio.us和flickr等网站允许用户用描述性标签标记内容。但他们忽略了庞大的_隐性_标签库:网页链接中的文本。这些链接实际上构成了连接网页创建者的社交网络,借助图论我们能计算出网络中各节点的信誉度。我们计划挖掘这些隐性标签,利用其背后的信誉层级体系来优化搜索。
你认为他们平均需要多久才能意识到这是在描述谷歌?
Now it means a smaller, younger, more technical group that just decided to make something great. They'll decide later if they want to raise VC-scale funding, and if they take it, they'll take it on their terms. 3\. Don't Maltreat Users I think everyone would agree that democracy and Ajax are elements of "Web 2.0." I also see a third: not to maltreat users. During the Bubble a lot of popular sites were quite high-handed with users. And not just in obvious ways, like making them register, or subjecting them to annoying ads. The very design of the average site in the late 90s was an abuse. Many of the most popular sites were loaded with obtrusive branding that made them slow to load and sent the user the message: this is our site, not yours. (There's a physical analog in the Intel and Microsoft stickers that come on some laptops.) I think the root of the problem was that sites felt they were giving something away for free, and till recently a company giving anything away for free could be pretty high-handed about it. Sometimes it reached the point of economic sadism: site owners assumed that the more pain they caused the user, the more benefit it must be to them. The most dramatic remnant of this model may be at salon.com, where you can read the beginning of a story, but to get the rest you have sit through a _movie_. At Y Combinator we advise all the startups we fund never to lord it over users. Never make users register, unless you need to in order to store something for them. If you do make users register, never make them wait for a confirmation link in an email; in fact, don't even ask for their email address unless you need it for some reason. Don't ask them any unnecessary questions. Never send them email unless they explicitly ask for it. Never frame pages you link to, or open them in new windows.
谷歌是Web 2.0三大组成部分的先驱:用Web 2.0的术语描述他们的核心业务时,听起来酷毙了——“不要虐待用户”是“不作恶”的子集,而谷歌地图当然也引爆了整个Ajax热潮。
Web 2.0意味着以互联网应有的方式使用它,而谷歌正是这么做的。这就是他们的秘密。他们顺风而行,而不是像平面媒体那样停滞不前、祈祷商业模式降临,或者像微软和唱片公司那样试图通过起诉客户逆风而上。
If you have a free version and a pay version, don't make the free version too restricted. And if you find yourself asking "should we allow users to do x?" just answer "yes" whenever you're unsure. Err on the side of generosity. In How to Start a Startup I advised startups never to let anyone fly under them, meaning never to let any other company offer a cheaper, easier solution. Another way to fly low is to give users more power. Let users do what they want. If you don't and a competitor does, you're in trouble. iTunes is Web 2.0ish in this sense. Finally you can buy individual songs instead of having to buy whole albums. The recording industry hated the idea and resisted it as long as possible. But it was obvious what users wanted, so Apple flew under the labels. [4] Though really it might be better to describe iTunes as Web 1.5. Web 2.0 applied to music would probably mean individual bands giving away DRMless songs for free. The ultimate way to be nice to users is to give them something for free that competitors charge for. During the 90s a lot of people probably thought we'd have some working system for micropayments by now. In fact things have gone in the other direction. The most successful sites are the ones that figure out new ways to give stuff away for free. Craigslist has largely destroyed the classified ad sites of the 90s, and OkCupid looks likely to do the same to the previous generation of dating sites. Serving web pages is very, very cheap. If you can make even a fraction of a cent per page view, you can make a profit. And technology for targeting ads continues to improve. I wouldn't be surprised if ten years from now eBay had been supplanted by an ad-supported freeBay (or, more likely, gBay). Odd as it might sound, we tell startups that they should try to make as little money as possible.
谷歌不会强行让事情按他们的方式发展。他们试图预测未来会发生什么,并提前站在那里等待。这是应对技术的方式——随着商业中技术成分的比重越来越大,这也是正确的商业之道。
谷歌是一家“Web 2.0”公司的事实表明,尽管这个术语有意义,但它也相当虚假。就像“对抗疗法”这个词一样,它只是意味着“把事情做对”,而当你需要一个特殊词汇来指代这一点时,这其实是个糟糕的信号。
If you can figure out a way to turn a billion dollar industry into a fifty million dollar industry, so much the better, if all fifty million go to you. Though indeed, making things cheaper often turns out to generate more money in the end, just as automating things often turns out to generate more jobs. The ultimate target is Microsoft. What a bang that balloon is going to make when someone pops it by offering a free web-based alternative to MS Office. [5] Who will? Google? They seem to be taking their time. I suspect the pin will be wielded by a couple of 20 year old hackers who are too naive to be intimidated by the idea. (How hard can it be?) The Common Thread Ajax, democracy, and not dissing users. What do they all have in common? I didn't realize they had anything in common till recently, which is one of the reasons I disliked the term "Web 2.0" so much. It seemed that it was being used as a label for whatever happened to be new—that it didn't predict anything. But there is a common thread. Web 2.0 means using the web the way it's meant to be used. The "trends" we're seeing now are simply the inherent nature of the web emerging from under the broken models that got imposed on it during the Bubble. I realized this when I read an interview with Joe Kraus, the co-founder of Excite. [6].
[1] 摘自2004年6月的会议网站:“虽然第一波互联网浪潮与浏览器紧密相关,但第二波浪潮将应用程序扩展到整个网络,并催生了新一代服务和商业机会。”如果这句话有任何意义,它似乎与基于网络的应用有关。
[2] 披露:Reddit由Y Combinator资助。尽管我最初是出于对自家团队的忠诚才开始使用它,但我现在已经彻底上瘾了。顺便一提,我也是!MSFT的投资者,不过今年早些时候已清仓。
> Excite really never got the business model right at all. We fell into the classic problem of how when a new medium comes out it adopts the practices, the content, the business models of the old medium—which fails, and then the more appropriate models get figured out.
[3] 我并不反对编辑。我花在编辑上的时间比写作还多,而且有一群挑剔的朋友会校对我写的几乎所有内容。我讨厌的是事后由他人进行的编辑。
[4] “显而易见”是轻描淡写的说法。在苹果最终把门挪到正确位置之前,用户已经翻窗多年了。
It may have seemed as if not much was happening during the years after the Bubble burst. But in retrospect, something was happening: the web was finding its natural angle of repose. The democracy component, for example—that's not an innovation, in the sense of something someone made happen. That's what the web naturally tends to produce. Ditto for the idea of delivering desktop-like applications over the web. That idea is almost as old as the web. But the first time around it was co-opted by Sun, and we got Java applets. Java has since been remade into a generic replacement for C++, but in 1996 the story about Java was that it represented a new model of software. Instead of desktop applications, you'd run Java "applets" delivered from a server. This plan collapsed under its own weight. Microsoft helped kill it, but it would have died anyway. There was no uptake among hackers. When you find PR firms promoting something as the next development platform, you can be sure it's not. If it were, you wouldn't need PR firms to tell you, because hackers would already be writing stuff on top of it, the way sites like Busmonster used Google Maps as a platform before Google even meant it to be one. The proof that Ajax is the next hot platform is that thousands of hackers have spontaneously started building things on top of it. Mikey likes it. There's another thing all three components of Web 2.0 have in common. Here's a clue. Suppose you approached investors with the following idea for a Web 2.0 startup:
[5] 提示:创建基于网络的Office替代品的方法,或许不是自己编写每个组件,而是为基于网络的应用建立协议,让它们能共享一个分布在多台服务器上的虚拟主目录。或者也可能是全部自己动手写。
[6] 引自杰西卡·利文斯顿的《创业者访谈录》。
> Sites like del.icio.us and flickr allow users to "tag" content with descriptive tokens. But there is also huge source of _implicit_ tags that they ignore: the text within web links. Moreover, these links represent a social network connecting the individuals and organizations who created the pages, and by using graph theory we can compute from this network an estimate of the reputation of each member. We plan to mine the web for these implicit tags, and use them together with the reputation hierarchy they embody to enhance web searches.
[7] 微软没有直接起诉客户,但他们似乎竭尽全力帮助SCO起诉客户。
致谢 感谢特雷弗·布莱克威尔、莎拉·哈林、杰西卡·利文斯顿、彼得·诺维格、亚伦·斯沃茨和杰夫·韦纳阅读本文草稿,并感谢欧莱礼和Adaptive Path的各位解答我的疑问。
How long do you think it would take them on average to realize that it was a description of Google? Google was a pioneer in all three components of Web 2.0: their core business sounds crushingly hip when described in Web 2.0 terms, "Don't maltreat users" is a subset of "Don't be evil," and of course Google set off the whole Ajax boom with Google Maps. Web 2.0 means using the web as it was meant to be used, and Google does. That's their secret. They're sailing with the wind, instead of sitting becalmed praying for a business model, like the print media, or trying to tack upwind by suing their customers, like Microsoft and the record labels. [7] Google doesn't try to force things to happen their way. They try to figure out what's going to happen, and arrange to be standing there when it does. That's the way to approach technology—and as business includes an ever larger technological component, the right way to do business. The fact that Google is a "Web 2.0" company shows that, while meaningful, the term is also rather bogus. It's like the word "allopathic." It just means doing things right, and it's a bad sign when you have a special word for that. Notes [1] From the conference site, June 2004: "While the first wave of the Web was closely tied to the browser, the second wave extends applications across the web and enables a new generation of services and business opportunities." To the extent this means anything, it seems to be about web-based applications. [2] Disclosure: Reddit was funded by Y Combinator. But although I started using it out of loyalty to the home team, I've become a genuine addict. While we're at it, I'm also an investor in !MSFT, having sold all my shares earlier this year. [3] I'm not against editing.
| | | 西班牙语译本
I spend more time editing than writing, and I have a group of picky friends who proofread almost everything I write. What I dislike is editing done after the fact by someone else. [4] Obvious is an understatement. Users had been climbing in through the window for years before Apple finally moved the door. [5] Hint: the way to create a web-based alternative to Office may not be to write every component yourself, but to establish a protocol for web-based apps to share a virtual home directory spread across multiple servers. Or it may be to write it all yourself. [6] In Jessica Livingston's _Founders at Work_. [7] Microsoft didn't sue their customers directly, but they seem to have done all they could to help SCO sue them. Thanks to Trevor Blackwell, Sarah Harlin, Jessica Livingston, Peter Norvig, Aaron Swartz, and Jeff Weiner for reading drafts of this, and to the guys at O'Reilly and Adaptive Path for answering my questions.
| Interview About Web 2.0 | | | Spanish Translation | German Translation | | | Russian Translation | Japanese Translation.
If you liked this, you may also like _Hackers & Painters_.
Want to start a startup? Get funded by Y Combinator.
November 2005 Venture funding works like gears. A typical startup goes through several rounds of funding, and at each round you want to take just enough money to reach the speed where you can shift into the next gear. Few startups get it quite right. Many are underfunded. A few are overfunded, which is like trying to start driving in third gear. I think it would help founders to understand funding better—not just the mechanics of it, but what investors are thinking. I was surprised recently when I realized that all the worst problems we faced in our startup were due not to competitors, but investors. Dealing with competitors was easy by comparison. I don't mean to suggest that our investors were nothing but a drag on us. They were helpful in negotiating deals, for example. I mean more that conflicts with investors are particularly nasty. Competitors punch you in the jaw, but investors have you by the balls. Apparently our situation was not unusual. And if trouble with investors is one of the biggest threats to a startup, managing them is one of the most important skills founders need to learn. Let's start by talking about the five sources of startup funding. Then we'll trace the life of a hypothetical (very fortunate) startup as it shifts gears through successive rounds. Friends and Family A lot of startups get their first funding from friends and family. Excite did, for example: after the founders graduated from college, they borrowed $15,000 from their parents to start a company. With the help of some part-time jobs they made it last 18 months. If your friends or family happen to be rich, the line blurs between them and angel investors. At Viaweb we got our first $10,000 of seed money from our friend Julian, but he was sufficiently rich that it's hard to say whether he should be classified as a friend or angel.
想创立一家初创公司? 获得 Y Combinator 的资金支持。
2005年11月 风险投资就像齿轮传动。一家典型的初创公司会经历多轮融资,每一轮你都只需筹集足够的资金,以达到能换挡进入下一阶段的速度。 很少有初创公司完全做对这一点。许多公司资金不足。少数公司资金过剩,这就像试图用三档起步开车。 我认为,如果创始人能更好地理解融资——不仅仅是它的运作机制,还包括投资者的想法——会有所帮助。最近我惊讶地意识到,我们在初创公司中面临的所有最严重的问题都不是来自竞争对手,而是来自投资者。相比之下,应对竞争对手要容易得多。 我并不是说我们的投资者对我们毫无帮助。例如,他们在谈判交易时就很有帮助。我的意思是,与投资者的冲突尤其棘手。竞争对手会打你的下巴,但投资者却捏住了你的命脉。 显然,我们的情况并不罕见。如果投资者带来的麻烦是初创公司最大的威胁之一,那么管理他们就是创始人需要学习的最重要技能之一。 让我们首先谈谈初创公司资金的五种来源。然后,我们将追踪一家假设的(非常幸运的)初创公司在多轮融资中换挡发展的历程。 亲友资助 许多初创公司的第一笔资金来自亲友。例如,Excite就是这样:创始人们大学毕业后,他们从父母那里借了1.5万美元创办公司。在一些兼职工作的帮助下,这笔钱支撑了18个月。 如果你的亲友恰好很富有,那么他们和天使投资人之间的界限就模糊了。在Viaweb,我们从朋友Julian那里获得了第一笔1万美元的种子资金,但他非常富有,很难说他应该被归类为朋友还是天使。他还是一名律师,这很棒,因为这意味着我们不必从最初那笔小额资金中支付法律费用。 从亲友那里筹集资金的优势是容易找到他们。你已经认识他们了。主要有三个劣势:你会把商业和个人生活混在一起;他们可能不像天使投资人或风险投资公司那样有广泛的人脉;而且他们可能不是合格投资者,这可能会在以后让你的生活复杂化。 美国证券交易委员会(SEC)将“合格投资者”定义为拥有超过100万美元流动资产或年收入超过20万美元的人。如果公司的股东都是合格投资者,监管负担会轻得多。一旦你从公众那里拿钱,你能做的事情就会受到更多限制。[1] 如果任何投资者不是合格投资者,初创公司在法律上的生活会更加复杂。在首次公开募股(IPO)中,这不仅可能增加费用,还可能改变结果。一位我问过的律师说:
当公司上市时,美国证券交易委员会将仔细审查该公司之前所有的股票发行行为,并要求其立即采取行动纠正任何违反证券法的行为。这些补救措施可能会延迟、阻碍甚至彻底扼杀首次公开募股。
当然,任何一家初创公司进行首次公开募股(IPO)的概率都很小。但并没有看起来那么渺茫。许多最终上市的公司起初并不被看好(谁能想到沃兹尼亚克和乔布斯业余时间创立的微型计算机公司会成为那个年代规模最大的IPO之一?)初创公司的价值很大程度上在于那微小的概率乘以巨大的回报。
He was also a lawyer, which was great, because it meant we didn't have to pay legal bills out of that initial small sum. The advantage of raising money from friends and family is that they're easy to find. You already know them. There are three main disadvantages: you mix together your business and personal life; they will probably not be as well connected as angels or venture firms; and they may not be accredited investors, which could complicate your life later. The SEC defines an "accredited investor" as someone with over a million dollars in liquid assets or an income of over $200,000 a year. The regulatory burden is much lower if a company's shareholders are all accredited investors. Once you take money from the general public you're more restricted in what you can do. [1] A startup's life will be more complicated, legally, if any of the investors aren't accredited. In an IPO, it might not merely add expense, but change the outcome. A lawyer I asked about it said:.
不过,我不向父母寻求种子资金并非因为他们不是合格投资者。创办Viaweb时,我根本不知道"合格投资者"这个概念,也没考虑过投资人脉的价值。拒绝父母投资纯粹是不想让他们蒙受损失。
咨询业务 另一种创业融资方式是找份工作。最理想的是承接能开发创业产品的咨询项目,这样就能逐步将咨询公司转型为产品公司,并让客户为研发买单。
这对有家室的人是个稳妥选择——它消除了创业的大部分风险。你永远不必经历零收入阶段。但风险与回报通常成正比:降低风险往往意味着平均回报率也会降低。这种情况下,你牺牲的是创业成功率,换取的是财务风险的降低。
> When the company goes public, the SEC will carefully study all prior issuances of stock by the company and demand that it take immediate action to cure any past violations of securities laws. Those remedial actions can delay, stall or even kill the IPO.
但咨询公司本身不也是创业吗?通常并非如此。初创公司不止要满足"新成立的小公司"这个条件。美国有数百万小企业,但只有几千家算得上初创公司。要成为初创公司,必须从事产品业务而非服务业务——这里的产品不一定是实体物品,但必须拥有可批量销售的核心产品,而非为单个客户定制服务。定制服务无法规模化。真正的初创公司应该像卖出百万张唱片的乐队,而非靠婚礼演出赚钱的乐团。
咨询业务的麻烦在于客户总爱打电话打扰。多数初创公司在破产边缘挣扎,客户干扰足以成为压垮骆驼的最后一根稻草——尤其当竞争对手能全职投入创业时。
选择咨询路线必须极度自律,要主动防止公司沦为依赖低利润业务的"杂草型"企业[2]。更危险的是,咨询业务可能成为失败的借口。就像读研一样,创业动力往往来自亲友期待。一旦你宣布创业,就等于踏上"不成功便成仁"的道路。此时除了致富你别无选择。
对失败的恐惧是强大驱动力。通常它阻碍人们行动,但当你公开雄心壮志后,这股力量就会转向有利方向。若仅满足于"先开咨询公司再转型"的温和目标,就失去了这种驱动力。
Of course the odds of any given startup doing an IPO are small. But not as small as they might seem. A lot of startups that end up going public didn't seem likely to at first. (Who could have guessed that the company Wozniak and Jobs started in their spare time selling plans for microcomputers would yield one of the biggest IPOs of the decade?) Much of the value of a startup consists of that tiny probability multiplied by the huge outcome. It wasn't because they weren't accredited investors that I didn't ask my parents for seed money, though. When we were starting Viaweb, I didn't know about the concept of an accredited investor, and didn't stop to think about the value of investors' connections. The reason I didn't take money from my parents was that I didn't want them to lose it. Consulting Another way to fund a startup is to get a job. The best sort of job is a consulting project in which you can build whatever software you wanted to sell as a startup. Then you can gradually transform yourself from a consulting company into a product company, and have your clients pay your development expenses. This is a good plan for someone with kids, because it takes most of the risk out of starting a startup. There never has to be a time when you have no revenues. Risk and reward are usually proportionate, however: you should expect a plan that cuts the risk of starting a startup also to cut the average return. In this case, you trade decreased financial risk for increased risk that your company won't succeed as a startup. But isn't the consulting company itself a startup? No, not generally. A company has to be more than small and newly founded to be a startup. There are millions of small businesses in America, but only a few thousand are startups. To be a startup, a company has to be a product business, not a service business.
咨询开发产品的优势是能验证市场需求。但如果你具备创业素质,就应该不需要这种"拐杖"。
天使投资人 天使投资人指富裕个人,这个词最初指百老汇戏剧赞助人,现在泛指个人投资者。科技领域发家的天使更理想:他们理解你的处境,还能提供人脉和建议——这些可能比资金更重要。del.icio.us融资时就接受了蒂姆·奥莱利的投资,虽然金额远低于领投的风投机构,但这位聪明且有影响力人物的加盟本身就是价值。
使用咨询收入或亲友资金时你可以随心所欲,但天使投资属于正规风险投资,这时就需要引入"退出策略"概念。年轻创业者常惊讶于投资人要求公司被收购或上市——因为投资人需要收回资本。他们只考虑具备退出可能的企业。
By which I mean not that it has to make something physical, but that it has to have one thing it sells to many people, rather than doing custom work for individual clients. Custom work doesn't scale. To be a startup you need to be the band that sells a million copies of a song, not the band that makes money by playing at individual weddings and bar mitzvahs. The trouble with consulting is that clients have an awkward habit of calling you on the phone. Most startups operate close to the margin of failure, and the distraction of having to deal with clients could be enough to put you over the edge. Especially if you have competitors who get to work full time on just being a startup. So you have to be very disciplined if you take the consulting route. You have to work actively to prevent your company growing into a "weed tree," dependent on this source of easy but low-margin money. [2] Indeed, the biggest danger of consulting may be that it gives you an excuse for failure. In a startup, as in grad school, a lot of what ends up driving you are the expectations of your family and friends. Once you start a startup and tell everyone that's what you're doing, you're now on a path labelled "get rich or bust." You now have to get rich, or you've failed. Fear of failure is an extraordinarily powerful force. Usually it prevents people from starting things, but once you publish some definite ambition, it switches directions and starts working in your favor. I think it's a pretty clever piece of jiujitsu to set this irresistible force against the slightly less immovable object of becoming rich. You won't have it driving you if your stated ambition is merely to start a consulting company that you will one day morph into a startup. An advantage of consulting, as a way to develop a product, is that you know you're making something at least one customer wants.
这并非自私行为。大型私有科技公司本就稀少,成功者最终要么被收购要么上市。员工也是时间投资者,同样渴望变现机会。当竞争对手用股票期权吸引人才时,坚持私有化的公司会失去顶尖人才。因此"退出"机制不仅是投资人要求,更是初创公司的本质属性。
另一个关键概念是估值。当某人以2万美元购买公司10%股份时,理论上公司估值20万美元。早期投资的估值实属玄学,随着公司发展才会趋近真实市值。初创公司常以低估值吸引能提供帮助的投资人——若能吸引乔布斯投资,哪怕每股只卖10美元也值得炫耀。但调整估值对待不同投资人既不现实也不合法,所以优待知名天使要趁早期估值自然较低时进行。
部分天使投资人组成联合体,任何创业活跃城市都存在这类组织。波士顿有Common Angels,湾区有Band of Angels,通过天使投资协会可找到本地团体[3]。但多数天使不隶属任何组织——越知名的天使越独立。
有些天使组织会收取项目推介费,切记永远不要接受这种要求。
But if you have what it takes to start a startup you should have sufficient vision not to need this crutch. Angel Investors _Angels_ are individual rich people. The word was first used for backers of Broadway plays, but now applies to individual investors generally. Angels who've made money in technology are preferable, for two reasons: they understand your situation, and they're a source of contacts and advice. The contacts and advice can be more important than the money. When del.icio.us took money from investors, they took money from, among others, Tim O'Reilly. The amount he put in was small compared to the VCs who led the round, but Tim is a smart and influential guy and it's good to have him on your side. You can do whatever you want with money from consulting or friends and family. With angels we're now talking about venture funding proper, so it's time to introduce the concept of _exit strategy_. Younger would-be founders are often surprised that investors expect them either to sell the company or go public. The reason is that investors need to get their capital back. They'll only consider companies that have an exit strategy—meaning companies that could get bought or go public. This is not as selfish as it sounds. There are few large, private technology companies. Those that don't fail all seem to get bought or go public. The reason is that employees are investors too—of their time—and they want just as much to be able to cash out. If your competitors offer employees stock options that might make them rich, while you make it clear you plan to stay private, your competitors will get the best people. So the principle of an "exit" is not just something forced on startups by investors, but part of what it means to be a startup. Another concept we need to introduce now is valuation. When someone buys shares in a company, that implicitly establishes a value for it.
相比机构化天使,个人天使更需警惕,因为他们更不注重声誉维护。知名风投不会太过分,否则将遭创业者抵制。而个人天使可能趁你资金链断裂时趁火打劫——我们创业时就吃过这种亏。当然个人天使也有优势:不受风投行规约束,例如允许创始人在融资轮次部分套现。我认为这种做法将更普及——多数创始人套现50万美元并不会降低创业热情。
对我们既打压又放行的天使,我的感激多于怨恨(创始人与投资人的关系就像家庭关系般复杂)。
寻找天使的最佳途径是人脉推荐。虽然可以 cold call 联系天使团体,但和风投一样,他们更重视可信人士推荐的项目。
If someone pays $20,000 for 10% of a company, the company is in theory worth $200,000. I say "in theory" because in early stage investing, valuations are voodoo. As a company gets more established, its valuation gets closer to an actual market value. But in a newly founded startup, the valuation number is just an artifact of the respective contributions of everyone involved. Startups often "pay" investors who will help the company in some way by letting them invest at low valuations. If I had a startup and Steve Jobs wanted to invest in it, I'd give him the stock for $10, just to be able to brag that he was an investor. Unfortunately, it's impractical (if not illegal) to adjust the valuation of the company up and down for each investor. Startups' valuations are supposed to rise over time. So if you're going to sell cheap stock to eminent angels, do it early, when it's natural for the company to have a low valuation. Some angel investors join together in syndicates. Any city where people start startups will have one or more of them. In Boston the biggest is the Common Angels. In the Bay Area it's the Band of Angels. You can find groups near you through the Angel Capital Association. [3] However, most angel investors don't belong to these groups. In fact, the more prominent the angel, the less likely they are to belong to a group. Some angel groups charge you money to pitch your idea to them. Needless to say, you should never do this. One of the dangers of taking investment from individual angels, rather than through an angel group or investment firm, is that they have less reputation to protect. A big-name VC firm will not screw you too outrageously, because other founders would avoid them if word got out. With individual angels you don't have this protection, as we found to our dismay in our own startup.
天使投资条款差异巨大:有些条款严苛如风投,早期项目可能只需两页协议。偶尔投资的天使往往自己也不清楚要什么条款,最终协议通常变成律师随手找的模板文件——这对初创公司很危险,因为条款可能像滚雪球般越来越复杂。有家初创公司收到70页投资协议后,因无力支付律师审阅费而放弃交易[4]。
解决方案是由创业方准备协议文件,部分天使会接受这种方式。
缺乏经验的天使常在签支票时临阵退缩。我们初期有位天使拖了数月才打款,最终在其律师(恰好也是我们的律师)反复催促下完成。投资人拖延很好理解:初创投资风险极高!对公司成立两个月的项目,多等一天就多1.7%的判断依据。但既然低价已包含风险溢价,拖延就不公平。
无论公平与否,只要允许,投资人就会拖延——连风投也不例外。融资拖延会严重分散创始人精力。应对之道就是制造竞争:当投资人知道你有其他选择时,不仅担心错失机会,更会确信你的价值。收购谈判同理——无人问津时门可罗雀,一旦出现买家就门庭若市。
In many startups' lives there comes a point when you're at the investors' mercy—when you're out of money and the only place to get more is your existing investors. When we got into such a scrape, our investors took advantage of it in a way that a name-brand VC probably wouldn't have. Angels have a corresponding advantage, however: they're also not bound by all the rules that VC firms are. And so they can, for example, allow founders to cash out partially in a funding round, by selling some of their stock directly to the investors. I think this will become more common; the average founder is eager to do it, and selling, say, half a million dollars worth of stock will not, as VCs fear, cause most founders to be any less committed to the business. The same angels who tried to screw us also let us do this, and so on balance I'm grateful rather than angry. (As in families, relations between founders and investors can be complicated.) The best way to find angel investors is through personal introductions. You could try to cold-call angel groups near you, but angels, like VCs, will pay more attention to deals recommended by someone they respect. Deal terms with angels vary a lot. There are no generally accepted standards. Sometimes angels' deal terms are as fearsome as VCs'. Other angels, particularly in the earliest stages, will invest based on a two-page agreement. Angels who only invest occasionally may not themselves know what terms they want. They just want to invest in this startup. What kind of anti-dilution protection do they want? Hell if they know. In these situations, the deal terms tend to be random: the angel asks his lawyer to create a vanilla agreement, and the terms end up being whatever the lawyer considers vanilla.
成交的关键是永远保持备选方案。听到投资或收购意向时,切记:支票到手前别当真!此时你或许想松口气回去写代码,但必须继续寻找其他投资人——哪怕只为促使当前这位行动[4]。
种子基金 种子基金像天使般进行早期小额投资,但像风投那样机构化运作。目前多数种子基金被称为"孵化器",虽然Y Combinator与其唯一共同点只是投资极早期项目。
全美约有800家孵化器,这个数字令人惊讶——我认识无数创业者,却想不起有谁从孵化器起步。孵化器定义模糊,核心特征似乎是提供办公空间("孵化"之名由此而来)。它们差异巨大:有的是政府资助的"高科技孵化器"面子工程,有的像Idealab那样内部孵化项目并雇佣团队。
Which in practice usually means, whatever existing agreement he finds lying around his firm. (Few legal documents are created from scratch.) These heaps o' boilerplate are a problem for small startups, because they tend to grow into the union of all preceding documents. I know of one startup that got from an angel investor what amounted to a five hundred pound handshake: after deciding to invest, the angel presented them with a 70-page agreement. The startup didn't have enough money to pay a lawyer even to read it, let alone negotiate the terms, so the deal fell through. One solution to this problem would be to have the startup's lawyer produce the agreement, instead of the angel's. Some angels might balk at this, but others would probably welcome it. Inexperienced angels often get cold feet when the time comes to write that big check. In our startup, one of the two angels in the initial round took months to pay us, and only did after repeated nagging from our lawyer, who was also, fortunately, his lawyer. It's obvious why investors delay. Investing in startups is risky! When a company is only two months old, every _day_ you wait gives you 1.7% more data about their trajectory. But the investor is already being compensated for that risk in the low price of the stock, so it is unfair to delay. Fair or not, investors do it if you let them. Even VCs do it. And funding delays are a big distraction for founders, who ought to be working on their company, not worrying about investors. What's a startup to do? With both investors and acquirers, the only leverage you have is competition. If an investor knows you have other investors lined up, he'll be a lot more eager to close-- and not just because he'll worry about losing the deal, but because if other investors are interested, you must be worth investing in. It's the same with acquisitions. No one wants to buy you till someone else wants to buy you, and then everyone wants to buy you.
泡沫时期的标准孵化器(多数已消亡)类似风投但干预更多,除办公场地外还强制使用其行政、法务、会计等资源。Y Combinator则相反,我们比风投干预更少,并坚持初创公司应在自己(哪怕简陋的)办公室运营。虽然讨厌被称"孵化器",但暂时没有更准确词汇——非要选的话,"脱笼器"(帮助逃离格子间)可能更贴切。
机构化运作使接触种子基金比找天使容易,直接官网发邮件即可。人脉推荐的重要性低于天使或风投。标准化流程是另一优势(天使团体也如此),种子基金通常采用统一投资条款。条款标准化不意味着优惠,但若其他被投公司发展良好,至少证明条款合理。
种子基金区别于其他投资者的特点是专注极早期投资(往往只是个创意)。虽然天使和风投偶尔也投早期,但他们同时覆盖后期阶段。
The key to closing deals is never to stop pursuing alternatives. When an investor says he wants to invest in you, or an acquirer says they want to buy you, _don't believe it till you get the check._ Your natural tendency when an investor says yes will be to relax and go back to writing code. Alas, you can't; you have to keep looking for more investors, if only to get this one to act. [4] Seed Funding Firms Seed firms are like angels in that they invest relatively small amounts at early stages, but like VCs in that they're companies that do it as a business, rather than individuals making occasional investments on the side. Till now, nearly all seed firms have been so-called "incubators," so Y Combinator gets called one too, though the only thing we have in common is that we invest in the earliest phase. According to the National Association of Business Incubators, there are about 800 incubators in the US. This is an astounding number, because I know the founders of a lot of startups, and I can't think of one that began in an incubator. What is an incubator? I'm not sure myself. The defining quality seems to be that you work in their space. That's where the name "incubator" comes from. They seem to vary a great deal in other respects. At one extreme is the sort of pork-barrel project where a town gets money from the state government to renovate a vacant building as a "high-tech incubator," as if it were merely lack of the right sort of office space that had till now prevented the town from becoming a startup hub. At the other extreme are places like Idealab, which generates ideas for new startups internally and hires people to work for them. The classic Bubble incubators, most of which now seem to be dead, were like VC firms except that they took a much bigger role in the startups they funded.
极早期投资面临独特问题,例如创业方向可能完全改变。因此种子投资者更看重团队而非创意——这适用于所有风险投资,但对种子期尤为关键。
和风投一样,种子基金的价值还包括专业建议,但建议类型不同:种子基金应指导如何对接风投(风投自己不需要),风投则应指导组建高管团队(种子期用不上)。早期问题多与技术相关,因此种子基金需具备解决技术和商业问题的双重能力。
种子基金和天使通常希望初创公司下一轮融资转向风投。不过也有从种子轮直接走向收购的案例,我认为这会越来越普遍。谷歌已积极采用这种模式,雅虎也在跟进——它们正直接与风投竞争。这是明智之举:何必等风投抬价?当公司发展到风投敢投资时,收购方早该有能力判断了——凭借技术底蕴,他们应该比风投更会甄别赢家。
风险投资基金 风投机构与种子基金同属专业公司,但管理他人资金且金额更大(平均单笔数百万美元),因此投资阶段较晚、获取难度更高、条款更苛刻。
In addition to working in their space, you were supposed to use their office staff, lawyers, accountants, and so on. Whereas incubators tend (or tended) to exert more control than VCs, Y Combinator exerts less. And we think it's better if startups operate out of their own premises, however crappy, than the offices of their investors. So it's annoying that we keep getting called an "incubator," but perhaps inevitable, because there's only one of us so far and no word yet for what we are. If we have to be called something, the obvious name would be "excubator." (The name is more excusable if one considers it as meaning that we enable people to escape cubicles.) Because seed firms are companies rather than individual people, reaching them is easier than reaching angels. Just go to their web site and send them an email. The importance of personal introductions varies, but is less than with angels or VCs. The fact that seed firms are companies also means the investment process is more standardized. (This is generally true with angel groups too.) Seed firms will probably have set deal terms they use for every startup they fund. The fact that the deal terms are standard doesn't mean they're favorable to you, but if other startups have signed the same agreements and things went well for them, it's a sign the terms are reasonable. Seed firms differ from angels and VCs in that they invest exclusively in the earliest phases—often when the company is still just an idea. Angels and even VC firms occasionally do this, but they also invest at later stages. The problems are different in the early stages. For example, in the first couple months a startup may completely redefine their idea. So seed investors usually care less about the idea than the people. This is true of all venture funding, but especially so in the seed stage. Like VCs, one of the advantages of seed firms is the advice they offer.
"风险投资家"有时被泛化使用,但风投与其他投资者有本质区别:风投采用对冲基金式的有限合伙结构。基金管理人(普通合伙人)每年收取2%管理费,并分得20%利润。
风投行业存在严重的马太效应。当投资取得谷歌式的成功时,会为机构带来声誉加成——创业者更倾向选择成功风投来背书自己。这就形成恶性循环:业绩差的风投只能接手被挑剩的项目,导致持续表现不佳。全美约千家风险基金中,仅50家可能持续盈利,新基金极难跻身此列。
某种意义上,二三线风投对创业者更划算。他们虽不及顶级机构聪明或人脉广,但求单若渴,因此能提供更优惠条件——不仅是更高估值(稀释更少股份),还包括更大控制权。我认为创始人将更容易保住CEO职位,并获难以被罢免的保障。
But because seed firms operate in an earlier phase, they need to offer different kinds of advice. For example, a seed firm should be able to give advice about how to approach VCs, which VCs obviously don't need to do; whereas VCs should be able to give advice about how to hire an "executive team," which is not an issue in the seed stage. In the earliest phases, a lot of the problems are technical, so seed firms should be able to help with technical as well as business problems. Seed firms and angel investors generally want to invest in the initial phases of a startup, then hand them off to VC firms for the next round. Occasionally startups go from seed funding direct to acquisition, however, and I expect this to become increasingly common. Google has been aggressively pursuing this route, and now Yahoo is too. Both now compete directly with VCs. And this is a smart move. Why wait for further funding rounds to jack up a startup's price? When a startup reaches the point where VCs have enough information to invest in it, the acquirer should have enough information to buy it. More information, in fact; with their technical depth, the acquirers should be better at picking winners than VCs. Venture Capital Funds VC firms are like seed firms in that they're actual companies, but they invest other people's money, and much larger amounts of it. VC investments average several million dollars. So they tend to come later in the life of a startup, are harder to get, and come with tougher terms. The word "venture capitalist" is sometimes used loosely for any venture investor, but there is a sharp difference between VCs and other investors: VC firms are organized as _funds_ , much like hedge funds or mutual funds. The fund managers, who are called "general partners," get about 2% of the fund annually as a management fee, plus about 20% of the fund's gains.
我预测最重大的变化是风投将允许创始人在融资时部分套现。传统上风投反对创始人在"流动性事件"前变现,但激烈的交易竞争将改变这愚蠢规则——随着风险投资日益成为卖方市场,这将成为自然让步。
选择不知名风投的劣势是可能被质疑"被顶级机构拒绝"。但就像大学声誉一样,公司表现才是终极评判标准。Viaweb完全依靠天使资金——我们从未觉得需要风投背书来装点门面[5]。
不知名机构的另一风险是(像个人天使那样)更不注重声誉维护。我认为多数导致风投在黑客圈恶名的伎俩都来自二三线机构——他们面临双重困境:合伙人能力较弱,却要处理更棘手项目(因为顶级风投已筛走优质标的)。
例如,二三线风投更可能假意锁定交易来拖延决策。某资深CFO曾说:"
There is a very sharp dropoff in performance among VC firms, because in the VC business both success and failure are self-perpetuating. When an investment scores spectacularly, as Google did for Kleiner and Sequoia, it generates a lot of good publicity for the VCs. And many founders prefer to take money from successful VC firms, because of the legitimacy it confers. Hence a vicious (for the losers) cycle: VC firms that have been doing badly will only get the deals the bigger fish have rejected, causing them to continue to do badly. As a result, of the thousand or so VC funds in the US now, only about 50 are likely to make money, and it is very hard for a new fund to break into this group. In a sense, the lower-tier VC firms are a bargain for founders. They may not be quite as smart or as well connected as the big-name firms, but they are much hungrier for deals. This means you should be able to get better terms from them. Better how? The most obvious is valuation: they'll take less of your company. But as well as money, there's power. I think founders will increasingly be able to stay on as CEO, and on terms that will make it fairly hard to fire them later. The most dramatic change, I predict, is that VCs will allow founders to cash out partially by selling some of their stock direct to the VC firm. VCs have traditionally resisted letting founders get anything before the ultimate "liquidity event." But they're also desperate for deals. And since I know from my own experience that the rule against buying stock from founders is a stupid one, this is a natural place for things to give as venture funding becomes more and more a seller's market. The disadvantage of taking money from less known firms is that people will assume, correctly or not, that you were turned down by the more exalted ones. But, like where you went to college, the name of your VC stops mattering once you have some performance to measure.
较好的投资方通常不会给出投资条款清单,除非他们确实有意达成交易。而二线或三线投资机构的交易破裂率要高得多——可能高达50%。
It's obvious why: the lower-tier firms' biggest fear, when chance throws them a bone, is that one of the big dogs will notice and take it away. The big dogs don't have to worry about that. Falling victim to this trick could really hurt you. As one VC told me:
> If you were talking to four VCs, told three of them that you accepted a term sheet, and then have to call them back to tell them you were just kidding, you are absolutely damaged goods.
So the more confident you are, the less you need a brand-name VC. We funded Viaweb entirely with angel money; it never occurred to us that the backing of a well known VC firm would make us seem more impressive. [5] Another danger of less known firms is that, like angels, they have less reputation to protect. I suspect it's the lower-tier firms that are responsible for most of the tricks that have given VCs such a bad reputation among hackers. They are doubly hosed: the general partners themselves are less able, and yet they have harder problems to solve, because the top VCs skim off all the best deals, leaving the lower-tier firms exactly the startups that are likely to blow up. For example, lower-tier firms are much more likely to pretend to want to do a deal with you just to lock you up while they decide if they really want to. One experienced CFO said:.
这里有一个部分解决方案:当风险投资公司向你提供投资条款清单时,询问他们最近10份条款清单中有多少最终达成了交易。这样至少能迫使他们如果想误导你就必须直接撒谎。
并非在风投机构工作的所有人都是合伙人。大多数公司还有少数初级员工,头衔类似助理或分析师。如果你接到风投公司的电话,请访问他们的网站,确认与你交谈的人是否是合伙人。很可能对方只是初级员工;这些人会在网上搜寻值得老板投资的项目。初级员工通常会表现得对你的公司非常乐观。他们并非假装;他们真心希望相信你是个优质项目,因为如果他们发现的这家公司获得投资,对他们而言将是巨大成功。不要被这种乐观误导。做决定的是合伙人,他们看问题的眼光更冷静。
由于风投涉及大额资金,附带条款往往更严格。多数条款只会在公司陷入困境时生效。例如风投通常会在协议中写明:在任何出售交易中,他们享有优先收回投资的权利。因此如果公司以低价出售,创始人可能分文不得。有些风投现在要求在任何出售中,他们必须先获得4倍投资回报,普通股持有者(也就是创始人)才能获得收益——这种霸王条款应该坚决抵制。
大额投资的另一个不同点是,创始人通常需要接受"股权兑现计划"——先交出股份,在随后4-5年间逐步赚回。风投不希望把数百万美元投给可能随时走人的创始人。从财务角度看这影响不大,但在某些情况下可能削弱创始人的话语权。如果风投实际控制了公司并解雇某位创始人,除非有特殊保护条款,否则他将失去所有未兑现的股份。这种情况下,股权兑现机制会成为约束创始人的缰绳。
> The better ones usually will not give a term sheet unless they really want to do a deal. The second or third tier firms have a much higher break rate—it could be as high as 50%.
初创企业获得大额融资后,最显著的变化是创始人将失去绝对控制权。十年前风投常要求创始人辞去CEO职务,改由他们指派的职业经理人接任。如今这种做法有所改变,部分因为互联网泡沫的教训证明,空降的职业经理人未必是优秀的CEO。
尽管创始人越来越能保住CEO职位,他们仍要让渡部分权力,因为董事会将拥有更大话语权。在种子轮阶段,董事会通常只是个形式;想和其他董事沟通时,对着隔壁房间喊一声就行。获得风投资金后情况完全不同。典型的风投交易中,董事会可能由两名风投代表、两名创始人和一名双方认可的外部人士组成。董事会拥有最高决策权,这意味着创始人现在需要说服他人而非直接发号施令。
不过这没听上去那么糟。比尔·盖茨也处于相同境地;他并不拥有微软的绝对控股权,原则上也需要说服而非命令。但他看起来仍然很有掌控力,不是吗?只要公司运转良好,董事会很少干涉。真正的风险出现在遭遇波折时,就像史蒂夫·乔布斯在苹果的经历。
It's obvious why: the lower-tier firms' biggest fear, when chance throws them a bone, is that one of the big dogs will notice and take it away. The big dogs don't have to worry about that. Falling victim to this trick could really hurt you. As one VC told me:
和天使投资人一样,风投更青睐通过熟人推荐的项目。虽然几乎所有风投基金都设有商业计划书投递渠道,但风投私下承认通过这种途径获得融资的几率近乎为零。有位风投最近告诉我,他从未见过任何初创企业以此方式成功融资。
我怀疑风投接受"盲投"商业计划书,更多是为了追踪行业趋势而非寻找项目。事实上,我强烈建议不要随机投递计划书给风投机构,他们会将此视为懒惰的表现。多花些功夫争取私人引荐。正如一位风投所说:
我并不难找。我认识很多人。如果你连联系我的办法都想不出来,又怎么能创建一家成功的公司?
> If you were talking to four VCs, told three of them that you accepted a term sheet, and then have to call them back to tell them you were just kidding, you are absolutely damaged goods.
对于初创公司创始人来说,最棘手的问题之一就是决定何时接触风投。你实际上只有一次机会,因为他们非常依赖第一印象。而且你不能先接触一部分人、把其他人留到以后,因为(a)他们会问你之前还接触过谁、什么时候接触的,(b)他们彼此之间会互通消息。如果你正在和某位风投人士洽谈,而他发现你几个月前被另一家风投拒绝过,你绝对会显得像是滞销货。
那么何时接触风投?当你能够说服他们的时候。如果创始人履历光鲜且创意不难理解,你可以很早就接触风投。而如果创始人籍籍无名且创意非常新颖,你可能需要先推出产品、证明用户喜爱它,才能让风投信服。
如果有几家风投对你感兴趣,他们有时会愿意共同分摊这笔交易。如果他们在风投圈的地位相近,这种情况更可能发生。这类交易对创始人可能是净收益,因为会有多家风投关注你的成功,而且你可以向每一家咨询关于其他家的建议。我认识的一位创始人写道:
> 双机构交易非常棒。虽然会多消耗一点股权,但能让两家机构相互制衡(还能向其中一家求证另一家是否越界)的价值无可估量。
Here's a partial solution: when a VC offers you a term sheet, ask how many of their last 10 term sheets turned into deals. This will at least force them to lie outright if they want to mislead you. Not all the people who work at VC firms are partners. Most firms also have a handful of junior employees called something like associates or analysts. If you get a call from a VC firm, go to their web site and check whether the person you talked to is a partner. Odds are it will be a junior person; they scour the web looking for startups their bosses could invest in. The junior people will tend to seem very positive about your company. They're not pretending; they _want_ to believe you're a hot prospect, because it would be a huge coup for them if their firm invested in a company they discovered. Don't be misled by this optimism. It's the partners who decide, and they view things with a colder eye. Because VCs invest large amounts, the money comes with more restrictions. Most only come into effect if the company gets into trouble. For example, VCs generally write it into the deal that in any sale, they get their investment back first. So if the company gets sold at a low price, the founders could get nothing. Some VCs now require that in any sale they get 4x their investment back before the common stock holders (that is, you) get anything, but this is an abuse that should be resisted. Another difference with large investments is that the founders are usually required to accept "vesting"—to surrender their stock and earn it back over the next 4-5 years. VCs don't want to invest millions in a company the founders could just walk away from. Financially, vesting has little effect, but in some situations it could mean founders will have less power. If VCs got de facto control of the company and fired one of the founders, he'd lose any unvested stock unless there was specific protection against this.
当你与风险投资人谈判时,请记住他们在这方面的经验远比你丰富。他们投资过数十家初创公司,而这可能是你第一次创业。但不要让他们或这种局面吓倒你。普通创始人比普通风险投资人更聪明。所以只需像处理任何复杂陌生情境时那样:谨慎推进,对任何异常之处提出质疑。
不幸的是,风险投资人常在协议中加入让创始人后期惊讶的条款,并常以"行业标准"为由辩护。标准?见鬼的标准!整个行业才诞生几十年,正在快速演变。当你在小规模运作时(Y Combinator对每笔交易使用相同条款,因为对于微小种子期投资而言,单独谈判的成本不划算),"标准"确实有用——但在风险投资级别上并不适用。这个级别的每次谈判都是独特的。
大多数成功的初创公司会从前述五种来源中获得多种资金。[6] 令人困惑的是,融资来源的名称也常被用作不同轮次的名称。解释其运作原理的最佳方式是跟踪一家假设初创公司的案例。
So vesting would in that situation force founders to toe the line. The most noticeable change when a startup takes serious funding is that the founders will no longer have complete control. Ten years ago VCs used to insist that founders step down as CEO and hand the job over to a business guy they supplied. This is less the rule now, partly because the disasters of the Bubble showed that generic business guys don't make such great CEOs. But while founders will increasingly be able to stay on as CEO, they'll have to cede some power, because the board of directors will become more powerful. In the seed stage, the board is generally a formality; if you want to talk to the other board members, you just yell into the next room. This stops with VC-scale money. In a typical VC funding deal, the board of directors might be composed of two VCs, two founders, and one outside person acceptable to both. The board will have ultimate power, which means the founders now have to convince instead of commanding. This is not as bad as it sounds, however. Bill Gates is in the same position; he doesn't have majority control of Microsoft; in principle he also has to convince instead of commanding. And yet he seems pretty commanding, doesn't he? As long as things are going smoothly, boards don't interfere much. The danger comes when there's a bump in the road, as happened to Steve Jobs at Apple. Like angels, VCs prefer to invest in deals that come to them through people they know. So while nearly all VC funds have some address you can send your business plan to, VCs privately admit the chance of getting funding by this route is near zero. One recently told me that he did not know a single startup that got funded this way. I suspect VCs accept business plans "over the transom" more as a way to keep tabs on industry trends than as a source of deals.
第一阶段:种子轮
我们的初创公司始于三个朋友的一个想法——可能是关于产品的构想,或者仅仅是"我们开公司吧"的念头。假设他们已有基本生活保障。但如果你有吃有住,很可能你本应有其他任务:学业或工作。所以若想全职创业,你的财务状况必然改变。
许多创始人声称创业时毫无计划。这其实比表面看起来少见:很多人必须宣称离职后才想到创意,否则前雇主可能主张所有权。
三位朋友决定冒险。由于多数初创公司处于竞争领域,你不仅需要全职投入,更要超负荷工作。因此部分或全部成员辞去工作或辍学(初创团队中有人可继续读研,但至少一人需全职投入公司)。
In fact, I would strongly advise against mailing your business plan randomly to VCs, because they treat this as evidence of laziness. Do the extra work of getting personal introductions. As one VC put it:.
初期他们在公寓运营公司,由于没有用户,基础设施成本极低。主要开支是公司注册(法律工作和注册费约数千美元)和创始人的生活费。
"种子投资"涵盖范围很广。对某些风投机构意味着50万美元,但对多数初创公司仅够数月生活费。假设我们的团队从朋友富有的叔叔那里获得1.5万美元,出让5%股权。此阶段只有普通股。他们预留20%作为员工期权池(但设置条款保证在被早期收购时可将未分配部分归己),三位创始人各得25%。
通过极度节俭,他们认为剩余资金能维持五个月。当资金还剩五个月时,何时需要开始下一轮融资?答案是:立刻。寻找投资者需要时间,交易达成(即使在获得承诺后)也总比你预期得更久。所以如果创始团队清楚自己在做什么,他们会立即接触天使投资人。当然他们的首要任务是开发软件1.0版本。
> I'm not hard to find. I know a lot of people. If you can't find some way to reach me, how are you going to create a successful company?
团队本希望首轮有更多资金,但轻度资金短缺教会他们重要一课:对初创公司而言,节俭就是力量。成本越低,选择余地越大——不仅在现阶段,在盈利前的每个阶段皆如此。当"烧钱率"过高时,你永远处于时间压力下,这意味着:(a) 没时间让创意进化;(b) 常被迫接受不利交易。
每家初创公司都应遵循:少花钱,快干活。
经过十周工作,三人组建成能体现产品理念的原型。这已偏离最初设想——在开发过程中他们产生了新想法。虽然只实现最终产品部分功能,但包含前所未有的创新。
他们还拟定了商业计划纲要,回答五个核心问题:做什么、用户需求、市场规模、盈利方式、竞争对手及制胜原因(最后一点不能只是"他们很烂"或"我们会拼命")。
One of the most difficult problems for startup founders is deciding when to approach VCs. You really only get one chance, because they rely heavily on first impressions. And you can't approach some and save others for later, because (a) they ask who else you've talked to and when and (b) they talk among themselves. If you're talking to one VC and he finds out that you were rejected by another several months ago, you'll definitely seem shopworn. So when do you approach VCs? When you can convince them. If the founders have impressive resumes and the idea isn't hard to understand, you could approach VCs quite early. Whereas if the founders are unknown and the idea is very novel, you might have to launch the thing and show that users loved it before VCs would be convinced. If several VCs are interested in you, they will sometimes be willing to split the deal between them. They're more likely to do this if they're close in the VC pecking order. Such deals may be a net win for founders, because you get multiple VCs interested in your success, and you can ask each for advice about the other. One founder I know wrote:
若需在演示和商业计划间分配时间,请侧重演示。软件不仅更具说服力,更是探索创意的更好方式。
第二阶段:天使轮
在开发原型期间,团队已通过人际网络寻找天使投资人。当原型完成时,他们找到几位投资人。演示后,一位天使愿意投资。此时团队寻求更多资金:希望维持一年运营并雇佣几名朋友,计划融资20万美元。
> Two-firm deals are great. It costs you a little more equity, but being able to play the two firms off each other (as well as ask one if the other is being out of line) is invaluable.
天使同意按投前估值100万美元投资。公司向天使发行价值20万美元的新股——若交易前有1000股,则新增200股。天使现持有200/1200股(16.7%),原股东股权均被稀释六分之一。交易后股权结构如下:
股东 股份 比例 天使 200 16.7% 叔叔 50 4.2% 每位创始人 250 20.8% 期权池 200 16.7% 总计 1200 100%
为简化起见,假设天使进行纯现金换股交易。现实中天使更可能采用可转换债券形式。这种贷款后期可转为股权,最终效果与购股相同,但能保护天使在后续融资中不被风投挤压。
When you do negotiate with VCs, remember that they've done this a lot more than you have. They've invested in dozens of startups, whereas this is probably the first you've founded. But don't let them or the situation intimidate you. The average founder is smarter than the average VC. So just do what you'd do in any complex, unfamiliar situation: proceed deliberately, and question anything that seems odd. It is, unfortunately, common for VCs to put terms in an agreement whose consequences surprise founders later, and also common for VCs to defend things they do by saying that they're standard in the industry. Standard, schmandard; the whole industry is only a few decades old, and rapidly evolving. The concept of "standard" is a useful one when you're operating on a small scale (Y Combinator uses identical terms for every deal because for tiny seed-stage investments it's not worth the overhead of negotiating individual deals), but it doesn't apply at the VC level. On that scale, every negotiation is unique. Most successful startups get money from more than one of the preceding five sources. [6] And, confusingly, the names of funding sources also tend to be used as the names of different rounds. The best way to explain how it all works is to follow the case of a hypothetical startup. Stage 1: Seed Round Our startup begins when a group of three friends have an idea-- either an idea for something they might build, or simply the idea "let's start a company." Presumably they already have some source of food and shelter. But if you have food and shelter, you probably also have something you're supposed to be working on: either classwork, or a job. So if you want to work full-time on a startup, your money situation will probably change too. A lot of startup founders say they started the company without any idea of what they planned to do.
谁支付法律费用?初创公司仅剩几千美元。实践中这常通过临时方案解决:可能找到愿低价服务的律师(寄望公司成功后的业务);可能某人有律师朋友;也可能天使支付律师费并代表双方(若选最后这种方式,确保律师是正式代表你而非仅提供建议,否则他只对投资者负责)。
投资20万美元的天使可能要求董事会席位,还可能要优先股——即比普通股享有额外权利的股票,通常包括重大决策否决权、防稀释条款,以及公司出售时优先收回投资的权利。
部分投资者可能要求创始人对这笔资金接受股权兑现条款,有些则不会。风投比天使更常要求兑现条款。Viaweb曾从天使处融资250万美元而未接受任何兑现条款,主要因我们当时太缺乏经验而被这个想法吓到。结果这反而有利,使我们更难被摆布。
我们的经历并不典型——这种规模的融资通常都有兑现条款。Y Combinator不要求兑现,因为:(a)我们投资金额很小;(b)我们认为没必要,致富期望足以激励创始人工作。但若投资数百万美元,我们或许会改变想法。
This is actually less common than it seems: many have to claim they thought of the idea after quitting because otherwise their former employer would own it. The three friends decide to take the leap. Since most startups are in competitive businesses, you not only want to work full-time on them, but more than full-time. So some or all of the friends quit their jobs or leave school. (Some of the founders in a startup can stay in grad school, but at least one has to make the company his full-time job.) They're going to run the company out of one of their apartments at first, and since they don't have any users they don't have to pay much for infrastructure. Their main expenses are setting up the company, which costs a couple thousand dollars in legal work and registration fees, and the living expenses of the founders. The phrase "seed investment" covers a broad range. To some VC firms it means $500,000, but to most startups it means several months' living expenses. We'll suppose our group of friends start with $15,000 from their friend's rich uncle, who they give 5% of the company in return. There's only common stock at this stage. They leave 20% as an options pool for later employees (but they set things up so that they can issue this stock to themselves if they get bought early and most is still unissued), and the three founders each get 25%. By living really cheaply they think they can make the remaining money last five months. When you have five months' runway left, how soon do you need to start looking for your next round? Answer: immediately. It takes time to find investors, and time (always more than you expect) for the deal to close even after they say yes. So if our group of founders know what they're doing they'll start sniffing around for angel investors right away. But of course their main job is to build version 1 of their software.
需补充的是,兑现条款也是创始人相互保护的方式,能解决创始人离职时的股权处理问题。因此有些创始人在公司创立时就自我施加此条款。
天使轮交易两周后完成,此时公司成立三个月。
获得首笔天使资金后的阶段,通常是初创公司最快乐的时期。很像博士后阶段:没有迫切的财务压力,责任也少。你能从事设计软件等有趣工作,还无需处理官僚事务(因为尚未雇佣行政人员)。尽情享受并高效工作——你永远不会比此刻更高效。
The friends might have liked to have more money in this first phase, but being slightly underfunded teaches them an important lesson. For a startup, cheapness is power. The lower your costs, the more options you have—not just at this stage, but at every point till you're profitable. When you have a high "burn rate," you're always under time pressure, which means (a) you don't have time for your ideas to evolve, and (b) you're often forced to take deals you don't like. Every startup's rule should be: spend little, and work fast. After ten weeks' work the three friends have built a prototype that gives one a taste of what their product will do. It's not what they originally set out to do—in the process of writing it, they had some new ideas. And it only does a fraction of what the finished product will do, but that fraction includes stuff that no one else has done before. They've also written at least a skeleton business plan, addressing the five fundamental questions: what they're going to do, why users need it, how large the market is, how they'll make money, and who the competitors are and why this company is going to beat them. (That last has to be more specific than "they suck" or "we'll work really hard.") If you have to choose between spending time on the demo or the business plan, spend most on the demo. Software is not only more convincing, but a better way to explore ideas. Stage 2: Angel Round While writing the prototype, the group has been traversing their network of friends in search of angel investors. They find some just as the prototype is demoable. When they demo it, one of the angels is willing to invest. Now the group is looking for more money: they want enough to last for a year, and maybe to hire a couple friends. So they're going to raise $200,000. The angel agrees to invest at a pre-money valuation of $1 million.
银行里有看似花不完的钱,创始人们开心地将原型转化为可发布产品。他们先以顾问形式试用一位朋友,一个月后将其转为1号员工,支付最低生活工资外加4年兑现的3%限制性股票(此后期权池降至13.7%)。[7] 他们还雇佣自由平面设计师。
给早期员工多少股份?差异极大,没有惯例。若在极早期招募到顶尖人才,给予与创始人相当的股份可能是明智之举。唯一通用规律是:员工所得股份随公司年龄呈多项式递减。换句话说,你的财富与加入时间呈幂律关系。所以若朋友邀你加入初创公司,别犹豫数月才决定。
一个月后(第四个月末),团队有了可发布产品。通过口碑传播逐渐获得用户。看到陌生用户使用系统带来大量新想法。同时他们开始对服务器状态产生强迫症般的担忧(开发VisiCalc的创始人们该多轻松啊)。
第六个月末,系统形成坚实核心功能,拥有少量但忠诚的用户。媒体开始报道,创始人们逐渐成为领域专家。
The company issues $200,000 worth of new shares to the angel; if there were 1000 shares before the deal, this means 200 additional shares. The angel now owns 200/1200 shares, or a sixth of the company, and all the previous shareholders' percentage ownership is diluted by a sixth. After the deal, the capitalization table looks like this: shareholder shares percent \------------------------------- angel 200 16.7 uncle 50 4.2 each founder 250 20.8 option pool 200 16.7 \---- ----- total 1200 100 To keep things simple, I had the angel do a straight cash for stock deal. In reality the angel might be more likely to make the investment in the form of a convertible loan. A convertible loan is a loan that can be converted into stock later; it works out the same as a stock purchase in the end, but gives the angel more protection against being squashed by VCs in future rounds. Who pays the legal bills for this deal? The startup, remember, only has a couple thousand left. In practice this turns out to be a sticky problem that usually gets solved in some improvised way. Maybe the startup can find lawyers who will do it cheaply in the hope of future work if the startup succeeds. Maybe someone has a lawyer friend. Maybe the angel pays for his lawyer to represent both sides. (Make sure if you take the latter route that the lawyer is _representing_ you rather than merely advising you, or his only duty is to the investor.) An angel investing $200k would probably expect a seat on the board of directors. He might also want preferred stock, meaning a special class of stock that has some additional rights over the common stock everyone else has. Typically these rights include vetoes over major strategic decisions, protection against being diluted in future rounds, and the right to get one's investment back first if the company is sold. Some investors might expect the founders to accept vesting for a sum this size, and others wouldn't.
假设这是家需要数百万美元投入的公司——可能需要巨额营销费用、昂贵基础设施建设或高薪销售团队。于是他们开始接触风投,通过多种渠道获得引荐:天使投资人介绍、会议结识、风投主动联系等。
第三阶段:A轮融资
带着完善的商业计划和可演示的真实系统,创始人们拜访被引荐的风投。他们觉得风投令人畏惧且难以捉摸。风投们都问同一个问题:你还接触过哪些机构?(风投像高中女生:对行业等级极度敏感,对公司的兴趣取决于其他风投的兴趣。)
VCs are more likely to require vesting than angels. At Viaweb we managed to raise $2.5 million from angels without ever accepting vesting, largely because we were so inexperienced that we were appalled at the idea. In practice this turned out to be good, because it made us harder to push around. Our experience was unusual; vesting is the norm for amounts that size. Y Combinator doesn't require vesting, because (a) we invest such small amounts, and (b) we think it's unnecessary, and that the hope of getting rich is enough motivation to keep founders at work. But maybe if we were investing millions we would think differently. I should add that vesting is also a way for founders to protect themselves against one another. It solves the problem of what to do if one of the founders quits. So some founders impose it on themselves when they start the company. The angel deal takes two weeks to close, so we are now three months into the life of the company. The point after you get the first big chunk of angel money will usually be the happiest phase in a startup's life. It's a lot like being a postdoc: you have no immediate financial worries, and few responsibilities. You get to work on juicy kinds of work, like designing software. You don't have to spend time on bureaucratic stuff, because you haven't hired any bureaucrats yet. Enjoy it while it lasts, and get as much done as you can, because you will never again be so productive. With an apparently inexhaustible sum of money sitting safely in the bank, the founders happily set to work turning their prototype into something they can release. They hire one of their friends—at first just as a consultant, so they can try him out—and then a month later as employee #1. They pay him the smallest salary he can live on, plus 3% of the company in restricted stock, vesting over four years. (So after this the option pool is down to 13.7%). [7] They also spend a little money on a freelance graphic designer.
一家风投提出投资意向并给出条款清单。这是交易条款的概要,具体细节由律师后续补充。接受条款清单意味着初创公司需在一段时间内拒绝其他风投,等待该机构完成尽职调查。尽职调查相当于背景审查,旨在发现可能摧毁公司的隐患:产品重大缺陷、未决诉讼、知识产权问题等。风投的法律财务调查非常彻底,但技术调查通常是笑话。[8]
调查未发现隐患,六周后交易完成。条款如下:按投前估值400万美元投资200万美元,即风投将持有公司33.3%股份(2/(4+2))。风投还要求交易前将期权池扩大100股。因此新股发行总量为750股,股权结构变为:
股东 股份 比例 风投 650 33.3% 天使 200 10.3% 叔叔 50 2.6% 每位创始人 250 12.8% 员工 36* 1.8% *未兑现期权池 264 13.5% 总计 1950 100%
这个图景在多个方面不现实。比如虽然比例可能如此,但风投不太可能保留原有股数。实际上所有公司文件都可能被重制,宛如公司重生。此外资金可能分多期到位,后期款项附带条件——不过这种情况在二线风投(专投更可疑项目)中比顶级机构更常见。
How much stock do you give early employees? That varies so much that there's no conventional number. If you get someone really good, really early, it might be wise to give him as much stock as the founders. The one universal rule is that the amount of stock an employee gets decreases polynomially with the age of the company. In other words, you get rich as a power of how early you were. So if some friends want you to come work for their startup, don't wait several months before deciding. A month later, at the end of month four, our group of founders have something they can launch. Gradually through word of mouth they start to get users. Seeing the system in use by real users—people they don't know—gives them lots of new ideas. Also they find they now worry obsessively about the status of their server. (How relaxing founders' lives must have been when startups wrote VisiCalc.) By the end of month six, the system is starting to have a solid core of features, and a small but devoted following. People start to write about it, and the founders are starting to feel like experts in their field. We'll assume that their startup is one that could put millions more to use. Perhaps they need to spend a lot on marketing, or build some kind of expensive infrastructure, or hire highly paid salesmen. So they decide to start talking to VCs. They get introductions to VCs from various sources: their angel investor connects them with a couple; they meet a few at conferences; a couple VCs call them after reading about them. Step 3: Series A Round Armed with their now somewhat fleshed-out business plan and able to demo a real, working system, the founders visit the VCs they have introductions to. They find the VCs intimidating and inscrutable.
当然阅读本文的风投可能对我假设的"允许天使保留10.3%股份"笑掉大牙。我承认这是童话版本——在简化过程中美化了所有人。现实中风投看待天使就像嫉妒的丈夫看待妻子的前男友。对他们而言,公司从他们投资那刻才真正存在。[9]
别误会必须先做天使轮才能接触风投。本例拉长时间线是为展示多种融资来源的运作。有些初创公司可从种子轮直接进入风投轮,我们投资的数家公司正是如此。
创始人被要求四年兑现股权,董事会重组为两名风投、两名创始人和双方认可的第五人。天使投资人愉快地让出董事会席位。
They all ask the same question: who else have you pitched to? (VCs are like high school girls: they're acutely aware of their position in the VC pecking order, and their interest in a company is a function of the interest other VCs show in it.) One of the VC firms says they want to invest and offers the founders a term sheet. A term sheet is a summary of what the deal terms will be when and if they do a deal; lawyers will fill in the details later. By accepting the term sheet, the startup agrees to turn away other VCs for some set amount of time while this firm does the "due diligence" required for the deal. Due diligence is the corporate equivalent of a background check: the purpose is to uncover any hidden bombs that might sink the company later, like serious design flaws in the product, pending lawsuits against the company, intellectual property issues, and so on. VCs' legal and financial due diligence is pretty thorough, but the technical due diligence is generally a joke. [8] The due diligence discloses no ticking bombs, and six weeks later they go ahead with the deal. Here are the terms: a $2 million investment at a pre-money valuation of $4 million, meaning that after the deal closes the VCs will own a third of the company (2 / (4 + 2)). The VCs also insist that prior to the deal the option pool be enlarged by an additional hundred shares. So the total number of new shares issued is 750, and the cap table becomes: shareholder shares percent \------------------------------- VCs 650 33.3 angel 200 10.3 uncle 50 2.6 each founder 250 12.8 employee 36 1.8 unvested option pool 264 13.5 \---- ----- total 1950 100 This picture is unrealistic in several respects. For example, while the percentages might end up looking like this, it's unlikely that the VCs would keep the existing numbers of shares. In fact, every bit of the startup's paperwork would probably be replaced, as if the company were being founded anew.
至此,我们的假设公司已无法在融资方面提供新启示——至少没有正面案例。[10] 此时公司几乎必定会招聘更多人——毕竟数百万资金需要投入使用。公司可能进行更多轮融资(估值理应更高)。如果运气爆棚可能上市(记住IPO本质也是融资轮次,无论其实际目的为何)。但这即便可能,也已超出本文范围。
任何经历过创业的人都会发现前文缺少关键要素:灾难。如果说初创公司有什么共性,那就是永远有状况发生——尤其在融资方面。
例如我们的假设公司从未在耗尽半轮资金前就获得下一轮融资。这过于理想化。许多初创公司(包括成功者)都曾濒临资金枯竭。当资金耗尽时会发生可怕后果,因为初创公司是为增长而非逆境设计的。
Also, the money might come in several tranches, the later ones subject to various conditions—though this is apparently more common in deals with lower-tier VCs (whose lot in life is to fund more dubious startups) than with the top firms. And of course any VCs reading this are probably rolling on the floor laughing at how my hypothetical VCs let the angel keep his 10.3 of the company. I admit, this is the Bambi version; in simplifying the picture, I've also made everyone nicer. In the real world, VCs regard angels the way a jealous husband feels about his wife's previous boyfriends. To them the company didn't exist before they invested in it. [9] I don't want to give the impression you have to do an angel round before going to VCs. In this example I stretched things out to show multiple sources of funding in action. Some startups could go directly from seed funding to a VC round; several of the companies we've funded have. The founders are required to vest their shares over four years, and the board is now reconstituted to consist of two VCs, two founders, and a fifth person acceptable to both. The angel investor cheerfully surrenders his board seat. At this point there is nothing new our startup can teach us about funding—or at least, nothing good. [10] The startup will almost certainly hire more people at this point; those millions must be put to work, after all. The company may do additional funding rounds, presumably at higher valuations. They may if they are extraordinarily fortunate do an IPO, which we should remember is also in principle a round of funding, regardless of its de facto purpose. But that, if not beyond the bounds of possibility, is beyond the scope of this article. Deals Fall Through Anyone who's been through a startup will find the preceding portrait to be missing something: disasters. If there's one thing all startups have in common, it's that something is always going wrong.
但前述融资案例最不现实之处在于它们全部成功了。在创业界,交易的本性不是达成,而是流产。创业者务必牢记:鸟会飞,鱼会游,交易会黄。
为什么?部分原因是你自我欺骗——你渴望交易成功于是开始相信它会成真。但即使排除这点,初创交易失败的频率仍高得吓人,远超房地产交易等。根源在于这是高风险环境。准备投资或收购的人会突发严重的"买家悔恨症"——直到临门一脚才真正意识到风险,继而恐慌。不仅新手天使如此,大公司也不例外。
所以当你作为创始人困惑为何天使投资人不回电话时,至少可以安慰自己:百倍规模的交易同样面临这种处境。
我展示的初创公司发展史如同骨架——虽然准确但不完整。要获得完整图景,还需加上所有可能的灾难。
And nowhere more than in matters of funding. For example, our hypothetical startup never spent more than half of one round before securing the next. That's more ideal than typical. Many startups—even successful ones—come close to running out of money at some point. Terrible things happen to startups when they run out of money, because they're designed for growth, not adversity. But the most unrealistic thing about the series of deals I've described is that they all closed. In the startup world, closing is not what deals do. What deals do is fall through. If you're starting a startup you would do well to remember that. Birds fly; fish swim; deals fall through. Why? Partly the reason deals seem to fall through so often is that you lie to yourself. You want the deal to close, so you start to believe it will. But even correcting for this, startup deals fall through alarmingly often—far more often than, say, deals to buy real estate. The reason is that it's such a risky environment. People about to fund or acquire a startup are prone to wicked cases of buyer's remorse. They don't really grasp the risk they're taking till the deal's about to close. And then they panic. And not just inexperienced angel investors, but big companies too. So if you're a startup founder wondering why some angel investor isn't returning your phone calls, you can at least take comfort in the thought that the same thing is happening to other deals a hundred times the size. The example of a startup's history that I've presented is like a skeleton—accurate so far as it goes, but needing to be fleshed out to be a complete picture. To get a complete picture, just add in every possible disaster. A frightening prospect? In a way. And yet also in a way encouraging. The very uncertainty of startups frightens away almost everyone. People overvalue stability—especially young people, who ironically need it least.
这前景可怕吗?某种角度是的。但从另一角度看也令人振奋。正是初创公司的不确定性吓退了绝大多数人。人们高估稳定——尤其是年轻人,讽刺的是他们最不需要稳定。因此就像任何真正勇敢的事业那样,决定创业本身就已完成一半路程。比赛当天,大多数选手根本不会现身。
[1] 这类法规旨在保护弱势群体免受欺诈;假定流动资产超百万者能自我保护。意外后果是:对冲基金等高回报投资仅对富人开放。
[2] 咨询业务是产品公司的坟墓(IBM最著名)。所以从咨询起家如同从坟墓出发,试图爬回活人世界。
And so in starting a startup, as in any really bold undertaking, merely deciding to do it gets you halfway there. On the day of the race, most of the other runners won't show up. Notes [1] The aim of such regulations is to protect widows and orphans from crooked investment schemes; people with a million dollars in liquid assets are assumed to be able to protect themselves. The unintended consequence is that the investments that generate the highest returns, like hedge funds, are available only to the rich. [2] Consulting is where product companies go to die. IBM is the most famous example. So starting as a consulting company is like starting out in the grave and trying to work your way up into the world of the living. [3] If "near you" doesn't mean the Bay Area, Boston, or Seattle, consider moving. It's not a coincidence you haven't heard of many startups from Philadelphia. [4] Investors are often compared to sheep. And they are like sheep, but that's a rational response to their situation. Sheep act the way they do for a reason. If all the other sheep head for a certain field, it's probably good grazing. And when a wolf appears, is he going to eat a sheep in the middle of the flock, or one near the edge? [5] This was partly confidence, and partly simple ignorance. We didn't know ourselves which VC firms were the impressive ones. We thought software was all that mattered. But that turned out to be the right direction to be naive in: it's much better to overestimate than underestimate the importance of making a good product. [6] I've omitted one source: government grants. I don't think these are even worth thinking about for the average startup.
[3] 若"你附近"不是湾区、波士顿或西雅图,请考虑搬家。你没听说过费城有多少初创公司并非偶然。
[4] 投资者常被比作羊群。这种比喻成立,但这是他们处境的理性反应。羊群行为有其道理:如果其他羊都奔向某片草地,那里大概水草丰美;当狼出现时,它会吃羊群中央还是边缘的羊?
[5] 这半因自信,半因无知。我们当时分不清哪些风投机构厉害,以为只要产品好就行。但这种天真恰是正确的方向:高估好产品的重要性远优于低估。
[6] 我漏掉一种来源:政府补助。对普通初创公司不值得考虑。政府设立补助计划本意良好,但申请流程必然繁琐,资金使用限制必然严苛,还不如打工赚钱。
Governments may mean well when they set up grant programs to encourage startups, but what they give with one hand they take away with the other: the process of applying is inevitably so arduous, and the restrictions on what you can do with the money so burdensome, that it would be easier to take a job to get the money. You should be especially suspicious of grants whose purpose is some kind of social engineering-- e.g. to encourage more startups to be started in Mississippi. Free money to start a startup in a place where few succeed is hardly free. Some government agencies run venture funding groups, which make investments rather than giving grants. For example, the CIA runs a venture fund called In-Q-Tel that is modelled on private sector funds and apparently generates good returns. They would probably be worth approaching—if you don't mind taking money from the CIA. [7] Options have largely been replaced with restricted stock, which amounts to the same thing. Instead of earning the right to buy stock, the employee gets the stock up front, and earns the right not to have to give it back. The shares set aside for this purpose are still called the "option pool." [8] First-rate technical people do not generally hire themselves out to do due diligence for VCs. So the most difficult part for startup founders is often responding politely to the inane questions of the "expert" they send to look you over. [9] VCs regularly wipe out angels by issuing arbitrary amounts of new stock. They seem to have a standard piece of casuistry for this situation: that the angels are no longer working to help the company, and so don't deserve to keep their stock. This of course reflects a willful misunderstanding of what investment means; like any investor, the angel is being compensated for risks he took earlier.
尤其要警惕带有社会工程目的的补助(比如鼓励在密西西比州创业)。在创业成功率低的地区拿"免费"资金代价高昂。
有些政府机构运营类似风投的基金(如中情局旗下的In-Q-Tel),可能值得接触——如果你不介意拿中情局的钱。
[7] 期权已基本被限制性股票取代。员工直接获得股票,但需逐步兑现所有权。预留股份仍称"期权池"。
By a similar logic, one could argue that the VCs should be deprived of their shares when the company goes public. [10] One new thing the company might encounter is a _down round_ , or a funding round at valuation lower than the previous round. Down rounds are bad news; it is generally the common stock holders who take the hit. Some of the most fearsome provisions in VC deal terms have to do with down rounds—like "full ratchet anti-dilution," which is as frightening as it sounds. Founders are tempted to ignore these clauses, because they think the company will either be a big success or a complete bust. VCs know otherwise: it's not uncommon for startups to have moments of adversity before they ultimately succeed. So it's worth negotiating anti-dilution provisions, even though you don't think you need to, and VCs will try to make you feel that you're being gratuitously troublesome. Thanks to Sam Altman, Hutch Fishman, Steve Huffman, Jessica Livingston, Sesha Pratap, Stan Reiss, Andy Singleton, Zak Stone, and Aaron Swartz for reading drafts of this.
[8] 一流技术人才通常不愿为风投做尽职调查。所以创始人最难的常是礼貌回应"专家"的白痴问题。
[9] 风投常通过任意增发新股抹杀天使权益。他们对此有标准说辞:天使不再为公司出力,故不应保留股份。这故意曲解了投资本质——天使本就是在为早期风险获取补偿。按此逻辑,公司上市时风投也该被剥夺股份。
[10] 公司可能遭遇"估值降低轮次"(即估值低于前轮的融资)。这类轮次通常由普通股股东承担损失。风投条款中最可怕的条款常涉及此类情况(如"完全棘轮反稀释条款")。
创始人易忽视这些条款,认为公司要么大成要么完蛋。但风投知道:初创公司在最终成功前常经历逆境。因此值得谈判反稀释条款——尽管你觉得没必要,尽管风投会让你觉得自己在无理取闹。
Want to start a startup? Get funded by Y Combinator.
October 2005 _(This essay is derived from a talk at the 2005Startup School.)_ How do you get good ideas for startups? That's probably the number one question people ask me. I'd like to reply with another question: why do people think it's hard to come up with ideas for startups? That might seem a stupid thing to ask. Why do they _think_ it's hard? If people can't do it, then it _is_ hard, at least for them. Right? Well, maybe not. What people usually say is not that they can't think of ideas, but that they don't have any. That's not quite the same thing. It could be the reason they don't have any is that they haven't tried to generate them. I think this is often the case. I think people believe that coming up with ideas for startups is very hard-- that it _must_ be very hard-- and so they don't try do to it. They assume ideas are like miracles: they either pop into your head or they don't. I also have a theory about why people think this. They overvalue ideas. They think creating a startup is just a matter of implementing some fabulous initial idea. And since a successful startup is worth millions of dollars, a good idea is therefore a million dollar idea. If coming up with an idea for a startup equals coming up with a million dollar idea, then of course it's going to seem hard. Too hard to bother trying. Our instincts tell us something so valuable would not be just lying around for anyone to discover. Actually, startup ideas are not million dollar ideas, and here's an experiment you can try to prove it: just try to sell one. Nothing evolves faster than markets. The fact that there's no market for startup ideas suggests there's no demand.
Which means, in the narrow sense of the word, that startup ideas are worthless. Questions The fact is, most startups end up nothing like the initial idea. It would be closer to the truth to say the main value of your initial idea is that, in the process of discovering it's broken, you'll come up with your real idea. The initial idea is just a starting point-- not a blueprint, but a question. It might help if they were expressed that way. Instead of saying that your idea is to make a collaborative, web-based spreadsheet, say: could one make a collaborative, web-based spreadsheet? A few grammatical tweaks, and a woefully incomplete idea becomes a promising question to explore. There's a real difference, because an assertion provokes objections in a way a question doesn't. If you say: I'm going to build a web-based spreadsheet, then critics-- the most dangerous of which are in your own head-- will immediately reply that you'd be competing with Microsoft, that you couldn't give people the kind of UI they expect, that users wouldn't want to have their data on your servers, and so on. A question doesn't seem so challenging. It becomes: let's try making a web-based spreadsheet and see how far we get. And everyone knows that if you tried this you'd be able to make _something_ useful. Maybe what you'd end up with wouldn't even be a spreadsheet. Maybe it would be some kind of new spreadsheet-like collaboration tool that doesn't even have a name yet. You wouldn't have thought of something like that except by implementing your way toward it. Treating a startup idea as a question changes what you're looking for. If an idea is a blueprint, it has to be right. But if it's a question, it can be wrong, so long as it's wrong in a way that leads to more ideas. One valuable way for an idea to be wrong is to be only a partial solution.
When someone's working on a problem that seems too big, I always ask: is there some way to bite off some subset of the problem, then gradually expand from there? That will generally work unless you get trapped on a local maximum, like 1980s-style AI, or C. Upwind So far, we've reduced the problem from thinking of a million dollar idea to thinking of a mistaken question. That doesn't seem so hard, does it? To generate such questions you need two things: to be familiar with promising new technologies, and to have the right kind of friends. New technologies are the ingredients startup ideas are made of, and conversations with friends are the kitchen they're cooked in. Universities have both, and that's why so many startups grow out of them. They're filled with new technologies, because they're trying to produce research, and only things that are new count as research. And they're full of exactly the right kind of people to have ideas with: the other students, who will be not only smart but elastic-minded to a fault. The opposite extreme would be a well-paying but boring job at a big company. Big companies are biased against new technologies, and the people you'd meet there would be wrong too. In an essay I wrote for high school students, I said a good rule of thumb was to stay upwind-- to work on things that maximize your future options. The principle applies for adults too, though perhaps it has to be modified to: stay upwind for as long as you can, then cash in the potential energy you've accumulated when you need to pay for kids. I don't think people consciously realize this, but one reason downwind jobs like churning out Java for a bank pay so well is precisely that they are downwind. The market price for that kind of work is higher because it gives you fewer options for the future.
A job that lets you work on exciting new stuff will tend to pay less, because part of the compensation is in the form of the new skills you'll learn. Grad school is the other end of the spectrum from a coding job at a big company: the pay's low but you spend most of your time working on new stuff. And of course, it's called "school," which makes that clear to everyone, though in fact all jobs are some percentage school. The right environment for having startup ideas need not be a university per se. It just has to be a situation with a large percentage of school. It's obvious why you want exposure to new technology, but why do you need other people? Can't you just think of new ideas yourself? The empirical answer is: no. Even Einstein needed people to bounce ideas off. Ideas get developed in the process of explaining them to the right kind of person. You need that resistance, just as a carver needs the resistance of the wood. This is one reason Y Combinator has a rule against investing in startups with only one founder. Practically every successful company has at least two. And because startup founders work under great pressure, it's critical they be friends. I didn't realize it till I was writing this, but that may help explain why there are so few female startup founders. I read on the Internet (so it must be true) that only 1.7% of VC-backed startups are founded by women. The percentage of female hackers is small, but not that small. So why the discrepancy? When you realize that successful startups tend to have multiple founders who were already friends, a possible explanation emerges. People's best friends are likely to be of the same sex, and if one group is a minority in some population, _pairs_ of them will be a minority squared. [1] Doodling What these groups of co-founders do together is more complicated than just sitting down and trying to think of ideas.
I suspect the most productive setup is a kind of together-alone-together sandwich. Together you talk about some hard problem, probably getting nowhere. Then, the next morning, one of you has an idea in the shower about how to solve it. He runs eagerly to to tell the others, and together they work out the kinks. What happens in that shower? It seems to me that ideas just pop into my head. But can we say more than that? Taking a shower is like a form of meditation. You're alert, but there's nothing to distract you. It's in a situation like this, where your mind is free to roam, that it bumps into new ideas. What happens when your mind wanders? It may be like doodling. Most people have characteristic ways of doodling. This habit is unconscious, but not random: I found my doodles changed after I started studying painting. I started to make the kind of gestures I'd make if I were drawing from life. They were atoms of drawing, but arranged randomly. [2] Perhaps letting your mind wander is like doodling with ideas. You have certain mental gestures you've learned in your work, and when you're not paying attention, you keep making these same gestures, but somewhat randomly. In effect, you call the same functions on random arguments. That's what a metaphor is: a function applied to an argument of the wrong type. Conveniently, as I was writing this, my mind wandered: would it be useful to have metaphors in a programming language? I don't know; I don't have time to think about this. But it's convenient because this is an example of what I mean by habits of mind. I spend a lot of time thinking about language design, and my habit of always asking "would x be useful in a programming language" just got invoked. If new ideas arise like doodles, this would explain why you have to work at something for a while before you have any. It's not just that you can't judge ideas till you're an expert in a field.
You won't even generate ideas, because you won't have any habits of mind to invoke. Of course the habits of mind you invoke on some field don't have to be derived from working in that field. In fact, it's often better if they're not. You're not just looking for good ideas, but for good _new_ ideas, and you have a better chance of generating those if you combine stuff from distant fields. As hackers, one of our habits of mind is to ask, could one open-source x? For example, what if you made an open-source operating system? A fine idea, but not very novel. Whereas if you ask, could you make an open-source play? you might be onto something. Are some kinds of work better sources of habits of mind than others? I suspect harder fields may be better sources, because to attack hard problems you need powerful solvents. I find math is a good source of metaphors-- good enough that it's worth studying just for that. Related fields are also good sources, especially when they're related in unexpected ways. Everyone knows computer science and electrical engineering are related, but precisely because everyone knows it, importing ideas from one to the other doesn't yield great profits. It's like importing something from Wisconsin to Michigan. Whereas (I claim) hacking and painting are also related, in the sense that hackers and painters are both makers, and this source of new ideas is practically virgin territory. Problems In theory you could stick together ideas at random and see what you came up with. What if you built a peer-to-peer dating site? Would it be useful to have an automatic book? Could you turn theorems into a commodity? When you assemble ideas at random like this, they may not be just stupid, but semantically ill-formed. What would it even mean to make theorems a commodity? You got me. I didn't think of that idea, just its name. You might come up with something useful this way, but I never have.
It's like knowing a fabulous sculpture is hidden inside a block of marble, and all you have to do is remove the marble that isn't part of it. It's an encouraging thought, because it reminds you there is an answer, but it's not much use in practice because the search space is too big. I find that to have good ideas I need to be working on some problem. You can't start with randomness. You have to start with a problem, then let your mind wander just far enough for new ideas to form. In a way, it's harder to see problems than their solutions. Most people prefer to remain in denial about problems. It's obvious why: problems are irritating. They're problems! Imagine if people in 1700 saw their lives the way we'd see them. It would have been unbearable. This denial is such a powerful force that, even when presented with possible solutions, people often prefer to believe they wouldn't work. I saw this phenomenon when I worked on spam filters. In 2002, most people preferred to ignore spam, and most of those who didn't preferred to believe the heuristic filters then available were the best you could do. I found spam intolerable, and I felt it had to be possible to recognize it statistically. And it turns out that was all you needed to solve the problem. The algorithm I used was ridiculously simple. Anyone who'd really tried to solve the problem would have found it. It was just that no one had really tried to solve the problem. [3] Let me repeat that recipe: finding the problem intolerable and feeling it must be possible to solve it. Simple as it seems, that's the recipe for a lot of startup ideas. Wealth So far most of what I've said applies to ideas in general. What's special about startup ideas? Startup ideas are ideas for companies, and companies have to make money. And the way to make money is to make something people want. Wealth is what people want.
I don't mean that as some kind of philosophical statement; I mean it as a tautology. So an idea for a startup is an idea for something people want. Wouldn't any good idea be something people want? Unfortunately not. I think new theorems are a fine thing to create, but there is no great demand for them. Whereas there appears to be great demand for celebrity gossip magazines. Wealth is defined democratically. Good ideas and valuable ideas are not quite the same thing; the difference is individual tastes. But valuable ideas are very close to good ideas, especially in technology. I think they're so close that you can get away with working as if the goal were to discover good ideas, so long as, in the final stage, you stop and ask: will people actually pay for this? Only a few ideas are likely to make it that far and then get shot down; RPN calculators might be one example. One way to make something people want is to look at stuff people use now that's broken. Dating sites are a prime example. They have millions of users, so they must be promising something people want. And yet they work horribly. Just ask anyone who uses them. It's as if they used the worse-is-better approach but stopped after the first stage and handed the thing over to marketers. Of course, the most obvious breakage in the average computer user's life is Windows itself. But this is a special case: you can't defeat a monopoly by a frontal attack. Windows can and will be overthrown, but not by giving people a better desktop OS. The way to kill it is to redefine the problem as a superset of the current one. The problem is not, what operating system should people use on desktop computers? but how should people use applications? There are answers to that question that don't even involve desktop computers. Everyone thinks Google is going to solve this problem, but it is a very subtle one, so subtle that a company as big as Google might well get it wrong.
I think the odds are better than 50-50 that the Windows killer-- or more accurately, Windows transcender-- will come from some little startup. Another classic way to make something people want is to take a luxury and make it into a commmodity. People must want something if they pay a lot for it. And it is a very rare product that can't be made dramatically cheaper if you try. This was Henry Ford's plan. He made cars, which had been a luxury item, into a commodity. But the idea is much older than Henry Ford. Water mills transformed mechanical power from a luxury into a commodity, and they were used in the Roman empire. Arguably pastoralism transformed a luxury into a commodity. When you make something cheaper you can sell more of them. But if you make something dramatically cheaper you often get qualitative changes, because people start to use it in different ways. For example, once computers get so cheap that most people can have one of their own, you can use them as communication devices. Often to make something dramatically cheaper you have to redefine the problem. The Model T didn't have all the features previous cars did. It only came in black, for example. But it solved the problem people cared most about, which was getting from place to place. One of the most useful mental habits I know I learned from Michael Rabin: that the best way to solve a problem is often to redefine it. A lot of people use this technique without being consciously aware of it, but Rabin was spectacularly explicit. You need a big prime number? Those are pretty expensive. How about if I give you a big number that only has a 10 to the minus 100 chance of not being prime? Would that do? Well, probably; I mean, that's probably smaller than the chance that I'm imagining all this anyway. Redefining the problem is a particularly juicy heuristic when you have competitors, because it's so hard for rigid-minded people to follow.
You can work in plain sight and they don't realize the danger. Don't worry about us. We're just working on search. Do one thing and do it well, that's our motto. Making things cheaper is actually a subset of a more general technique: making things easier. For a long time it was most of making things easier, but now that the things we build are so complicated, there's another rapidly growing subset: making things easier to _use_. This is an area where there's great room for improvement. What you want to be able to say about technology is: it just works. How often do you say that now? Simplicity takes effort-- genius, even. The average programmer seems to produce UI designs that are almost willfully bad. I was trying to use the stove at my mother's house a couple weeks ago. It was a new one, and instead of physical knobs it had buttons and an LED display. I tried pressing some buttons I thought would cause it to get hot, and you know what it said? "Err." Not even "Error." "Err." You can't just say "Err" to the user of a _stove_. You should design the UI so that errors are impossible. And the boneheads who designed this stove even had an example of such a UI to work from: the old one. You turn one knob to set the temperature and another to set the timer. What was wrong with that? It just worked. It seems that, for the average engineer, more options just means more rope to hang yourself. So if you want to start a startup, you can take almost any existing technology produced by a big company, and assume you could build something way easier to use. Design for Exit Success for a startup approximately equals getting bought. You need some kind of exit strategy, because you can't get the smartest people to work for you without giving them options likely to be worth something. Which means you either have to get bought or go public, and the number of startups that go public is very small.
If success probably means getting bought, should you make that a conscious goal? The old answer was no: you were supposed to pretend that you wanted to create a giant, public company, and act surprised when someone made you an offer. Really, you want to buy us? Well, I suppose we'd consider it, for the right price. I think things are changing. If 98% of the time success means getting bought, why not be open about it? If 98% of the time you're doing product development on spec for some big company, why not think of that as your task? One advantage of this approach is that it gives you another source of ideas: look at big companies, think what they should be doing, and do it yourself. Even if they already know it, you'll probably be done faster. Just be sure to make something multiple acquirers will want. Don't fix Windows, because the only potential acquirer is Microsoft, and when there's only one acquirer, they don't have to hurry. They can take their time and copy you instead of buying you. If you want to get market price, work on something where there's competition. If an increasing number of startups are created to do product development on spec, it will be a natural counterweight to monopolies. Once some type of technology is captured by a monopoly, it will only evolve at big company rates instead of startup rates, whereas alternatives will evolve with especial speed. A free market interprets monopoly as damage and routes around it. The Woz Route The most productive way to generate startup ideas is also the most unlikely-sounding: by accident. If you look at how famous startups got started, a lot of them weren't initially supposed to be startups. Lotus began with a program Mitch Kapor wrote for a friend. Apple got started because Steve Wozniak wanted to build microcomputers, and his employer, Hewlett-Packard, wouldn't let him do it at work. Yahoo began as David Filo's personal collection of links.
This is not the only way to start startups. You can sit down and consciously come up with an idea for a company; we did. But measured in total market cap, the build-stuff-for-yourself model might be more fruitful. It certainly has to be the most fun way to come up with startup ideas. And since a startup ought to have multiple founders who were already friends before they decided to start a company, the rather surprising conclusion is that the best way to generate startup ideas is to do what hackers do for fun: cook up amusing hacks with your friends. It seems like it violates some kind of conservation law, but there it is: the best way to get a "million dollar idea" is just to do what hackers enjoy doing anyway. Notes [1] This phenomenon may account for a number of discrepancies currently blamed on various forbidden isms. Never attribute to malice what can be explained by math. [2] A lot of classic abstract expressionism is doodling of this type: artists trained to paint from life using the same gestures but without using them to represent anything. This explains why such paintings are (slightly) more interesting than random marks would be. [3] Bill Yerazunis had solved the problem, but he got there by another path. He made a general-purpose file classifier so good that it also worked for spam.
| One Specific Idea | | | Romanian Translation | Japanese Translation | | | Traditional Chinese Translation | Russian Translation | | | Arabic Translation.
想创立一家初创公司? 获得 Y Combinator 的资助。
2005年10月 _(本文源自2005年初创学校的一次演讲)_ 如何为初创公司想出好点子?这可能是人们问我最多的问题。 我想用另一个问题来回答:为什么人们认为想出初创公司的点子很难? 这似乎是个愚蠢的问题。为什么他们会_觉得_难?如果人们做不到,那至少对他们来说确实很难,对吧? 嗯,也许并非如此。人们通常说的不是他们想不出点子,而是他们没有任何点子。这两者并不完全相同。他们没有任何点子的原因可能是他们根本没有尝试去生成它们。 我认为这种情况很常见。人们认为想出初创公司的点子非常困难——甚至_必须_非常困难——所以他们不去尝试。他们假设点子就像奇迹:要么突然出现在脑海中,要么就不会出现。 我还有一个关于人们为何这样想的理论。他们高估了点子的价值。他们认为创立一家初创公司只是实现某个绝妙的初始想法。而既然一家成功的初创公司价值数百万美元,那么一个好点子自然就是一个价值百万美元的点子。 如果为初创公司想出一个点子等同于想出一个价值百万美元的点子,那当然会显得很难。难到不值得尝试。我们的直觉告诉我们,如此有价值的东西不会随便被任何人发现。 实际上,初创公司的点子并不是价值百万美元的点子,这里有一个实验可以证明:试着卖一个点子看看。没有什么比市场变化得更快。初创公司点子没有市场的事实表明没有需求。这意味着,从狭义上讲,初创公司的点子毫无价值。 问题 事实上,大多数初创公司最终与最初的设想完全不同。更接近真相的说法是,初始点子的主要价值在于,在发现它行不通的过程中,你会想出真正的点子。 初始点子只是一个起点——不是蓝图,而是一个问题。如果用问题的方式表达可能会更有帮助。不要说你的想法是做一个基于网络的协作电子表格,而是问:能否做一个基于网络的协作电子表格?通过一些语法调整,一个糟糕的不完整点子变成了一个值得探索的有前景的问题。 这有真正的区别,因为断言会引发反对,而问题则不会。如果你说:我要做一个基于网络的电子表格,那么批评者——最危险的是你脑海中的那些——会立即反驳说你会与微软竞争,你无法提供用户期望的界面,用户不会想把数据放在你的服务器上,等等。 问题则不会显得那么具有挑战性。它变成了:让我们尝试做一个基于网络的电子表格,看看能走多远。而且大家都知道,如果你尝试这样做,你一定能做出_一些_有用的东西。也许你最终得到的甚至不是一个电子表格。也许它是一种尚未命名的新型协作工具。除非你通过实践去实现,否则你不会想到这样的东西。 将初创公司的点子视为一个问题会改变你的寻找方向。如果点子是一个蓝图,它必须是正确的。但如果它是一个问题,它可以是错误的,只要它的错误能引导出更多点子。 点子的一种有价值的错误方式是只提供部分解决方案。当有人面对一个看似太大的问题时,我总是问:有没有办法先解决其中的一部分,然后逐步扩展?这种方法通常有效,除非你陷入局部最优,比如20世纪80年代的人工智能或C语言。 顺风而行 到目前为止,我们已经将问题从想出一个价值百万美元的点子简化为想出一个错误的问题。这似乎并不难,对吧? 要生成这样的问题,你需要两件事:熟悉有前景的新技术,以及拥有合适的朋友。新技术是初创公司点子的原料,而与朋友的对话则是烹饪这些点子的厨房。 大学同时具备这两点,因此许多初创公司从中诞生。大学充满了新技术,因为它们致力于研究,而只有新事物才算研究。而且大学里充满了适合一起想点子的人:其他学生,他们不仅聪明,而且思维灵活到近乎偏执。 相反的极端是在大公司里有一份高薪但无聊的工作。大公司对新技术的态度偏保守,而且你在那里遇到的人也不太合适。 在我为高中生写的一篇文章中,我说一个好的经验法则是保持顺风而行——从事能最大化你未来选择的事情。这一原则也适用于成年人,尽管可能需要稍作修改:尽可能长时间保持顺风而行,然后在需要为家庭支付时兑现你积累的潜力。 我不认为人们有意识地意识到这一点,但像为银行编写Java代码这样的“顺风”工作之所以报酬丰厚,正是因为它们是顺风而行。这类工作的市场价格更高,因为它为未来提供的选择更少。一份让你从事激动人心的新事物的工作往往报酬较低,因为部分报酬是以你将学到的新技能形式体现的。 研究生院与大公司的编码工作处于光谱的另一端:报酬低,但大部分时间都在研究新事物。当然,它被称为“学校”,这让所有人都清楚这一点,尽管实际上所有工作都带有一定比例的“学校”成分。 产生初创公司点子的合适环境不一定是大学本身。它只需要是一个“学校”成分较高的环境。 显然,你需要接触新技术,但为什么还需要其他人?难道不能自己想出新点子吗?经验回答是:不能。即使是爱因斯坦也需要有人交流想法。点子是在向合适的人解释的过程中发展起来的。你需要这种阻力,就像雕刻家需要木材的阻力一样。 这也是Y Combinator有一条规则不投资只有一位创始人的初创公司的原因之一。几乎每一家成功的公司都至少有两名创始人。而且由于初创公司创始人在巨大压力下工作,他们必须是朋友这一点至关重要。 直到写这篇文章时我才意识到,这可能有助于解释为什么女性初创公司创始人如此之少。我在互联网上读到(所以这一定是真的),只有1.7%的风投支持的初创公司由女性创立。女性黑客的比例很小,但并没有那么小。那么为什么会有这种差异? 当你意识到成功的初创公司通常由已经是朋友的几位创始人共同创立时,一个可能的解释就出现了。人们最好的朋友很可能是同性,如果某一群体在某个群体中是少数,那么他们的_配对_将是少数中的少数。[1] 涂鸦 这些联合创始人群体一起做的事情比坐下来试图想点子要复杂得多。我怀疑最高效的模式是一种“一起-独自-一起”的三明治结构。你们一起讨论某个难题,可能毫无进展。然后,第二天早上,其中一个人在洗澡时想到了解决方案。他急切地跑去告诉其他人,然后大家一起解决细节问题。 在洗澡时发生了什么?在我看来,点子就是突然出现在脑海中。但我们能说得更多吗? 洗澡就像一种冥想。你清醒,但没有什么能分散你的注意力。正是在这种情况下,你的思维可以自由漫游,从而碰撞出新点子。 当你的思维漫游时会发生什么?可能就像涂鸦。大多数人都有自己独特的涂鸦方式。这种习惯是无意识的,但并非随机:我发现我开始学习绘画后,我的涂鸦方式也变了。我开始做出如果我在写生时会做出的那种手势。它们是绘画的原子,但随机排列。[2] 也许让你的思维漫游就像用点子涂鸦。你在工作中学到了一些思维手势,当你不注意时,你会继续做出这些手势,但有些随机。实际上,你是在随机参数上调用相同的函数。这就是隐喻:将函数应用于错误类型的参数。 方便的是,当我写到这里时,我的思维漫游了:在编程语言中加入隐喻会有用吗?我不知道;我没有时间去思考这个问题。但这很方便,因为这是我所说的思维习惯的一个例子。我花了很多时间思考语言设计,而我总是问“x在编程语言中是否有用”的习惯刚刚被触发了。 如果新点子像涂鸦一样产生,这就能解释为什么你必须在一件事情上工作一段时间后才能有点子。不仅仅是因为你只有成为某个领域的专家后才能判断点子。你甚至不会生成点子,因为你没有任何思维习惯可以调用。 当然,你在某个领域调用的思维习惯不必源自该领域的工作。事实上,如果不是这样往往更好。你不仅在寻找好点子,还在寻找好的_新_点子,而如果你结合来自遥远领域的东西,你更有可能生成这些点子。作为黑客,我们的一个思维习惯是问:能否开源x?例如,如果你做一个开源操作系统会怎样?这是个好点子,但并不新颖。而如果你问:能否做一部开源戏剧?你可能会有新发现。 某些类型的工作比其他工作更适合作为思维习惯的来源吗?我怀疑更难的领域可能是更好的来源,因为要解决难题,你需要强大的溶剂。我发现数学是一个很好的隐喻来源——好到值得仅仅为此而学习。相关领域也是很好的来源,尤其是当它们以意想不到的方式相关时。大家都知道计算机科学和电气工程相关,但正因为大家都知道这一点,从一个领域引入点子到另一个领域不会带来巨大收益。这就像从威斯康星州进口东西到密歇根州。而(我认为)黑客和绘画也是相关的,因为黑客和画家都是创造者,而这个新点子的来源几乎是一片处女地。 问题 理论上,你可以随机拼凑点子,看看能想出什么。如果你做一个点对点的交友网站会怎样?拥有一本自动化的书会有用吗?你能将定理变成商品吗?当你像这样随机组合点子时,它们可能不仅仅是愚蠢的,而且在语义上是不成立的。将定理变成商品是什么意思?你问住我了。我没有想出这个点子,只是它的名字。 你可能会通过这种方式想出一些有用的东西,但我从来没有。这就像知道一块大理石中隐藏着一座绝妙的雕塑,你只需要去掉不属于它的部分。这是一个鼓舞人心的想法,因为它提醒你答案是存在的,但在实践中用处不大,因为搜索空间太大了。 我发现,要想出好点子,我需要解决某个问题。你不能从随机性开始。你必须从一个问题开始,然后让你的思维漫游到足以形成新点子的程度。 在某种程度上,发现问题比发现解决方案更难。大多数人宁愿对问题视而不见。原因显而易见:问题令人恼火。它们是问题!想象一下,如果1700年的人们像我们看待他们的生活那样看待自己的生活。那将是无法忍受的。这种否认是如此强大的力量,以至于即使面对可能的解决方案,人们也往往宁愿相信它们不会奏效。 我在开发垃圾邮件过滤器时看到了这种现象。2002年,大多数人宁愿忽略垃圾邮件,而那些不忽略的人则宁愿相信当时可用的启发式过滤器是最好的选择。 我发现垃圾邮件无法容忍,而且我觉得必须有可能通过统计方法识别它。事实证明,这就是解决问题所需的全部。我使用的算法简单得可笑。任何真正尝试解决这个问题的人都会发现它。只是没有人真正尝试过解决这个问题。[3] 让我重复这个配方:发现一个问题无法容忍,并觉得必须有可能解决它。尽管看起来简单,但这是许多初创公司点子的配方。 财富 到目前为止,我所说的多数适用于一般点子。初创公司的点子有什么特别之处?初创公司的点子是为公司而生的点子,而公司必须赚钱。而赚钱的方法是做人们想要的东西。 财富就是人们想要的东西。我不是在说某种哲学陈述;我是在说一个同义反复。 因此,初创公司的点子就是人们想要的东西的点子。难道任何好点子不都是人们想要的东西吗?不幸的是,并非如此。我认为创造新定理是一件好事,但对它们的需求并不大。而名人八卦杂志似乎有很大的需求。财富是由民主定义的。好点子和有价值的点子并不完全相同;区别在于个人品味。 但有价值的点子与好点子非常接近,尤其是在技术领域。我认为它们如此接近,以至于你可以假装目标是发现好点子,只要在最后阶段停下来问:人们真的会为此付费吗?只有少数点子可能会走到这一步然后被否决;RPN计算器可能是一个例子。 让人们想要的东西的一种方法是看看现在人们使用的那些有问题的东西。交友网站就是一个典型的例子。它们有数百万用户,所以它们一定提供了人们想要的东西。然而它们的工作方式糟糕透顶。问问任何使用它们的人就知道了。就好像它们采用了“越差越好”的方法,但在第一阶段后就停止了,然后把东西交给了营销人员。 当然,普通电脑用户生活中最明显的问题是Windows本身。但这是一个特例:你不能通过正面攻击击败垄断。Windows可以被推翻,但不会通过提供更好的桌面操作系统来实现。击败它的方法是将问题重新定义为当前问题的超集。问题不是“人们应该在桌面电脑上使用什么操作系统?”,而是“人们应该如何使用应用程序?”这个问题的答案甚至不涉及桌面电脑。 每个人都认为谷歌会解决这个问题,但这是一个非常微妙的问题,微妙到像谷歌这样的大公司很可能会搞错。我认为Windows的终结者——或者更准确地说,Windows的超越者——有超过50%的概率会来自某家小初创公司。 另一种经典的让人们想要的东西的方法是拿一种奢侈品并将其变成商品。如果人们愿意为某样东西支付高价,那么他们一定想要它。而很少有产品在努力后不能大幅降低成本。 这是亨利·福特的计划。他将汽车从奢侈品变成了商品。但这个想法比亨利·福特古老得多。水车将机械动力从奢侈品变成了商品,而它们在罗马帝国时期就被使用了。可以说,畜牧业将奢侈品变成了商品。 当你让某样东西更便宜时,你可以卖出更多。但如果你让某样东西大幅降价,通常会带来质的变化,因为人们开始以不同的方式使用它。例如,一旦电脑便宜到大多数人可以拥有一台,你就可以将它们用作通讯设备。 通常,要让某样东西大幅降价,你必须重新定义问题。T型车没有之前汽车的所有功能。例如,它只有黑色。但它解决了人们最关心的问题:从一个地方到另一个地方。 我所知道的最有用的思维习惯之一是从迈克尔·拉宾那里学到的:解决问题的最佳方法通常是重新定义它。许多人在无意识地使用这种技巧,但拉宾的做法非常明确。你需要一个大素数?那些相当昂贵。如果我给你一个只有10的负100次方概率不是素数的大数呢?这样可以吗?嗯,可能吧;我是说,这可能比我凭空想象这一切的概率还要小。 当你面对竞争对手时,重新定义问题是一个特别有用的启发式方法,因为思维僵化的人很难跟上。你可以在他们眼皮底下工作,而他们不会意识到危险。别担心我们。我们只是在做搜索。做一件事并做好,这是我们的座右铭。 让东西更便宜实际上是一个更通用技术的子集:让东西更容易。长期以来,它主要是让东西更容易,但现在我们构建的东西如此复杂,另一个快速增长的子集是:让东西更容易_使用_。 这是一个有很大改进空间的领域。关于技术,你希望能够说的是:它就能用。你现在多久会说一次这样的话? 简单需要努力——甚至是天才。普通程序员似乎设计出的用户界面几乎是有意为之的糟糕。几周前,我试图使用我母亲家的炉子。那是一个新炉子,没有物理旋钮,而是按钮和LED显示屏。我按了一些我以为会让它变热的按钮,你猜它显示什么?“错误。”甚至不是“错误”。“错误。”你不能对_炉子_的用户只说“错误”。你应该设计用户界面,使错误不可能发生。而设计这个炉子的笨蛋甚至有一个可以借鉴的界面例子:旧的炉子。你转动一个旋钮设置温度,另一个设置定时器。那有什么问题?它就能用。 对普通工程师来说,更多的选项似乎只是更多的绳子来吊死自己。因此,如果你想创立一家初创公司,你可以拿任何大公司生产的现有技术,假设你可以构建一个更容易使用的东西。 为退出而设计 初创公司的成功大致等同于被收购。你需要某种退出策略,因为如果没有可能值钱的期权,你无法让最聪明的人为你工作。这意味着你要么被收购,要么上市,而上市的初创公司数量非常少。 如果成功很可能意味着被收购,你应该将其作为一个明确的目标吗?过去的答案是否定的:你应该假装你想创建一家大型的上市公司,并在有人出价时表现得惊讶。真的,你想收购我们?嗯,我想我们会考虑,只要价格合适。 我认为事情正在改变。如果98%的情况下成功意味着被收购,为什么不公开承认呢?如果98%的情况下你是在为某家大公司做产品开发,为什么不把这视为你的任务呢?这种方法的一个优势是它为你提供了另一个点子来源:看看大公司,想想他们应该做什么,然后自己去做。即使他们已经知道了,你可能会更快完成。 只要确保做出多个收购方会想要的东西。不要修复Windows,因为唯一的潜在收购方是微软,而当只有一个收购方时,他们不必着急。他们可以慢慢来,复制你而不是收购你。如果你想得到市场价格,就做有竞争的东西。 如果越来越多的初创公司为产品开发而创立,它将自然成为垄断的制衡力量。一旦某种技术被垄断捕获,它只会以大公司的速度发展,而不是初创公司的速度,而替代品将以特别快的速度发展。自由市场将垄断视为损害并绕过它。 沃兹之路 产生初创公司点子最高效的方式也是最不可能的方式:偶然。如果你看看著名初创公司是如何起步的,很多最初并不打算成为初创公司。Lotus始于Mitch Kapor为朋友写的一个程序。苹果的诞生是因为Steve Wozniak想制造微型计算机,而他的雇主惠普不允许他在工作中做这件事。雅虎始于David Filo的个人链接收藏。 这并不是创立初创公司的唯一方式。你可以坐下来有意识地想出一个公司的点子;我们就是这样做的。但以总市值衡量,为自己构建东西的模式可能更有成果。这肯定是想出初创公司点子最有趣的方式。而且由于一家初创公司应该有几位在决定创立公司之前就是朋友的联合创始人,相当令人惊讶的结论是,产生初创公司点子的最佳方式就是黑客们为了乐趣所做的事情:与朋友一起捣鼓有趣的玩意儿。 这似乎违反了某种守恒定律,但事实就是如此:获得“百万美元点子”的最佳方式就是做黑客们喜欢做的事情。 注释 [1] 这种现象可能解释了目前归咎于各种禁忌主义的许多差异。能用数学解释的,就不要归咎于恶意。 [2] 许多经典的抽象表现主义就是这种类型的涂鸦:艺术家们受过写实绘画的训练,使用同样的手势但不用于表现任何东西。这解释了为什么这样的画比随机标记(稍微)更有趣。 [3] Bill Yerazunis解决了这个问题,但他走的是另一条路。他做了一个通用的文件分类器,效果非常好,以至于也能用于垃圾邮件。
| 一个具体的点子 | | | 罗马尼亚语翻译 | 日语翻译 | | | 繁体中文翻译 | 俄语翻译 | | | 阿拉伯语翻译.
[](https://s.turbifycdn.com/aah/paulgraham/what-i-did-this-summer-11.gif) October 2005 The first Summer Founders Program has just finished. We were surprised how well it went. Overall only about 10% of startups succeed, but if I had to guess now, I'd predict three or four of the eight startups we funded will make it. Of the startups that needed further funding, I believe all have either closed a round or are likely to soon. Two have already turned down (lowball) acquisition offers. We would have been happy if just one of the eight seemed promising by the end of the summer. What's going on? Did some kind of anomaly make this summer's applicants especially good? We worry about that, but we can't think of one. We'll find out this winter. The whole summer was full of surprises. The best was that the hypothesis we were testing seems to be correct. Young hackers can start viable companies. This is good news for two reasons: (a) it's an encouraging thought, and (b) it means that Y Combinator, which is predicated on the idea, is not hosed. Age More precisely, the hypothesis was that success in a startup depends mainly on how smart and energetic you are, and much less on how old you are or how much business experience you have. The results so far bear this out. The 2005 summer founders ranged in age from 18 to 28 (average 23), and there is no correlation between their ages and how well they're doing. This should not really be surprising. Bill Gates and Michael Dell were both 19 when they started the companies that made them famous. Young founders are not a new phenomenon: the trend began as soon as computers got cheap enough for college kids to afford them. Another of our hypotheses was that you can start a startup on less money than most people think. Other investors were surprised to hear the most we gave any group was $20,000.
[](https://s.turbifycdn.com/aah/paulgraham/what-i-did-this-summer-11.gif)
首届夏季创始人计划刚刚结束。结果之好令我们惊讶。总体而言,初创企业的成功率仅约10%,但如果现在要我猜测,我会预测我们资助的八家公司中有三到四家能成功。
在需要进一步融资的初创企业中,我相信它们要么已完成一轮融资,要么即将完成。其中两家已经拒绝了(低价的)收购要约。
如果到夏季结束时八家公司中仅有一家看起来有希望,我们本会感到满意。发生了什么?是某种异常现象使今年夏天的申请者特别优秀吗?我们对此感到担忧,但想不出原因。今年冬天我们会找到答案。
But we knew it was possible to start on that little because we started Viaweb on $10,000. And so it proved this summer. Three months' funding is enough to get into second gear. We had a demo day for potential investors ten weeks in, and seven of the eight groups had a prototype ready by that time. One, Reddit, had already launched, and were able to give a demo of their live site. A researcher who studied the SFP startups said the one thing they had in common was that they all worked ridiculously hard. People this age are commonly seen as lazy. I think in some cases it's not so much that they lack the appetite for work, but that the work they're offered is unappetizing. The experience of the SFP suggests that if you let motivated people do real work, they work hard, whatever their age. As one of the founders said "I'd read that starting a startup consumed your life, but I had no idea what that meant until I did it." I'd feel guilty if I were a boss making people work this hard. But we're not these people's bosses. They're working on their own projects. And what makes them work is not us but their competitors. Like good athletes, they don't work hard because the coach yells at them, but because they want to win. We have less power than bosses, and yet the founders work harder than employees. It seems like a win for everyone. The only catch is that we get on average only about 5-7% of the upside, while an employer gets nearly all of it. (We're counting on it being 5-7% of a much larger number.) As well as working hard, the groups all turned out to be extraordinarily responsible. I can't think of a time when one failed to do something they'd promised to, even by being late for an appointment. This is another lesson the world has yet to learn.
整个夏天充满了惊喜。最好的是,我们正在测试的假设似乎是正确的。年轻的黑客可以创立可行的公司。这是个好消息,原因有二:(a) 这是个令人鼓舞的想法,(b) 这意味着基于这一理念的Y Combinator不会失败。
更准确地说,这个假设是:初创企业的成功主要取决于你有多聪明和精力充沛,而年龄或商业经验的影响要小得多。到目前为止的结果证实了这一点。2005年夏季创始人的年龄从18岁到28岁不等(平均23岁),他们的年龄与表现之间没有相关性。
这其实并不令人惊讶。比尔·盖茨和迈克尔·戴尔在创立使他们成名的公司时都是19岁。年轻的创始人并非新现象:这一趋势始于计算机便宜到大学生也能买得起的时候。
我们的另一个假设是:创立初创企业所需的资金比大多数人想象的要少。其他投资者听说我们给任何团队的最高金额是2万美元时都很惊讶。但我们知道用这么少的钱起步是可能的,因为我们用1万美元创立了Viaweb。
今年夏天证明了这一点。三个月的资金足以让企业进入第二档。我们在十周时为潜在投资者举办了演示日,八支团队中有七支在那时准备好了原型。其中一支团队Reddit已经上线,能够演示他们的实时网站。
One of the founders discovered that the hardest part of arranging a meeting with executives at a big cell phone carrier was getting a rental company to rent him a car, because he was too young. I think the problem here is much the same as with the apparent laziness of people this age. They seem lazy because the work they're given is pointless, and they act irresponsible because they're not given any power. Some of them, anyway. We only have a sample size of about twenty, but it seems so far that if you let people in their early twenties be their own bosses, they rise to the occasion. Morale The summer founders were as a rule very idealistic. They also wanted very much to get rich. These qualities might seem incompatible, but they're not. These guys want to get rich, but they want to do it by changing the world. They wouldn't (well, seven of the eight groups wouldn't) be interested in making money by speculating in stocks. They want to make something people use. I think this makes them more effective as founders. As hard as people will work for money, they'll work harder for a cause. And since success in a startup depends so much on motivation, the paradoxical result is that the people likely to make the most money are those who aren't in it just for the money. The founders of Kiko, for example, are working on an Ajax calendar. They want to get rich, but they pay more attention to design than they would if that were their only motivation. You can tell just by looking at it. I never considered it till this summer, but this might be another reason startups run by hackers tend to do better than those run by MBAs. Perhaps it's not just that hackers understand technology better, but that they're driven by more powerful motivations. Microsoft, as I've said before, is a dangerously misleading example. Their mean corporate culture only works for monopolies. Google is a better model.
一位研究SFP初创企业的研究人员说,它们的共同点是都极其努力工作。这个年龄段的人通常被视为懒惰。我认为在某些情况下,与其说他们缺乏工作的欲望,不如说他们被提供的工作没有吸引力。
SFP的经验表明,如果你让有动力的人做真正的工作,他们会努力工作,无论年龄多大。正如一位创始人所说:“我读过创立初创企业会占据你的生活,但直到我做了才知道那是什么意思。”
如果我是老板,让员工这么努力工作,我会感到内疚。但我们不是这些人的老板。他们在为自己的项目工作。驱使他们工作的不是我们,而是他们的竞争对手。就像优秀的运动员一样,他们努力工作不是因为教练对他们大喊大叫,而是因为他们想赢。
我们的权力比老板小,但创始人比员工更努力工作。这对每个人来说似乎都是双赢。唯一的陷阱是,我们平均只获得约5-7%的收益,而雇主几乎获得全部收益。(我们指望这是更大数字的5-7%。)
Considering that the summer founders are the sharks in this ocean, we were surprised how frightened most of them were of competitors. But now that I think of it, we were just as frightened when we started Viaweb. For the first year, our initial reaction to news of a competitor was always: we're doomed. Just as a hypochondriac magnifies his symptoms till he's convinced he has some terrible disease, when you're not used to competitors you magnify them into monsters. Here's a handy rule for startups: competitors are rarely as dangerous as they seem. Most will self-destruct before you can destroy them. And it certainly doesn't matter how many of them there are, any more than it matters to the winner of a marathon how many runners are behind him. "It's a crowded market," I remember one founder saying worriedly. "Are you the current leader?" I asked. "Yes." "Is anyone able to develop software faster than you?" "Probably not." "Well, if you're ahead now, and you're the fastest, then you'll stay ahead. What difference does it make how many others there are?" Another group was worried when they realized they had to rewrite their software from scratch. I told them it would be a bad sign if they didn't. The main function of your initial version is to be rewritten. That's why we advise groups to ignore issues like scalability, internationalization, and heavy-duty security at first. [1] I can imagine an advocate of "best practices" saying these ought to be considered from the start. And he'd be right, except that they interfere with the primary function of software in a startup: to be a vehicle for experimenting with its own design. Having to retrofit internationalization or scalability is a pain, certainly. The only bigger pain is not needing to, because your initial version was too big and rigid to evolve into something users wanted. I suspect this is another reason startups beat big companies.
除了努力工作,这些团队还表现得非常负责。我想不出有哪次他们未能兑现承诺,甚至包括迟到。这是世界尚未学到的另一课。一位创始人发现,与一家大型手机运营商的高管安排会议最困难的部分是租车公司拒绝租车给他,因为他太年轻了。
我认为这里的问题与这个年龄段的人表面上的懒惰非常相似。他们显得懒惰是因为被分配的工作毫无意义,他们表现得不负责任是因为没有被赋予任何权力。至少对其中一些人来说是这样。我们只有大约二十个样本,但到目前为止,如果你让二十岁出头的人自己做主,他们会挺身而出。
夏季创始人通常非常理想主义。他们也迫切想致富。这些品质看似矛盾,实则不然。这些人想致富,但他们想通过改变世界来实现。他们(好吧,八支团队中有七支)不会对通过股票投机赚钱感兴趣。他们想创造人们使用的东西。
我认为这使他们作为创始人更有效。人们为钱努力工作,但为事业会更加努力。由于初创企业的成功很大程度上取决于动机,矛盾的结果是,最可能赚大钱的人并不是只为了钱而创业的人。
例如,Kiko的创始人正在开发一款Ajax日历。他们想致富,但如果这是唯一动机,他们不会如此关注设计。你一看就能明白。
Startups can be irresponsible and release version 1s that are light enough to evolve. In big companies, all the pressure is in the direction of over-engineering. What Got Learned One thing we were curious about this summer was where these groups would need help. That turned out to vary a lot. Some we helped with technical advice-- for example, about how to set up an application to run on multiple servers. Most we helped with strategy questions, like what to patent, and what to charge for and what to give away. Nearly all wanted advice about dealing with future investors: how much money should they take and what kind of terms should they expect? However, all the groups quickly learned how to deal with stuff like patents and investors. These problems aren't intrinsically difficult, just unfamiliar. It was surprising-- slightly frightening even-- how fast they learned. The weekend before the demo day for investors, we had a practice session where all the groups gave their presentations. They were all terrible. We tried to explain how to make them better, but we didn't have much hope. So on demo day I told the assembled angels and VCs that these guys were hackers, not MBAs, and so while their software was good, we should not expect slick presentations from them. The groups then proceeded to give fabulously slick presentations. Gone were the mumbling recitations of lists of features. It was as if they'd spent the past week at acting school. I still don't know how they did it. Perhaps watching each others' presentations helped them see what they'd been doing wrong. Just as happens in college, the summer founders learned a lot from one another-- maybe more than they learned from us. A lot of the problems they face are the same, from dealing with investors to hacking Javascript. I don't want to give the impression there were no problems this summer. A lot went wrong, as usually happens with startups.
直到今年夏天我才想到,这可能是黑客运营的初创企业比MBA运营的初创企业表现更好的另一个原因。也许不仅因为黑客更懂技术,还因为他们被更强大的动机驱动。正如我之前所说,微软是一个危险且误导性的例子。他们刻薄的企业文化只适用于垄断企业。谷歌是更好的榜样。
考虑到夏季创始人是这片海洋中的鲨鱼,我们惊讶于他们大多数人对竞争对手的恐惧。但现在回想起来,我们在创立Viaweb时也同样害怕。第一年,我们对竞争对手消息的第一反应总是:我们完了。就像疑病症患者放大症状直到确信自己患有某种可怕疾病一样,当你不习惯竞争对手时,你会把他们放大成怪物。
对初创企业来说,这是一个方便的规则:竞争对手很少像看起来那么危险。大多数会在你摧毁他们之前自我毁灭。当然,他们的数量并不重要,就像马拉松冠军不在乎身后有多少跑者一样。
“这是一个拥挤的市场,”我记得一位创始人忧心忡忡地说。
One group got an "exploding term-sheet" from some VCs. Pretty much all the groups who had dealings with big companies found that big companies do everything infinitely slowly. (This is to be expected. If big companies weren't incapable, there would be no room for startups to exist.) And of course there were the usual nightmares associated with servers. In short, the disasters this summer were just the usual childhood diseases. Some of this summer's eight startups will probably die eventually; it would be extraordinary if all eight succeeded. But what kills them will not be dramatic, external threats, but a mundane, internal one: not getting enough done. So far, though, the news is all good. In fact, we were surprised how much fun the summer was for us. The main reason was how much we liked the founders. They're so earnest and hard-working. They seem to like us too. And this illustrates another advantage of investing over hiring: our relationship with them is way better than it would be between a boss and an employee. Y Combinator ends up being more like an older brother than a parent. I was surprised how much time I spent making introductions. Fortunately I discovered that when a startup needed to talk to someone, I could usually get to the right person by at most one hop. I remember wondering, how did my friends get to be so eminent? and a second later realizing: shit, I'm forty. Another surprise was that the three-month batch format, which we were forced into by the constraints of the summer, turned out to be an advantage. When we started Y Combinator, we planned to invest the way other venture firms do: as proposals came in, we'd evaluate them and decide yes or no. The SFP was just an experiment to get things started. But it worked so well that we plan to do all our investing this way, one cycle in the summer and one in winter.
“你是目前的领导者吗?”我问。
“有人能比你们更快开发软件吗?”
“好吧,如果你现在领先,而且你是最快的,那么你会保持领先。其他人的数量有什么关系?”
另一支团队在意识到必须从头重写软件时感到担忧。我告诉他们,如果不这样做才是不好的迹象。初始版本的主要功能就是被重写。
这就是为什么我们建议团队一开始忽略可扩展性、国际化和重型安全等问题。[1] 我能想象“最佳实践”的倡导者会说这些应该从一开始就考虑。他是对的,只是它们干扰了初创企业软件的主要功能:作为实验自身设计的载体。不得不事后添加国际化或可扩展性确实很痛苦。唯一更大的痛苦是不需要这样做,因为你的初始版本过于庞大和僵化,无法演变成用户想要的东西。
It's more efficient for us, and better for the startups too. Several groups said our weekly dinners saved them from a common problem afflicting startups: working so hard that one has no social life. (I remember that part all too well.) This way, they were guaranteed a social event at least once a week. Independence I've heard Y Combinator described as an "incubator." Actually we're the opposite: incubators exert more control than ordinary VCs, and we make a point of exerting less. Among other things, incubators usually make you work in their office-- that's where the word "incubator" comes from. That seems the wrong model. If investors get too involved, they smother one of the most powerful forces in a startup: the feeling that it's your own company. Incubators were conspicuous failures during the Bubble. There's still debate about whether this was because of the Bubble, or because they're a bad idea. My vote is they're a bad idea. I think they fail because they select for the wrong people. When we were starting a startup, we would never have taken funding from an "incubator." We can find office space, thanks; just give us the money. And people with that attitude are the ones likely to succeed in startups. Indeed, one quality all the founders shared this summer was a spirit of independence. I've been wondering about that. Are some people just a lot more independent than others, or would everyone be this way if they were allowed to? As with most nature/nurture questions, the answer is probably: some of each. But my main conclusion from the summer is that there's more environment in the mix than most people realize. I could see that from how the founders' attitudes _changed_ during the summer. Most were emerging from twenty or so years of being told what to do. They seemed a little surprised at having total freedom.
我怀疑这是初创企业击败大公司的另一个原因。初创企业可以不负责任地发布足够轻量以演化的1.0版本。在大公司中,所有压力都指向过度工程化。
今年夏天我们好奇的一件事是这些团队在哪些方面需要帮助。结果差异很大。有些我们需要提供技术建议——例如,如何设置应用程序在多台服务器上运行。大多数我们需要帮助解决战略问题,比如申请什么专利,什么收费什么免费。几乎所有人都想获得关于未来投资者的建议:他们应该拿多少钱,应该期待什么样的条款?
然而,所有团队都很快学会了如何处理专利和投资者等问题。这些问题本质上并不难,只是不熟悉。
令人惊讶——甚至有点可怕——的是他们学习的速度。在投资者演示日前的周末,我们举行了一次练习会,所有团队都进行了演示。演示都很糟糕。我们试图解释如何改进,但并不抱太大希望。因此在演示日,我告诉在场的天使投资人和风险投资家,这些人是黑客,不是MBA,所以虽然他们的软件很好,但不应期待他们能做出流畅的演示。
But they grew into it really quickly; some of these guys now seem about four inches taller (metaphorically) than they did at the beginning of the summer. When we asked the summer founders what surprised them most about starting a company, one said "the most shocking thing is that it worked." It will take more experience to know for sure, but my guess is that a lot of hackers could do this-- that if you put people in a position of independence, they develop the qualities they need. Throw them off a cliff, and most will find on the way down that they have wings. The reason this is news to anyone is that the same forces work in the other direction too. Most hackers are employees, and this molds you into someone to whom starting a startup seems impossible as surely as starting a startup molds you into someone who can handle it. If I'm right, "hacker" will mean something different in twenty years than it does now. Increasingly it will mean the people who run the company. Y Combinator is just accelerating a process that would have happened anyway. Power is shifting from the people who deal with money to the people who create technology, and if our experience this summer is any guide, this will be a good thing. Notes [1] By heavy-duty security I mean efforts to protect against truly determined attackers. The image shows us, the 2005 summer founders, and Smartleaf co-founders Mark Nitzberg and Olin Shivers at the 30-foot table Kate Courteau designed for us. Photo by Alex Lewin. Thanks to Sarah Harlin, Steve Huffman, Jessica Livingston, Zak Stone, and Aaron Swartz for reading drafts of this.
| Romanian Translation | | | Japanese Translation.
然后,这些团队进行了极其流畅的演示。结结巴巴的功能列表背诵消失了。仿佛他们过去一周在表演学校度过。我至今不知道他们是如何做到的。
也许观看彼此的演示帮助他们看到了自己的错误。就像在大学里一样,夏季创始人从彼此身上学到了很多——可能比从我们这里学到的更多。他们面临的许多问题是相同的,从与投资者打交道到编写Javascript。
我不想给人留下今年夏天没有问题的印象。许多事情出错了,这在初创企业中很常见。一支团队从一些风险投资公司那里得到了一份“爆炸性条款”。几乎所有与大公司打交道的团队都发现大公司做任何事情都无限缓慢。(这是意料之中的。如果大公司不是无能,初创企业就没有生存空间。)当然,还有通常与服务器相关的噩梦。
简而言之,今年夏天的灾难只是常见的成长烦恼。今年夏天的八家初创企业中,有些最终可能会失败;如果八家全部成功,那将是奇迹。但杀死它们的不会是戏剧性的外部威胁,而是平凡的内部问题:没有完成足够的工作。
不过,到目前为止,消息都是好的。事实上,我们惊讶于这个夏天对我们来说如此有趣。主要原因是
August 2005 Thirty years ago, one was supposed to work one's way up the corporate ladder. That's less the rule now. Our generation wants to get paid up front. Instead of developing a product for some big company in the expectation of getting job security in return, we develop the product ourselves, in a startup, and sell it to the big company. At the very least we want options. Among other things, this shift has created the appearance of a rapid increase in economic inequality. But really the two cases are not as different as they look in economic statistics. Economic statistics are misleading because they ignore the value of safe jobs. An easy job from which one can't be fired is worth money; exchanging the two is one of the commonest forms of corruption. A sinecure is, in effect, an annuity. Except sinecures don't appear in economic statistics. If they did, it would be clear that in practice socialist countries have nontrivial disparities of wealth, because they usually have a class of powerful bureaucrats who are paid mostly by seniority and can never be fired. While not a sinecure, a position on the corporate ladder was genuinely valuable, because big companies tried not to fire people, and promoted from within based largely on seniority. A position on the corporate ladder had a value analogous to the "goodwill" that is a very real element in the valuation of companies. It meant one could expect future high paying jobs. One of main causes of the decay of the corporate ladder is the trend for takeovers that began in the 1980s. Why waste your time climbing a ladder that might disappear before you reach the top? And, by no coincidence, the corporate ladder was one of the reasons the early corporate raiders were so successful. It's not only economic statistics that ignore the value of safe jobs. Corporate balance sheets do too.
One reason it was profitable to carve up 1980s companies and sell them for parts was that they hadn't formally acknowledged their implicit debt to employees who had done good work and expected to be rewarded with high-paying executive jobs when their time came. In the movie _Wall Street_ , Gordon Gekko ridicules a company overloaded with vice presidents. But the company may not be as corrupt as it seems; those VPs' cushy jobs were probably payment for work done earlier. I like the new model better. For one thing, it seems a bad plan to treat jobs as rewards. Plenty of good engineers got made into bad managers that way. And the old system meant people had to deal with a lot more corporate politics, in order to protect the work they'd invested in a position on the ladder. The big disadvantage of the new system is that it involves more risk. If you develop ideas in a startup instead of within a big company, any number of random factors could sink you before you can finish. But maybe the older generation would laugh at me for saying that the way we do things is riskier. After all, projects within big companies were always getting cancelled as a result of arbitrary decisions from higher up. My father's entire industry (breeder reactors) disappeared that way. For better or worse, the idea of the corporate ladder is probably gone for good. The new model seems more liquid, and more efficient. But it is less of a change, financially, than one might think. Our fathers weren't _that_ stupid.
| Romanian Translation | | | Japanese Translation.
2005年8月 三十年前,人们理应沿着企业晋升阶梯一步步向上爬。如今这已不再是铁律。我们这代人想要预先获得报酬。我们不再指望通过为某家大公司开发产品来换取职业保障,而是选择在初创企业自己开发产品,然后将其出售给大公司。至少我们也要求获得期权。 这种转变带来的诸多影响之一,就是经济不平等现象看似急剧加剧。但实际上,这两种情况在经济统计数据中呈现的差异并非真实差距。 经济统计具有误导性,因为它忽视了稳定工作的价值。一份轻松且不会被解雇的工作本身就是金钱;二者间的交易是最常见的腐败形式之一。事实上,闲职就是一种年金。只不过经济统计中从不体现闲职价值。若将其纳入统计,就会明显看出社会主义国家实际存在着显著的财富差距——因为这些国家通常存在一个由资深官僚构成的阶层,他们主要按资历获取报酬且永不失业。 虽然不算闲职,但企业晋升阶梯上的职位确实具有实质价值,因为大公司尽量避免解雇员工,且晋升主要依据资历。这种职位的价值类似于企业估值中非常真实的"商誉"概念,意味着持有者可以预期未来获得高薪职位。 企业晋升阶梯衰败的主因之一,是始于1980年代的收购浪潮。何必费心攀登一座可能在登顶前就消失的阶梯? 绝非巧合的是,这种阶梯制度正是早期企业狙击手如此成功的原因之一。不仅经济统计会忽略稳定工作的价值,企业资产负债表同样如此。1980年代的公司被拆分出售能获利,部分原因就在于它们从未正式承认对优秀员工的隐性债务——这些员工理应在其时获得高薪管理职位作为回报。 在电影《华尔街》中,戈登·盖柯嘲笑某公司副总裁泛滥。但该公司可能没那么腐败:这些副总裁的闲职很可能是对他们过往工作的偿付。 我更喜欢新模式。首先,将职位作为奖励本就不是好主意。多少优秀工程师就这样被培养成了糟糕的管理者。旧体系还意味着人们必须应对更多办公室政治,以保护他们在晋升阶梯上投入的心血。 新体系的最大劣势是风险更高。若在初创企业而非大公司内部开发创意,无数随机因素都可能让你半途夭折。但老一辈或许会嘲笑我说我们的方式更冒险——毕竟大公司内部项目也常因高层武断决策而夭折。我父亲所在的整个行业(增殖反应堆)就是这样消失的。 无论好坏,企业晋升阶梯的理念可能永远消失了。新模式看起来更具流动性,也更高效。但从财务角度看,这种转变并不像人们想象的那么剧烈。我们的父辈并没有那么愚蠢。
August 2005 _(This essay is derived from a talk at Defcon 2005.)_ Suppose you wanted to get rid of economic inequality. There are two ways to do it: give money to the poor, or take it away from the rich. But they amount to the same thing, because if you want to give money to the poor, you have to get it from somewhere. You can't get it from the poor, or they just end up where they started. You have to get it from the rich. There is of course a way to make the poor richer without simply shifting money from the rich. You could help the poor become more productive — for example, by improving access to education. Instead of taking money from engineers and giving it to checkout clerks, you could enable people who would have become checkout clerks to become engineers. This is an excellent strategy for making the poor richer. But the evidence of the last 200 years shows that it doesn't reduce economic inequality, because it makes the rich richer too. If there are more engineers, then there are more opportunities to hire them and to sell them things. Henry Ford couldn't have made a fortune building cars in a society in which most people were still subsistence farmers; he would have had neither workers nor customers. If you want to reduce economic inequality instead of just improving the overall standard of living, it's not enough just to raise up the poor. What if one of your newly minted engineers gets ambitious and goes on to become another Bill Gates? Economic inequality will be as bad as ever. If you actually want to compress the gap between rich and poor, you have to push down on the top as well as pushing up on the bottom. How do you push down on the top? You could try to decrease the productivity of the people who make the most money: make the best surgeons operate with their left hands, force popular actors to overeat, and so on. But this approach is hard to implement.
(本文源自2005年Defcon大会的演讲)
假设你想消除经济不平等。有两种方法可以实现:给穷人钱,或者从富人那里拿走钱。但它们本质上是相同的,因为如果你想给穷人钱,你必须从某个地方获取。你不能从穷人那里拿,否则他们最终还是会回到原点。你必须从富人那里拿。
当然,有一种方法可以让穷人变得更富有,而不只是简单地将钱从富人那里转移。你可以帮助穷人提高生产力——例如,通过改善教育机会。与其从工程师那里拿钱给收银员,不如让那些原本可能成为收银员的人成为工程师。
这是让穷人变得更富有的绝佳策略。但过去200年的证据表明,这并不会减少经济不平等,因为它也会让富人变得更富有。如果有更多的工程师,就会有更多的机会雇佣他们并向他们销售产品。亨利·福特在一个大多数人仍是自给自足农民的社会中不可能通过制造汽车致富;他既不会有工人,也不会有客户。
如果你想减少经济不平等,而不仅仅是提高整体生活水平,仅仅提升穷人是不够的。如果你培养的新工程师中有人雄心勃勃,最终成为另一个比尔·盖茨呢?经济不平等仍会和以前一样严重。如果你真的想缩小贫富差距,你必须在压低顶层的同时抬高底层。
The only practical solution is to let people do the best work they can, and then (either by taxation or by limiting what they can charge) to confiscate whatever you deem to be surplus. So let's be clear what reducing economic inequality means. It is identical with taking money from the rich. When you transform a mathematical expression into another form, you often notice new things. So it is in this case. Taking money from the rich turns out to have consequences one might not foresee when one phrases the same idea in terms of "reducing inequality." The problem is, risk and reward have to be proportionate. A bet with only a 10% chance of winning has to pay more than one with a 50% chance of winning, or no one will take it. So if you lop off the top of the possible rewards, you thereby decrease people's willingness to take risks. Transposing into our original expression, we get: decreasing economic inequality means decreasing the risk people are willing to take. There are whole classes of risks that are no longer worth taking if the maximum return is decreased. One reason high tax rates are disastrous is that this class of risks includes starting new companies. Investors Startups are intrinsically risky. A startup is like a small boat in the open sea. One big wave and you're sunk. A competing product, a downturn in the economy, a delay in getting funding or regulatory approval, a patent suit, changing technical standards, the departure of a key employee, the loss of a big account — any one of these can destroy you overnight. It seems only about 1 in 10 startups succeeds. [1] Our startup paid its first round of outside investors 36x. Which meant, with current US tax rates, that it made sense to invest in us if we had better than a 1 in 24 chance of succeeding. That sounds about right. That's probably roughly how we looked when we were a couple of nerds with no business experience operating out of an apartment.
如何压低顶层?你可以尝试降低那些赚最多钱的人的生产力:让最好的外科医生用左手做手术,强迫受欢迎的演员暴饮暴食,等等。但这种方法很难实施。唯一可行的解决方案是让人们尽其所能地工作,然后(通过税收或限制他们的收费)没收你认为多余的部分。
因此,让我们明确减少经济不平等的含义。它与从富人那里拿钱是相同的。
当你将一个数学表达式转换为另一种形式时,你常常会注意到新的事物。这里也是如此。从富人那里拿钱会带来一些后果,而这些后果在用“减少不平等”表达时可能不会被预见。
问题在于,风险和回报必须成比例。一个只有10%胜率的赌注必须比50%胜率的赌注支付更多,否则没人会接受。因此,如果你削减可能的最高回报,你就会降低人们承担风险的意愿。
转换回我们最初的表述,我们得到:减少经济不平等意味着减少人们愿意承担的风险。
If that kind of risk doesn't pay, venture investing, as we know it, doesn't happen. That might be ok if there were other sources of capital for new companies. Why not just have the government, or some large almost-government organization like Fannie Mae, do the venture investing instead of private funds? I'll tell you why that wouldn't work. Because then you're asking government or almost-government employees to do the one thing they are least able to do: take risks. As anyone who has worked for the government knows, the important thing is not to make the right choices, but to make choices that can be justified later if they fail. If there is a safe option, that's the one a bureaucrat will choose. But that is exactly the wrong way to do venture investing. The nature of the business means that you want to make terribly risky choices, if the upside looks good enough. VCs are currently paid in a way that makes them focus on the upside: they get a percentage of the fund's gains. And that helps overcome their understandable fear of investing in a company run by nerds who look like (and perhaps are) college students. If VCs weren't allowed to get rich, they'd behave like bureaucrats. Without hope of gain, they'd have only fear of loss. And so they'd make the wrong choices. They'd turn down the nerds in favor of the smooth-talking MBA in a suit, because that investment would be easier to justify later if it failed. Founders But even if you could somehow redesign venture funding to work without allowing VCs to become rich, there's another kind of investor you simply cannot replace: the startups' founders and early employees. What they invest is their time and ideas. But these are equivalent to money; the proof is that investors are willing (if forced) to treat them as interchangeable, granting the same status to "sweat equity" and the equity they've purchased with cash.
如果最大回报被降低,许多类别的风险就不再值得承担。高税率之所以灾难性的原因之一是,这类风险包括创办新公司。
初创企业本质上是高风险的。初创企业就像大海中的一叶小舟。一个大浪就能让你沉没。竞争产品、经济衰退、融资或监管批准的延迟、专利诉讼、技术标准的变化、关键员工的离职、大客户的流失——任何一项都可能在一夜之间摧毁你。似乎只有大约十分之一的初创企业能够成功。[1]
我们的初创企业为第一轮外部投资者带来了36倍的回报。这意味着,按照美国当前的税率,如果我们成功的概率高于1/24,投资我们就是合理的。这听起来差不多。当我们还是两个没有商业经验、在公寓里办公的书呆子时,情况可能大致如此。
如果这种风险得不到回报,我们所知的风险投资就不会发生。
如果新公司有其他资金来源,这或许没问题。为什么不让政府或类似房利美这样的大型准政府组织代替私人基金进行风险投资呢?
The fact that you're investing time doesn't change the relationship between risk and reward. If you're going to invest your time in something with a small chance of succeeding, you'll only do it if there is a proportionately large payoff. [2] If large payoffs aren't allowed, you may as well play it safe. Like many startup founders, I did it to get rich. But not because I wanted to buy expensive things. What I wanted was security. I wanted to make enough money that I didn't have to worry about money. If I'd been forbidden to make enough from a startup to do this, I would have sought security by some other means: for example, by going to work for a big, stable organization from which it would be hard to get fired. Instead of busting my ass in a startup, I would have tried to get a nice, low-stress job at a big research lab, or tenure at a university. That's what everyone does in societies where risk isn't rewarded. If you can't ensure your own security, the next best thing is to make a nest for yourself in some large organization where your status depends mostly on seniority. [3] Even if we could somehow replace investors, I don't see how we could replace founders. Investors mainly contribute money, which in principle is the same no matter what the source. But the founders contribute ideas. You can't replace those. Let's rehearse the chain of argument so far. I'm heading for a conclusion to which many readers will have to be dragged kicking and screaming, so I've tried to make each link unbreakable. Decreasing economic inequality means taking money from the rich. Since risk and reward are equivalent, decreasing potential rewards automatically decreases people's appetite for risk. Startups are intrinsically risky. Without the prospect of rewards proportionate to the risk, founders will not invest their time in a startup. Founders are irreplaceable. So eliminating economic inequality means eliminating startups.
我来告诉你为什么这行不通。因为这样一来,你要求政府或准政府员工做他们最不擅长的事情:承担风险。
任何为政府工作过的人都知道,重要的不是做出正确的选择,而是做出那些如果失败后可以合理解释的选择。如果有安全的选择,官僚会选择它。但这恰恰是风险投资的错误方式。这一行业的本质意味着,如果潜在收益足够高,你希望做出极其冒险的选择。
风险投资家目前的报酬方式让他们专注于潜在收益:他们获得基金收益的一定比例。这有助于克服他们对投资一家由看起来像(或确实是)大学生的书呆子运营的公司的恐惧。
如果不允许风险投资家致富,他们会表现得像官僚一样。没有获利的希望,他们只会害怕损失。因此,他们会做出错误的选择。他们会拒绝书呆子,转而选择西装革履、能说会道的MBA,因为如果投资失败,后者更容易事后解释。
但即使你能以某种方式重新设计风险投资,使其在不允许风险投资家致富的情况下运作,还有一类投资者你根本无法替代:初创企业的创始人和早期员工。
Economic inequality is not just a consequence of startups. It's the engine that drives them, in the same way a fall of water drives a water mill. People start startups in the hope of becoming much richer than they were before. And if your society tries to prevent anyone from being much richer than anyone else, it will also prevent one person from being much richer at t2 than t1. Growth This argument applies proportionately. It's not just that if you eliminate economic inequality, you get no startups. To the extent you reduce economic inequality, you decrease the number of startups. [4] Increase taxes, and willingness to take risks decreases in proportion. And that seems bad for everyone. New technology and new jobs both come disproportionately from new companies. Indeed, if you don't have startups, pretty soon you won't have established companies either, just as, if you stop having kids, pretty soon you won't have any adults. It sounds benevolent to say we ought to reduce economic inequality. When you phrase it that way, who can argue with you? _Inequality_ has to be bad, right? It sounds a good deal less benevolent to say we ought to reduce the rate at which new companies are founded. And yet the one implies the other. Indeed, it may be that reducing investors' appetite for risk doesn't merely kill off larval startups, but kills off the most promising ones especially. Startups yield faster growth at greater risk than established companies. Does this trend also hold among startups? That is, are the riskiest startups the ones that generate most growth if they succeed? I suspect the answer is yes. And that's a chilling thought, because it means that if you cut investors' appetite for risk, the most beneficial startups are the first to go. Not all rich people got that way from startups, of course.
他们投入的是时间和想法。但这些等同于金钱;证明是投资者愿意(如果被迫)将它们视为可互换的,给予“汗水股权”和用现金购买的股权相同的地位。
投入时间并不会改变风险与回报的关系。如果你要将时间投入一个成功概率很小的项目,你只会这样做,前提是存在与之成比例的巨额回报。[2] 如果巨额回报不被允许,你不如选择稳妥的方式。
和许多初创企业创始人一样,我这样做是为了致富。但不是因为我想买昂贵的东西。我想要的是安全感。我想赚足够的钱,这样我就不必担心钱的问题。如果我被禁止通过初创企业赚到足够的钱来实现这一点,我会通过其他方式寻求安全感:例如,去一家大型稳定的组织工作,很难被解雇。我不会在初创企业拼命工作,而是会试图在一家大型研究实验室找到一份轻松、低压力的工作,或者在大学获得终身教职。
在风险不被奖励的社会中,每个人都会这样做。如果你无法确保自己的安全,次优选择是在某个大型组织中为自己筑巢,你的地位主要取决于资历。[3]
即使我们能以某种方式替代投资者,我也看不出如何替代创始人。投资者主要贡献金钱,原则上无论来源如何都是一样的。但创始人贡献的是想法。你无法替代这些。
What if we let people get rich by starting startups, but taxed away all other surplus wealth? Wouldn't that at least decrease inequality? Less than you might think. If you made it so that people could only get rich by starting startups, people who wanted to get rich would all start startups. And that might be a great thing. But I don't think it would have much effect on the distribution of wealth. People who want to get rich will do whatever they have to. If startups are the only way to do it, you'll just get far more people starting startups. (If you write the laws very carefully, that is. More likely, you'll just get a lot of people doing things that can be made to look on paper like startups.) If we're determined to eliminate economic inequality, there is still one way out: we could say that we're willing to go ahead and do without startups. What would happen if we did? At a minimum, we'd have to accept lower rates of technological growth. If you believe that large, established companies could somehow be made to develop new technology as fast as startups, the ball is in your court to explain how. (If you can come up with a remotely plausible story, you can make a fortune writing business books and consulting for large companies.) [5] Ok, so we get slower growth. Is that so bad? Well, one reason it's bad in practice is that other countries might not agree to slow down with us. If you're content to develop new technologies at a slower rate than the rest of the world, what happens is that you don't invent anything at all. Anything you might discover has already been invented elsewhere. And the only thing you can offer in return is raw materials and cheap labor. Once you sink that low, other countries can do whatever they like with you: install puppet governments, siphon off your best workers, use your women as prostitutes, dump their toxic waste on your territory — all the things we do to poor countries now.
让我们回顾一下到目前为止的论证链条。我正走向一个许多读者会抗拒的结论,因此我试图让每个环节都无懈可击。减少经济不平等意味着从富人那里拿钱。由于风险和回报是等价的,减少潜在回报会自动降低人们承担风险的意愿。初创企业本质上是高风险的。如果没有与风险成比例的回报前景,创始人不会将时间投入初创企业。创始人是不可替代的。因此,消除经济不平等意味着消除初创企业。
经济不平等不仅是初创企业的结果。它是驱动初创企业的引擎,就像落水驱动水车一样。人们创办初创企业是希望变得比从前富有得多。如果你的社会试图阻止任何人比其他人富有得多,它也会阻止一个人在t2时比t1时富有得多。
这一论证是成比例的。不仅仅是如果你消除经济不平等,你就不会有初创企业。你减少经济不平等的程度,就会减少初创企业的数量。[4] 提高税收,承担风险的意愿会成比例下降。
这对所有人来说似乎都不好。新技术和新工作都主要来自新公司。事实上,如果你没有初创企业,很快你也不会有成熟的公司,就像如果你停止生育,很快你就不会有任何成年人。
说我们应该减少经济不平等听起来很仁慈。当你这样表达时,谁能反驳你?“不平等”一定是坏的,对吧?说我们应该降低新公司的创立率听起来就不那么仁慈了。然而,前者意味着后者。
The only defense is to isolate yourself, as communist countries did in the twentieth century. But the problem then is, you have to become a police state to enforce it. Wealth and Power I realize startups are not the main target of those who want to eliminate economic inequality. What they really dislike is the sort of wealth that becomes self-perpetuating through an alliance with power. For example, construction firms that fund politicians' campaigns in return for government contracts, or rich parents who get their children into good colleges by sending them to expensive schools designed for that purpose. But if you try to attack this type of wealth through _economic_ policy, it's hard to hit without destroying startups as collateral damage. The problem here is not wealth, but corruption. So why not go after corruption? We don't need to prevent people from being rich if we can prevent wealth from translating into power. And there has been progress on that front. Before he died of drink in 1925, Commodore Vanderbilt's wastrel grandson Reggie ran down pedestrians on five separate occasions, killing two of them. By 1969, when Ted Kennedy drove off the bridge at Chappaquiddick, the limit seemed to be down to one. Today it may well be zero. But what's changed is not variation in wealth. What's changed is the ability to translate wealth into power. How do you break the connection between wealth and power? Demand transparency. Watch closely how power is exercised, and demand an account of how decisions are made. Why aren't all police interrogations videotaped? Why did 36% of Princeton's class of 2007 come from prep schools, when only 1.7% of American kids attend them? Why did the US really invade Iraq? Why don't government officials disclose more about their finances, and why only during their term of office? A friend of mine who knows a lot about computer security says the single most important step is to log everything.
事实上,降低投资者对风险的偏好不仅可能扼杀初期的初创企业,还可能尤其扼杀最有前途的那些。初创企业比成熟公司以更高的风险带来更快的增长。这一趋势在初创企业中也成立吗?即,风险最高的初创企业是否在成功时带来最大的增长?我怀疑答案是肯定的。这是一个令人不寒而栗的想法,因为这意味着如果你削减投资者对风险的偏好,最有价值的初创企业会最先消失。
当然,并非所有富人都是通过初创企业致富的。如果我们允许人们通过创办初创企业致富,但对所有其他剩余财富征税呢?这至少会减少不平等吧?
比你想象的要少。如果你让人们只能通过创办初创企业致富,那些想致富的人都会去创办初创企业。这可能是件好事。但我不认为这会对财富分配产生太大影响。想致富的人会做任何必须做的事。如果初创企业是唯一的途径,你只会看到更多人创办初创企业。(前提是你非常仔细地制定法律。更有可能的是,你只会看到很多人做那些在纸面上看起来像初创企业的事情。)
如果我们决心消除经济不平等,仍有一条出路:我们可以说我们愿意放弃初创企业。如果我们这样做,会发生什么?
至少,我们必须接受较低的技术增长率。如果你认为大型成熟公司可以以某种方式像初创企业一样快速开发新技术,那么你需要解释如何实现。(如果你能想出一个哪怕勉强合理的故事,你可以通过写商业书籍和为大型公司咨询致富。)[5]
Back when he was a kid trying to break into computers, what worried him most was the idea of leaving a trail. He was more inconvenienced by the need to avoid that than by any obstacle deliberately put in his path. Like all illicit connections, the connection between wealth and power flourishes in secret. Expose all transactions, and you will greatly reduce it. Log everything. That's a strategy that already seems to be working, and it doesn't have the side effect of making your whole country poor. I don't think many people realize there is a connection between economic inequality and risk. I didn't fully grasp it till recently. I'd known for years of course that if one didn't score in a startup, the other alternative was to get a cozy, tenured research job. But I didn't understand the equation governing my behavior. Likewise, it's obvious empirically that a country that doesn't let people get rich is headed for disaster, whether it's Diocletian's Rome or Harold Wilson's Britain. But I did not till recently understand the role risk played. If you try to attack wealth, you end up nailing risk as well, and with it growth. If we want a fairer world, I think we're better off attacking one step downstream, where wealth turns into power. Notes [1] Success here is defined from the initial investors' point of view: either an IPO, or an acquisition for more than the valuation at the last round of funding. The conventional 1 in 10 success rate is suspiciously neat, but conversations with VCs suggest it's roughly correct for startups overall. Top VC firms expect to do better. [2] I'm not claiming founders sit down and calculate the expected after-tax return from a startup. They're motivated by examples of other people who did it. And those examples do reflect after-tax returns. [3] Conjecture: The variation in wealth in a (non-corrupt) country or organization will be inversely proportional to the prevalence of systems of seniority.
好吧,那么我们会有更慢的增长。这有那么糟糕吗?实际上,一个糟糕的原因是其他国家可能不会同意和我们一起放慢速度。如果你满足于以比世界其他地区更慢的速度开发新技术,结果是你根本不会发明任何东西。你可能发现的任何东西都已在其他地方发明。你唯一能提供的回报是原材料和廉价劳动力。一旦你沦落到这种地步,其他国家可以对你为所欲为:扶植傀儡政府、挖走你最优秀的工人、将你的女性用作妓女、将他们的有毒废物倾倒到你的领土上——所有我们现在对贫穷国家做的事情。唯一的防御是像20世纪的共产主义国家那样孤立自己。但问题是,你必须成为一个警察国家来强制执行。
我意识到初创企业并不是那些想消除经济不平等的人的主要目标。他们真正厌恶的是那种通过与权力结盟而自我延续的财富。例如,建筑公司资助政客的竞选活动以换取政府合同,或富有的父母通过将孩子送到为此目的设计的昂贵学校将他们送入好大学。但如果你试图通过经济政策打击这种财富,很难在不摧毁初创企业作为附带损害的情况下做到。
这里的问题不是财富,而是腐败。那么为什么不直接打击腐败呢?
如果我们能阻止财富转化为权力,我们就不需要阻止人们致富。在这方面已经取得了一些进展。1925年,范德比尔特海军上将的败家子孙子雷吉因酗酒去世前,曾五次撞倒行人,导致两人死亡。到1969年,当泰德·肯尼迪在查帕奎迪克驾车坠桥时,上限似乎已降至一人。今天可能是零。但改变的并不是财富的差异。改变的是将财富转化为权力的能力。
如何打破财富与权力之间的联系?要求透明。密切关注权力的行使方式,并要求解释决策是如何做出的。为什么不是所有的警察审讯都被录像?为什么普林斯顿大学2007届学生中有36%来自预科学校,而美国只有1.7%的孩子上这类学校?美国为什么真的入侵伊拉克?为什么政府官员不披露更多关于他们的财务状况,而且为什么只在任期内披露?
So if you suppress variation in wealth, seniority will become correspondingly more important. So far, I know of no counterexamples, though in very corrupt countries you may get both simultaneously. (Thanks to Daniel Sobral for pointing this out.) [4] In a country with a truly feudal economy, you might be able to redistribute wealth successfully, because there are no startups to kill. [5] The speed at which startups develop new techology is the other reason they pay so well. As I explained in "How to Make Wealth", what you do in a startup is compress a lifetime's worth of work into a few years. It seems as dumb to discourage that as to discourage risk-taking. Thanks to Chris Anderson, Trevor Blackwell, Dan Giffin, Jessica Livingston, and Evan Williams for reading drafts of this essay, and to Langley Steinert, Sangam Pant, and Mike Moritz for information about venture investing.
| Romanian Translation | | | Dutch Translation | Traditional Chinese Translation | | | Japanese Translation | Hebrew Translation.
我的一位精通计算机安全的朋友说,最重要的一步是记录一切。当他还是个孩子试图入侵计算机时,最让他担心的是留下痕迹的想法。为了避免这一点,他比面对任何故意设置的障碍更感到不便。
像所有非法联系一样,财富与权力的联系在秘密中蓬勃发展。公开所有交易,你将大大减少它。记录一切。这一策略似乎已经奏效,而且不会让你的整个国家陷入贫困的副作用。
我不认为许多人意识到经济不平等与风险之间存在联系。直到最近我才完全理解这一点。多年来我当然知道,如果在初创企业中不成功,另一种选择是获得一份舒适、有终身职位的科研工作。但我没有理解支配我行为的等式。同样,从经验上看,一个不允许人们致富的国家注定会走向灾难,无论是戴克里先的罗马还是哈罗德·威尔逊的英国。但直到最近我才理解风险在其中扮演的角色。
如果你试图打击财富,你最终也会打击风险,随之而来的是增长。如果我们想要一个更公平的世界,我认为更好的方法是打击财富转化为权力的环节。
[1] 这里的成功是从初始投资者的角度定义的:要么是IPO,要么是以高于上一轮融资估值的价格被收购。传统的1/10成功率看起来过于整齐,但与风险投资家的对话表明,这对初创企业整体来说大致正确。顶级风险投资公司期望做得更好。
If you liked this, you may also like _Hackers & Painters_.
[2] 我并不是说创始人会坐下来计算初创企业的税后预期回报。他们受到其他人成功例子的激励。而这些例子确实反映了税后回报。
[3] 推测:一个(非腐败的)国家或组织中财富的差异将与资历制度的普遍程度成反比。因此,如果你压制财富的差异,资历将相应地变得更加重要。到目前为止,我还没有发现反例,尽管在非常腐败的国家,你可能会同时看到两者。(感谢Daniel Sobral指出这一点。)
[4] 在一个真正封建经济的国家,你可能能够成功重新分配财富,因为没有初创企业可扼杀。
[5] 初创企业开发新技术的速度是它们报酬丰厚的另一个原因。正如我在《如何创造财富》中解释的那样,你在初创企业中所做的是将一生的工作量压缩到几年中。打击这一点就像打击冒险一样愚蠢。
感谢 Chris Anderson、Trevor Blackwell、Dan Giffin、Jessica Livingston和Evan Williams阅读本文草稿,以及Langley Steinert、Sangam Pant和Mike Moritz提供关于风险投资的信息。
如果你喜欢这篇文章,可能也会喜欢《黑客与画家》。
August 2005 _(This essay is derived from a talk at Oscon 2005.)_ Lately companies have been paying more attention to open source. Ten years ago there seemed a real danger Microsoft would extend its monopoly to servers. It seems safe to say now that open source has prevented that. A recent survey found 52% of companies are replacing Windows servers with Linux servers. [1] More significant, I think, is _which_ 52% they are. At this point, anyone proposing to run Windows on servers should be prepared to explain what they know about servers that Google, Yahoo, and Amazon don't. But the biggest thing business has to learn from open source is not about Linux or Firefox, but about the forces that produced them. Ultimately these will affect a lot more than what software you use. We may be able to get a fix on these underlying forces by triangulating from open source and blogging. As you've probably noticed, they have a lot in common. Like open source, blogging is something people do themselves, for free, because they enjoy it. Like open source hackers, bloggers compete with people working for money, and often win. The method of ensuring quality is also the same: Darwinian. Companies ensure quality through rules to prevent employees from screwing up. But you don't need that when the audience can communicate with one another. People just produce whatever they want; the good stuff spreads, and the bad gets ignored. And in both cases, feedback from the audience improves the best work. Another thing blogging and open source have in common is the Web. People have always been willing to do great work for free, but before the Web it was harder to reach an audience or collaborate on projects. Amateurs I think the most important of the new principles business has to learn is that people work a lot harder on stuff they like. Well, that's news to no one.
(本文源自2005年Oscon大会的演讲)
最近企业界对开源越来越关注。十年前微软似乎真的可能将其垄断地位延伸至服务器领域,而现在可以确定地说,开源阻止了这种情况发生。近期调查显示52%的企业正在用Linux服务器替换Windows服务器[1]。
我认为更重要的是这52%企业的身份。如今若有人提议在服务器上运行Windows系统,他必须准备好解释:为什么谷歌、雅虎和亚马逊都不懂服务器,而他却懂?
但商业世界从开源中学到的最重要经验并非关于Linux或Firefox,而是催生它们的深层力量。这些力量最终影响的远不止你使用的软件类型。
So how can I claim business has to learn it? When I say business doesn't know this, I mean the structure of business doesn't reflect it. Business still reflects an older model, exemplified by the French word for working: _travailler_. It has an English cousin, travail, and what it means is torture. [2] This turns out not to be the last word on work, however. As societies get richer, they learn something about work that's a lot like what they learn about diet. We know now that the healthiest diet is the one our peasant ancestors were forced to eat because they were poor. Like rich food, idleness only seems desirable when you don't get enough of it. I think we were designed to work, just as we were designed to eat a certain amount of fiber, and we feel bad if we don't. There's a name for people who work for the love of it: amateurs. The word now has such bad connotations that we forget its etymology, though it's staring us in the face. "Amateur" was originally rather a complimentary word. But the thing to be in the twentieth century was professional, which amateurs, by definition, are not. That's why the business world was so surprised by one lesson from open source: that people working for love often surpass those working for money. Users don't switch from Explorer to Firefox because they want to hack the source. They switch because it's a better browser. It's not that Microsoft isn't trying. They know controlling the browser is one of the keys to retaining their monopoly. The problem is the same they face in operating systems: they can't pay people enough to build something better than a group of inspired hackers will build for free. I suspect professionalism was always overrated-- not just in the literal sense of working for money, but also connotations like formality and detachment.
通过观察开源和博客的共性,我们或许能捕捉这些底层力量。正如你可能注意到的,二者存在诸多相似之处:和开源一样,博客是人们出于热爱而免费创作的事物;和开源黑客一样,博主们与职业人士竞争且常占上风;质量保障机制也同样遵循达尔文法则——企业通过规章制度防止员工犯错,而当受众能自由交流时,这些约束就不再必要。人们自由创作,优质内容自然传播,劣质内容无人问津。在这两个领域,受众反馈都推动着精品的进化。
博客与开源的另一个共同点是都依赖互联网。人们始终愿意免费创造伟大作品,但唯有网络时代才让广泛传播与协作成为可能。
业余爱好者 我认为商业世界最需领悟的新原则是:人们在热爱的事物上会更勤奋工作。这看似常识,为何我仍断言商业界尚未领悟?因为企业架构并未体现这一认知。
现行商业模式仍沿袭古老范式,法语中"工作"(travailler)一词的英文同源词"travail"直指"折磨"[2]。但随着社会富裕,我们对工作的认知正经历类似饮食观念的革新。如今我们知道,祖辈因贫困被迫食用的粗粮恰恰是最健康的选择。正如饕餮美食只在匮乏时才显珍贵,清闲唯有在不得时才显诱人。人类天生需要工作,就像身体需要特定纤维量,不足时便会不适。
为热爱而工作的人被称为"amateur"(业余爱好者)。这个词如今饱含贬义,使我们忽略了其词源本意——它原本是褒义词。但二十世纪推崇的是"professional"(专业人士),而业余者显然不属此列。
Inconceivable as it would have seemed in, say, 1970, I think professionalism was largely a fashion, driven by conditions that happened to exist in the twentieth century. One of the most powerful of those was the existence of "channels." Revealingly, the same term was used for both products and information: there were distribution channels, and TV and radio channels. It was the narrowness of such channels that made professionals seem so superior to amateurs. There were only a few jobs as professional journalists, for example, so competition ensured the average journalist was fairly good. Whereas anyone can express opinions about current events in a bar. And so the average person expressing his opinions in a bar sounds like an idiot compared to a journalist writing about the subject. On the Web, the barrier for publishing your ideas is even lower. You don't have to buy a drink, and they even let kids in. Millions of people are publishing online, and the average level of what they're writing, as you might expect, is not very good. This has led some in the media to conclude that blogs don't present much of a threat-- that blogs are just a fad. Actually, the fad is the word "blog," at least the way the print media now use it. What they mean by "blogger" is not someone who publishes in a weblog format, but anyone who publishes online. That's going to become a problem as the Web becomes the default medium for publication. So I'd like to suggest an alternative word for someone who publishes online. How about "writer?" Those in the print media who dismiss the writing online because of its low average quality are missing an important point: no one reads the _average_ blog. In the old world of channels, it meant something to talk about average quality, because that's what you were getting whether you liked it or not. But now you can read any writer you want. So the average quality of writing online isn't what the print media are competing against.
这就是为什么开源给商界带来震撼一课:为爱创作的人常超越为钱工作者。用户从IE转向Firefox并非想修改源码,而是因为它更优秀。
微软并非不努力。他们清楚浏览器是维系垄断的关键之一,但遭遇与操作系统相同的困境:再高的薪酬也难打造出比激情黑客免费作品更优秀的产品。
我怀疑专业主义始终被高估——不仅指为金钱工作的本义,还包括其形式化与疏离感等内涵。尽管1970年代难以想象,但我认为专业主义很大程度上是二十世纪特定条件下的时尚产物。
其中最关键的因素是"渠道"的存在。意味深长的是,产品与信息共享这一术语:既有分销渠道,也有电视频道。正是渠道的稀缺性造就了专业人士的优越地位。以新闻业为例,专业记者岗位有限,竞争保证了平均水准;而酒吧里任何人都能议论时事,相比记者文章自然显得浅薄。
网络时代,发表观点的门槛更低。无需消费,孩童亦可参与。数百万人在线创作,平均水平确实不高,这使某些媒体人断言博客不足为惧——不过是时髦泡沫。
They're competing against the best writing online. And, like Microsoft, they're losing. I know that from my own experience as a reader. Though most print publications are online, I probably read two or three articles on individual people's sites for every one I read on the site of a newspaper or magazine. And when I read, say, New York Times stories, I never reach them through the Times front page. Most I find through aggregators like Google News or Slashdot or Delicious. Aggregators show how much better you can do than the channel. The New York Times front page is a list of articles written by people who work for the New York Times. Delicious is a list of articles that are interesting. And it's only now that you can see the two side by side that you notice how little overlap there is. Most articles in the print media are boring. For example, the president notices that a majority of voters now think invading Iraq was a mistake, so he makes an address to the nation to drum up support. Where is the man bites dog in that? I didn't hear the speech, but I could probably tell you exactly what he said. A speech like that is, in the most literal sense, not news: there is nothing _new_ in it. [3] Nor is there anything new, except the names and places, in most "news" about things going wrong. A child is abducted; there's a tornado; a ferry sinks; someone gets bitten by a shark; a small plane crashes. And what do you learn about the world from these stories? Absolutely nothing. They're outlying data points; what makes them gripping also makes them irrelevant. As in software, when professionals produce such crap, it's not surprising if amateurs can do better.
其实真正过时的是"博客"这个词,至少是传统媒体使用它的方式。他们所谓的"博主"实指所有网络创作者。随着网络成为默认发布平台,这种称谓将引发混乱。我建议换个词:"作家"如何?
传统媒体人因网络作品平均质量低而轻视之,却忽略了关键:没人会阅读"平均水准"的博客。在渠道垄断时代,谈论平均质量尚有意义,因为受众别无选择;如今人们只读心仪作者。传统媒体真正的竞争对手不是网络平均水准,而是网络顶尖作品。如同微软,他们正在败退。
个人阅读体验印证这点:虽然多数传统媒体都有网络版,但我阅读个人网站文章的数量是报刊网站的两三倍。即便阅读《纽约时报》文章,我也从不通过其首页,而是经由Google News、Slashdot或Delicious等聚合器。聚合器揭示了渠道模式的局限:《纽约时报》首页展示的是其雇员作品,Delicious呈现的则是全网精华,二者重合度之低令人惊讶。
传统媒体多数文章乏善可陈。比如总统发现多数选民认为伊战错误,便发表演说争取支持——这算什么新闻?虽未亲听演讲,我都能复述其内容。这种演说字面意义上就不算新闻,毫无新意[3]。多数"坏事新闻"同样陈腐:儿童绑架、龙卷风、渡轮沉没、鲨鱼袭人、小飞机失事...这些故事教会我们什么?一无所获。它们只是离群数据点,其震撼性正源于无关性。
Live by the channel, die by the channel: if you depend on an oligopoly, you sink into bad habits that are hard to overcome when you suddenly get competition. [4] Workplaces Another thing blogs and open source software have in common is that they're often made by people working at home. That may not seem surprising. But it should be. It's the architectural equivalent of a home-made aircraft shooting down an F-18. Companies spend millions to build office buildings for a single purpose: to be a place to work. And yet people working in their own homes, which aren't even designed to be workplaces, end up being more productive. This proves something a lot of us have suspected. The average office is a miserable place to get work done. And a lot of what makes offices bad are the very qualities we associate with professionalism. The sterility of offices is supposed to suggest efficiency. But suggesting efficiency is a different thing from actually being efficient. The atmosphere of the average workplace is to productivity what flames painted on the side of a car are to speed. And it's not just the way offices look that's bleak. The way people act is just as bad. Things are different in a startup. Often as not a startup begins in an apartment. Instead of matching beige cubicles they have an assortment of furniture they bought used. They work odd hours, wearing the most casual of clothing. They look at whatever they want online without worrying whether it's "work safe." The cheery, bland language of the office is replaced by wicked humor. And you know what? The company at this stage is probably the most productive it's ever going to be. Maybe it's not a coincidence. Maybe some aspects of professionalism are actually a net lose. To me the most demoralizing aspect of the traditional office is that you're supposed to be there at certain times.
如同软件行业,当专业人士产出如此糟粕时,业余者胜出不足为奇。成也渠道,败也渠道:依赖垄断的企业会养成难以克服的恶习,当竞争突至时便一败涂地[4]。
工作场所 博客与开源另一共性是创作者常居家工作。这看似平常却意义非凡——就像自制飞机击落F-18战机。企业耗费巨资建造办公楼,专为工作而设计;而人们在非工作设计的家中反而效率更高。
这印证了许多人的猜想:普通办公室根本不适合高效工作。而许多"专业感"设计恰恰是元凶。办公室的刻板本欲彰显效率,但"显得高效"与"真正高效"天差地别。
普通办公环境的"生产力氛围"如同车身火焰贴纸之于车速。不仅环境压抑,人员行为同样糟糕。
初创公司截然不同:它们常始于公寓,用二手家具替代标准化格子间;工作时间灵活,衣着随意;网络浏览不受限制;办公室客套被犀利幽默取代。而此刻,往往是公司最具生产力的阶段。
There are usually a few people in a company who really have to, but the reason most employees work fixed hours is that the company can't measure their productivity. The basic idea behind office hours is that if you can't make people work, you can at least prevent them from having fun. If employees have to be in the building a certain number of hours a day, and are forbidden to do non-work things while there, then they must be working. In theory. In practice they spend a lot of their time in a no-man's land, where they're neither working nor having fun. If you could measure how much work people did, many companies wouldn't need any fixed workday. You could just say: this is what you have to do. Do it whenever you like, wherever you like. If your work requires you to talk to other people in the company, then you may need to be here a certain amount. Otherwise we don't care. That may seem utopian, but it's what we told people who came to work for our company. There were no fixed office hours. I never showed up before 11 in the morning. But we weren't saying this to be benevolent. We were saying: if you work here we expect you to get a lot done. Don't try to fool us just by being here a lot. The problem with the facetime model is not just that it's demoralizing, but that the people pretending to work interrupt the ones actually working. I'm convinced the facetime model is the main reason large organizations have so many meetings. Per capita, large organizations accomplish very little. And yet all those people have to be on site at least eight hours a day. When so much time goes in one end and so little achievement comes out the other, something has to give. And meetings are the main mechanism for taking up the slack. For one year I worked at a regular nine to five job, and I remember well the strange, cozy feeling that comes over one during meetings. I was very aware, because of the novelty, that I was being paid for programming.
这或许并非巧合。专业主义的某些方面可能净损效率。
传统办公室最令人沮丧的是强制坐班。虽然少数岗位确需如此,但多数员工固定工时的根本原因在于企业无法衡量其产出。
坐班制度的底层逻辑是:若不能确保工作,至少可阻止娱乐。理论上,员工被禁锢在办公场所且禁止私事,就必须工作。实际上他们大量时间处于"无人区"——既非工作也非娱乐。
若能衡量产出,多数企业根本无需固定工时。只需规定任务,何时何地完成随个人意愿。除非协作必需,否则无需到场。
这看似乌托邦,却正是我们对员工的要求:无固定工时(我本人从不在上午11点前出现)。这非关仁慈,而是明确:我们只看重成果,别想用"刷脸"蒙混过关。
It seemed just amazing, as if there was a machine on my desk that spat out a dollar bill every two minutes no matter what I did. Even while I was in the bathroom! But because the imaginary machine was always running, I felt I always ought to be working. And so meetings felt wonderfully relaxing. They counted as work, just like programming, but they were so much easier. All you had to do was sit and look attentive. Meetings are like an opiate with a network effect. So is email, on a smaller scale. And in addition to the direct cost in time, there's the cost in fragmentation-- breaking people's day up into bits too small to be useful. You can see how dependent you've become on something by removing it suddenly. So for big companies I propose the following experiment. Set aside one day where meetings are forbidden-- where everyone has to sit at their desk all day and work without interruption on things they can do without talking to anyone else. Some amount of communication is necessary in most jobs, but I'm sure many employees could find eight hours worth of stuff they could do by themselves. You could call it "Work Day." The other problem with pretend work is that it often looks better than real work. When I'm writing or hacking I spend as much time just thinking as I do actually typing. Half the time I'm sitting drinking a cup of tea, or walking around the neighborhood. This is a critical phase-- this is where ideas come from-- and yet I'd feel guilty doing this in most offices, with everyone else looking busy. It's hard to see how bad some practice is till you have something to compare it to. And that's one reason open source, and even blogging in some cases, are so important. They show us what real work looks like. We're funding eight new startups at the moment. A friend asked what they were doing for office space, and seemed surprised when I said we expected them to work out of whatever apartments they found to live in.
刷脸模式不仅打击士气,更会干扰真正工作者。我确信这是大机构会议泛滥的主因——人均产出极低,却要全员每天坐满八小时。如此巨大时间投入与微弱产出间的差额,只能由会议填补。
我曾有段朝九晚五经历,仍记得会议带来的奇异安逸感。由于新鲜,我清楚意识到自己是在"被付费编程",就像桌上有台每分钟吐0.5美元的机器(即使如厕时也在吐钱)。正因这台想象机器永不停转,我总觉应该工作。于是会议成了美妙放松——它们算工作时间却轻松得多,只需坐着假装专注。
会议如同具有网络效应的鸦片,电子邮件亦然。除了直接时间成本,它们还碎片化工作日,摧毁深度工作可能。
要检验依赖程度,只需突然戒断。因此我建议大企业做此实验:设定"纯工作日",禁止一切会议,所有人必须专注处理无需协作的事务。尽管某些岗位必需沟通,但多数人定能找到八小时独立工作内容。
假装工作的另一问题是常比真实工作更体面。当我写作或编程时,思考与打字时间各半——另一半时间在喝茶或散步。这恰是创意诞生的关键阶段,但在多数办公室,看着周围人"忙碌"的样子,这种状态会令我愧疚。
But we didn't propose that to save money. We did it because we want their software to be good. Working in crappy informal spaces is one of the things startups do right without realizing it. As soon as you get into an office, work and life start to drift apart. That is one of the key tenets of professionalism. Work and life are supposed to be separate. But that part, I'm convinced, is a mistake. Bottom-Up The third big lesson we can learn from open source and blogging is that ideas can bubble up from the bottom, instead of flowing down from the top. Open source and blogging both work bottom-up: people make what they want, and the best stuff prevails. Does this sound familiar? It's the principle of a market economy. Ironically, though open source and blogs are done for free, those worlds resemble market economies, while most companies, for all their talk about the value of free markets, are run internally like communist states. There are two forces that together steer design: ideas about what to do next, and the enforcement of quality. In the channel era, both flowed down from the top. For example, newspaper editors assigned stories to reporters, then edited what they wrote. Open source and blogging show us things don't have to work that way. Ideas and even the enforcement of quality can flow bottom-up. And in both cases the results are not merely acceptable, but better. For example, open source software is more reliable precisely because it's open source; anyone can find mistakes. The same happens with writing. As we got close to publication, I found I was very worried about the essays in Hackers & Painters that hadn't been online. Once an essay has had a couple thousand page views I feel reasonably confident about it. But these had had literally orders of magnitude less scrutiny. It felt like releasing software without testing it.
没有对比就难察弊端。这正是开源乃至博客的价值所在:它们展现了真实工作的模样。
我们正资助八家初创公司。当朋友问及办公场地时,对方对我们"在家办公"的要求颇感惊讶。这并非为省钱,而是为保证软件质量——初创公司在简陋环境中的无意之举往往正确。一旦进入正式办公室,工作与生活就开始割裂。
这恰是专业主义的核心教条之一:工作与生活应当分离。但我确信这是谬误。
自下而上 开源与博客的第三课是:创意可以自下而上涌现,而非自上而下灌输。二者都遵循此道:人们创造所欲,优胜劣汰。
That's what all publishing used to be like. If you got ten people to read a manuscript, you were lucky. But I'd become so used to publishing online that the old method now seemed alarmingly unreliable, like navigating by dead reckoning once you'd gotten used to a GPS. The other thing I like about publishing online is that you can write what you want and publish when you want. Earlier this year I wrote something that seemed suitable for a magazine, so I sent it to an editor I know. As I was waiting to hear back, I found to my surprise that I was hoping they'd reject it. Then I could put it online right away. If they accepted it, it wouldn't be read by anyone for months, and in the meantime I'd have to fight word-by-word to save it from being mangled by some twenty five year old copy editor. [5] Many employees would _like_ to build great things for the companies they work for, but more often than not management won't let them. How many of us have heard stories of employees going to management and saying, please let us build this thing to make money for you-- and the company saying no? The most famous example is probably Steve Wozniak, who originally wanted to build microcomputers for his then-employer, HP. And they turned him down. On the blunderometer, this episode ranks with IBM accepting a non-exclusive license for DOS. But I think this happens all the time. We just don't hear about it usually, because to prove yourself right you have to quit and start your own company, like Wozniak did. Startups So these, I think, are the three big lessons open source and blogging have to teach business: (1) that people work harder on stuff they like, (2) that the standard office environment is very unproductive, and (3) that bottom-up often works better than top-down.
这听起来是否耳熟?正是市场经济的原理。讽刺的是,尽管开源与博客皆属无偿创作,其运作却更接近市场经济;而整日鼓吹自由市场的企业,内部运作反而像计划经济。
设计演进受两种力量驱动:关于下一步的创意,以及质量把控。渠道时代,二者皆自上而下。例如报纸编辑指派选题并审核稿件。
开源与博客证明还有另一条路:创意甚至质量把控都可自下而上。结果不仅可行,且更优越。开源软件更可靠正因开放特性——人人可纠错。
写作亦然。在《黑客与画家》出版前夕,我特别担忧书中未公开的篇章——经过数千次浏览检验的文章令我安心,而这些未曝光文章就像未经测试就发布的软件。
传统出版皆如此境。若有十人读过手稿已属幸运。但习惯了网络发布后,传统方式显得惊心 unreliable,如同用航位推测法替代GPS导航。
I can imagine managers at this point saying: what is this guy talking about? What good does it do me to know that my programmers would be more productive working at home on their own projects? I need their asses in here working on version 3.2 of our software, or we're never going to make the release date. And it's true, the benefit that specific manager could derive from the forces I've described is near zero. When I say business can learn from open source, I don't mean any specific business can. I mean business can learn about new conditions the same way a gene pool does. I'm not claiming companies can get smarter, just that dumb ones will die. So what will business look like when it has assimilated the lessons of open source and blogging? I think the big obstacle preventing us from seeing the future of business is the assumption that people working for you have to be employees. But think about what's going on underneath: the company has some money, and they pay it to the employee in the hope that he'll make something worth more than they paid him. Well, there are other ways to arrange that relationship. Instead of paying the guy money as a salary, why not give it to him as investment? Then instead of coming to your office to work on your projects, he can work wherever he wants on projects of his own. Because few of us know any alternative, we have no idea how much better we could do than the traditional employer-employee relationship. Such customs evolve with glacial slowness. Our employer-employee relationship still retains a big chunk of master-servant DNA. [6] I dislike being on either end of it. I'll work my ass off for a customer, but I resent being told what to do by a boss. And being a boss is also horribly frustrating; half the time it's easier just to do stuff yourself than to get someone else to do it for you. I'd rather do almost anything than give or receive a performance review.
网络发布的另一优势是自由创作与即时发布。今年我写了篇适合杂志的文章,寄给相熟编辑后,竟暗自盼望退稿——这样就能立刻网络发布。若被录用,读者要等数月,期间还得逐字与25岁的文案编辑角力[5]。
许多员工渴望为公司创造价值,却屡遭管理层阻挠。类似沃兹尼亚克的故事屡见不鲜——他本想为惠普开发微型电脑,却遭拒绝。这个与IBM接受DOS非独家授权齐名的商业失误,其实时刻在重演,只是多数人没有沃兹尼亚克那样用创业证明自己的机会。
初创企业 因此,开源与博客给商业的三堂课是:1)人们为热爱更勤奋;2)标准办公环境严重低效;3)自下而上常优于自上而下。
此刻或有管理者质疑:程序员在家做自己项目更高效对我何用?我需要他们来办公室赶制软件3.2版,否则无法按期发布。
确实,特定管理者从这些力量中获益近乎零。当我说商业可向开源学习时,非指具体企业能立即应用,而是指商业生态会像基因库般适应新环境。非谓企业能变聪明,只是愚蠢者终将淘汰。
On top of its unpromising origins, employment has accumulated a lot of cruft over the years. The list of what you can't ask in job interviews is now so long that for convenience I assume it's infinite. Within the office you now have to walk on eggshells lest anyone say or do something that makes the company prey to a lawsuit. And God help you if you fire anyone. Nothing shows more clearly that employment is not an ordinary economic relationship than companies being sued for firing people. In any purely economic relationship you're free to do what you want. If you want to stop buying steel pipe from one supplier and start buying it from another, you don't have to explain why. No one can accuse you of _unjustly_ switching pipe suppliers. Justice implies some kind of paternal obligation that isn't there in transactions between equals. Most of the legal restrictions on employers are intended to protect employees. But you can't have action without an equal and opposite reaction. You can't expect employers to have some kind of paternal responsibility toward employees without putting employees in the position of children. And that seems a bad road to go down. Next time you're in a moderately large city, drop by the main post office and watch the body language of the people working there. They have the same sullen resentment as children made to do something they don't want to. Their union has exacted pay increases and work restrictions that would have been the envy of previous generations of postal workers, and yet they don't seem any happier for it. It's demoralizing to be on the receiving end of a paternalistic relationship, no matter how cozy the terms. Just ask any teenager. I see the disadvantages of the employer-employee relationship because I've been on both sides of a better one: the investor-founder relationship. I wouldn't claim it's painless.
当商业消化开源与博客的启示后会是何样?阻碍我们预见未来的,是"员工必属雇员"的思维定势。究其本质:企业用资金换取员工创造更大价值。这种关系本可其他形式存在——何不以投资替代工资?让工作者在自己选择的地方做自己的项目?
因缺乏认知,我们难以想象比传统雇佣更好的模式。这类习俗演化极慢,当今雇佣关系仍残留主仆制的基因[6]。
我厌恶这种关系的两端:愿为客户拼命工作,却抗拒老板指令;当老板同样痛苦——有时亲力亲为比指挥他人更高效。我宁做任何事也不愿参与绩效考核。
雇佣制不仅源流不佳,更在演进中积累沉疴。面试禁问清单已长得只能假设其无限长;办公室内言行需如履薄冰以防诉讼;解雇员工更是噩梦。
When I was running a startup, the thought of our investors used to keep me up at night. And now that I'm an investor, the thought of our startups keeps me up at night. All the pain of whatever problem you're trying to solve is still there. But the pain hurts less when it isn't mixed with resentment. I had the misfortune to participate in what amounted to a controlled experiment to prove that. After Yahoo bought our startup I went to work for them. I was doing exactly the same work, except with bosses. And to my horror I started acting like a child. The situation pushed buttons I'd forgotten I had. The big advantage of investment over employment, as the examples of open source and blogging suggest, is that people working on projects of their own are enormously more productive. And a startup is a project of one's own in two senses, both of them important: it's creatively one's own, and also economically ones's own. Google is a rare example of a big company in tune with the forces I've described. They've tried hard to make their offices less sterile than the usual cube farm. They give employees who do great work large grants of stock to simulate the rewards of a startup. They even let hackers spend 20% of their time on their own projects. Why not let people spend 100% of their time on their own projects, and instead of trying to approximate the value of what they create, give them the actual market value? Impossible? That is in fact what venture capitalists do. So am I claiming that no one is going to be an employee anymore-- that everyone should go and start a startup? Of course not. But more people could do it than do it now. At the moment, even the smartest students leave school thinking they have to get a job. Actually what they need to do is make something valuable.
最能说明雇佣非纯粹经济关系的,莫过于企业因解雇被诉。纯粹经济关系中,你有权自由选择——更换钢管供应商无需解释,没人会指控这是"不公正"转换。"公正"暗含的家长式义务,本不该存在于平等主体间。
多数雇佣法律限制本为保护员工,但作用力等于反作用力。要求雇主承担家长责任,必然将员工置于孩童地位。这绝非良途。
下次路过邮局,请观察工作人员体态语言——他们像被强迫做事的孩子般闷闷不乐。工会争取到的薪资福利和工作限制本应令前辈艳羡,但他们并未因此更快乐。家长式关系中的受施者注定士气低落,无论条件多优渥。问问青少年便知。
我清楚雇佣关系的弊端,因体验过更优模式——投资者与创始人的关系。这绝非轻松:创业时投资人令我夜不能寐;成为YC投资人后,初创公司让我失眠。难题依旧,但少了怨恨的痛苦。
雅虎收购我们后,我被迫参与了一场对照实验:做着完全相同的工作,只是有了老板。可怕的是,我开始表现得像个孩子——这个情境激活了我遗忘已久的按钮。
A job is one way to do that, but the more ambitious ones will ordinarily be better off taking money from an investor than an employer. Hackers tend to think business is for MBAs. But business administration is not what you're doing in a startup. What you're doing is business _creation_. And the first phase of that is mostly product creation-- that is, hacking. That's the hard part. It's a lot harder to create something people love than to take something people love and figure out how to make money from it. Another thing that keeps people away from starting startups is the risk. Someone with kids and a mortgage should think twice before doing it. But most young hackers have neither. And as the example of open source and blogging suggests, you'll enjoy it more, even if you fail. You'll be working on your own thing, instead of going to some office and doing what you're told. There may be more pain in your own company, but it won't hurt as much. That may be the greatest effect, in the long run, of the forces underlying open source and blogging: finally ditching the old paternalistic employer-employee relationship, and replacing it with a purely economic one, between equals. Notes [1] Survey by Forrester Research reported in the cover story of Business Week, 31 Jan 2005. Apparently someone believed you have to replace the actual server in order to switch the operating system. [2] It derives from the late Latin _tripalium_ , a torture device so called because it consisted of three stakes. I don't know how the stakes were used. "Travel" has the same root. [3] It would be much bigger news, in that sense, if the president faced unscripted questions by giving a press conference. [4] One measure of the incompetence of newspapers is that so many still make you register to read stories.
正如开源与博客所示,投资优于雇佣的关键在于:为自己项目工作的人效率倍增。初创公司在双重意义上是自己的项目:既是创作自主,也是经济自主。
谷歌是少数顺应这些趋势的大企业:努力打破格子间单调;用巨额股票奖励模拟创业回报;甚至允许黑客用20%时间做自己的项目。
为何不让员工100%投入个人项目,并给予真实市场价值?这看似不可能,却正是风投的运作模式。
我并非主张雇佣制消亡——人人都该创业。但适合者应远多于现状。如今最聪明的毕业生仍认为必须求职[6],其实他们真正需要的是创造价值。工作只是方式之一,对雄心者而言,拿投资比拿工资更明智。
黑客常认为商业属于MBA。但初创公司所做并非商业管理,而是商业创造——其第一阶段主要是产品创造(即编程)。这才是难点:打造用户热爱的产品,远比从中盈利困难得多。
I have yet to find a blog that tried that. [5] They accepted the article, but I took so long to send them the final version that by the time I did the section of the magazine they'd accepted it for had disappeared in a reorganization. [6] The word "boss" is derived from the Dutch _baas_ , meaning "master." Thanks to Sarah Harlin, Jessica Livingston, and Robert Morris for reading drafts of this.
| French Translation | | | Russian Translation | Japanese Translation | | | Spanish Translation | Arabic Translation.
风险是阻碍创业的另一因素。有家室房贷者确应慎重,但多数年轻黑客两者皆无。
如开源与博客所示,即使失败,过程也更愉悦——你在做自己的事,而非听命行事。自己的公司或许更痛苦,但痛感更轻。
长远看,开源与博客底层力量的最大影响,或许正是彻底抛弃家长式雇佣关系,代之以平等主体间的纯粹经济关系。
注释: [1] 福雷斯特研究公司2005年1月31日《商业周刊》封面报道。显然有人认为更换操作系统必须替换物理服务器。 [2] 源自拉丁语"tripalium"(三根木桩构成的刑具)。"travel"同源。 [3] 若总统召开即兴记者会回应未预设问题,才是真新闻。 [4] 众多报纸仍要求注册阅读,这种无能程度在博客界闻所未闻。 [5] 文章虽被采用,因我拖延交稿,待完成时该杂志栏目已在重组中消失。 [6] "boss"(老板)源自荷兰语"baas"(主人)。
致谢:Sarah Harlin、Jessica Livingston和Robert Morris的审阅。
[](https://s.turbifycdn.com/aah/paulgraham/hiring-is-obsolete-11.gif) Want to start a startup? Get funded by Y Combinator.
May 2005 _(This essay is derived from a talk at the Berkeley CSUA.)_ The three big powers on the Internet now are Yahoo, Google, and Microsoft. Average age of their founders: 24. So it is pretty well established now that grad students can start successful companies. And if grad students can do it, why not undergrads? Like everything else in technology, the cost of starting a startup has decreased dramatically. Now it's so low that it has disappeared into the noise. The main cost of starting a Web-based startup is food and rent. Which means it doesn't cost much more to start a company than to be a total slacker. You can probably start a startup on ten thousand dollars of seed funding, if you're prepared to live on ramen. The less it costs to start a company, the less you need the permission of investors to do it. So a lot of people will be able to start companies now who never could have before. The most interesting subset may be those in their early twenties. I'm not so excited about founders who have everything investors want except intelligence, or everything except energy. The most promising group to be liberated by the new, lower threshold are those who have everything investors want except experience. Market Rate I once claimed that nerds were unpopular in secondary school mainly because they had better things to do than work full-time at being popular. Some said I was just telling people what they wanted to hear. Well, I'm now about to do that in a spectacular way: I think undergraduates are undervalued. Or more precisely, I think few realize the huge spread in the value of 20 year olds. Some, it's true, are not very capable.
[](https://s.turbifycdn.com/aah/paulgraham/hiring-is-obsolete-11.gif) 想创业? 获得 Y Combinator 的资助。
2005年5月 _(本文源自于在伯克利CSUA的一次演讲。)_ 如今互联网的三大巨头是雅虎、谷歌和微软。它们创始人的平均年龄:24岁。因此,研究生可以创办成功的企业,这一点现在已经相当明确了。既然研究生能做到,本科生为什么不行? 与技术领域的其他事物一样,创业的成本已大幅下降。现在成本如此之低,几乎可以忽略不计。基于互联网的创业主要成本是食物和房租。这意味着创业的成本比无所事事地混日子高不了多少。如果你愿意靠拉面度日,或许用一万美元的种子资金就能创业。 创业成本越低,就越不需要投资者的许可。因此,现在很多人可以创业,而以前他们根本做不到。 最有趣的群体可能是二十出头的年轻人。我对那些除了聪明才智外具备投资者所需一切条件,或除了精力外样样俱全的创始人并不那么兴奋。新的、更低的门槛解放的最有前途的群体,是那些除了经验外具备投资者所需一切条件的年轻人。 市场价值 我曾声称,书呆子在中学不受欢迎,主要是因为他们有比全职追求受欢迎更好的事情要做。有人说我只是在告诉人们他们想听的话。好吧,我现在要以一种惊人的方式再次这么做:我认为本科生被低估了。 更准确地说,我认为很少有人意识到20岁年轻人价值的巨大差异。确实,有些人能力不强。但另一些人的能力却超过了绝大多数30岁的人。[1] 迄今为止,问题一直在于很难将他们挑选出来。如果能够回到过去,世界上每一位风险投资家都会试图投资微软。但当时谁会这么做?有多少人能理解这个19岁的年轻人就是比尔·盖茨? 评判年轻人很难,因为(a)他们变化很快,(b)他们之间差异巨大,以及(c)他们个人表现不稳定。最后一点是个大问题。年轻时,即使你很聪明,偶尔也会说些蠢话、做些蠢事。因此,如果筛选标准是过滤掉说蠢话的人(许多投资者和雇主会无意识地这么做),你就会得到很多误判。 大多数直接从大学招聘人员的组织只了解22岁年轻人的平均价值,而这并不高。因此,20世纪大部分时间的观念是,每个人都必须从某个初级职位的实习生开始。组织意识到新人的能力差异很大,但他们没有深入思考这一点,反而倾向于压制这种差异,认为即使是最有前途的年轻人也应该从底层做起,这样他们才不会骄傲自满。 大型组织总是低估最有生产力的年轻人,因为年轻人尚无业绩可衡量,而对他们能力的任何猜测误差都会趋向于平均值。 一个特别有生产力的22岁年轻人该怎么办?你可以做的一件事是绕过组织,直接面向用户。从经济角度看,任何雇佣你的公司都是客户的代理人。他们对你的估值(尽管他们可能没有意识到)是在试图猜测你对用户的价值。但有一种方法可以挑战他们的判断。如果你愿意,你可以选择通过创办自己的公司,让用户直接评估你的价值。 市场比任何雇主都更具辨别力。而且它完全不带歧视。在互联网上,没人知道你是一条狗。更重要的是,没人知道你22岁。用户只关心你的网站或软件是否能满足他们的需求。他们不在乎背后的人是不是高中生。 如果你真的很有生产力,为什么不让雇主按市场价支付你的价值呢?既然你可以创业并让他们收购公司来得到你,为什么要去大公司做一名普通员工? 当大多数人听到“创业”这个词时,他们会想到那些已经上市的著名公司。但大多数成功的创业公司是通过被收购实现的。通常收购方不仅想要技术,还想要创造技术的人。 大公司经常在创业公司盈利前就收购它们。显然,在这种情况下,他们追求的不是收入。他们想要的是开发团队和他们迄今构建的软件。当一家创业公司在六个月内以两三百万美元的价格被收购时,这实际上更像是一笔招聘奖金,而不是收购。 我认为这种事情会越来越多,而且对每个人都有好处。对创业的人来说显然更好,因为他们能提前获得一大笔钱。但我认为这对收购方也更好。大公司的核心问题,以及它们生产力远低于小公司的主要原因,是难以衡量每个人的工作价值。收购初创公司为他们解决了这个问题:收购方在开发者证明自己之前无需支付费用。收购方在下跌时受到保护,但仍能获得大部分上涨收益。 产品开发 收购创业公司还解决了困扰大公司的另一个问题:他们无法进行产品开发。大公司擅长从现有产品中提取价值,但不擅长创造新产品。 为什么?值得详细研究这一现象,因为这是创业公司存在的理由。 首先,大多数大公司都有某种需要保护的势力范围,这往往会扭曲他们的开发决策。例如,基于网络的应用现在很热门,但在微软内部肯定有很多矛盾心理,因为基于网络的软件这一理念本身就威胁到桌面软件。因此,微软最终拥有的任何基于网络的应用,很可能像Hotmail一样,是在公司外部开发的。 大公司不擅长开发新产品的另一个原因是,做这种事的人在大型公司中往往没有太大权力(除非他们恰好是CEO)。颠覆性技术是由颠覆性的人开发的。他们要么不为大公司工作,要么被唯唯诺诺的人排挤,影响力相对较小。 大公司还会失败,因为他们通常每种东西只开发一个。当你只有一个网络浏览器时,你无法对它做任何真正冒险的事。如果有十家不同的创业公司设计了十种不同的网络浏览器,你选择最好的一个,结果可能会更好。 这个问题的更普遍版本是,新想法太多,公司无法全部探索。现在可能有500家创业公司认为他们在开发微软可能会购买的东西。即使是微软,可能也无法在内部管理500个开发项目。 大公司的薪酬方式也不对。在大公司开发新产品的人,无论成功与否,薪酬大致相同。创业公司的人如果产品成功,期望变得富有;如果失败,则一无所获。[2]因此,创业公司的人自然会更努力地工作。 大公司的庞大规模本身就是障碍。在创业公司,开发者通常被迫直接与用户交流,无论他们是否愿意,因为没有其他人做销售和支持。做销售很痛苦,但从试图向人们销售东西中学到的,远比从焦点小组中阅读他们的反馈要多得多。 当然,大公司不擅长产品开发,因为他们什么都不擅长。大公司的一切都比小公司慢,而产品开发必须快速进行,因为你需要经过多次迭代才能做出好东西。 趋势 我认为大公司收购创业公司的趋势只会加速。剩下的最大障碍之一是骄傲。大多数公司,至少在潜意识里,觉得他们应该能够在内部开发东西,而收购创业公司在某种程度上是承认失败。因此,就像人们通常对待承认失败一样,他们会尽可能推迟。这使得收购最终发生时非常昂贵。 公司应该做的是在创业公司年轻时就出去发现它们,而不是等到风险投资将它们吹嘘成需要数亿美元收购的东西。风险投资增加的很多东西,收购方根本不需要。 为什么收购方不尝试预测那些他们未来需要花费数亿美元收购的公司,并早期以十分之一或二十分之一的价格拿下它们?因为他们无法提前预测赢家?如果只支付二十分之一的钱,他们只需要预测二十分之一的准确度。他们肯定能做到这一点。 我认为收购技术的公司会逐渐学会瞄准更早期的创业公司。他们不一定会直接收购。解决方案可能是投资和收购的某种混合:例如,购买公司的一部分,并获得以后收购剩余部分的期权。 当公司收购创业公司时,他们实际上是将招聘和产品开发结合在一起。我认为这比分开进行更高效,因为你总能得到真正致力于他们工作的人。 此外,这种方法产生的开发团队已经能够良好合作。他们之间的任何冲突都在创业的炙热铁砧上被熨平了。当收购方得到他们时,他们已经能默契配合。这在软件中很有价值,因为很多错误发生在不同人代码的边界处。 投资者 创业成本的降低不仅让黑客相对于雇主有更多权力,也让他们相对于投资者有更多权力。 风险投资家的传统智慧是,不应该让黑客经营自己的公司。创始人应该接受MBA作为他们的老板,自己则担任诸如首席技术官之类的头衔。在某些情况下,这可能是个好主意。但我认为创始人将越来越能够在控制权问题上反击,因为他们不像过去那样需要投资者的钱了。 创业公司是一个相对较新的现象。仙童半导体被认为是第一家获得风险投资支持的创业公司,成立于1959年,不到五十年前。以社会变革的时间尺度衡量,我们现在处于测试前阶段。因此,我们不应假设创业公司现在的工作方式就是它们必须的工作方式。 仙童需要大量资金才能起步。他们必须建造实际的工厂。如今,基于互联网的创业公司的第一轮风险投资资金花在哪里?更多的钱并不能更快地写出软件;不需要用于设施,因为现在设施可以相当便宜;钱真正能为你买到的只有销售和营销。我承认销售团队有价值。但营销越来越无关紧要。在互联网上,任何真正好的东西都会通过口碑传播。 投资者的权力来自金钱。当创业公司需要的钱减少时,投资者对它们的权力就减少。因此,未来的创始人如果不愿意,可能不必接受新的CEO。风险投资家将不得不被拖拽着走上这条路,但就像许多人们不得不被拖拽着走向的事物一样,这对他们实际上可能是好事。 谷歌是事物发展方向的一个标志。作为投资条件,他们的投资者坚持要求他们雇佣一位年长且有经验的人担任CEO。但据我所知,创始人并没有屈服并接受风险投资家想要的人。他们拖延了整整一年,当他们最终接受一位CEO时,他们选择了一位拥有计算机科学博士学位的人。 在我看来,创始人似乎仍然是公司中最有权势的人,而从谷歌的表现来看,他们的年轻和缺乏经验似乎并没有伤害他们。事实上,我怀疑谷歌的表现比创始人当初屈服于风险投资家的要求,让他们在获得第一轮融资后立即让某个MBA接管公司要好。 我并不是说风险投资家安插的商业人员没有价值。他们当然有价值。但他们不需要成为创始人的老板,这正是CEO这个头衔的含义。我预测,未来风险投资家安插的高管将越来越多地是COO而不是CEO。创始人将直接管理工程,并通过COO管理公司的其他部分。 开放的笼子 无论是雇主还是投资者,权力的天平都在慢慢向年轻人倾斜。然而,他们似乎是最后一个意识到这一点的人。只有最有雄心的本科生才会在毕业时考虑创办自己的公司。大多数人只想找份工作。 也许这应该是这样。也许如果创业的想法令人望而生畏,你会过滤掉不坚定的人。但我怀疑这个过滤器设置得有点高。我认为有些人如果尝试,可以创办成功的创业公司,但他们却让自己被吸入大公司的进气管道。 你有没有注意到,当动物被放出笼子时,它们一开始并不总是意识到门是开着的?通常需要用棍子戳它们才能让它们出来。类似的事情发生在博客上。人们本可以在1995年就在线发表文章,但博客直到最近几年才真正兴起。1995年,我们认为只有专业作家才有权发表他们的想法,其他这样做的人都是怪人。现在在线发表变得如此流行,以至于每个人都想这么做,甚至包括印刷媒体的记者。但博客最近兴起并不是因为任何技术创新;只是花了八年时间让每个人意识到笼子是开放的。 我认为大多数本科生还没有意识到经济笼子是开放的。很多人被父母告知,成功的途径是找到一份好工作。这在他们的父母上大学时是正确的,但现在不那么正确了。成功的途径是创造有价值的东西,而你不需要为现有公司工作就能做到这一点。事实上,如果你不这样做,往往能做得更好。 当我和本科生交谈时,最让我惊讶的是他们的保守。当然不是在政治上。我的意思是他们似乎不愿意冒险。这是一个错误,因为你越年轻,就越能承担风险。 风险 风险和回报总是成正比的。例如,股票比债券风险更大,长期来看总是有更高的回报。那么为什么还有人投资债券?关键在于“长期”这个词。股票在三十年内会产生更高的回报,但它们可能每年都会贬值。因此,你应该投资什么取决于你多快需要钱。如果你年轻,你应该选择你能找到的最冒险的投资。 所有这些关于投资的讨论可能看起来非常理论化。大多数本科生可能负债多于资产。他们可能觉得自己没有什么可投资的。但这不是真的:他们有可以投资的时间,同样的风险规则也适用于此。二十出头正是承担疯狂职业风险的时候。 风险总是与回报成正比的原因是市场力量使其如此。人们会为稳定性支付额外费用。因此,如果你选择稳定性——通过购买债券,或为大公司工作——你将付出代价。 风险更大的职业选择平均回报更高,因为对它们的需求更少。像创业这样的极端选择如此可怕,以至于大多数人甚至不会尝试。因此,考虑到所涉及的奖励,你不会遇到你想象的那么多竞争。 数学是残酷的。虽然也许十家创业公司中有九家会失败,但成功的那一家给创始人带来的回报将超过他们在普通工作中所得的十倍。[3]这就是创业“平均”回报更高的意义所在。 记住这一点。如果你创业,你可能会失败。大多数创业公司都失败了。这是这个行业的本质。但尝试有90%失败几率的事情并不一定是错误,如果你能承担风险的话。40岁时失败,当你需要养家时,可能会很严重。但如果你22岁失败,那又怎样?如果你大学一毕业就尝试创业,结果失败了,你会在23岁时破产,但聪明得多。仔细想想,这大致是你希望从研究生项目中得到的东西。 即使你的创业公司失败了,你也不会损害你在雇主面前的前景。为了确认这一点,我问了一些在大公司工作的朋友。我问了雅虎、谷歌、亚马逊、思科和微软的经理,他们对两个24岁、能力相当的候选人会怎么看,一个尝试创业但失败了,另一个大学毕业后两年一直在一家大公司做开发。每个人都回答说,他们会更喜欢那个尝试创办自己公司的人。负责雅虎工程的Zod Nazem说:.
But others are more capable than all but a handful of 30 year olds. [1] Till now the problem has always been that it's difficult to pick them out. Every VC in the world, if they could go back in time, would try to invest in Microsoft. But which would have then? How many would have understood that this particular 19 year old was Bill Gates? It's hard to judge the young because (a) they change rapidly, (b) there is great variation between them, and (c) they're individually inconsistent. That last one is a big problem. When you're young, you occasionally say and do stupid things even when you're smart. So if the algorithm is to filter out people who say stupid things, as many investors and employers unconsciously do, you're going to get a lot of false positives. Most organizations who hire people right out of college are only aware of the average value of 22 year olds, which is not that high. And so the idea for most of the twentieth century was that everyone had to begin as a trainee in some entry-level job. Organizations realized there was a lot of variation in the incoming stream, but instead of pursuing this thought they tended to suppress it, in the belief that it was good for even the most promising kids to start at the bottom, so they didn't get swelled heads. The most productive young people will _always_ be undervalued by large organizations, because the young have no performance to measure yet, and any error in guessing their ability will tend toward the mean. What's an especially productive 22 year old to do? One thing you can do is go over the heads of organizations, directly to the users. Any company that hires you is, economically, acting as a proxy for the customer. The rate at which they value you (though they may not consciously realize it) is an attempt to guess your value to the user. But there's a way to appeal their judgement.
实际上,我更看重那个创业失败的人。你可以直接引用我的话!
这就是答案。想被雅虎录用?先创办自己的公司吧。
If you want, you can opt to be valued directly by users, by starting your own company. The market is a lot more discerning than any employer. And it is completely non-discriminatory. On the Internet, nobody knows you're a dog. And more to the point, nobody knows you're 22. All users care about is whether your site or software gives them what they want. They don't care if the person behind it is a high school kid. If you're really productive, why not make employers pay market rate for you? Why go work as an ordinary employee for a big company, when you could start a startup and make them buy it to get you? When most people hear the word "startup," they think of the famous ones that have gone public. But most startups that succeed do it by getting bought. And usually the acquirer doesn't just want the technology, but the people who created it as well. Often big companies buy startups before they're profitable. Obviously in such cases they're not after revenues. What they want is the development team and the software they've built so far. When a startup gets bought for 2 or 3 million six months in, it's really more of a hiring bonus than an acquisition. I think this sort of thing will happen more and more, and that it will be better for everyone. It's obviously better for the people who start the startup, because they get a big chunk of money up front. But I think it will be better for the acquirers too. The central problem in big companies, and the main reason they're so much less productive than small companies, is the difficulty of valuing each person's work. Buying larval startups solves that problem for them: the acquirer doesn't pay till the developers have proven themselves. Acquirers are protected on the downside, but still get most of the upside. Product Development Buying startups also solves another problem afflicting big companies: they can't do product development.
客户才是真正的老板 既然连大公司都如此看重创业的年轻黑客,为什么更多人不去尝试呢?为何大学生如此保守?我想是因为他们在体制内浸淫太久。
人生前二十年就像被管道从一个机构输送到另一个机构。你可能没怎么选择过中学,高中毕业后又理所当然要上大学。虽然有几所大学可选,但本质上大同小异。就这样在既定轨道上行驶二十年后,"下一站:职场"似乎成了自然选择。
Big companies are good at extracting the value from existing products, but bad at creating new ones. Why? It's worth studying this phenomenon in detail, because this is the raison d'etre of startups. To start with, most big companies have some kind of turf to protect, and this tends to warp their development decisions. For example, Web-based applications are hot now, but within Microsoft there must be a lot of ambivalence about them, because the very idea of Web-based software threatens the desktop. So any Web-based application that Microsoft ends up with, will probably, like Hotmail, be something developed outside the company. Another reason big companies are bad at developing new products is that the kind of people who do that tend not to have much power in big companies (unless they happen to be the CEO). Disruptive technologies are developed by disruptive people. And they either don't work for the big company, or have been outmaneuvered by yes-men and have comparatively little influence. Big companies also lose because they usually only build one of each thing. When you only have one Web browser, you can't do anything really risky with it. If ten different startups design ten different Web browsers and you take the best, you'll probably get something better. The more general version of this problem is that there are too many new ideas for companies to explore them all. There might be 500 startups right now who think they're making something Microsoft might buy. Even Microsoft probably couldn't manage 500 development projects in-house. Big companies also don't pay people the right way. People developing a new product at a big company get paid roughly the same whether it succeeds or fails. People at a startup expect to get rich if the product succeeds, and get nothing if it fails. [2] So naturally the people at the startup work a lot harder. The mere bigness of big companies is an obstacle.
但大学其实是终点站。表面上进入公司像是又进入一个新机构,实则天翻地覆。毕业是你人生的支点,从此从净消费者转变为净生产者。
另一巨变是:现在方向盘在你手中。值得退后一步看清局势,而非随波逐流。
In startups, developers are often forced to talk directly to users, whether they want to or not, because there is no one else to do sales and support. It's painful doing sales, but you learn much more from trying to sell people something than reading what they said in focus groups. And then of course, big companies are bad at product development because they're bad at everything. Everything happens slower in big companies than small ones, and product development is something that has to happen fast, because you have to go through a lot of iterations to get something good. Trend I think the trend of big companies buying startups will only accelerate. One of the biggest remaining obstacles is pride. Most companies, at least unconsciously, feel they ought to be able to develop stuff in house, and that buying startups is to some degree an admission of failure. And so, as people generally do with admissions of failure, they put it off for as long as possible. That makes the acquisition very expensive when it finally happens. What companies should do is go out and discover startups when they're young, before VCs have puffed them up into something that costs hundreds of millions to acquire. Much of what VCs add, the acquirer doesn't need anyway. Why don't acquirers try to predict the companies they're going to have to buy for hundreds of millions, and grab them early for a tenth or a twentieth of that? Because they can't predict the winners in advance? If they're only paying a twentieth as much, they only have to predict a twentieth as well. Surely they can manage that. I think companies that acquire technology will gradually learn to go after earlier stage startups. They won't necessarily buy them outright. The solution may be some hybrid of investment and acquisition: for example, to buy a chunk of the company and get an option to buy the rest later.
多数大学生——很可能早在大学前——就总在琢磨雇主想要什么。但真正关键的是客户需求,因为正是客户给雇主发薪水的钱。
When companies buy startups, they're effectively fusing recruiting and product development. And I think that's more efficient than doing the two separately, because you always get people who are really committed to what they're working on. Plus this method yields teams of developers who already work well together. Any conflicts between them have been ironed out under the very hot iron of running a startup. By the time the acquirer gets them, they're finishing one another's sentences. That's valuable in software, because so many bugs occur at the boundaries between different people's code. Investors The increasing cheapness of starting a company doesn't just give hackers more power relative to employers. It also gives them more power relative to investors. The conventional wisdom among VCs is that hackers shouldn't be allowed to run their own companies. The founders are supposed to accept MBAs as their bosses, and themselves take on some title like Chief Technical Officer. There may be cases where this is a good idea. But I think founders will increasingly be able to push back in the matter of control, because they just don't need the investors' money as much as they used to. Startups are a comparatively new phenomenon. Fairchild Semiconductor is considered the first VC-backed startup, and they were founded in 1959, less than fifty years ago. Measured on the time scale of social change, what we have now is pre-beta. So we shouldn't assume the way startups work now is the way they have to work. Fairchild needed a lot of money to get started. They had to build actual factories. What does the first round of venture funding for a Web-based startup get spent on today? More money can't get software written faster; it isn't needed for facilities, because those can now be quite cheap; all money can really buy you is sales and marketing. A sales force is worth something, I'll admit. But marketing is increasingly irrelevant.
与其揣摩雇主心思,不如直接思考用户需求。两者的差异正是创业者的优势所在。比如大公司偏爱温顺的应声虫,但这只是大企业病的产物,绝非客户所需。
研究生院 我大学毕业时并未清醒意识到这些——部分因为我直接读了研。即便有志创业,读研也是不错选择。你可以毕业后创业,甚至像雅虎和谷歌创始人那样中途辍学。
On the Internet, anything genuinely good will spread by word of mouth. Investors' power comes from money. When startups need less money, investors have less power over them. So future founders may not have to accept new CEOs if they don't want them. The VCs will have to be dragged kicking and screaming down this road, but like many things people have to be dragged kicking and screaming toward, it may actually be good for them. Google is a sign of the way things are going. As a condition of funding, their investors insisted they hire someone old and experienced as CEO. But from what I've heard the founders didn't just give in and take whoever the VCs wanted. They delayed for an entire year, and when they did finally take a CEO, they chose a guy with a PhD in computer science. It sounds to me as if the founders are still the most powerful people in the company, and judging by Google's performance, their youth and inexperience doesn't seem to have hurt them. Indeed, I suspect Google has done better than they would have if the founders had given the VCs what they wanted, when they wanted it, and let some MBA take over as soon as they got their first round of funding. I'm not claiming the business guys installed by VCs have no value. Certainly they have. But they don't need to become the founders' bosses, which is what that title CEO means. I predict that in the future the executives installed by VCs will increasingly be COOs rather than CEOs. The founders will run engineering directly, and the rest of the company through the COO. The Open Cage With both employers and investors, the balance of power is slowly shifting towards the young. And yet they seem the last to realize it. Only the most ambitious undergrads even consider starting their own company when they graduate. Most just want to get a job. Maybe this is as it should be. Maybe if the idea of starting a startup is intimidating, you filter out the uncommitted.
研究生院是绝佳的创业跳板:这里聚集着聪明人,比本科生或职场人拥有更多自由时间。只要导师开明,你尽可从容打磨创意。杨致远和大卫·费罗1994年2月创建雅虎目录,当年秋天日访问量就破百万,但他们直到1995年3月才正式辍学创业。
你也可以先创业,失败后再读研。初创企业往往速朽,一年内就能见分晓。
But I suspect the filter is set a little too high. I think there are people who could, if they tried, start successful startups, and who instead let themselves be swept into the intake ducts of big companies. Have you ever noticed that when animals are let out of cages, they don't always realize at first that the door's open? Often they have to be poked with a stick to get them out. Something similar happened with blogs. People could have been publishing online in 1995, and yet blogging has only really taken off in the last couple years. In 1995 we thought only professional writers were entitled to publish their ideas, and that anyone else who did was a crank. Now publishing online is becoming so popular that everyone wants to do it, even print journalists. But blogging has not taken off recently because of any technical innovation; it just took eight years for everyone to realize the cage was open. I think most undergrads don't realize yet that the economic cage is open. A lot have been told by their parents that the route to success is to get a good job. This was true when their parents were in college, but it's less true now. The route to success is to build something valuable, and you don't have to be working for an existing company to do that. Indeed, you can often do it better if you're not. When I talk to undergrads, what surprises me most about them is how conservative they are. Not politically, of course. I mean they don't seem to want to take risks. This is a mistake, because the younger you are, the more risk you can take. Risk Risk and reward are always proportionate. For example, stocks are riskier than bonds, and over time always have greater returns. So why does anyone invest in bonds? The catch is that phrase "over time." Stocks will generate greater returns over thirty years, but they might lose value from year to year. So what you should invest in depends on how soon you need the money.
若成功,读研计划或许要推迟——但届时你的研究生生活将远比靠奖学金滋润得多。
经验之惑 年轻人不敢创业的另一原因是自觉经验不足,这也正是投资人的顾虑。
If you're young, you should take the riskiest investments you can find. All this talk about investing may seem very theoretical. Most undergrads probably have more debts than assets. They may feel they have nothing to invest. But that's not true: they have their time to invest, and the same rule about risk applies there. Your early twenties are exactly the time to take insane career risks. The reason risk is always proportionate to reward is that market forces make it so. People will pay extra for stability. So if you choose stability-- by buying bonds, or by going to work for a big company-- it's going to cost you. Riskier career moves pay better on average, because there is less demand for them. Extreme choices like starting a startup are so frightening that most people won't even try. So you don't end up having as much competition as you might expect, considering the prizes at stake. The math is brutal. While perhaps 9 out of 10 startups fail, the one that succeeds will pay the founders more than 10 times what they would have made in an ordinary job. [3] That's the sense in which startups pay better "on average." Remember that. If you start a startup, you'll probably fail. Most startups fail. It's the nature of the business. But it's not necessarily a mistake to try something that has a 90% chance of failing, if you can afford the risk. Failing at 40, when you have a family to support, could be serious. But if you fail at 22, so what? If you try to start a startup right out of college and it tanks, you'll end up at 23 broke and a lot smarter. Which, if you think about it, is roughly what you hope to get from a graduate program. Even if your startup does tank, you won't harm your prospects with employers. To make sure I asked some friends who work for big companies.
大学时我常听人把"经验"挂嘴边。经验的价值究竟何在?显然不是经历本身,而是它重塑你大脑的方式。获得"经验"后大脑究竟有何不同?能否加速这种改变?
根据观察,缺乏经验者通常缺的是这点:每个初创企业都需要三要素——优秀团队、用户想要的产品、控制成本。菜鸟最容易栽在第二点。许多本科生技术完全过关,也不特别挥霍,他们的致命伤往往是没意识到必须做出人们真正需要的东西。
I asked managers at Yahoo, Google, Amazon, Cisco and Microsoft how they'd feel about two candidates, both 24, with equal ability, one who'd tried to start a startup that tanked, and another who'd spent the two years since college working as a developer at a big company. Every one responded that they'd prefer the guy who'd tried to start his own company. Zod Nazem, who's in charge of engineering at Yahoo, said:.
这非年轻人专利,各年龄段创业者都常造出无人问津的产品。
> I actually put more value on the guy with the failed startup. And you can quote me!
所幸这个缺陷容易弥补。若本科生都是蹩脚程序员,问题就棘手多了——编程需多年修炼,但洞悉用户需求不需那么久。我的假设是:只需敲打黑客们的脑袋说:醒醒!别坐在那空想用户需求。去找真实用户,看看他们要什么。
多数成功创业不仅解决具体问题,更是解决人们已知的痛点。
So there you have it. Want to get hired by Yahoo? Start your own company. The Man is the Customer If even big employers think highly of young hackers who start companies, why don't more do it? Why are undergrads so conservative? I think it's because they've spent so much time in institutions. The first twenty years of everyone's life consists of being piped from one institution to another. You probably didn't have much choice about the secondary schools you went to. And after high school it was probably understood that you were supposed to go to college. You may have had a few different colleges to choose between, but they were probably pretty similar. So by this point you've been riding on a subway line for twenty years, and the next stop seems to be a job. Actually college is where the line ends. Superficially, going to work for a company may feel like just the next in a series of institutions, but underneath, everything is different. The end of school is the fulcrum of your life, the point where you go from net consumer to net producer. The other big change is that now, you're steering. You can go anywhere you want. So it may be worth standing back and understanding what's going on, instead of just doing the default thing. All through college, and probably long before that, most undergrads have been thinking about what employers want. But what really matters is what customers want, because they're the ones who give employers the money to pay you. So instead of thinking about what employers want, you're probably better off thinking directly about what users want. To the extent there's any difference between the two, you can even use that to your advantage if you start a company of your own. For example, big companies like docile conformists.
"经验"带给大脑的关键转变,就是明白必须解决人们的实际问题。领悟这点后,你会快速进阶至下一阶段:找出这些问题。这需要下功夫,因为软件的实际使用场景(尤其是高价软件)常超乎想象。比如PPT名义上是展示创意,实则是缓解演讲恐惧——它能让你做场空洞但光鲜的演示,让观众在暗处看幻灯片而非在亮处盯着你。
这些洞察本应显而易见。关键在于要有意识去发现:创业点子不同于课程设计。创业目标不是写出酷炫代码,而是做出人们想要的东西。为此你必须观察用户——忘记编程,专注用户。这需要思维转换,因为你在校写的软件几乎都没有真实用户。
But this is merely an artifact of their bigness, not something customers need. Grad School I didn't consciously realize all this when I was graduating from college-- partly because I went straight to grad school. Grad school can be a pretty good deal, even if you think of one day starting a startup. You can start one when you're done, or even pull the ripcord part way through, like the founders of Yahoo and Google. Grad school makes a good launch pad for startups, because you're collected together with a lot of smart people, and you have bigger chunks of time to work on your own projects than an undergrad or corporate employee would. As long as you have a fairly tolerant advisor, you can take your time developing an idea before turning it into a company. David Filo and Jerry Yang started the Yahoo directory in February 1994 and were getting a million hits a day by the fall, but they didn't actually drop out of grad school and start a company till March 1995. You could also try the startup first, and if it doesn't work, then go to grad school. When startups tank they usually do it fairly quickly. Within a year you'll know if you're wasting your time. If it fails, that is. If it succeeds, you may have to delay grad school a little longer. But you'll have a much more enjoyable life once there than you would on a regular grad student stipend. Experience Another reason people in their early twenties don't start startups is that they feel they don't have enough experience. Most investors feel the same. I remember hearing a lot of that word "experience" when I was in college. What do people really mean by it? Obviously it's not the experience itself that's valuable, but something it changes in your brain. What's different about your brain after you have "experience," and can you make that change happen faster? I now have some data on this, and I can tell you what tends to be missing when people lack experience.
就像魔方即将完成前仍看似混乱,许多本科生距离成功创业只差几步——如果他们愿意的话。他们技术足够,只是还没悟透:创造财富的本质是满足用户需求,而雇主不过是用户需求的风险共担代理。
若你年轻又聪明,这两者都不需要。你不需要别人告诉你用户要什么,因为你自己能发现;你也不该共担风险,因为年轻正该冒险。
I've said that every startup needs three things: to start with good people, to make something users want, and not to spend too much money. It's the middle one you get wrong when you're inexperienced. There are plenty of undergrads with enough technical skill to write good software, and undergrads are not especially prone to waste money. If they get something wrong, it's usually not realizing they have to make something people want. This is not exclusively a failing of the young. It's common for startup founders of all ages to build things no one wants. Fortunately, this flaw should be easy to fix. If undergrads were all bad programmers, the problem would be a lot harder. It can take years to learn how to program. But I don't think it takes years to learn how to make things people want. My hypothesis is that all you have to do is smack hackers on the side of the head and tell them: Wake up. Don't sit here making up a priori theories about what users need. Go find some users and see what they need. Most successful startups not only do something very specific, but solve a problem people already know they have. The big change that "experience" causes in your brain is learning that you need to solve people's problems. Once you grasp that, you advance quickly to the next step, which is figuring out what those problems are. And that takes some effort, because the way software actually gets used, especially by the people who pay the most for it, is not at all what you might expect. For example, the stated purpose of Powerpoint is to present ideas. Its real role is to overcome people's fear of public speaking. It allows you to give an impressive-looking talk about nothing, and it causes the audience to sit in a dark room looking at slides, instead of a bright one looking at you. This kind of thing is out there for anyone to see.
来自长辈的忠告 最后,请允许我和你们父母一起说:别辍学创业。毕业后有的是时间创业。事实上,先工作几年学习企业运作或许更好。
The key is to know to look for it-- to realize that having an idea for a startup is not like having an idea for a class project. The goal in a startup is not to write a cool piece of software. It's to make something people want. And to do that you have to look at users-- forget about hacking, and just look at users. This can be quite a mental adjustment, because little if any of the software you write in school even has users. A few steps before a Rubik's Cube is solved, it still looks like a mess. I think there are a lot of undergrads whose brains are in a similar position: they're only a few steps away from being able to start successful startups, if they wanted to, but they don't realize it. They have more than enough technical skill. They just haven't realized yet that the way to create wealth is to make what users want, and that employers are just proxies for users in which risk is pooled. If you're young and smart, you don't need either of those. You don't need someone else to tell you what users want, because you can figure it out yourself. And you don't want to pool risk, because the younger you are, the more risk you should take. A Public Service Message I'd like to conclude with a joint message from me and your parents. Don't drop out of college to start a startup. There's no rush. There will be plenty of time to start companies after you graduate. In fact, it may be just as well to go work for an existing company for a couple years after you graduate, to learn how companies work. And yet, when I think about it, I can't imagine telling Bill Gates at 19 that he should wait till he graduated to start a company. He'd have told me to get lost. And could I have honestly claimed that he was harming his future-- that he was learning less by working at ground zero of the microcomputer revolution than he would have if he'd been taking classes back at Harvard? No, probably not.
但细想之下,我无法想象对19岁的比尔·盖茨说"等毕业再创业"。他肯定会叫我滚开。我能真心说他在毁前程吗——说他在微电脑革命前线学到的,还不如回哈佛上课多?恐怕不能。
没错,为他人工作几年或许能学到宝贵经验,但同样时间里经营自己的公司何尝不是?
And yes, while it is probably true that you'll learn some valuable things by going to work for an existing company for a couple years before starting your own, you'd learn a thing or two running your own company during that time too. The advice about going to work for someone else would get an even colder reception from the 19 year old Bill Gates. So I'm supposed to finish college, then go work for another company for two years, and then I can start my own? I have to wait till I'm 23? That's _four years_. That's more than twenty percent of my life so far. Plus in four years it will be way too late to make money writing a Basic interpreter for the Altair. And he'd be right. The Apple II was launched just two years later. In fact, if Bill had finished college and gone to work for another company as we're suggesting, he might well have gone to work for Apple. And while that would probably have been better for all of us, it wouldn't have been better for him. So while I stand by our responsible advice to finish college and then go work for a while before starting a startup, I have to admit it's one of those things the old tell the young, but don't expect them to listen to. We say this sort of thing mainly so we can claim we warned you. So don't say I didn't warn you. Notes [1] The average B-17 pilot in World War II was in his early twenties. (Thanks to Tad Marko for pointing this out.) [2] If a company tried to pay employees this way, they'd be called unfair. And yet when they buy some startups and not others, no one thinks of calling that unfair. [3] The 1/10 success rate for startups is a bit of an urban legend. It's suspiciously neat.
这套说辞对19岁的盖茨会更刺耳:读完大学再打工两年才能创业?等到23岁?那可是四年!比我目前生命的五分之一还长。何况四年后Altair的BASIC解释器早没赚头了。
他是对的。苹果II两年后就发布了。若盖茨按我们建议毕业打工,很可能去了苹果。虽然对世界或许是好事,但对他可不是。
My guess is the odds are slightly worse. Thanks to Jessica Livingston for reading drafts of this, to the friends I promised anonymity to for their opinions about hiring, and to Karen Nguyen and the Berkeley CSUA for organizing this talk.
| Russian Translation | | | Romanian Translation | Japanese Translation.
所以,尽管我坚持"毕业工作再创业"的负责任建议,但不得不承认:这就像长辈总说而晚辈不听的那些话。我们说这些主要是为了事后能说"早警告过你"。所以别说我没提醒你。
注释 [1] 二战期间B-17飞行员的平均年龄才二十出头(感谢Tad Marko指出) [2] 若公司如此对待员工会被斥不公,但收购某些初创企业时却无人质疑 [3] 初创企业十分之一成功率的说法像是都市传说,我猜实际概率更低
If you liked this, you may also like _Hackers & Painters_.
致谢 Jessica Livingston审阅草稿,匿名好友分享招聘见解,Karen Nguyen和伯克利CSUA筹办演讲。
如果你喜欢这篇文章,可能也会喜欢《黑客与画家》。
Want to start a startup? Get funded by Y Combinator.
April 2005 This summer, as an experiment, some friends and I are giving seed funding to a bunch of new startups. It's an experiment because we're prepared to fund younger founders than most investors would. That's why we're doing it during the summer—so even college students can participate. We know from Google and Yahoo that grad students can start successful startups. And we know from experience that some undergrads are as capable as most grad students. The accepted age for startup founders has been creeping downward. We're trying to find the lower bound. The deadline has now passed, and we're sifting through 227 applications. We expected to divide them into two categories, promising and unpromising. But we soon saw we needed a third: promising people with unpromising ideas. [1] The Artix Phase We should have expected this. It's very common for a group of founders to go through one lame idea before realizing that a startup has to make something people will pay for. In fact, we ourselves did. Viaweb wasn't the first startup Robert Morris and I started. In January 1995, we and a couple friends started a company called Artix. The plan was to put art galleries on the Web. In retrospect, I wonder how we could have wasted our time on anything so stupid. Galleries are not especially excited about being on the Web even now, ten years later. They don't want to have their stock visible to any random visitor, like an antique store. [2] Besides which, art dealers are the most technophobic people on earth. They didn't become art dealers after a difficult choice between that and a career in the hard sciences. Most of them had never seen the Web before we came to tell them why they should be on it. Some didn't even have computers.
想创业吗? 获得 Y Combinator 的资助。
2005年4月 今年夏天,作为一项实验,我和一些朋友将为一批新创公司提供 种子资金。这是一项实验,因为我们准备资助比大多数投资者更年轻的创始人。这就是为什么我们选择在夏天进行——这样连大学生也能参与。 从谷歌和雅虎的例子中我们知道,研究生可以创办成功的创业公司。而根据经验,一些本科生也能做到大多数研究生能做到的事。创业公司创始人的年龄门槛一直在下降。我们正试图找到这个下限。 截止日期已过,我们正在筛选227份申请。我们原本以为可以将它们分为两类:有希望的和没希望的。但很快我们发现需要第三类:有潜力的创始人带着没希望的想法。[1] Artix阶段 我们本应预料到这一点。创始团队在意识到创业必须做人们愿意付钱的东西之前,往往会经历一个糟糕的想法阶段。事实上,我们自己就是这样。 Viaweb并不是我和罗伯特·莫里斯创办的第一家公司。1995年1月,我们和几个朋友创办了一家名为Artix的公司。计划是将艺术画廊搬到网上。回想起来,我不知道我们怎么会把时间浪费在如此愚蠢的事情上。十年后的今天,画廊对上网仍然不太 热衷。他们不希望自己的库存像古董店一样被随机访客看到。[2] 此外,艺术品经销商是地球上最抗拒技术的人。他们成为艺术品经销商并不是在艰难的科学事业和艺术之间做出选择的结果。大多数人从未见过互联网,直到我们去告诉他们为什么应该上网。有些人甚至没有电脑。用“难卖”来形容这种情况都算轻了;我们很快沦落到免费建站的地步,即便如此也很难说服画廊。 渐渐地,我们意识到与其为不想上网的人做网站,不如为想要网站的人做。事实上,可以开发软件让想要网站的人自己动手。于是我们放弃了Artix,创办了新公司Viaweb,开发在线商店软件。这一次我们成功了。 我们并不孤单。微软也不是保罗·艾伦和比尔·盖茨创办的第一家公司。第一家名为Traf-o-data,似乎没有Micro-soft那么成功。 为罗伯特辩护一下,他对Artix持怀疑态度。是我把他拉进来的。[3]但他也有乐观的时候。如果我们这些当时29岁和30岁的人会对如此愚蠢的想法感到兴奋,那么21或22岁的黑客向我们推销不太可能赚钱的想法也就不足为奇了。 静物效应 为什么会这样?为什么优秀的黑客会有糟糕的商业想法? 看看我们的例子。我们有如此糟糕的想法的一个原因是,这是我们想到的第一件事。当时我在纽约试图成为一名穷困潦倒的艺术家(穷困部分其实很容易),所以我经常出入画廊。当我了解到互联网时,很自然地将两者结合起来。为画廊做网站——就是它了! 如果你要花多年时间做某件事,你可能会认为至少花几天时间考虑不同的想法是明智的,而不是选择第一个想到的。你会这么想。但人们不会。事实上,这在画静物时是一个常见问题。你把一堆东西放在桌子上,可能会花五到十分钟重新排列以使其看起来有趣。但你迫不及待想开始画画,十分钟的重新排列感觉非常漫长。于是你开始画。三天后,盯着它看了二十个小时,你会后悔自己设置了如此尴尬和无聊的构图,但那时已经太晚了。 部分问题在于大项目往往从小项目发展而来。你为了在空闲时间快速素描而布置了一个静物,几天后你还在画它。我曾经花了一个月时间画了三个版本的静物,而布置它只用了四分钟。在每一个时间点(一天、一周、一个月),我都觉得已经投入了太多时间,来不及改变了。 因此,糟糕想法的最大原因是静物效应:你想出一个随机的想法,一头扎进去,然后在每一个时间点(一天、一周、一个月)都觉得已经投入了太多时间,这一定就是那个正确的想法。 如何解决?我不认为我们应该放弃一头扎进去的做法。投入一个想法是好事。解决方案在于另一端:意识到在某件事上投入时间并不会让它变好。 这在命名上最为明显。Viaweb最初叫Webgen,但我们发现别人已经有一个产品叫这个名字。我们对这个名字如此执着,甚至提出给他公司5%的股份来换取这个名字。但他不同意,我们只好另想一个。[4]我们能想到的最好名字是Viaweb,一开始我们并不喜欢。就像有了一个新妈妈。但三天后我们就爱上了它,而Webgen听起来既老套又蹩脚。 如果连改名字这样简单的事情都如此困难,想象一下抛弃一个想法有多难。名字只有一个点与你的大脑相连。而一个公司的想法会与你的思想交织在一起。因此你必须有意地对此打折扣。尽管一头扎进去,但之后要记得在清晨的冷光下审视你的想法并问:这是人们愿意付钱的东西吗?在所有我们能做的东西中,这是人们最愿意付钱的东西吗? 污秽 我们在Artix上犯的第二个错误也很常见。将画廊搬上网看起来很酷。 我父亲教给我最有价值的东西之一是一句古老的约克郡谚语:哪里有污秽,哪里就有钱。意思是肮脏的工作有回报。更切题的是,反之亦然。人们喜欢的工作报酬不高,这是供需关系决定的。最极端的例子是开发编程语言,完全没有报酬,因为人们太喜欢做这件事了,以至于免费做。 当我们创办Artix时,我对商业仍然矛盾。我想一只脚留在艺术界。大错特错。创业就像滑翔翼起飞:你最好全心全意去做,或者干脆不做。公司的目的,尤其是创业公司,是赚钱。你不能三心二意。 这并不是说你必须做最恶心的工作,比如发垃圾邮件,或者创办一家唯一目的是专利诉讼的公司。我的意思是,如果你要创办一家做很酷的事情的公司,目标最好是赚钱顺便可能很酷,而不是很酷顺便可能赚钱。 赚钱已经够难了,不可能偶然做到。除非这是你的首要任务,否则它根本不会发生。 鬣狗 当我审视我们创办Artix的动机时,我发现了第三个错误:胆怯。如果当时有人建议我们进入电子商务领域,我们会觉得这个想法很可怕。这样的领域肯定会被那些每家都有五百万美元风投的可怕创业公司占据。而我们觉得自己在竞争稍小的为画廊建站的业务中还能应付。 我们在安全方面错得离谱。事实证明,风投支持的创业公司并不可怕。他们太忙于花掉所有那些 钱 来写软件。1995年,电子商务领域的竞争在新闻稿中看起来很激烈,但在软件层面并非如此。实际上从来都不是。像Open Market这样的大鱼(愿他们安息)只是假装成产品公司的咨询公司[5],而我们这一端的市场产品只是几百行的Perl脚本。或者可以用几百行Perl实现;实际上它们可能是几万行的C++或Java。一旦我们真正进入电子商务领域,发现竞争出奇地容易。 那么我们为什么害怕?我们觉得自己擅长编程,但对做一件神秘的、未分化的称为“商业”的事情缺乏信心。事实上,并没有“商业”这种东西。有的是销售、推广、弄清楚人们想要什么、决定收费多少、客户支持、付账单、让客户付钱、注册公司、融资等等。这些组合起来并不像看起来那么难,因为有些任务(比如融资和注册公司)是O(1)的麻烦,无论公司大小,而其他任务(比如销售和推广)更多地取决于精力和想象力,而不是任何特殊训练。 Artix就像一只鬣狗,满足于靠腐肉生存,因为我们害怕狮子。结果狮子根本没有牙齿,而为画廊上网的业务连腐肉都算不上。 熟悉的问题 总结所有这些错误来源,难怪我们会有如此糟糕的公司想法。我们做了想到的第一件事;我们对是否进入商业领域本身就很矛盾;我们故意选择了一个贫瘠的市场以避免竞争。 查看夏季创始人计划的申请,我看到了所有这三个迹象。但第一个是迄今为止最大的问题。大多数申请团队没有停下来问:在所有我们能做的事情中,这是最有希望赚钱的吗? 如果他们经历过他们的Artix阶段,他们就会学会问这个问题。在艺术品经销商给我们的接待之后,我们已经准备好了。这一次,我们想,让我们做人们想要的东西。 读一周的《华尔街日报》应该能让任何人想到两三个新的创业点子。文章中充满了需要解决的问题的描述。但大多数申请人似乎没有在寻找想法上花太多功夫。 我们预计最常见的提案是多人在线游戏。我们没猜错:这是第二常见的。最常见的是博客、日历、交友网站和Friendster的某种组合。也许这里有一些新的杀手级应用有待发现,但当有价值、未解决的问题就摆在眼前时,在这种迷雾中摸索似乎很荒谬。为什么没有人提出新的微支付方案?也许是一个雄心勃勃的项目,但我不相信我们已经考虑了所有可能性。而报纸和杂志(字面意思)迫切需要解决方案。 为什么这么少申请人真正思考过客户想要什么?我认为许多人的问题,就像大多数二十出头的年轻人一样,是他们一生都被训练着跳过预设的圈套。他们花了15-20年解决别人为他们设定的问题。而花多少时间决定哪些问题值得解决?两三个课程项目?他们擅长解决问题,但不擅长选择问题。 但我相信这只是训练的结果。更准确地说,是评分的结果。为了使评分高效,每个人都必须解决同样的问题,这意味着问题必须提前确定。如果学校教学生如何选择问题以及如何解决问题,那将很棒,但我不知道在实践中如何运行这样的课程。 铜与锡 好消息是,选择问题是可以学习的。我从经验中知道这一点。黑客可以学会制作客户想要的东西。[6] 这是一个有争议的观点。一位“创业”专家告诉我,任何创业公司都必须包括商业人士,因为只有他们才能专注于客户的需求。我引用他的话可能会永远得罪他,但我必须冒险,因为他的邮件完美地体现了这种观点:.
It doesn't do justice to the situation to describe it as a hard _sell_ ; we soon sank to building sites for free, and it was hard to convince galleries even to do that. Gradually it dawned on us that instead of trying to make Web sites for people who didn't want them, we could make sites for people who did. In fact, software that would let people who wanted sites make their own. So we ditched Artix and started a new company, Viaweb, to make software for building online stores. That one succeeded. We're in good company here. Microsoft was not the first company Paul Allen and Bill Gates started either. The first was called Traf-o-data. It does not seem to have done as well as Micro-soft. In Robert's defense, he was skeptical about Artix. I dragged him into it. [3] But there were moments when he was optimistic. And if we, who were 29 and 30 at the time, could get excited about such a thoroughly boneheaded idea, we should not be surprised that hackers aged 21 or 22 are pitching us ideas with little hope of making money. The Still Life Effect Why does this happen? Why do good hackers have bad business ideas? Let's look at our case. One reason we had such a lame idea was that it was the first thing we thought of. I was in New York trying to be a starving artist at the time (the starving part is actually quite easy), so I was haunting galleries anyway. When I learned about the Web, it seemed natural to mix the two. Make Web sites for galleries—that's the ticket! If you're going to spend years working on something, you'd think it might be wise to spend at least a couple days considering different ideas, instead of going with the first that comes into your head. You'd think. But people don't. In fact, this is a constant problem when you're painting still lifes. You plonk down a bunch of stuff on a table, and maybe spend five or ten minutes rearranging it to look interesting.
> 麻省理工学院的衍生公司中,80%能够成功,前提是团队在初创时至少有一位管理人员。这位商业人士代表着"客户的声音",正是这一点确保工程师和产品开发不偏离正轨。
在我看来,这种说法纯属无稽之谈。黑客完全有能力直接倾听客户的声音,根本不需要商务人士来替他们放大信号。拉里·佩奇和谢尔盖·布林当年不过是计算机科学专业的研究生,按这种标准大概只能算"工程师"。难道你们以为谷歌的成功全靠某个商务人士在他们耳边嘀咕客户需求?要我说,对谷歌帮助最大的商务人士,是那些在谷歌刚起步时"贴心"地把Altavista搜索引擎撞上山头的家伙。
But you're so impatient to get started painting that ten minutes of rearranging feels very long. So you start painting. Three days later, having spent twenty hours staring at it, you're kicking yourself for having set up such an awkward and boring composition, but by then it's too late. Part of the problem is that big projects tend to grow out of small ones. You set up a still life to make a quick sketch when you have a spare hour, and days later you're still working on it. I once spent a month painting three versions of a still life I set up in about four minutes. At each point (a day, a week, a month) I thought I'd already put in so much time that it was too late to change. So the biggest cause of bad ideas is the still life effect: you come up with a random idea, plunge into it, and then at each point (a day, a week, a month) feel you've put so much time into it that this must be _the_ idea. How do we fix that? I don't think we should discard plunging. Plunging into an idea is a good thing. The solution is at the other end: to realize that having invested time in something doesn't make it good. This is clearest in the case of names. Viaweb was originally called Webgen, but we discovered someone else had a product called that. We were so attached to our name that we offered him _5% of the company_ if he'd let us have it. But he wouldn't, so we had to think of another. [4] The best we could do was Viaweb, which we disliked at first. It was like having a new mother. But within three days we loved it, and Webgen sounded lame and old-fashioned. If it's hard to change something so simple as a name, imagine how hard it is to garbage-collect an idea. A name only has one point of attachment into your head. An idea for a company gets woven into your thoughts. So you must consciously discount for that.
理解客户需求的难点在于意识到这件事需要被理解。但这种认知可以快速习得,就像看懂一幅歧义图中的第二种形象——当有人告诉你图中既有鸭子又有兔子时,你很难不立即发现它。
Plunge in, by all means, but remember later to look at your idea in the harsh light of morning and ask: is this something people will pay for? Is this, of all the things we could make, the thing people will pay most for? Muck The second mistake we made with Artix is also very common. Putting galleries on the Web seemed cool. One of the most valuable things my father taught me is an old Yorkshire saying: where there's muck, there's brass. Meaning that unpleasant work pays. And more to the point here, vice versa. Work people like doesn't pay well, for reasons of supply and demand. The most extreme case is developing programming languages, which doesn't pay at all, because people like it so much they do it for free. When we started Artix, I was still ambivalent about business. I wanted to keep one foot in the art world. Big, big, mistake. Going into business is like a hang-glider launch: you'd better do it wholeheartedly, or not at all. The purpose of a company, and a startup especially, is to make money. You can't have divided loyalties. Which is not to say that you have to do the most disgusting sort of work, like spamming, or starting a company whose only purpose is patent litigation. What I mean is, if you're starting a company that will do something cool, the aim had better be to make money and maybe be cool, not to be cool and maybe make money. It's hard enough to make money that you can't do it by accident. Unless it's your first priority, it's unlikely to happen at all. Hyenas When I probe our motives with Artix, I see a third mistake: timidity. If you'd proposed at the time that we go into the e-commerce business, we'd have found the idea terrifying. Surely a field like that would be dominated by fearsome startups with five million dollars of VC money each. Whereas we felt pretty sure that we could hold our own in the slightly less competitive business of generating Web sites for art galleries.
相比黑客们日常解决的问题,满足客户需求简直易如反掌。任何能编写优化编译器的人,只要他们决定专注于用户体验问题,就一定能设计出清晰易懂的界面。当这种量级的脑力被投入到琐碎但有利可图的问题上时,财富创造的速度将超乎想象。
这就是初创企业的精髓:让顶尖人才做"屈才"的工作。大公司总想为岗位匹配最合适的人选,而初创公司之所以能赢,恰恰因为它们反其道而行——让那些在大公司本该做"研究"的聪明人,去解决最迫切的世俗问题。想想爱因斯坦去设计电冰箱的场景吧。[7]
We erred ridiculously far on the side of safety. As it turns out, VC-backed startups are not that fearsome. They're too busy trying to spend all that money to get software written. In 1995, the e-commerce business was very competitive as measured in press releases, but not as measured in software. And really it never was. The big fish like Open Market (rest their souls) were just consulting companies pretending to be product companies [5], and the offerings at our end of the market were a couple hundred lines of Perl scripts. Or could have been implemented as a couple hundred lines of Perl; in fact they were probably tens of thousands of lines of C++ or Java. Once we actually took the plunge into e-commerce, it turned out to be surprisingly easy to compete. So why were we afraid? We felt we were good at programming, but we lacked confidence in our ability to do a mysterious, undifferentiated thing we called "business." In fact there is no such thing as "business." There's selling, promotion, figuring out what people want, deciding how much to charge, customer support, paying your bills, getting customers to pay you, getting incorporated, raising money, and so on. And the combination is not as hard as it seems, because some tasks (like raising money and getting incorporated) are an O(1) pain in the ass, whether you're big or small, and others (like selling and promotion) depend more on energy and imagination than any kind of special training. Artix was like a hyena, content to survive on carrion because we were afraid of the lions. Except the lions turned out not to have any teeth, and the business of putting galleries online barely qualified as carrion. A Familiar Problem Sum up all these sources of error, and it's no wonder we had such a bad idea for a company.
若想了解人性需求,不妨读读戴尔·卡耐基的《人性的弱点》。[8] 当朋友推荐这本书时,我简直不敢相信他是认真的。但在他坚持下我读了,结果证明他是对的。这本书直指人类经验中最困难的课题:如何跳出自我中心,从他人视角看问题。
We did the first thing we thought of; we were ambivalent about being in business at all; and we deliberately chose an impoverished market to avoid competition. Looking at the applications for the Summer Founders Program, I see signs of all three. But the first is by far the biggest problem. Most of the groups applying have not stopped to ask: of all the things we could do, is _this_ the one with the best chance of making money? If they'd already been through their Artix phase, they'd have learned to ask that. After the reception we got from art dealers, we were ready to. This time, we thought, let's make something people want. Reading the _Wall Street Journal_ for a week should give anyone ideas for two or three new startups. The articles are full of descriptions of problems that need to be solved. But most of the applicants don't seem to have looked far for ideas. We expected the most common proposal to be for multiplayer games. We were not far off: this was the second most common. The most common was some combination of a blog, a calendar, a dating site, and Friendster. Maybe there is some new killer app to be discovered here, but it seems perverse to go poking around in this fog when there are valuable, unsolved problems lying about in the open for anyone to see. Why did no one propose a new scheme for micropayments? An ambitious project, perhaps, but I can't believe we've considered every alternative. And newspapers and magazines are (literally) dying for a solution. Why did so few applicants really think about what customers want? I think the problem with many, as with people in their early twenties generally, is that they've been trained their whole lives to jump through predefined hoops. They've spent 15-20 years solving problems other people have set for them. And how much time deciding what problems would be good to solve? Two or three course projects? They're good at solving problems, but bad at choosing them.
多数聪明人在这方面表现糟糕。但当这种能力与原始脑力结合时,就像在铜中加入锡——生成的青铜硬度剧增,宛若另一种金属。
一个既懂技术又懂需求的程序员将拥有惊人能量。这种能量不仅体现在赚钱能力上:看看Firefox那群志愿者创造的奇迹就知道了。
But that, I'm convinced, is just the effect of training. Or more precisely, the effect of grading. To make grading efficient, everyone has to solve the same problem, and that means it has to be decided in advance. It would be great if schools taught students how to choose problems as well as how to solve them, but I don't know how you'd run such a class in practice. Copper and Tin The good news is, choosing problems is something that can be learned. I know that from experience. Hackers can learn to make things customers want. [6] This is a controversial view. One expert on "entrepreneurship" told me that any startup had to include business people, because only they could focus on what customers wanted. I'll probably alienate this guy forever by quoting him, but I have to risk it, because his email was such a perfect example of this view:.
Artix的失败教训让人领悟"做人们需要的东西"的重要性,就像断水才能让人意识到水的珍贵。但如果夏季创始人们能用我们的资金直接跳过Artix阶段,岂不皆大欢喜?这个夏天要验证的核心问题正是:他们需要多久才能领悟这个道理?
> 80% of MIT spinoffs succeed _provided_ they have at least one management person in the team at the start. The business person represents the "voice of the customer" and that's what keeps the engineers and product development on track.
我们决定为SFP项目制作T恤,正在构思背后的印花内容。此前我们计划印上...
若能读到此文,我本该在工作的
This is, in my opinion, a crock. Hackers are perfectly capable of hearing the voice of the customer without a business person to amplify the signal for them. Larry Page and Sergey Brin were grad students in computer science, which presumably makes them "engineers." Do you suppose Google is only good because they had some business guy whispering in their ears what customers wanted? It seems to me the business guys who did the most for Google were the ones who obligingly flew Altavista into a hillside just as Google was getting started. The hard part about figuring out what customers want is figuring out that you need to figure it out. But that's something you can learn quickly. It's like seeing the other interpretation of an ambiguous picture. As soon as someone tells you there's a rabbit as well as a duck, it's hard not to see it. And compared to the sort of problems hackers are used to solving, giving customers what they want is easy. Anyone who can write an optimizing compiler can design a UI that doesn't confuse users, once they _choose_ to focus on that problem. And once you apply that kind of brain power to petty but profitable questions, you can create wealth very rapidly. That's the essence of a startup: having brilliant people do work that's beneath them. Big companies try to hire the right person for the job. Startups win because they don't—because they take people so smart that they would in a big company be doing "research," and set them to work instead on problems of the most immediate and mundane sort. Think Einstein designing refrigerators. [7] If you want to learn what people want, read Dale Carnegie's _How to Win Friends and Influence People._ [8] When a friend recommended this book, I couldn't believe he was serious. But he insisted it was good, so I read it, and he was right. It deals with the most difficult problem in human experience: how to see things from other people's point of view, instead of thinking only of yourself.
[1] SFP申请者:请不要认为落选意味着我们否定你的创意。由于今年夏天我们希望保持初创团队的小规模,一些优秀提案同样会被婉拒。
[2] 古董商总试图让每位顾客相信,他们展示的物件是稀世珍品,仅有少数人得见。实则那些东西可能已在货架上积压多年,被推销给一拨又一拨买家。
Most smart people don't do that very well. But adding this ability to raw brainpower is like adding tin to copper. The result is bronze, which is so much harder that it seems a different metal. A hacker who has learned what to make, and not just how to make, is extraordinarily powerful. And not just at making money: look what a small group of volunteers has achieved with Firefox. Doing an Artix teaches you to make something people want in the same way that not drinking anything would teach you how much you depend on water. But it would be more convenient for all involved if the Summer Founders didn't learn this on our dime—if they could skip the Artix phase and go right on to make something customers wanted. That, I think, is going to be the real experiment this summer. How long will it take them to grasp this? We decided we ought to have T-Shirts for the SFP, and we'd been thinking about what to print on the back. Till now we'd been planning to use.
[3] 不过他对Viaweb也曾持怀疑态度。我有确凿证据——在初创期的某个月份,我们打过赌:若他通过Viaweb赚到百万美元,就得去打耳洞。后来我们可没让他赖账。
> If you can read this, I should be working.
[4] 我曾编写程序生成"Web"与三字母单词的所有组合。由此发现多数三字母词都很糟糕:Webpig(网络猪)、Webdog(网络狗)、Webfat(网络肥)、Webzit(网络痘)、Webfug。但其中有个Webvia,我调换顺序得到了Viaweb。
[5] 销售服务远比产品容易,正如靠婚礼演出谋生比卖唱片简单。但产品利润更丰厚。泡沫时期,许多公司借咨询服务创造营收,将其包装成产品销售收入——这更符合上市故事的需要。
but now we've decided it's going to be
[6] 特雷弗·布莱克威尔提出初创公式:"观察有消费能力的人群,发现他们浪费时间之处,设计解决方案并尝试销售。令人惊讶的是,再微小的问题都可能孕育出盈利市场。"
> Make something people want.
[7] 要让顶尖人才从事枯燥工作,必须提供超额回报。这正是初创公司总用股权而非单纯薪资吸引人的原因。
[8] 建议购买1940-50年代的旧版,而非为迎合当下潮流改编的新版。原版虽含某些非政治正确观点,但带着时代背景阅读原著,总比读那些为保护你而净化的新版更有价值。
Notes [1] SFP applicants: please don't assume that not being accepted means we think your idea is bad. Because we want to keep the number of startups small this first summer, we're going to have to turn down some good proposals too. [2] Dealers try to give each customer the impression that the stuff they're showing him is something special that only a few people have seen, when in fact it may have been sitting in their racks for years while they tried to unload it on buyer after buyer. [3] On the other hand, he was skeptical about Viaweb too. I have a precise measure of that, because at one point in the first couple months we made a bet: if he ever made a million dollars out of Viaweb, he'd get his ear pierced. We didn't let him off, either. [4] I wrote a program to generate all the combinations of "Web" plus a three letter word. I learned from this that most three letter words are bad: Webpig, Webdog, Webfat, Webzit, Webfug. But one of them was Webvia; I swapped them to make Viaweb. [5] It's much easier to sell services than a product, just as it's easier to make a living playing at weddings than by selling recordings. But the margins are greater on products. So during the Bubble a lot of companies used consulting to generate revenues they could attribute to the sale of products, because it made a better story for an IPO. [6] Trevor Blackwell presents the following recipe for a startup: "Watch people who have money to spend, see what they're wasting their time on, cook up a solution, and try selling it to them. It's surprising how small a problem can be and still provide a profitable market for a solution." [7] You need to offer especially large rewards to get great people to do tedious work.
致谢 比尔·伯奇、特雷弗·布莱克威尔、杰西卡·利文斯顿和罗伯特·莫里斯审阅了本文草稿。
That's why startups always pay equity rather than just salary. [8] Buy an old copy from the 1940s or 50s instead of the current edition, which has been rewritten to suit present fashions. The original edition contained a few unPC ideas, but it's always better to read an original book, bearing in mind that it's a book from a past era, than to read a new version sanitized for your protection. Thanks to Bill Birch, Trevor Blackwell, Jessica Livingston, and Robert Morris for reading drafts of this.
| Russian Translation | | | Italian Translation | Japanese Translation.
If you liked this, you may also like _Hackers & Painters_.
April 2005 "Suits make a corporate comeback," says the _New York Times_. Why does this sound familiar? Maybe because the suit was also back in February, September 2004, June 2004, March 2004, September 2003, November 2002, April 2002, and February 2002. Why do the media keep running stories saying suits are back? Because PR firms tell them to. One of the most surprising things I discovered during my brief business career was the existence of the PR industry, lurking like a huge, quiet submarine beneath the news. Of the stories you read in traditional media that aren't about politics, crimes, or disasters, more than half probably come from PR firms. I know because I spent years hunting such "press hits." Our startup spent its entire marketing budget on PR: at a time when we were assembling our own computers to save money, we were paying a PR firm $16,000 a month. And they were worth it. PR is the news equivalent of search engine optimization; instead of buying ads, which readers ignore, you get yourself inserted directly into the stories. [1] Our PR firm was one of the best in the business. In 18 months, they got press hits in over 60 different publications. And we weren't the only ones they did great things for.
《纽约时报》宣称:"西装正迎来企业界的回归"。为何这话似曾相识?或许因为早在2005年2月、2004年9月、2004年6月、2004年3月、2003年9月、2002年11月、2002年4月和2002年2月,媒体就反复宣告过西装的复兴。
为何媒体持续炒作"西装回归"?因为公关公司在幕后推动。我短暂商旅生涯中最惊人的发现,就是潜伏在新闻海面下的巨型潜艇——公关产业。在传统媒体涉及政治、犯罪与灾难之外的报道中,超半数内容都源自公关公司。
这番认知源于我多年追踪"媒体曝光"的经历。我们的初创企业将全部营销预算投入公关:在靠自行组装电脑省钱的阶段,我们每月支付公关公司1.6万美元。这笔钱物有所值。公关就是新闻界的搜索引擎优化——与其购买被读者无视的广告,不如直接植入报道。[1]
我们的公关公司是业内翘楚。18个月内,他们让60多家媒体进行了报道。其他客户同样获益匪浅:1997年某初创公司创始人咨询是否该雇佣他们,我盛赞其物超所值,却暗自嘀咕——谁会为拍卖网站取名"eBay"?
In 1997 I got a call from another startup founder considering hiring them to promote his company. I told him they were PR gods, worth every penny of their outrageous fees. But I remember thinking his company's name was odd. Why call an auction site "eBay"? Symbiosis PR is not dishonest. Not quite. In fact, the reason the best PR firms are so effective is precisely that they aren't dishonest. They give reporters genuinely valuable information. A good PR firm won't bug reporters just because the client tells them to; they've worked hard to build their credibility with reporters, and they don't want to destroy it by feeding them mere propaganda. If anyone is dishonest, it's the reporters. The main reason PR firms exist is that reporters are lazy. Or, to put it more nicely, overworked. Really they ought to be out there digging up stories for themselves. But it's so tempting to sit in their offices and let PR firms bring the stories to them. After all, they know good PR firms won't lie to them. A good flatterer doesn't lie, but tells his victim selective truths (what a nice color your eyes are). Good PR firms use the same strategy: they give reporters stories that are true, but whose truth favors their clients. For example, our PR firm often pitched stories about how the Web let small merchants compete with big ones. This was perfectly true. But the reason reporters ended up writing stories about this particular truth, rather than some other one, was that small merchants were our target market, and we were paying the piper. Different publications vary greatly in their reliance on PR firms. At the bottom of the heap are the trade press, who make most of their money from advertising and would give the magazines away for free if advertisers would let them. [2] The average trade publication is a bunch of ads, glued together by just enough articles to make it look like a magazine.
公关并非欺诈。顶尖公关公司的核心竞争力恰恰在于诚信。他们为记者提供真实有价值的信息,不会因客户施压而骚扰记者——其精心建立的媒体信誉不容虚假宣传玷污。
若说存在欺骗,问题多在记者身上。公关业存在的根本原因,是记者们的懈怠(或委婉说——超负荷)。本该主动挖掘新闻的他们,却安坐办公室等待公关公司投喂。毕竟,他们深知优秀公关公司不会撒谎。
高明谄媚者不说谎,只选择性陈述真相(比如夸赞对方瞳色美丽)。优秀公关公司同理:提供真实却对客户有利的报道角度。
例如,我们公司常推广"网络助小商户对抗巨头"的选题。这完全属实。但记者们聚焦这一现象而非其他真相,只因小商户是我们的目标客户——谁付费,谁点戏。
They're so desperate for "content" that some will print your press releases almost verbatim, if you take the trouble to write them to read like articles. At the other extreme are publications like the _New York Times_ and the _Wall Street Journal_. Their reporters do go out and find their own stories, at least some of the time. They'll listen to PR firms, but briefly and skeptically. We managed to get press hits in almost every publication we wanted, but we never managed to crack the print edition of the _Times_. [3] The weak point of the top reporters is not laziness, but vanity. You don't pitch stories to them. You have to approach them as if you were a specimen under their all-seeing microscope, and make it seem as if the story you want them to run is something they thought of themselves. Our greatest PR coup was a two-part one. We estimated, based on some fairly informal math, that there were about 5000 stores on the Web. We got one paper to print this number, which seemed neutral enough. But once this "fact" was out there in print, we could quote it to other publications, and claim that with 1000 users we had 20% of the online store market. This was roughly true. We really did have the biggest share of the online store market, and 5000 was our best guess at its size. But the way the story appeared in the press sounded a lot more definite. Reporters like definitive statements. For example, many of the stories about Jeremy Jaynes's conviction say that he was one of the 10 worst spammers. This "fact" originated in Spamhaus's ROKSO list, which I think even Spamhaus would admit is a rough guess at the top spammers. The first stories about Jaynes cited this source, but now it's simply repeated as if it were part of the indictment. [4] All you can say with certainty about Jaynes is that he was a fairly big spammer.
不同媒体对公关公司的依赖度差异显著。行业媒体处于食物链底端,其营收主要来自广告,甚至愿免费赠刊。[2]普通行业刊物就像用勉强像文章的胶水粘合的广告合集,渴求"内容"到几乎原文照登精心伪装的新闻稿。
而《纽约时报》《华尔街日报》等顶级媒体则处于另一极端。他们的记者至少会部分自主采编,对公关公司持审慎态度。我们几乎攻陷所有目标媒体,却始终未能登陆《时报》印刷版。[3]
顶级记者的弱点不是懒惰而是虚荣。你不能直接推销选题,必须让他们觉得这是其明察秋毫的自主发现。
我们最成功的公关案例分两步走:通过非正式统计估算全网约有5000家网店,先让某媒体刊登这个看似中立的数字。待其成为"既定事实",便可向其他媒体宣称我们1000用户占据20%市场份额。
But reporters don't want to print vague stuff like "fairly big." They want statements with punch, like "top ten." And PR firms give them what they want. Wearing suits, we're told, will make us 3.6 percent more productive. Buzz Where the work of PR firms really does get deliberately misleading is in the generation of "buzz." They usually feed the same story to several different publications at once. And when readers see similar stories in multiple places, they think there is some important trend afoot. Which is exactly what they're supposed to think. When Windows 95 was launched, people waited outside stores at midnight to buy the first copies. None of them would have been there without PR firms, who generated such a buzz in the news media that it became self-reinforcing, like a nuclear chain reaction. I doubt PR firms realize it yet, but the Web makes it possible to track them at work. If you search for the obvious phrases, you turn up several efforts over the years to place stories about the return of the suit. For example, the Reuters article that got picked up by USA Today in September 2004. "The suit is back," it begins. Trend articles like this are almost always the work of PR firms. Once you know how to read them, it's straightforward to figure out who the client is. With trend stories, PR firms usually line up one or more "experts" to talk about the industry generally. In this case we get three: the NPD Group, the creative director of GQ, and a research director at Smith Barney. [5] When you get to the end of the experts, look for the client. And bingo, there it is: The Men's Wearhouse.
这基本属实——我们确是最大网店平台,5000家也是最佳估算。但媒体报道使其显得确凿无疑。
记者钟爱斩钉截铁的论断。比如众多关于Jeremy Jaynes定罪的报道称其为"十大垃圾邮件发送者"之一。该"事实"源自Spamhaus的ROKSO名单(即便Spamhaus也承认这只是粗略排名)。早期报道尚注明出处,如今却如同起诉书内容般被直接引用。[4]
关于Jaynes唯一能确定的是"相当活跃的垃圾邮件发送者"。但记者厌恶"相当"这类模糊表述,他们需要"十大"这样的劲爆标题——而公关公司深谙此道。就像西装能提升3.6%生产力的论断。
公关公司真正刻意操纵的是制造"热点"。他们通常同时向多家媒体投放相同选题。当读者在不同平台看到相似报道,自然会认为重大趋势正在形成——这正是设计好的认知。
Not surprising, considering The Men's Wearhouse was at that moment running ads saying "The Suit is Back." Talk about a successful press hit-- a wire service article whose first sentence is your own ad copy. The secret to finding other press hits from a given pitch is to realize that they all started from the same document back at the PR firm. Search for a few key phrases and the names of the clients and the experts, and you'll turn up other variants of this story. Casual fridays are out and dress codes are in writes Diane E. Lewis in _The Boston Globe_. In a remarkable coincidence, Ms. Lewis's industry contacts also include the creative director of GQ. Ripped jeans and T-shirts are out, writes Mary Kathleen Flynn in _US News & World Report_. And _she too_ knows the creative director of GQ. Men's suits are back writes Nicole Ford in Sexbuzz.Com ("the ultimate men's entertainment magazine"). Dressing down loses appeal as men suit up at the office writes Tenisha Mercer of _The Detroit News_. Now that so many news articles are online, I suspect you could find a similar pattern for most trend stories placed by PR firms. I propose we call this new sport "PR diving," and I'm sure there are far more striking examples out there than this clump of five stories. Online After spending years chasing them, it's now second nature to me to recognize press hits for what they are. But before we hired a PR firm I had no idea where articles in the mainstream media came from. I could tell a lot of them were crap, but I didn't realize why.
Windows 95发售时,午夜排队抢购的盛况完全由公关公司导演。他们在媒体制造的连锁反应,如同核裂变般自我强化。
虽然公关公司尚未察觉,但网络已使其行踪可循。搜索关键词就会发现多年来西装回归的系列策划。例如2004年9月《今日美国》转载的路透社文章开篇即宣告:"西装回来了"。
此类趋势报道几乎都是公关公司手笔。掌握诀窍后,锁定客户易如反掌。趋势类报道通常配备数位"行业专家"点评,本例中就包括NPD集团、GQ创意总监和史密斯巴尼研究主管。[5]专家名单之后,正主浮出水面:Men's Wearhouse。
这不意外——当时Men's Wearhouse正在投放"西装回归"的广告。首句即广告语的通讯社报道,堪称公关杰作。
Remember the exercises in critical reading you did in school, where you had to look at a piece of writing and step back and ask whether the author was telling the whole truth? If you really want to be a critical reader, it turns out you have to step back one step further, and ask not just whether the author is telling the truth, but _why he's writing about this subject at all._ Online, the answer tends to be a lot simpler. Most people who publish online write what they write for the simple reason that they want to. You can't see the fingerprints of PR firms all over the articles, as you can in so many print publications-- which is one of the reasons, though they may not consciously realize it, that readers trust bloggers more than _Business Week_. I was talking recently to a friend who works for a big newspaper. He thought the print media were in serious trouble, and that they were still mostly in denial about it. "They think the decline is cyclic," he said. "Actually it's structural." In other words, the readers are leaving, and they're not coming back. Why? I think the main reason is that the writing online is more honest. Imagine how incongruous the _New York Times_ article about suits would sound if you read it in a blog: > The urge to look corporate-- sleek, commanding, prudent, yet with just a touch of hubris on your well-cut sleeve-- is an unexpected development in a time of business disgrace..
追踪同系列报道的秘诀是识别其共同的公关底稿。搜索关键词与客户/专家姓名,就能发现报道变体:
- 《波士顿环球报》Diane E. Lewis撰文称"休闲星期五过时,正装规范回归"——巧合的是,其信源也包括GQ创意总监。 - 《美国新闻与世界报道》Mary Kathleen Flynn报道"破洞牛仔裤T恤失宠"——她也"恰好"认识GQ创意总监。 - Sexbuzz.com("终极男性娱乐杂志")Nicole Ford宣布"男装西装归来"。 - 《底特律新闻》Tenisha Mercer描述"办公室休闲风褪色,男士重拾正装"。
如今多数新闻都已上网,相信任何公关制造的潮流都能找到类似传播矩阵。我提议将这种侦查游戏命名为"公关深潜",且必有比这五篇更惊人的案例。
多年追逐让我对"媒体曝光"形成条件反射般的识别力。但在雇佣公关公司前,我完全不懂主流媒体报道的源头。虽能察觉许多内容粗劣,却不明白成因。
The problem with this article is not just that it originated in a PR firm. The whole tone is bogus. This is the tone of someone writing down to their audience. Whatever its flaws, the writing you find online is authentic. It's not mystery meat cooked up out of scraps of pitch letters and press releases, and pressed into molds of zippy journalese. It's people writing what they think. I didn't realize, till there was an alternative, just how artificial most of the writing in the mainstream media was. I'm not saying I used to believe what I read in _Time_ and _Newsweek_. Since high school, at least, I've thought of magazines like that more as guides to what ordinary people were being told to think than as sources of information. But I didn't realize till the last few years that writing for publication didn't have to mean writing that way. I didn't realize you could write as candidly and informally as you would if you were writing to a friend. Readers aren't the only ones who've noticed the change. The PR industry has too. A hilarious article on the site of the PR Society of America gets to the heart of the matter:
记得学校教的批判性阅读吗?那时我们要退后一步审视作者是否陈述全部真相。但真正的批判性阅读需要再退一步——不仅判断真实性,更要追问"作者为何要写这个主题"。
网络世界的答案往往更纯粹。多数网络作者写作只因心之所向。你很难像在纸媒那样看到公关公司的指纹——或许这正是读者潜意识里更信任博主而非《商业周刊》的原因。
最近与某大报友人交谈,他认为纸媒深陷结构性危机却仍自欺欺人:"他们以为衰退是周期性的,实则是根本性的。"换言之,流失的读者永不回头。
为何?我认为核心在于网络写作更诚实。试想《纽约时报》这段西装报道出现在博客会多么怪异:
> Bloggers are sensitive about becoming mouthpieces for other organizations and companies, which is the reason they began blogging in the first place.
> 在这个商业丑闻频发的时代,人们对"企业范儿"的渴望——精致、权威、谨慎,却又在剪裁考究的袖口暗藏傲气——着实出人意料。
这篇文章的问题不仅在于它出自一家公关公司之手。整篇文章的基调都是虚假的,透着一股居高临下对读者说教的腔调。
尽管存在各种缺陷,你在网上读到的文字至少是真实的。它们不是用推销信和新闻稿的边角料拼凑出来的"神秘肉饼",再塞进浮夸新闻体的模具里成型。这些文字记录的是人们真实的想法。
直到出现另一种选择,我才意识到主流媒体的大多数内容有多么做作。我并不是说过去会相信《时代周刊》和《新闻周刊》的内容——至少从高中起,我就把这类杂志视为观察大众被灌输什么思想的指南,而非信息来源。但直到最近几年我才明白,公开发表的文字本不必如此刻板。我从未意识到,写作可以像给朋友写信那样坦率随意。
PR people fear bloggers for the same reason readers like them. And that means there may be a struggle ahead. As this new kind of writing draws readers away from traditional media, we should be prepared for whatever PR mutates into to compensate. When I think how hard PR firms work to score press hits in the traditional media, I can't imagine they'll work any less hard to feed stories to bloggers, if they can figure out how. Notes [1] PR has at least one beneficial feature: it favors small companies. If PR didn't work, the only alternative would be to advertise, and only big companies can afford that. [2] Advertisers pay less for ads in free publications, because they assume readers ignore something they get for free. This is why so many trade publications nominally have a cover price and yet give away free subscriptions with such abandon. [3] Different sections of the _Times_ vary so much in their standards that they're practically different papers. Whoever fed the style section reporter this story about suits coming back would have been sent packing by the regular news reporters. [4] The most striking example I know of this type is the "fact" that the Internet worm of 1988 infected 6000 computers. I was there when it was cooked up, and this was the recipe: someone guessed that there were about 60,000 computers attached to the Internet, and that the worm might have infected ten percent of them. Actually no one knows how many computers the worm infected, because the remedy was to reboot them, and this destroyed all traces. But people like numbers. And so this one is now replicated all over the Internet, like a little worm of its own. [5] Not all were necessarily supplied by the PR firm.
察觉到这种变化的不仅是读者。公关行业也注意到了。美国公关协会官网上某篇令人捧腹的文章直指核心:
> 博主们对成为其他组织和公司的传声筒极为敏感,而这恰恰是他们最初开始写博客的原因。
公关人员畏惧博主的原因,与读者喜爱博主的原因如出一辙。这意味着未来可能有一场角力。随着这类新型写作方式将读者从传统媒体吸引走,我们必须准备好面对公关行业为弥补损失而可能产生的任何变异。想到公关公司为在传统媒体上获得报道机会所付出的巨大努力,我无法想象如果他们找到方法,会不竭尽全力向博主输送故事。
注释 [1] 公关至少有一个优点:它有利于小公司。如果公关无效,唯一的替代方案就是广告,而只有大公司才负担得起广告费用。
Reporters sometimes call a few additional sources on their own, like someone adding a few fresh vegetables to a can of soup. Thanks to Ingrid Basset, Trevor Blackwell, Sarah Harlin, Jessica Livingston, Jackie McDonough, Robert Morris, and Aaron Swartz (who also found the PRSA article) for reading drafts of this. Correction: Earlier versions used a recent _Business Week_ article mentioning del.icio.us as an example of a press hit, but Joshua Schachter tells me it was spontaneous.
| The Web is a Writing Environment | A Sell-Out's Tale | How to Pitch Bloggers | Blogging for Milk | 7 Habits of Highly Effective Blog PR | PR People Need To Learn To Deal With New Gatekeepers | Marqui Blogosphere Program | PR Watch | Real Men Exfoliate | How the News is Made | January 2006: The suit is back yet again | The Decline of the Tie | Japanese Translation.
[2] 广告商在免费出版物上投放广告时出价更低,因为他们认为读者会忽视免费获得的内容。这就是为什么如此多的行业刊物名义上有定价,却又大肆派发免费订阅。
[3] 《纽约时报》不同版块的标准差异巨大,简直像不同的报纸。那些向时尚版记者灌输“西装回潮”故事的人,如果遇到常规新闻记者,早就被赶走了。
[4] 我所知最典型的例子是1988年“互联网蠕虫感染了6000台电脑”这一“事实”。我亲眼目睹了这个数字的捏造过程:有人猜测当时约有6万台电脑联网,而蠕虫可能感染了其中的10%。
实际上无人知晓蠕虫感染的准确数量,因为解决方法是重启电脑,这销毁了所有痕迹。但人们喜欢具体数字。于是这个数字如今像一条小蠕虫般爬满整个互联网。
If you liked this, you may also like _Hackers & Painters_.
[5] 并非所有信息都必然由公关公司提供。记者有时会自行联系几个额外信源,就像往罐头汤里加几片新鲜蔬菜。
致谢 感谢Ingrid Basset、Trevor Blackwell、Sarah Harlin、Jessica Livingston、Jackie McDonough、Robert Morris和Aaron Swartz(他还找到了PRSA的文章)阅读本文草稿。
更正:早期版本曾引用《商业周刊》一篇提及del.icio.us的文章作为公关案例,但Joshua Schachter告知我那是自发报道。
| 网络是写作环境 | 出卖者的自白 | 如何向博主推销故事 | 博客换牛奶 | 高效博客公关七习惯 | 公关人需学会应对新守门人 | Marqui博客圈计划 | 公关观察 | 真男人也去角质 | 新闻制造术 | 2006年1月:西装再次回潮 | 领带的衰落 | 日文译本
如果你喜欢这篇文章,可能也会喜欢《黑客与画家》。
March 2005 All the best hackers I know are gradually switching to Macs. My friend Robert said his whole research group at MIT recently bought themselves Powerbooks. These guys are not the graphic designers and grandmas who were buying Macs at Apple's low point in the mid 1990s. They're about as hardcore OS hackers as you can get. The reason, of course, is OS X. Powerbooks are beautifully designed and run FreeBSD. What more do you need to know? I got a Powerbook at the end of last year. When my IBM Thinkpad's hard disk died soon after, it became my only laptop. And when my friend Trevor showed up at my house recently, he was carrying a Powerbook identical to mine. For most of us, it's not a switch to Apple, but a return. Hard as this was to believe in the mid 90s, the Mac was in its time the canonical hacker's computer. In the fall of 1983, the professor in one of my college CS classes got up and announced, like a prophet, that there would soon be a computer with half a MIPS of processing power that would fit under an airline seat and cost so little that we could save enough to buy one from a summer job. The whole room gasped. And when the Mac appeared, it was even better than we'd hoped. It was small and powerful and cheap, as promised. But it was also something we'd never considered a computer could be: fabulously well designed. I had to have one. And I wasn't alone. In the mid to late 1980s, all the hackers I knew were either writing software for the Mac, or wanted to. Every futon sofa in Cambridge seemed to have the same fat white book lying open on it. If you turned it over, it said "Inside Macintosh." Then came Linux and FreeBSD, and hackers, who follow the most powerful OS wherever it leads, found themselves switching to Intel boxes.
我所认识的所有顶尖黑客都在逐渐转向使用Mac。我的朋友罗伯特说,他在MIT的整个研究小组最近都给自己买了Powerbook。这些人可不是90年代中期苹果低谷时购买Mac的平面设计师或老奶奶。他们是你能遇到的最硬核的操作系统黑客。
原因当然是OS X。Powerbook设计精美,运行FreeBSD。还需要知道什么更多呢?
我在去年年底买了一台Powerbook。当我的IBM Thinkpad硬盘不久后坏掉时,它成了我唯一的笔记本电脑。最近我的朋友特雷弗来我家时,也带着一台和我一模一样的Powerbook。
对我们大多数人来说,这不是转向苹果,而是一次回归。尽管在90年代中期这难以置信,但Mac曾经是黑客的标准计算机。
1983年秋天,我大学计算机科学课上的一位教授站起来像先知一样宣布,很快将有一种处理能力达到半MIPS的电脑,可以放在飞机座位下,价格低廉到我们靠暑假打工就能买得起。整个教室都倒吸一口气。当Mac出现时,它甚至比我们希望的还要好。它小巧、强大且便宜,正如承诺的那样。但它还具备我们从未想过电脑可以拥有的特质:设计得极其出色。
If you cared about design, you could buy a Thinkpad, which was at least not actively repellent, if you could get the Intel and Microsoft stickers off the front. [1] With OS X, the hackers are back. When I walked into the Apple store in Cambridge, it was like coming home. Much was changed, but there was still that Apple coolness in the air, that feeling that the show was being run by someone who really cared, instead of random corporate deal-makers. So what, the business world may say. Who cares if hackers like Apple again? How big is the hacker market, after all? Quite small, but important out of proportion to its size. When it comes to computers, what hackers are doing now, everyone will be doing in ten years. Almost all technology, from Unix to bitmapped displays to the Web, became popular first within CS departments and research labs, and gradually spread to the rest of the world. I remember telling my father back in 1986 that there was a new kind of computer called a Sun that was a serious Unix machine, but so small and cheap that you could have one of your own to sit in front of, instead of sitting in front of a VT100 connected to a single central Vax. Maybe, I suggested, he should buy some stock in this company. I think he really wishes he'd listened. In 1994 my friend Koling wanted to talk to his girlfriend in Taiwan, and to save long-distance bills he wrote some software that would convert sound to data packets that could be sent over the Internet. We weren't sure at the time whether this was a proper use of the Internet, which was still then a quasi-government entity. What he was doing is now called VoIP, and it is a huge and rapidly growing business. If you want to know what ordinary people will be doing with computers in ten years, just walk around the CS department at a good university. Whatever they're doing, you'll be doing.
我必须拥有一台。而且不止我一个人这么想。在80年代中后期,我认识的所有黑客要么在为Mac编写软件,要么渴望这么做。剑桥的每张蒲团沙发上似乎都摊开着一本相同的厚厚白皮书。如果你翻过来,上面写着《Inside Macintosh》。
后来出现了Linux和FreeBSD,黑客们追随最强大的操作系统,转而使用Intel机器。如果你在意设计,可以买一台Thinkpad,至少它不会让人反感——只要你能把前面那些Intel和微软的贴纸撕掉。[1]
随着OS X的出现,黑客们回来了。当我走进剑桥的苹果商店时,感觉就像回家一样。许多东西都变了,但空气中依然弥漫着那种苹果特有的酷劲,那种感觉表明这家店是由真正在乎产品的人运营的,而不是随波逐流的公司交易员。
商业世界可能会说:那又怎样?黑客再次喜欢苹果又有什么关系?毕竟黑客市场有多大?
很小,但重要性与规模不成正比。在计算机领域,黑客现在做的事情,十年后所有人都会做。几乎所有技术,从Unix到位图显示再到万维网,最初都是在计算机科学系和研究实验室流行起来,然后逐渐传播到全世界。
In the matter of "platforms" this tendency is even more pronounced, because novel software originates with great hackers, and they tend to write it first for whatever computer they personally use. And software sells hardware. Many if not most of the initial sales of the Apple II came from people who bought one to run VisiCalc. And why did Bricklin and Frankston write VisiCalc for the Apple II? Because they personally liked it. They could have chosen any machine to make into a star. If you want to attract hackers to write software that will sell your hardware, you have to make it something that they themselves use. It's not enough to make it "open." It has to be open and good. And open and good is what Macs are again, finally. The intervening years have created a situation that is, as far as I know, without precedent: Apple is popular at the low end and the high end, but not in the middle. My seventy year old mother has a Mac laptop. My friends with PhDs in computer science have Mac laptops. [2] And yet Apple's overall market share is still small. Though unprecedented, I predict this situation is also temporary. So Dad, there's this company called Apple. They make a new kind of computer that's as well designed as a Bang & Olufsen stereo system, and underneath is the best Unix machine you can buy. Yes, the price to earnings ratio is kind of high, but I think a lot of people are going to want these. Notes [1] These horrible stickers are much like the intrusive ads popular on pre-Google search engines. They say to the customer: you are unimportant. We care about Intel and Microsoft, not you. [2] Y Combinator is (we hope) visited mostly by hackers. The proportions of OSes are: Windows 66.4%, Macintosh 18.8%, Linux 11.4%, and FreeBSD 1.5%.
我记得1986年曾告诉父亲,有一种叫Sun的新型计算机是真正的Unix机器,但小巧便宜到可以人手一台,而不必再面对连接中央Vax的VT100终端。我建议他或许应该买些这家公司的股票。我想他现在一定后悔没听我的。
1994年,我的朋友Koling想和在台湾的女友通话,为了节省长途话费,他编写了将声音转换为数据包通过互联网传输的软件。当时我们不确定这是否是互联网的正确用法,毕竟那时互联网还是半政府性质的实体。他做的事情现在被称为VoIP,已经成为一个庞大且快速增长的产业。
如果你想知道普通人十年后会用电脑做什么,只需去一所好大学的计算机系转转。他们在做什么,你将来就会做什么。
在"平台"问题上,这种趋势更加明显,因为新颖的软件源于伟大的黑客,而他们倾向于先为自己个人使用的电脑编写程序。软件带动硬件销售。Apple II最初的销量中,许多(如果不是大多数)来自那些为了运行VisiCalc而购买它的人。为什么Bricklin和Frankston要为Apple II开发VisiCalc?因为他们个人喜欢它。他们本可以选择任何机器来创造明星产品。
如果你想吸引黑客编写能带动硬件销售的软件,就必须让他们自己使用这种硬件。仅仅"开放"是不够的。它必须既开放又优秀。
The Mac number is a big change from what it would have been five years ago.
| Italian Translation | | | Russian Translation | Chinese Translation.
而Mac终于再次做到了既开放又优秀。这些年的发展创造了一个据我所知史无前例的局面:苹果在低端和高端市场都很受欢迎,但在中端市场却不温不火。我七十岁的母亲有一台Mac笔记本。我那些拥有计算机科学博士学位的朋友们也使用Mac笔记本。[2] 然而苹果的整体市场份额仍然很小。
尽管前所未有,但我预测这种情况也是暂时的。
所以爸爸,有家叫苹果的公司。他们生产的新型电脑设计得像Bang & Olufsen音响系统一样精美,而内核是你能买到的最好的Unix机器。是的,市盈率有点高,但我认为很多人都会想要这些产品。
[1] 这些可怕的贴纸很像谷歌之前搜索引擎上流行的侵入式广告。它们向顾客传递的信息是:你不重要。我们在乎的是英特尔和微软,不是你。
[2] Y Combinator(我们希望)主要访问者是黑客。操作系统比例为:Windows 66.4%,Macintosh 18.8%,Linux 11.4%,FreeBSD 1.5%。Mac的数字与五年前相比发生了巨大变化。
March 2005 _(In the process of answering an email, I accidentally wrote a tiny essay about writing. I usually spend weeks on an essay. This one took 67 minutes—23 of writing, and 44 of rewriting.)_ I think it's far more important to write well than most people realize. Writing doesn't just communicate ideas; it generates them. If you're bad at writing and don't like to do it, you'll miss out on most of the ideas writing would have generated.
As for how to write well, here's the short version: Write a bad version 1 as fast as you can; rewrite it over and over; cut ~~out~~ everything unnecessary; write in a conversational tone; develop a nose for bad writing, so you can see and fix it in yours; imitate writers you like; if you can't get started, tell someone what you plan to write about, then write down what you said; expect 80% of the ideas in an essay to happen after you start writing it, and 50% of those you start with to be wrong; be confident enough to cut; have friends you trust read your stuff and tell you which bits are confusing or drag; don't (always) make detailed outlines; mull ideas over for a few days before writing; carry a small notebook or scrap paper with you; start writing when you think of the first sentence; if a deadline forces you to start before that, just say the most important sentence first; write about stuff you like; don't try to sound impressive; don't hesitate to change the topic on the fly; use footnotes to contain digressions; use anaphora to knit sentences together; read your essays out loud to see (a) where you stumble over awkward phrases and (b) which bits are boring (the paragraphs you dread reading); try to tell the reader something new and useful; work in fairly big quanta of time; when you restart, begin by rereading what you have so far; when you finish, leave yourself something easy to start with; accumulate notes for topics you plan to cover at the bottom of the file; don't feel obliged to cover any of them; write for a reader who won't read the essay as carefully as you do, just as pop songs are designed to sound ok on crappy car radios; if you say anything mistaken, fix it immediately; ask friends which sentence you'll regret most; go back and tone down harsh remarks; publish stuff online, because an audience makes you write more, and thus generate more ideas; print out drafts instead of just looking at them on the screen; use simple, germanic words; learn to distinguish surprises from digressions; learn to recognize the approach of an ending, and when one appears, grab it.
| Russian Translation | | | Japanese Translation | Romanian Translation | | | Spanish Translation | German Translation | | | Chinese Translation | Hungarian Translation | | | Catalan Translation | Danish Translation | | | Arabic Translation.
2005年3月 _(在回复邮件时,我无意间写了一篇关于写作的短文。通常我会花数周时间写一篇文章,但这篇只用了67分钟——23分钟写作,44分钟修改。)_ 我认为写作的重要性远超大多数人的认知。写作不仅是传递想法的工具,更是催生想法的源泉。如果你不擅长写作且厌恶写作,就会错失写作可能孕育的大部分灵感。 关于如何写好文章,以下是简明指南:尽快写出糟糕的初稿;反复修改;删减所有冗余内容;采用对话式语气;培养对拙劣文字的嗅觉,以便发现并修正自己的问题;模仿你欣赏的作家;若无从下笔,先向他人口述计划写的内容,再记录所说的话;接受文章中80%的灵感会在动笔后涌现,且初始想法中50%是错的;要有删减的魄力;请可信赖的朋友阅读并指出晦涩或拖沓处;不必(总是)列详细提纲;动笔前酝酿想法数日;随身携带小笔记本或便签纸;想到第一句话时立即开写;若截止日期迫使你提前动笔,直接写下最重要的句子;写你感兴趣的内容;别刻意追求深刻;随时灵活切换主题;用脚注处理题外话;用指代衔接句子;大声朗读以发现(a)拗口处和(b)乏味段落(那些你害怕重读的部分);力求向读者传递新颖有用的信息;以大块时间专注写作;重启写作时先重读已写内容;收尾时给自己留个容易的起点;在文档底部积累计划涉及的主题笔记;无需强迫自己覆盖所有笔记;为粗读的读者而写,就像流行歌曲要为劣质车载收音机优化效果;发现错误立即修正;询问朋友哪些句子会让你后悔;回头软化过激言论;在线发布文章,因为读者能促使你多写从而产生更多灵感;打印草稿而非仅屏幕审阅;使用简单的日耳曼语系词汇;学会区分意外发现与离题内容;学会识别结尾的临近,当它出现时果断抓住。
| 俄语译本 | | | 日语译本 | 罗马尼亚语译本 | | | 西班牙语译本 | 德语译本 | | | 中文译本 | 匈牙利语译本 | | | 加泰罗尼亚语译本 | 丹麦语译本 | | | 阿拉伯语译本
[](https://s.turbifycdn.com/aah/paulgraham/undergraduation-11.gif) Want to start a startup? Get funded by Y Combinator.
March 2005 _(Parts of this essay began as replies to students who wrote to me with questions.)_ Recently I've had several emails from computer science undergrads asking what to do in college. I might not be the best source of advice, because I was a philosophy major in college. But I took so many CS classes that most CS majors thought I was one. I was certainly a hacker, at least. Hacking What should you do in college to become a good hacker? There are two main things you can do: become very good at programming, and learn a lot about specific, cool problems. These turn out to be equivalent, because each drives you to do the other. The way to be good at programming is to work (a) a lot (b) on hard problems. And the way to make yourself work on hard problems is to work on some very engaging project. Odds are this project won't be a class assignment. My friend Robert learned a lot by writing network software when he was an undergrad. One of his projects was to connect Harvard to the Arpanet; it had been one of the original nodes, but by 1984 the connection had died. [1] Not only was this work not for a class, but because he spent all his time on it and neglected his studies, he was kicked out of school for a year. [2] It all evened out in the end, and now he's a professor at MIT. But you'll probably be happier if you don't go to that extreme; it caused him a lot of worry at the time. Another way to be good at programming is to find other people who are good at it, and learn what they know. Programmers tend to sort themselves into tribes according to the type of work they do and the tools they use, and some tribes are smarter than others.
Look around you and see what the smart people seem to be working on; there's usually a reason. Some of the smartest people around you are professors. So one way to find interesting work is to volunteer as a research assistant. Professors are especially interested in people who can solve tedious system-administration type problems for them, so that is a way to get a foot in the door. What they fear are flakes and resume padders. It's all too common for an assistant to result in a net increase in work. So you have to make it clear you'll mean a net decrease. Don't be put off if they say no. Rejection is almost always less personal than the rejectee imagines. Just move on to the next. (This applies to dating too.) Beware, because although most professors are smart, not all of them work on interesting stuff. Professors have to publish novel results to advance their careers, but there is more competition in more interesting areas of research. So what less ambitious professors do is turn out a series of papers whose conclusions are novel because no one else cares about them. You're better off avoiding these. I never worked as a research assistant, so I feel a bit dishonest recommending that route. I learned to program by writing stuff of my own, particularly by trying to reverse-engineer Winograd's SHRDLU. I was as obsessed with that program as a mother with a new baby. Whatever the disadvantages of working by yourself, the advantage is that the project is all your own. You never have to compromise or ask anyone's permission, and if you have a new idea you can just sit down and start implementing it. In your own projects you don't have to worry about novelty (as professors do) or profitability (as businesses do).
All that matters is how hard the project is technically, and that has no correlation to the nature of the application. "Serious" applications like databases are often trivial and dull technically (if you ever suffer from insomnia, try reading the technical literature about databases) while "frivolous" applications like games are often very sophisticated. I'm sure there are game companies out there working on products with more intellectual content than the research at the bottom nine tenths of university CS departments. If I were in college now I'd probably work on graphics: a network game, for example, or a tool for 3D animation. When I was an undergrad there weren't enough cycles around to make graphics interesting, but it's hard to imagine anything more fun to work on now. Math When I was in college, a lot of the professors believed (or at least wished) that computer science was a branch of math. This idea was strongest at Harvard, where there wasn't even a CS major till the 1980s; till then one had to major in applied math. But it was nearly as bad at Cornell. When I told the fearsome Professor Conway that I was interested in AI (a hot topic then), he told me I should major in math. I'm still not sure whether he thought AI required math, or whether he thought AI was nonsense and that majoring in something rigorous would cure me of such stupid ambitions. In fact, the amount of math you need as a hacker is a lot less than most university departments like to admit. I don't think you need much more than high school math plus a few concepts from the theory of computation. (You have to know what an n^2 algorithm is if you want to avoid writing them.) Unless you're planning to write math applications, of course. Robotics, for example, is all math. But while you don't literally need math for most kinds of hacking, in the sense of knowing 1001 tricks for differentiating formulas, math is very much worth studying for its own sake.
It's a valuable source of metaphors for almost any kind of work.[3] I wish I'd studied more math in college for that reason. Like a lot of people, I was mathematically abused as a child. I learned to think of math as a collection of formulas that were neither beautiful nor had any relation to my life (despite attempts to translate them into "word problems"), but had to be memorized in order to do well on tests. One of the most valuable things you could do in college would be to learn what math is really about. This may not be easy, because a lot of good mathematicians are bad teachers. And while there are many popular books on math, few seem good. The best I can think of are W. W. Sawyer's. And of course Euclid. [4] Everything Thomas Huxley said "Try to learn something about everything and everything about something." Most universities aim at this ideal. But what's everything? To me it means, all that people learn in the course of working honestly on hard problems. All such work tends to be related, in that ideas and techniques from one field can often be transplanted successfully to others. Even others that seem quite distant. For example, I write essays the same way I write software: I sit down and blow out a lame version 1 as fast as I can type, then spend several weeks rewriting it. Working on hard problems is not, by itself, enough. Medieval alchemists were working on a hard problem, but their approach was so bogus that there was little to learn from studying it, except possibly about people's ability to delude themselves. Unfortunately the sort of AI I was trying to learn in college had the same flaw: a very hard problem, blithely approached with hopelessly inadequate techniques. Bold? Closer to fraudulent. The social sciences are also fairly bogus, because they're so much influenced by intellectual fashions.
If a physicist met a colleague from 100 years ago, he could teach him some new things; if a psychologist met a colleague from 100 years ago, they'd just get into an ideological argument. Yes, of course, you'll learn something by taking a psychology class. The point is, you'll learn more by taking a class in another department. The worthwhile departments, in my opinion, are math, the hard sciences, engineering, history (especially economic and social history, and the history of science), architecture, and the classics. A survey course in art history may be worthwhile. Modern literature is important, but the way to learn about it is just to read. I don't know enough about music to say. You can skip the social sciences, philosophy, and the various departments created recently in response to political pressures. Many of these fields talk about important problems, certainly. But the way they talk about them is useless. For example, philosophy talks, among other things, about our obligations to one another; but you can learn more about this from a wise grandmother or E. B. White than from an academic philosopher. I speak here from experience. I should probably have been offended when people laughed at Clinton for saying "It depends on what the meaning of the word 'is' is." I took about five classes in college on what the meaning of "is" is. Another way to figure out which fields are worth studying is to create the _dropout graph._ For example, I know many people who switched from math to computer science because they found math too hard, and no one who did the opposite. People don't do hard things gratuitously; no one will work on a harder problem unless it is proportionately (or at least log(n)) more rewarding. So probably math is more worth studying than computer science. By similar comparisons you can make a graph of all the departments in a university. At the bottom you'll find the subjects with least intellectual content.
If you use this method, you'll get roughly the same answer I just gave. Language courses are an anomaly. I think they're better considered as extracurricular activities, like pottery classes. They'd be far more useful when combined with some time living in a country where the language is spoken. On a whim I studied Arabic as a freshman. It was a lot of work, and the only lasting benefits were a weird ability to identify semitic roots and some insights into how people recognize words. Studio art and creative writing courses are wildcards. Usually you don't get taught much: you just work (or don't work) on whatever you want, and then sit around offering "crits" of one another's creations under the vague supervision of the teacher. But writing and art are both very hard problems that (some) people work honestly at, so they're worth doing, especially if you can find a good teacher. Jobs Of course college students have to think about more than just learning. There are also two practical problems to consider: jobs, and graduate school. In theory a liberal education is not supposed to supply job training. But everyone knows this is a bit of a fib. Hackers at every college learn practical skills, and not by accident. What you should learn to get a job depends on the kind you want. If you want to work in a big company, learn how to hack Blub on Windows. If you want to work at a cool little company or research lab, you'll do better to learn Ruby on Linux. And if you want to start your own company, which I think will be more and more common, master the most powerful tools you can find, because you're going to be in a race against your competitors, and they'll be your horse. There is not a direct correlation between the skills you should learn in college and those you'll use in a job. You should aim slightly high in college.
[](https://s.turbifycdn.com/aah/paulgraham/undergraduation-11.gif) 想创业? 获得 Y Combinator 的资金支持。
2005年3月 _(本文部分内容最初是对学生来信提问的回复。)_ 最近我收到几封计算机专业本科生的邮件,询问大学期间该做什么。我可能不是最佳建议来源,因为大学时我主修哲学。不过我选修了太多计算机课程,以至于多数计算机专业学生都以为我是他们中的一员。至少,我确实是个黑客。 黑客之道 大学期间如何成为优秀黑客?有两件事至关重要:精通编程,深入了解某些酷炫的特定问题。这两者本质相通,因为每件事都会推动你去做另一件。 成为编程高手的途径是(a)大量(b)攻克难题。而让自己坚持攻克难题的方法,是投身于极具吸引力的项目。 这类项目通常不会是课堂作业。我的朋友Robert本科时通过编写网络软件学到很多。他曾将哈佛重新接入Arpanet(该网络曾是早期节点,但到1984年连接已中断)[1]。这项目不仅与课程无关,还让他因荒废学业被勒令休学一年[2]。最终结果证明付出值得——他现在是MIT教授。不过你最好别走这种极端,当年他可没少焦虑。 另一条精进之路是向高手学习。程序员会按工作类型和工具形成不同圈子,有些圈子更聪明。观察身边聪明人在做什么,通常存在深层原因。 教授可能是你身边最聪明的人。成为研究助理是接触有趣工作的好方法。教授尤其需要能解决繁琐系统管理问题的人,这是打开机会之门的突破口。他们最怕遇到混日子和刷简历的人——太多助理最终反而增加了工作量。你必须明确自己会是净减负者。 被拒绝也别气馁。拒绝往往没你想的那么针对个人。换下个目标就行(追异性同理)。 注意:虽然多数教授聪明,但并非所有人都研究有趣课题。教授需要发表新成果推动职业发展,而越有趣的领域竞争越激烈。于是有些教授会产出系列"新颖"论文——其结论只因无人关心才显独特。这类研究最好避开。 我从未当过研究助理,所以推荐这条路径时有点心虚。我是通过自主编程学习,特别是尝试逆向工程Winograd的SHRDLU。当时我对那个程序的痴迷程度堪比母亲对待新生儿。 独立工作的劣势是孤独,优势则是完全自主。无需妥协或请示,有新想法坐下就能实现。 个人项目不必像教授那样追求创新,或像企业那样考虑盈利。技术难度才是关键,而这与应用性质无关。"严肃"如数据库的应用常技术平庸(失眠时不妨读数据库文献),"轻浮"如游戏的程序反而技术精深。我相信某些游戏公司的智力成果,能碾压九成大学计算机系的科研。 若我现在读本科,可能会钻研图形学:比如网络游戏或3D动画工具。当年计算机性能不足导致图形学乏味,但如今这恐怕是最有趣的方向了。 数学 我读大学时,许多教授坚信(或希望)计算机科学是数学分支。哈佛这观念最甚——1980年代前连计算机专业都没有,只能主修应用数学。康奈尔情况也差不多。当我向可怕的Conway教授表示对AI感兴趣(当时的热点),他建议我改学数学。至今我不确定他是认为AI需要数学基础,还是觉得AI纯属胡闹,想用严谨数学治好我的愚蠢野心。 实际上,黑客所需的数学远比多数院系声称的少。我认为掌握高中数学加上计算理论的部分概念足矣(比如必须明白n^2算法才能避免写出它)。当然,编写数学应用除外——比如机器人领域全是数学。 尽管多数编程不需解微分方程这类数学技巧,但数学本身绝对值得学习。它能为你提供解决各类问题的隐喻[3]。正因如此,我后悔大学没多修数学课。 和多数人一样,我童年遭受过数学虐待。老师把数学教成一堆既不美、又与生活无关的公式(尽管试图转化为"应用题"),只为考试死记硬背。 大学最该做的事之一,是弄清数学的真正本质。这不容易,因为优秀数学家往往不善教学。虽然数学科普书不少,但佳作寥寥。我认为W. W.
In workouts a football player may bench press 300 pounds, even though he may never have to exert anything like that much force in the course of a game. Likewise, if your professors try to make you learn stuff that's more advanced than you'll need in a job, it may not just be because they're academics, detached from the real world. They may be trying to make you lift weights with your brain. The programs you write in classes differ in three critical ways from the ones you'll write in the real world: they're small; you get to start from scratch; and the problem is usually artificial and predetermined. In the real world, programs are bigger, tend to involve existing code, and often require you to figure out what the problem is before you can solve it. You don't have to wait to leave (or even enter) college to learn these skills. If you want to learn how to deal with existing code, for example, you can contribute to open-source projects. The sort of employer you want to work for will be as impressed by that as good grades on class assignments. In existing open-source projects you don't get much practice at the third skill, deciding what problems to solve. But there's nothing to stop you starting new projects of your own. And good employers will be even more impressed with that. What sort of problem should you try to solve? One way to answer that is to ask what you need as a user. For example, I stumbled on a good algorithm for spam filtering because I wanted to stop getting spam. Now what I wish I had was a mail reader that somehow prevented my inbox from filling up. I tend to use my inbox as a todo list. But that's like using a screwdriver to open bottles; what one really wants is a bottle opener. Grad School What about grad school? Should you go? And how do you get into a good one? In principle, grad school is professional training in research, and you shouldn't go unless you want to do research as a career.
And yet half the people who get PhDs in CS don't go into research. I didn't go to grad school to become a professor. I went because I wanted to learn more. So if you're mainly interested in hacking and you go to grad school, you'll find a lot of other people who are similarly out of their element. And if half the people around you are out of their element in the same way you are, are you really out of your element? There's a fundamental problem in "computer science," and it surfaces in situations like this. No one is sure what "research" is supposed to be. A lot of research is hacking that had to be crammed into the form of an academic paper to yield one more quantum of publication. So it's kind of misleading to ask whether you'll be at home in grad school, because very few people are quite at home in computer science. The whole field is uncomfortable in its own skin. So the fact that you're mainly interested in hacking shouldn't deter you from going to grad school. Just be warned you'll have to do a lot of stuff you don't like. Number one will be your dissertation. Almost everyone hates their dissertation by the time they're done with it. The process inherently tends to produce an unpleasant result, like a cake made out of whole wheat flour and baked for twelve hours. Few dissertations are read with pleasure, especially by their authors. But thousands before you have suffered through writing a dissertation. And aside from that, grad school is close to paradise. Many people remember it as the happiest time of their lives. And nearly all the rest, including me, remember it as a period that would have been, if they hadn't had to write a dissertation. [5] The danger with grad school is that you don't see the scary part upfront. PhD programs start out as college part 2, with several years of classes. So by the time you face the horror of writing a dissertation, you're already several years in.
If you quit now, you'll be a grad-school dropout, and you probably won't like that idea. When Robert got kicked out of grad school for writing the Internet worm of 1988, I envied him enormously for finding a way out without the stigma of failure. On the whole, grad school is probably better than most alternatives. You meet a lot of smart people, and your glum procrastination will at least be a powerful common bond. And of course you have a PhD at the end. I forgot about that. I suppose that's worth something. The greatest advantage of a PhD (besides being the union card of academia, of course) may be that it gives you some baseline confidence. For example, the Honeywell thermostats in my house have the most atrocious UI. My mother, who has the same model, diligently spent a day reading the user's manual to learn how to operate hers. She assumed the problem was with her. But I can think to myself "If someone with a PhD in computer science can't understand this thermostat, it _must_ be badly designed." If you still want to go to grad school after this equivocal recommendation, I can give you solid advice about how to get in. A lot of my friends are CS professors now, so I have the inside story about admissions. It's quite different from college. At most colleges, admissions officers decide who gets in. For PhD programs, the professors do. And they try to do it well, because the people they admit are going to be working for them. Apparently only recommendations really matter at the best schools. Standardized tests count for nothing, and grades for little. The essay is mostly an opportunity to disqualify yourself by saying something stupid. The only thing professors trust is recommendations, preferably from people they know. [6] So if you want to get into a PhD program, the key is to impress your professors. And from my friends who are professors I know what impresses them: not merely trying to impress them.
They're not impressed by students who get good grades or want to be their research assistants so they can get into grad school. They're impressed by students who get good grades and want to be their research assistants because they're genuinely interested in the topic. So the best thing you can do in college, whether you want to get into grad school or just be good at hacking, is figure out what you truly like. It's hard to trick professors into letting you into grad school, and impossible to trick problems into letting you solve them. College is where faking stops working. From this point, unless you want to go work for a big company, which is like reverting to high school, the only way forward is through doing what you love. Notes [1] No one seems to have minded, which shows how unimportant the Arpanet (which became the Internet) was as late as 1984. [2] This is why, when I became an employer, I didn't care about GPAs. In fact, we actively sought out people who'd failed out of school. We once put up posters around Harvard saying "Did you just get kicked out for doing badly in your classes because you spent all your time working on some project of your own? Come work for us!" We managed to find a kid who had been, and he was a great hacker. When Harvard kicks undergrads out for a year, they have to get jobs. The idea is to show them how awful the real world is, so they'll understand how lucky they are to be in college. This plan backfired with the guy who came to work for us, because he had more fun than he'd had in school, and made more that year from stock options than any of his professors did in salary. So instead of crawling back repentant at the end of the year, he took another year off and went to Europe. He did eventually graduate at about 26. [3] Eric Raymond says the best metaphors for hackers are in set theory, combinatorics, and graph theory.
Trevor Blackwell reminds you to take math classes intended for math majors. "'Math for engineers' classes sucked mightily. In fact any 'x for engineers' sucks, where x includes math, law, writing and visual design." [4] Other highly recommended books: _What is Mathematics?_ , by Courant and Robbins; _Geometry and the Imagination_ by Hilbert and Cohn-Vossen. And for those interested in graphic design, Byrne's Euclid. [5] If you wanted to have the perfect life, the thing to do would be to go to grad school, secretly write your dissertation in the first year or two, and then just enjoy yourself for the next three years, dribbling out a chapter at a time. This prospect will make grad students' mouths water, but I know of no one who's had the discipline to pull it off. [6] One professor friend says that 15-20% of the grad students they admit each year are "long shots." But what he means by long shots are people whose applications are perfect in every way, except that no one on the admissions committee knows the professors who wrote the recommendations. So if you want to get into grad school in the sciences, you need to go to college somewhere with real research professors. Otherwise you'll seem a risky bet to admissions committees, no matter how good you are. Which implies a surprising but apparently inevitable consequence: little liberal arts colleges are doomed. Most smart high school kids at least consider going into the sciences, even if they ultimately choose not to.
Why go to a college that limits their options? Thanks to Trevor Blackwell, Alex Lewin, Jessica Livingston, Robert Morris, Eric Raymond, and several anonymous CS professors for reading drafts of this, and to the students whose questions began it.
| More Advice for Undergrads | Joel Spolsky: Advice for Computer Science College Students | Eric Raymond: How to Become a Hacker.
Sawyer的书最佳,当然还有欧几里得[4]。 通识教育 赫胥黎说:"尽量广博地涉猎,精深地专研。"多数大学追求这种理想。 但"广博"指什么?我认为是所有人在认真解决难题时获得的智慧。这类工作本质相通——某个领域的思路常能成功移植到看似遥远的领域。比如我写文章和写软件方式相同:先快速敲出糟糕的初稿,再用数周重写。 单攻克难题还不够。炼金术士也在解决难题,但其方法谬误到除了自欺欺人外毫无学习价值。不幸的是,我大学时钻研的AI领域也有同样缺陷:用明显不足的技术轻率挑战超难问题。是勇敢?更接近欺诈。 社会科学也较虚浮,受学术潮流影响太大。物理学家遇见百年前的同行能传授新知;心理学家遇见百年前的同行只会陷入意识形态争论。当然,心理学课也有价值,但选其他领域的课收获更大。 我认为值得学习的领域包括:数学、硬科学、工程、历史(尤其是经济史/社会史/科学史)、建筑、古典学。艺术史概论可能有价值。现代文学很重要,但自学阅读即可。音乐领域我不够了解。 可以跳过社会科学、哲学和因政治压力新设的院系。这些领域确实探讨重要问题,但探讨方式无效。比如哲学讨论人与人之间的义务,但智慧祖母或E.B.怀特的作品比哲学教授更能给你启发。 我现身说法:当人们嘲笑克林顿说"这取决于'是'这个词的含义是什么"时,我本该感到被冒犯——大学时我修了五门关于"是"之含义的课程。 判断学科价值的另一方法是绘制"退学流向图"。比如我认识许多因数学太难转计算机专业的人,却未见反向案例。人不会无故选择更难的路——除非回报成正比(或至少log(n))。因此数学可能比计算机科学更值得学习。通过类似比较,你能绘制全校各院系价值图谱,底层是智力含量最低的学科。 用此法得出的结论与我前述建议大致吻合。 语言课是特例,最好视为陶艺课般的课外活动。若结合海外生活体验会实用得多。我大一突发奇想学阿拉伯语,付出巨大却只收获识别闪族词根的奇怪能力,以及对人类识词机制的些许洞察。 艺术创作与写作课像抽奖。通常老师不怎么教,只是让学生自由创作(或不创作),然后在松散指导下互评作品。但写作和艺术都是有人真诚钻研的难题,值得尝试——尤其找到好老师时。 工作 大学生当然不能只考虑学习,还需思考两个现实问题:工作和研究生院。 理论上通识教育不提供职业培训,但众所周知这是善意的谎言。每个学校的黑客都在学习实用技能,且非偶然。 该学什么取决于想找的工作。想进大公司就学Windows下的Blub语言;想去酷炫小公司或实验室就学Linux下的Ruby;想创业(我认为会越来越普遍)就掌握能找到的最强大工具——你将与竞争对手赛跑,这些工具就是你的赛马。 在校所学与职场所用技能并非直接对应。大学目标应定得稍高些。 橄榄球员训练时能卧推300磅,尽管比赛从不需要这么大力量。同样,教授让你学习比职场所需更超前的知识,未必因为他们脱离现实,可能是想让你的大脑"举重"。 课堂编程与真实编程有三点关键差异:规模小;从零开始;问题常是人为设定的。现实中程序更庞大,常涉及既有代码,且往往需要先定义问题再解决。 不必等到毕业(甚至入学)才学习这些技能。比如想学习处理既有代码,可以参与开源项目。优秀雇主对此的重视程度不亚于课堂作业高分。 现有开源项目很少锻炼第三项技能——决定解决什么问题。但你可以自主启动新项目,这会让优秀雇主更印象深刻。 该解决什么问题?答案是:你作为用户需要什么。比如我偶然发明优秀垃圾邮件过滤算法,就因自己想屏蔽垃圾邮件。现在我渴望能防止收件箱爆满的邮件客户端——我把收件箱当待办清单用,但这像用螺丝刀开瓶盖,真正需要的是开瓶器。 研究生院 该读研吗?如何进入好学校? 理论上研究生院是研究职业培训,除非想以研究为业否则不该读。但半数计算机博士最终未进入研究领域。我读研就不是为当教授,而是想学更多。 所以如果你痴迷编程却去读研,会发现许多同类人。当半数人都与你同样"错位",真的算错位吗? "计算机科学"存在根本性问题——没人确定"研究"该是什么。很多研究只是被硬塞进论文形式的编程成果,只为增加发表量。 因此问"是否适合读研"容易误导——几乎没人真正适合计算机科学,整个领域都处于认知失调中。热爱编程不该阻碍你读研,但要准备好做大量不喜欢的事。 头号噩梦是毕业论文。几乎所有人写完时都痛恨自己的论文。这个过程注定产出令人不快的成果,就像用全麦粉烘烤十二小时的蛋糕。少有人(尤其是作者自己)会愉快阅读毕业论文。 但无数前辈都熬过来了。除此之外,研究生院近乎天堂。许多人视其为人生最快乐时光,而其他多数人(包括我)则认为——如果没有毕业论文,那本应如此[5]。 研究生院的危险在于:恐怖部分不会提前显现。前几年仍是大学延续,等面临论文恐惧时已深陷数年。此时放弃会背负"辍学"标签,多数人不愿接受。当Robert因编写1988年蠕虫病毒被开除时,我无比羡慕他找到了免于"失败"污名的退出方式。 总体而言,研究生院可能优于多数选择。你能遇见许多聪明人,共同的拖延抑郁至少成为强力纽带。当然最终还能获得博士学位——我差点忘了,这总归有点价值。 博士学位的最大价值(除了作为学术界的入场券)或许是赋予基准自信。比如我家霍尼韦尔恒温器的UI极其反人类。我母亲认真研读整天说明书才学会操作,她以为是自己的问题。而我会想:"如果计算机博士都搞不懂这设计,那它肯定烂透了。" 若听完这番模棱两可的建议仍想读研,我可以给出实用申请策略。如今许多朋友是计算机教授,我了解录取内幕——与本科截然不同。研究生录取由教授决定,他们非常认真,因为录取者将为其工作。 顶尖学校基本只看推荐信。标准化考试毫无价值,成绩影响甚微。个人陈述主要是说蠢话自毁的机会。教授只信任推荐信,最好是熟人写的[6]。 因此申请博士项目的关键,是给教授留下印象。据我的教授朋友透露,真正打动他们的是:不刻意讨好。只为读研而刷高分或当研究助理不会打动他们,真正热爱课题的学生才会。 所以无论为读研还是成为优秀黑客,大学最该做的是找到真正热爱之事。你很难骗教授录取你,更不可能骗问题让你解决。大学是"伪装"失效的起点。此后除非想去大公司(如同退回高中),否则唯一出路就是做你热爱之事。 注释 [1] 当时无人介意,可见直到1984年Arpanet(互联网前身)仍无足轻重。 [2] 因此我成为雇主后从不看GPA。事实上我们主动寻找被退学者。有次在哈佛贴海报:"是否因沉迷个人项目荒废学业被退学?来为我们工作吧!"真找到个这样的孩子,结果是个出色黑客。 哈佛让退学生休学一年去工作,本意是展示现实世界多残酷,好让他们珍惜复学机会。但来我们这工作的家伙玩得比上学还开心,那年股票期权收入超过所有教授工资。于是年底他非但没悔悟返校,反而又休学一年去了欧洲。最终他约26岁才毕业。 [3] Eric Raymond认为对黑客最有用的数学是集合论、组合数学和图论。 Trevor Blackwell提醒:要选数学专业开的课。"'工科数学'烂透了。实际上所有'工科x'(包括数学、法律、写作和视觉设计)都很糟。" [4] 其他强烈推荐书籍:柯朗与罗宾斯的《数学是什么?》、希尔伯特与康福森的《直观几何》。对平面设计感兴趣可看伯恩版《几何原本》。 [5] 完美人生的做法是:读研头一两年秘密写完论文,之后三年逍遥度日,偶尔交一章。这设想会让研究生流口水,但我没见过真有执行力实现的人。 [6] 有位教授朋友说,每年录取的15-20%研究生是"高风险人选"——指申请材料完美,但推荐人无人认识。 因此想读理科研究生,本科就要去有真正研究型教授的学校。否则录取委员会总会觉得你风险高,无论多优秀。 这导致惊人却必然的后果:小型文理学院注定衰亡。多数聪明高中生至少考虑过理科方向,何必选择限制自己选项的大学? 致谢 感谢Trevor Blackwell、Alex Lewin、Jessica Livingston、Robert Morris、Eric Raymond和几位匿名计算机教授阅读本文草稿,以及最初提问的学生们。
March 2005 A couple months ago I got an email from a recruiter asking if I was interested in being a "technologist in residence" at a new venture capital fund. I think the idea was to play Karl Rove to the VCs' George Bush. I considered it for about four seconds. Work for a VC fund? Ick. One of my most vivid memories from our startup is going to visit Greylock, the famous Boston VCs. They were the most arrogant people I've met in my life. And I've met a lot of arrogant people. [1] I'm not alone in feeling this way, of course. Even a VC friend of mine dislikes VCs. "Assholes," he says. But lately I've been learning more about how the VC world works, and a few days ago it hit me that there's a reason VCs are the way they are. It's not so much that the business attracts jerks, or even that the power they wield corrupts them. The real problem is the way they're paid. The problem with VC funds is that they're _funds_. Like the managers of mutual funds or hedge funds, VCs get paid a percentage of the money they manage: about 2% a year in management fees, plus a percentage of the gains. So they want the fund to be huge-- hundreds of millions of dollars, if possible. But that means each partner ends up being responsible for investing a lot of money. And since one person can only manage so many deals, each deal has to be for multiple millions of dollars. This turns out to explain nearly all the characteristics of VCs that founders hate. It explains why VCs take so agonizingly long to make up their minds, and why their due diligence feels like a body cavity search. [2] With so much at stake, they have to be paranoid. It explains why they steal your ideas. Every founder knows that VCs will tell your secrets to your competitors if they end up investing in them. It's not unheard of for VCs to meet you when they have no intention of funding you, just to pick your brain for a competitor.
几个月前,我收到一封猎头邮件,询问我是否有兴趣成为一家新风险投资基金的"驻场技术专家"。我猜这个角色大概相当于VC圈里的卡尔·罗夫(辅佐小布什的政治操盘手)。
我考虑了大约四秒钟。为风投基金工作?呕。
创业时期最鲜活的记忆之一,是拜访波士顿著名风投Greylock。他们是我这辈子见过最傲慢的人——而我可没少见识傲慢之徒。[1]
当然,并非只有我这么想。我的一位VC朋友也讨厌同行:"全是混蛋",他说。
但随着我对风投运作模式了解渐深,几天前突然顿悟:VC的种种行径确有缘由。与其说是行业吸引混蛋,或是权力腐蚀人心,不如说问题出在薪酬结构上。
This prospect makes naive founders clumsily secretive. Experienced founders treat it as a cost of doing business. Either way it sucks. But again, the only reason VCs are so sneaky is the giant deals they do. With so much at stake, they have to be devious. It explains why VCs tend to interfere in the companies they invest in. They want to be on your board not just so that they can advise you, but so that they can watch you. Often they even install a new CEO. Yes, he may have extensive business experience. But he's also their man: these newly installed CEOs always play something of the role of a political commissar in a Red Army unit. With so much at stake, VCs can't resist micromanaging you. The huge investments themselves are something founders would dislike, if they realized how damaging they can be. VCs don't invest $x million because that's the amount you need, but because that's the amount the structure of their business requires them to invest. Like steroids, these sudden huge investments can do more harm than good. Google survived enormous VC funding because it could legitimately absorb large amounts of money. They had to buy a lot of servers and a lot of bandwidth to crawl the whole Web. Less fortunate startups just end up hiring armies of people to sit around having meetings. In principle you could take a huge VC investment, put it in treasury bills, and continue to operate frugally. You just try it. And of course giant investments mean giant valuations. They have to, or there's not enough stock left to keep the founders interested. You might think a high valuation is a great thing. Many founders do. But you can't eat paper. You can't benefit from a high valuation unless you can somehow achieve what those in the business call a "liquidity event," and the higher your valuation, the narrower your options for doing that.
风投基金的根本问题在于它们是"基金"。与共同基金或对冲基金经理类似,VC按管理资金比例抽成:每年约2%管理费,再加利润分成。因此他们追求庞大规模——最好能管理数亿美元。这意味着每位合伙人需负责巨额投资,而个人精力有限,每笔交易都必须是千万级规模。
这几乎解释了创始人厌恶的所有VC特质。
它解释了为何VC决策慢如蜗牛,尽职调查像直肠检查般令人不适[2]。涉及巨额资金时,他们不得不疑神疑鬼。
它解释了为何窃取创意。所有创始人都知道,若VC最终投资了你的竞争对手,他们会毫不犹豫泄露你的机密。更不乏VC假意约谈只為套取情报。天真的创始人笨拙地严防死守,老练的则视之为商业成本。无论如何都糟透了。但重申一次,VC如此狡诈只因交易规模太大——巨额赌注前,他们不得不阴险。
它解释了为何VC总爱干涉被投企业。他们加入董事会不仅为提供建议,更是为了监视。常会空降CEO——此人或许确有商业经验,但本质是VC安插的"政委"。涉及巨额资金时,他们忍不住要微观管理。
若意识到危害,创始人本应抗拒巨额融资。VC投X百万美元非因你需要,而是其商业模式要求。如同类固醇,突然注入的巨资弊大于利。谷歌能消化巨额风投是因确需大量服务器和带宽抓取全网。运气欠佳的创业公司只能雇人成天开会。
Many a founder would be happy to sell his company for $15 million, but VCs who've just invested at a pre-money valuation of $8 million won't hear of that. You're rolling the dice again, whether you like it or not. Back in 1997, one of our competitors raised $20 million in a single round of VC funding. This was at the time more than the valuation of our entire company. Was I worried? Not at all: I was delighted. It was like watching a car you're chasing turn down a street that you know has no outlet. Their smartest move at that point would have been to take every penny of the $20 million and use it to buy us. We would have sold. Their investors would have been furious of course. But I think the main reason they never considered this was that they never imagined we could be had so cheap. They probably assumed we were on the same VC gravy train they were. In fact we only spent about $2 million in our entire existence. And that gave us flexibility. We could sell ourselves to Yahoo for $50 million, and everyone was delighted. If our competitor had done that, the last round of investors would presumably have lost money. I assume they could have vetoed such a deal. But no one those days was paying a lot more than Yahoo. So unless their founders could pull off an IPO (which would be difficult with Yahoo as a competitor), they had no choice but to ride the thing down. The puffed-up companies that went public during the Bubble didn't do it just because they were pulled into it by unscrupulous investment bankers. Most were pushed just as hard from the other side by VCs who'd invested at high valuations, leaving an IPO as the only way out. The only people dumber were retail investors. So it was literally IPO or bust. Or rather, IPO then bust, or just bust. Add up all the evidence of VCs' behavior, and the resulting personality is not attractive. In fact, it's the classic villain: alternately cowardly, greedy, sneaky, and overbearing.
理论上你可以把风投资金买成国债继续节俭运营——尽管试试看。
巨额投资必然伴随超高估值,否则创始人持股将失去激励。高估值看似美妙(许多创始人确实这么想),但纸面富贵不能果腹。除非实现"流动性事件",否则高估值毫无意义——而估值越高,退出路径越窄。多少创始人愿以1500万美元出售公司,但刚按800万投前估值注资的VC绝不同意。不管情愿与否,你只能继续赌命。
1997年,某竞争对手单轮融资2000万美元——超过我们公司总估值。我慌吗?简直欣喜若狂,就像看着前车驶入死胡同。
当时他们最明智的做法本该是用这2000万收购我们(我们绝对会卖)。其投资者当然会暴怒,但我猜他们根本没想到我们如此"便宜"——大概以为我们也坐着VC的豪华列车。
实际上我们全程只花了200万,这赋予我们灵活性。5000万美元卖给雅虎时皆大欢喜。若那家竞争对手这么做,后期投资者必然亏损(他们很可能否决交易)。当时没人出价高过雅虎,除非能强行IPO(有雅虎竞争谈何容易),否则只能坐视沉没。
I used to take it for granted that VCs were like this. Complaining that VCs were jerks used to seem as naive to me as complaining that users didn't read the reference manual. Of course VCs were jerks. How could it be otherwise? But I realize now that they're not intrinsically jerks. VCs are like car salesmen or bureaucrats: the nature of their work turns them into jerks. I've met a few VCs I like. Mike Moritz seems a good guy. He even has a sense of humor, which is almost unheard of among VCs. From what I've read about John Doerr, he sounds like a good guy too, almost a hacker. But they work for the very best VC funds. And my theory explains why they'd tend to be different: just as the very most popular kids don't have to persecute nerds, the very best VCs don't have to act like VCs. They get the pick of all the best deals. So they don't have to be so paranoid and sneaky, and they can choose those rare companies, like Google, that will actually benefit from the giant sums they're compelled to invest. VCs often complain that in their business there's too much money chasing too few deals. Few realize that this also describes a flaw in the way funding works at the level of individual firms. Perhaps this was the sort of strategic insight I was supposed to come up with as a "technologist in residence." If so, the good news is that they're getting it for free. The bad news is it means that if you're not one of the very top funds, you're condemned to be the bad guys. Notes [1] After Greylock booted founder Philip Greenspun out of ArsDigita, he wrote a hilarious but also very informative essay about it. [2] Since most VCs aren't tech guys, the technology side of their due diligence tends to be like a body cavity search by someone with a faulty knowledge of human anatomy. After a while we were quite sore from VCs attempting to probe our nonexistent database orifice.
泡沫时期上市的浮夸公司,不单是被无良投行引诱,更多是被高估值注资的VC逼迫——IPO成为唯一出路。比他们更蠢的只有散户。所以实质是"不IPO就完蛋",或者说"IPO然后完蛋,或者直接完蛋"。
综合所有VC行为证据,得出的形象并不讨喜:集怯懦、贪婪、狡诈与专横于一身的经典反派。
我曾理所当然认为VC就该如此。抱怨VC混蛋,就像抱怨用户不看说明书般天真。VC当然是混蛋,不然呢?
但现在我明白,他们并非天生混蛋。VC如同车贩子或官僚——职业性质使其变成混蛋。
我也遇到过喜欢的VC。红杉的莫里茨似乎不错,甚至具备VC圈罕见的幽默感。从报道看,KPCB的约翰·杜尔也像好人,近乎极客气质。但他们效力于顶级基金。我的理论正好解释其特殊性:正如最受欢迎的学生无需霸凌书呆子,顶级VC也不必像典型VC行事——他们能挑最好的项目,自然不用疑神疑鬼,还能选中谷歌这类真正需要巨额资金的公司。
VC常抱怨行业"资金过剩而好项目稀缺",却少有人意识到这同样揭示了单个基金运作模式的缺陷。
No, we don't use Oracle. We just store the data in files. Our secret is to use an OS that doesn't lose our data. Which OS? FreeBSD. Why do you use that instead of Windows NT? Because it's better and it doesn't cost anything. What, you're using a _freeware_ OS? How many times that conversation was repeated. Then when we got to Yahoo, we found they used FreeBSD and stored their data in files too.
| Chinese Translation | | | Japanese Translation.
或许这就是"驻场技术专家"该提供的战略洞察。好消息是他们免费得到了,坏消息是:若非顶级基金,注定要当恶人。
[1] Greylock将ArsDigita创始人菲利普·格林斯彭赶走后,他写了篇妙趣横生又信息量巨大的文章。
[2] 由于多数VC不懂技术,其技术尽调就像解剖学知识欠缺的直肠检查。我们被VC们徒劳探查"数据库孔洞"搞得烦不胜烦:
"不用Oracle?就存文件里?" "秘诀是选用不会丢数据的系统" "什么系统?FreeBSD" "为什么不用Windows NT?" "因为更好用还免费" "什么?你们用免费系统?"
这类对话反复上演。后来到了雅虎才发现——他们也用FreeBSD存文件。
Want to start a startup? Get funded by Y Combinator.
March 2005 _(This essay is derived from a talk at the Harvard Computer Society.)_ You need three things to create a successful startup: to start with good people, to make something customers actually want, and to spend as little money as possible. Most startups that fail do it because they fail at one of these. A startup that does all three will probably succeed. And that's kind of exciting, when you think about it, because all three are doable. Hard, but doable. And since a startup that succeeds ordinarily makes its founders rich, that implies getting rich is doable too. Hard, but doable. If there is one message I'd like to get across about startups, that's it. There is no magically difficult step that requires brilliance to solve. The Idea In particular, you don't need a brilliant idea to start a startup around. The way a startup makes money is to offer people better technology than they have now. But what people have now is often so bad that it doesn't take brilliance to do better. Google's plan, for example, was simply to create a search site that didn't suck. They had three new ideas: index more of the Web, use links to rank search results, and have clean, simple web pages with unintrusive keyword-based ads. Above all, they were determined to make a site that was good to use. No doubt there are great technical tricks within Google, but the overall plan was straightforward. And while they probably have bigger ambitions now, this alone brings them a billion dollars a year. [1] There are plenty of other areas that are just as backward as search was before Google. I can think of several heuristics for generating ideas for startups, but most reduce to this: look at something people are trying to do, and figure out how to do it in a way that doesn't suck.
想创业吗? 获得 Y Combinator 的资助。
(本文改编自在哈佛计算机协会的演讲。)
For example, dating sites currently suck far worse than search did before Google. They all use the same simple-minded model. They seem to have approached the problem by thinking about how to do database matches instead of how dating works in the real world. An undergrad could build something better as a class project. And yet there's a lot of money at stake. Online dating is a valuable business now, and it might be worth a hundred times as much if it worked. An idea for a startup, however, is only a beginning. A lot of would-be startup founders think the key to the whole process is the initial idea, and from that point all you have to do is execute. Venture capitalists know better. If you go to VC firms with a brilliant idea that you'll tell them about if they sign a nondisclosure agreement, most will tell you to get lost. That shows how much a mere idea is worth. The market price is less than the inconvenience of signing an NDA. Another sign of how little the initial idea is worth is the number of startups that change their plan en route. Microsoft's original plan was to make money selling programming languages, of all things. Their current business model didn't occur to them until IBM dropped it in their lap five years later. Ideas for startups are worth something, certainly, but the trouble is, they're not transferrable. They're not something you could hand to someone else to execute. Their value is mainly as starting points: as questions for the people who had them to continue thinking about. What matters is not ideas, but the people who have them. Good people can fix bad ideas, but good ideas can't save bad people. People What do I mean by good people? One of the best tricks I learned during our startup was a rule for deciding who to hire. Could you describe the person as an animal? It might be hard to translate that into another language, but I think everyone in the US knows what it means.
要创建一个成功的创业公司,你需要三件事:优秀的人才、客户真正想要的产品,以及尽可能少的资金消耗。大多数失败的创业公司都在这三点中的某一点上栽了跟头。而三者兼备的创业公司,大概率会成功。
仔细想想,这其实挺令人振奋的,因为这三件事都是可以实现的。难,但可行。而一家成功的创业公司通常会让创始人变得富有,这意味着致富也是可以实现的。难,但可行。
It means someone who takes their work a little too seriously; someone who does what they do so well that they pass right through professional and cross over into obsessive. What it means specifically depends on the job: a salesperson who just won't take no for an answer; a hacker who will stay up till 4:00 AM rather than go to bed leaving code with a bug in it; a PR person who will cold-call _New York Times_ reporters on their cell phones; a graphic designer who feels physical pain when something is two millimeters out of place. Almost everyone who worked for us was an animal at what they did. The woman in charge of sales was so tenacious that I used to feel sorry for potential customers on the phone with her. You could sense them squirming on the hook, but you knew there would be no rest for them till they'd signed up. If you think about people you know, you'll find the animal test is easy to apply. Call the person's image to mind and imagine the sentence "so-and-so is an animal." If you laugh, they're not. You don't need or perhaps even want this quality in big companies, but you need it in a startup. For programmers we had three additional tests. Was the person genuinely smart? If so, could they actually get things done? And finally, since a few good hackers have unbearable personalities, could we stand to have them around? That last test filters out surprisingly few people. We could bear any amount of nerdiness if someone was truly smart. What we couldn't stand were people with a lot of attitude. But most of those weren't truly smart, so our third test was largely a restatement of the first. When nerds are unbearable it's usually because they're trying too hard to seem smart. But the smarter they are, the less pressure they feel to act smart.
如果关于创业公司我有什么核心理念想传达,那就是:创业没有哪一步是神奇到需要天才才能解决的。
具体来说,你并不需要一个绝妙的创意才能创业。创业公司赚钱的方式是为人们提供比现有技术更好的产品。但人们现在使用的产品往往糟糕透顶,以至于做出更好的东西并不需要多高的天赋。
So as a rule you can recognize genuinely smart people by their ability to say things like "I don't know," "Maybe you're right," and "I don't understand x well enough." This technique doesn't always work, because people can be influenced by their environment. In the MIT CS department, there seems to be a tradition of acting like a brusque know-it-all. I'm told it derives ultimately from Marvin Minsky, in the same way the classic airline pilot manner is said to derive from Chuck Yeager. Even genuinely smart people start to act this way there, so you have to make allowances. It helped us to have Robert Morris, who is one of the readiest to say "I don't know" of anyone I've met. (At least, he was before he became a professor at MIT.) No one dared put on attitude around Robert, because he was obviously smarter than they were and yet had zero attitude himself. Like most startups, ours began with a group of friends, and it was through personal contacts that we got most of the people we hired. This is a crucial difference between startups and big companies. Being friends with someone for even a couple days will tell you more than companies could ever learn in interviews. [2] It's no coincidence that startups start around universities, because that's where smart people meet. It's not what people learn in classes at MIT and Stanford that has made technology companies spring up around them. They could sing campfire songs in the classes so long as admissions worked the same. If you start a startup, there's a good chance it will be with people you know from college or grad school. So in theory you ought to try to make friends with as many smart people as you can in school, right? Well, no. Don't make a conscious effort to schmooze; that doesn't work well with hackers. What you should do in college is work on your own projects. Hackers should do this even if they don't plan to start startups, because it's the only real way to learn how to program.
例如,谷歌最初的计划只是做一个不烂的搜索引擎。他们有三个新点子:索引更多网页、用链接排名搜索结果,以及设计简洁的网页界面,搭配不扰人的关键词广告。最重要的是,他们决心打造一个真正好用的网站。谷歌内部无疑有许多高明的技术技巧,但整体计划其实很简单。尽管他们如今的野心可能更大,但仅凭这一点,他们每年就能赚取十亿美元。[1]
还有许多领域和谷歌之前的搜索引擎一样落后。我能想到几条启发创业点子的经验法则,但大多数可以归结为:观察人们正在尝试做什么,然后想办法把它做得不那么烂。
比如,目前的交友网站比谷歌之前的搜索引擎还要糟糕得多。它们都采用同样简单粗暴的模式。设计这些网站的人似乎是从数据库匹配的角度思考问题,而不是从现实中的约会逻辑出发。一个本科生都能在课程项目中做出更好的东西。然而,这里涉及大量金钱。在线交友如今已是一门有价值的生意,如果它能真正有效,市场可能比现在大一百倍。
In some cases you may collaborate with other students, and this is the best way to get to know good hackers. The project may even grow into a startup. But once again, I wouldn't aim too directly at either target. Don't force things; just work on stuff you like with people you like. Ideally you want between two and four founders. It would be hard to start with just one. One person would find the moral weight of starting a company hard to bear. Even Bill Gates, who seems to be able to bear a good deal of moral weight, had to have a co-founder. But you don't want so many founders that the company starts to look like a group photo. Partly because you don't need a lot of people at first, but mainly because the more founders you have, the worse disagreements you'll have. When there are just two or three founders, you know you have to resolve disputes immediately or perish. If there are seven or eight, disagreements can linger and harden into factions. You don't want mere voting; you need unanimity. In a technology startup, which most startups are, the founders should include technical people. During the Internet Bubble there were a number of startups founded by business people who then went looking for hackers to create their product for them. This doesn't work well. Business people are bad at deciding what to do with technology, because they don't know what the options are, or which kinds of problems are hard and which are easy. And when business people try to hire hackers, they can't tell which ones are good. Even other hackers have a hard time doing that. For business people it's roulette. Do the founders of a startup have to include business people? That depends. We thought so when we started ours, and we asked several people who were said to know about this mysterious thing called "business" if they would be the president. But they all said no, so I had to do it myself. And what I discovered was that business was no great mystery.
然而,创业点子只是一个开始。许多潜在的创业者认为整个创业过程的关键在于最初的创意,之后只需要执行即可。风投们更清楚真相。如果你带着一个绝妙的点子去找风投,要求他们签保密协议才肯透露,大多数人会让你滚蛋。这说明仅仅一个点子的价值有多低——市场定价甚至抵不上一份保密协议的麻烦。
初始点子价值不高的另一个迹象是,许多创业公司中途会改变计划。微软最初的计划是卖编程语言(谁能想到呢?),直到五年后IBM把操作系统业务丢给他们,他们才想到现在的商业模式。
It's not something like physics or medicine that requires extensive study. You just try to get people to pay you for stuff. I think the reason I made such a mystery of business was that I was disgusted by the idea of doing it. I wanted to work in the pure, intellectual world of software, not deal with customers' mundane problems. People who don't want to get dragged into some kind of work often develop a protective incompetence at it. Paul Erdos was particularly good at this. By seeming unable even to cut a grapefruit in half (let alone go to the store and buy one), he forced other people to do such things for him, leaving all his time free for math. Erdos was an extreme case, but most husbands use the same trick to some degree. Once I was forced to discard my protective incompetence, I found that business was neither so hard nor so boring as I feared. There are esoteric areas of business that are quite hard, like tax law or the pricing of derivatives, but you don't need to know about those in a startup. All you need to know about business to run a startup are commonsense things people knew before there were business schools, or even universities. If you work your way down the Forbes 400 making an x next to the name of each person with an MBA, you'll learn something important about business school. After Warren Buffett, you don't hit another MBA till number 22, Phil Knight, the CEO of Nike. There are only 5 MBAs in the top 50\. What you notice in the Forbes 400 are a lot of people with technical backgrounds. Bill Gates, Steve Jobs, Larry Ellison, Michael Dell, Jeff Bezos, Gordon Moore. The rulers of the technology business tend to come from technology, not business.
创业点子当然有价值,但问题在于它们无法转让。你不能把点子交给别人去执行。它们的价值主要是作为起点:让想到点子的人继续深入思考。
重要的不是点子,而是拥有点子的人。优秀的人可以修正糟糕的点子,但再好的点子也救不了糟糕的团队。
So if you want to invest two years in something that will help you succeed in business, the evidence suggests you'd do better to learn how to hack than get an MBA. [3] There is one reason you might want to include business people in a startup, though: because you have to have at least one person willing and able to focus on what customers want. Some believe only business people can do this-- that hackers can implement software, but not design it. That's nonsense. There's nothing about knowing how to program that prevents hackers from understanding users, or about not knowing how to program that magically enables business people to understand them. If you can't understand users, however, you should either learn how or find a co-founder who can. That is the single most important issue for technology startups, and the rock that sinks more of them than anything else. What Customers Want It's not just startups that have to worry about this. I think most businesses that fail do it because they don't give customers what they want. Look at restaurants. A large percentage fail, about a quarter in the first year. But can you think of one restaurant that had really good food and went out of business? Restaurants with great food seem to prosper no matter what. A restaurant with great food can be expensive, crowded, noisy, dingy, out of the way, and even have bad service, and people will keep coming. It's true that a restaurant with mediocre food can sometimes attract customers through gimmicks. But that approach is very risky. It's more straightforward just to make the food good. It's the same with technology. You hear all kinds of reasons why startups fail. But can you think of one that had a massively popular product and still failed? In nearly every failed startup, the real problem was that customers didn't want the product. For most, the cause of death is listed as "ran out of funding," but that's only the immediate cause.
我说的“优秀的人”是什么意思?在我们创业期间,我学到的一个最佳技巧是关于招聘的准则:你能用“野兽”来形容这个人吗?这个词可能难以翻译成其他语言,但在美国,每个人都明白它的含义。它指的是那些对工作过于认真的人;那些把事情做到极致,以至于超越了专业范畴、进入痴迷状态的人。
具体含义因岗位而异:销售员死缠烂打绝不接受“不”作为答案;程序员会熬夜到凌晨四点也不愿留下带bug的代码睡觉;公关人员会直接冷拨《纽约时报》记者的手机;平面设计师看到元素偏移两毫米就会感到生理不适。
为我们工作的几乎每个人都是各自领域的“野兽”。负责销售的女性极其坚韧,我甚至曾为电话那头的潜在客户感到抱歉。你能感觉到他们在钩子上挣扎,但你知道,除非他们签单,否则她绝不会放手。
Why couldn't they get more funding? Probably because the product was a dog, or never seemed likely to be done, or both. When I was trying to think of the things every startup needed to do, I almost included a fourth: get a version 1 out as soon as you can. But I decided not to, because that's implicit in making something customers want. The only way to make something customers want is to get a prototype in front of them and refine it based on their reactions. The other approach is what I call the "Hail Mary" strategy. You make elaborate plans for a product, hire a team of engineers to develop it (people who do this tend to use the term "engineer" for hackers), and then find after a year that you've spent two million dollars to develop something no one wants. This was not uncommon during the Bubble, especially in companies run by business types, who thought of software development as something terrifying that therefore had to be carefully planned. We never even considered that approach. As a Lisp hacker, I come from the tradition of rapid prototyping. I would not claim (at least, not here) that this is the right way to write every program, but it's certainly the right way to write software for a startup. In a startup, your initial plans are almost certain to be wrong in some way, and your first priority should be to figure out where. The only way to do that is to try implementing them. Like most startups, we changed our plan on the fly. At first we expected our customers to be Web consultants. But it turned out they didn't like us, because our software was easy to use and we hosted the site. It would be too easy for clients to fire them. We also thought we'd be able to sign up a lot of catalog companies, because selling online was a natural extension of their existing business. But in 1996 that was a hard sell. The middle managers we talked to at catalog companies saw the Web not as an opportunity, but as something that meant more work for them.
回想你认识的人,你会发现“野兽测试”很容易应用。在脑海中想象这个人的形象,然后默念“某某是个野兽”。如果你笑了,那他们就不是。在大公司里,你可能不需要甚至不想要这种特质,但在创业公司中,你必须拥有它。
对程序员,我们还有三条额外测试:这个人是否真的聪明?如果是,他们能否真正完成任务?最后,因为少数优秀黑客性格难以忍受,我们能否容忍他们的存在?
We did get a few of the more adventurous catalog companies. Among them was Frederick's of Hollywood, which gave us valuable experience dealing with heavy loads on our servers. But most of our users were small, individual merchants who saw the Web as an opportunity to build a business. Some had retail stores, but many only existed online. And so we changed direction to focus on these users. Instead of concentrating on the features Web consultants and catalog companies would want, we worked to make the software easy to use. I learned something valuable from that. It's worth trying very, very hard to make technology easy to use. Hackers are so used to computers that they have no idea how horrifying software seems to normal people. Stephen Hawking's editor told him that every equation he included in his book would cut sales in half. When you work on making technology easier to use, you're riding that curve up instead of down. A 10% improvement in ease of use doesn't just increase your sales 10%. It's more likely to double your sales. How do you figure out what customers want? Watch them. One of the best places to do this was at trade shows. Trade shows didn't pay as a way of getting new customers, but they were worth it as market research. We didn't just give canned presentations at trade shows. We used to show people how to build real, working stores. Which meant we got to watch as they used our software, and talk to them about what they needed. No matter what kind of startup you start, it will probably be a stretch for you, the founders, to understand what users want. The only kind of software you can build without studying users is the sort for which you are the typical user. But this is just the kind that tends to be open source: operating systems, programming languages, editors, and so on. So if you're developing technology for money, you're probably not going to be developing it for people like you.
最后一条测试筛掉的人 surprisingly 很少。如果一个人真的聪明,我们可以忍受任何程度的书呆子气。我们无法忍受的是那些态度傲慢的人。但大多数傲慢的人并不真正聪明,所以第三条测试很大程度上是第一条的重述。
书呆子之所以让人难以忍受,通常是因为他们太努力显得聪明。但他们越聪明,就越不需要刻意表现。因此,你可以通过一个人能否坦然说出“我不知道”“也许你是对的”“我对X还不够了解”来判断他是否真的聪明。
Indeed, you can use this as a way to generate ideas for startups: what do people who are not like you want from technology? When most people think of startups, they think of companies like Apple or Google. Everyone knows these, because they're big consumer brands. But for every startup like that, there are twenty more that operate in niche markets or live quietly down in the infrastructure. So if you start a successful startup, odds are you'll start one of those. Another way to say that is, if you try to start the kind of startup that has to be a big consumer brand, the odds against succeeding are steeper. The best odds are in niche markets. Since startups make money by offering people something better than they had before, the best opportunities are where things suck most. And it would be hard to find a place where things suck more than in corporate IT departments. You would not believe the amount of money companies spend on software, and the crap they get in return. This imbalance equals opportunity. If you want ideas for startups, one of the most valuable things you could do is find a middle-sized non-technology company and spend a couple weeks just watching what they do with computers. Most good hackers have no more idea of the horrors perpetrated in these places than rich Americans do of what goes on in Brazilian slums. Start by writing software for smaller companies, because it's easier to sell to them. It's worth so much to sell stuff to big companies that the people selling them the crap they currently use spend a lot of time and money to do it. And while you can outhack Oracle with one frontal lobe tied behind your back, you can't outsell an Oracle salesman. So if you want to win through better technology, aim at smaller customers. [4] They're the more strategically valuable part of the market anyway. In technology, the low end always eats the high end.
这种方法并不总是奏效,因为人会受环境影响。在MIT计算机系,似乎有一种传统是表现得像个粗鲁的万事通。据说这源于Marvin Minsky,就像经典飞行员风格源于Chuck Yeager一样。即使真正聪明的人在那里也会开始这样表现,所以你得有所保留。
Robert Morris对我们帮助很大,他是我见过最愿意说“我不知道”的人之一(至少在他成为MIT教授之前是如此)。没人敢在他面前摆谱,因为他显然比他们聪明得多,却毫无傲慢之气。
和大多数创业公司一样,我们最初是一群朋友组成的团队,大部分员工也是通过私人关系招募的。这是创业公司和大公司的一个关键区别。即使只和某人做几天朋友,你也能比公司通过面试了解得更多。[2]
It's easier to make an inexpensive product more powerful than to make a powerful product cheaper. So the products that start as cheap, simple options tend to gradually grow more powerful till, like water rising in a room, they squash the "high-end" products against the ceiling. Sun did this to mainframes, and Intel is doing it to Sun. Microsoft Word did it to desktop publishing software like Interleaf and Framemaker. Mass-market digital cameras are doing it to the expensive models made for professionals. Avid did it to the manufacturers of specialized video editing systems, and now Apple is doing it to Avid. _Henry Ford_ did it to the car makers that preceded him. If you build the simple, inexpensive option, you'll not only find it easier to sell at first, but you'll also be in the best position to conquer the rest of the market. It's very dangerous to let anyone fly under you. If you have the cheapest, easiest product, you'll own the low end. And if you don't, you're in the crosshairs of whoever does. Raising Money To make all this happen, you're going to need money. Some startups have been self-funding-- Microsoft for example-- but most aren't. I think it's wise to take money from investors. To be self-funding, you have to start as a consulting company, and it's hard to switch from that to a product company. Financially, a startup is like a pass/fail course. The way to get rich from a startup is to maximize the company's chances of succeeding, not to maximize the amount of stock you retain. So if you can trade stock for something that improves your odds, it's probably a smart move. To most hackers, getting investors seems like a terrifying and mysterious process. Actually it's merely tedious. I'll try to give an outline of how it works. The first thing you'll need is a few tens of thousands of dollars to pay your expenses while you develop a prototype. This is called seed capital.
创业公司围绕大学诞生并非偶然,因为那里是聪明人聚集的地方。MIT和斯坦福周围涌现科技公司,并不是因为人们在课堂上学到了什么。哪怕课堂上只教篝火歌曲,只要招生标准不变,结果也会一样。
如果你要创业,很可能合伙人会是你在大学或研究生院认识的人。所以理论上,你应该在学校里尽可能多结交聪明人,对吧?其实不然。不要刻意去社交,这对黑客并不管用。
Because so little money is involved, raising seed capital is comparatively easy-- at least in the sense of getting a quick yes or no. Usually you get seed money from individual rich people called "angels." Often they're people who themselves got rich from technology. At the seed stage, investors don't expect you to have an elaborate business plan. Most know that they're supposed to decide quickly. It's not unusual to get a check within a week based on a half-page agreement. We started Viaweb with $10,000 of seed money from our friend Julian. But he gave us a lot more than money. He's a former CEO and also a corporate lawyer, so he gave us a lot of valuable advice about business, and also did all the legal work of getting us set up as a company. Plus he introduced us to one of the two angel investors who supplied our next round of funding. Some angels, especially those with technology backgrounds, may be satisfied with a demo and a verbal description of what you plan to do. But many will want a copy of your business plan, if only to remind themselves what they invested in. Our angels asked for one, and looking back, I'm amazed how much worry it caused me. "Business plan" has that word "business" in it, so I figured it had to be something I'd have to read a book about business plans to write. Well, it doesn't. At this stage, all most investors expect is a brief description of what you plan to do and how you're going to make money from it, and the resumes of the founders. If you just sit down and write out what you've been saying to one another, that should be fine. It shouldn't take more than a couple hours, and you'll probably find that writing it all down gives you more ideas about what to do. For the angel to have someone to make the check out to, you're going to have to have some kind of company. Merely incorporating yourselves isn't hard.
在大学里,你应该做自己的项目。即使不打算创业,黑客也应该这样做,因为这是学习编程的唯一真正途径。有时你会和其他学生合作,这是结识优秀黑客的最佳方式。项目甚至可能发展成创业公司。但再次强调,不要太直接瞄准这两个目标。顺其自然,只和你喜欢的人一起做你喜欢的事。
理想的创始人数量是2到4人。单打独斗会很难。独自一人承受创业的道德压力太重。即使是比尔·盖茨这样能承受巨大压力的人,也需要联合创始人。但创始人也不宜过多,否则公司会变成集体照。部分原因是初期不需要那么多人,但主要是因为创始人越多,分歧就越严重。当只有两三个创始人时,你们知道必须立即解决分歧,否则就会完蛋。如果有七八个创始人,分歧可能拖延并固化成派系。你们需要的不是简单投票,而是全体一致。
The problem is, for the company to exist, you have to decide who the founders are, and how much stock they each have. If there are two founders with the same qualifications who are both equally committed to the business, that's easy. But if you have a number of people who are expected to contribute in varying degrees, arranging the proportions of stock can be hard. And once you've done it, it tends to be set in stone. I have no tricks for dealing with this problem. All I can say is, try hard to do it right. I do have a rule of thumb for recognizing when you have, though. When everyone feels they're getting a slightly bad deal, that they're doing more than they should for the amount of stock they have, the stock is optimally apportioned. There is more to setting up a company than incorporating it, of course: insurance, business license, unemployment compensation, various things with the IRS. I'm not even sure what the list is, because we, ah, skipped all that. When we got real funding near the end of 1996, we hired a great CFO, who fixed everything retroactively. It turns out that no one comes and arrests you if you don't do everything you're supposed to when starting a company. And a good thing too, or a lot of startups would never get started. [5] It can be dangerous to delay turning yourself into a company, because one or more of the founders might decide to split off and start another company doing the same thing. This does happen. So when you set up the company, as well as as apportioning the stock, you should get all the founders to sign something agreeing that everyone's ideas belong to this company, and that this company is going to be everyone's only job. [If this were a movie, ominous music would begin here.] While you're at it, you should ask what else they've signed. One of the worst things that can happen to a startup is to run into intellectual property problems.
在大多数科技创业公司中,创始人应包括技术人员。互联网泡沫期间,许多创业公司由商务人士创立,然后他们寻找黑客来开发产品。这效果不佳。商务人士不擅长决定技术方向,因为他们不知道有哪些选择,也不知道哪些问题难、哪些容易。当他们试图招聘黑客时,也无法判断哪些人是优秀的。即使是其他黑客也很难判断。对商务人士来说,这就像轮盘赌。
创业公司的创始人中必须有商务人士吗?视情况而定。我们创业时以为是这样的,于是询问了几位据说懂“商业”这种神秘事物的人是否愿意担任总裁。但他们全都拒绝了,我只好自己上。结果我发现,商业并没有那么神秘。它不像物理或医学需要大量学习。你只需要想办法让人为你的东西付钱。
我认为自己曾把商业想得过于神秘,是因为我对从事商业感到厌恶。我想活在纯粹理性的软件世界里,而不是处理客户琐碎的问题。人们如果不想被拖入某种工作,往往会发展出一种“保护性无能”。Paul Erdos在这方面特别擅长。他表现得连切葡萄柚都不会(更别说去商店买了),迫使别人替他做这些事,从而把所有时间留给数学。Erdos是个极端例子,但大多数丈夫都在某种程度上使用同样的伎俩。
We did, and it came closer to killing us than any competitor ever did. As we were in the middle of getting bought, we discovered that one of our people had, early on, been bound by an agreement that said all his ideas belonged to the giant company that was paying for him to go to grad school. In theory, that could have meant someone else owned big chunks of our software. So the acquisition came to a screeching halt while we tried to sort this out. The problem was, since we'd been about to be acquired, we'd allowed ourselves to run low on cash. Now we needed to raise more to keep going. But it's hard to raise money with an IP cloud over your head, because investors can't judge how serious it is. Our existing investors, knowing that we needed money and had nowhere else to get it, at this point attempted certain gambits which I will not describe in detail, except to remind readers that the word "angel" is a metaphor. The founders thereupon proposed to walk away from the company, after giving the investors a brief tutorial on how to administer the servers themselves. And while this was happening, the acquirers used the delay as an excuse to welch on the deal. Miraculously it all turned out ok. The investors backed down; we did another round of funding at a reasonable valuation; the giant company finally gave us a piece of paper saying they didn't own our software; and six months later we were bought by Yahoo for much more than the earlier acquirer had agreed to pay. So we were happy in the end, though the experience probably took several years off my life. Don't do what we did. Before you consummate a startup, ask everyone about their previous IP history. Once you've got a company set up, it may seem presumptuous to go knocking on the doors of rich people and asking them to invest tens of thousands of dollars in something that is really just a bunch of guys with some ideas.
当我被迫抛弃这种“保护性无能”后,我发现商业既不像想象中那么难,也不那么无聊。商业中确实有深奥难懂的领域,比如税法或衍生品定价,但创业公司不需要这些。创业所需的商业知识,不过是商学院甚至大学出现之前人们就懂的常识。
如果你浏览福布斯400富豪榜,在每个拥有MBA学位的人旁边打叉,你会发现关于商学院的重要事实。在沃伦·巴菲特之后,直到第22位的耐克CEO菲尔·奈特才出现下一个MBA。前50名中只有5个MBA。在福布斯400中,你会注意到许多技术背景的人:比尔·盖茨、史蒂夫·乔布斯、拉里·埃里森、迈克尔·戴尔、杰夫·贝索斯、戈登·摩尔。科技行业的统治者往往来自技术领域,而非商业领域。因此,如果你想花两年时间学习对商业成功有帮助的东西,证据表明学习编程比读MBA更有用。[3]
But when you look at it from the rich people's point of view, the picture is more encouraging. Most rich people are looking for good investments. If you really think you have a chance of succeeding, you're doing them a favor by letting them invest. Mixed with any annoyance they might feel about being approached will be the thought: are these guys the next Google? Usually angels are financially equivalent to founders. They get the same kind of stock and get diluted the same amount in future rounds. How much stock should they get? That depends on how ambitious you feel. When you offer x percent of your company for y dollars, you're implicitly claiming a certain value for the whole company. Venture investments are usually described in terms of that number. If you give an investor new shares equal to 5% of those already outstanding in return for $100,000, then you've done the deal at a pre-money valuation of $2 million. How do you decide what the value of the company should be? There is no rational way. At this stage the company is just a bet. I didn't realize that when we were raising money. Julian thought we ought to value the company at several million dollars. I thought it was preposterous to claim that a couple thousand lines of code, which was all we had at the time, were worth several million dollars. Eventually we settled on one million, because Julian said no one would invest in a company with a valuation any lower. [6] What I didn't grasp at the time was that the valuation wasn't just the value of the code we'd written so far. It was also the value of our ideas, which turned out to be right, and of all the future work we'd do, which turned out to be a lot. The next round of funding is the one in which you might deal with actual venture capital firms. But don't wait till you've burned through your last round of funding to start approaching them. VCs are slow to make up their minds. They can take months.
不过,有一个理由让你可能想在创业团队中加入商务人士:因为至少需要一个人愿意且能够专注于客户需求。有人认为只有商务人士能做到这一点——黑客可以编写软件,但不会设计软件。这是胡说八道。懂编程不会阻碍黑客理解用户,不懂编程也不会神奇地让商务人士理解用户。
如果你无法理解用户,要么学会理解,要么找一个能理解的联合创始人。这是科技创业公司最重要的问题,也是导致最多创业公司失败的绊脚石。
You don't want to be running out of money while you're trying to negotiate with them. Getting money from an actual VC firm is a bigger deal than getting money from angels. The amounts of money involved are larger, millions usually. So the deals take longer, dilute you more, and impose more onerous conditions. Sometimes the VCs want to install a new CEO of their own choosing. Usually the claim is that you need someone mature and experienced, with a business background. Maybe in some cases this is true. And yet Bill Gates was young and inexperienced and had no business background, and he seems to have done ok. Steve Jobs got booted out of his own company by someone mature and experienced, with a business background, who then proceeded to ruin the company. So I think people who are mature and experienced, with a business background, may be overrated. We used to call these guys "newscasters," because they had neat hair and spoke in deep, confident voices, and generally didn't know much more than they read on the teleprompter. We talked to a number of VCs, but eventually we ended up financing our startup entirely with angel money. The main reason was that we feared a brand-name VC firm would stick us with a newscaster as part of the deal. That might have been ok if he was content to limit himself to talking to the press, but what if he wanted to have a say in running the company? That would have led to disaster, because our software was so complex. We were a company whose whole m.o. was to win through better technology. The strategic decisions were mostly decisions about technology, and we didn't need any help with those. This was also one reason we didn't go public. Back in 1998 our CFO tried to talk me into it. In those days you could go public as a dogfood portal, so as a company with a real product and real revenues, we might have done well.
不仅是创业公司需要担心这一点。我认为大多数企业失败是因为没有满足客户需求。看看餐饮业。很大比例的餐厅倒闭,第一年约有四分之一。但你能想到哪家食物真正美味却关门的餐厅吗?
But I feared it would have meant taking on a newscaster-- someone who, as they say, "can talk Wall Street's language." I'm happy to see Google is bucking that trend. They didn't talk Wall Street's language when they did their IPO, and Wall Street didn't buy. And now Wall Street is collectively kicking itself. They'll pay attention next time. Wall Street learns new languages fast when money is involved. You have more leverage negotiating with VCs than you realize. The reason is other VCs. I know a number of VCs now, and when you talk to them you realize that it's a seller's market. Even now there is too much money chasing too few good deals. VCs form a pyramid. At the top are famous ones like Sequoia and Kleiner Perkins, but beneath those are a huge number you've never heard of. What they all have in common is that a dollar from them is worth one dollar. Most VCs will tell you that they don't just provide money, but connections and advice. If you're talking to Vinod Khosla or John Doerr or Mike Moritz, this is true. But such advice and connections can come very expensive. And as you go down the food chain the VCs get rapidly dumber. A few steps down from the top you're basically talking to bankers who've picked up a few new vocabulary words from reading _Wired_. (Does your product use _XML?_ ) So I'd advise you to be skeptical about claims of experience and connections. Basically, a VC is a source of money. I'd be inclined to go with whoever offered the most money the soonest with the least strings attached. You may wonder how much to tell VCs. And you should, because some of them may one day be funding your competitors. I think the best plan is not to be overtly secretive, but not to tell them everything either. After all, as most VCs say, they're more interested in the people than the ideas. The main reason they want to talk about your idea is to judge you, not the idea.
食物出色的餐厅似乎无论如何都能兴旺。一家食物出色的餐厅可以价格昂贵、拥挤、嘈杂、昏暗、位置偏僻,甚至服务糟糕,但人们依然会光顾。确实,平庸的餐厅有时能通过噱头吸引顾客。但这种方法风险很大。更直接的方法是让食物变好。
科技行业也是如此。你听过创业公司失败的各种理由。但你能想到哪家拥有极受欢迎产品却依然失败的创业公司吗?
几乎每一家失败的创业公司,真正问题都是客户不想要他们的产品。大多数死因被记录为“资金耗尽”,但这只是直接原因。为什么他们无法获得更多资金?很可能因为产品很烂,或者看起来永远无法完成,或两者兼有。
So as long as you seem like you know what you're doing, you can probably keep a few things back from them. [7] Talk to as many VCs as you can, even if you don't want their money, because a) they may be on the board of someone who will buy you, and b) if you seem impressive, they'll be discouraged from investing in your competitors. The most efficient way to reach VCs, especially if you only want them to know about you and don't want their money, is at the conferences that are occasionally organized for startups to present to them. Not Spending It When and if you get an infusion of real money from investors, what should you do with it? Not spend it, that's what. In nearly every startup that fails, the proximate cause is running out of money. Usually there is something deeper wrong. But even a proximate cause of death is worth trying hard to avoid. During the Bubble many startups tried to "get big fast." Ideally this meant getting a lot of customers fast. But it was easy for the meaning to slide over into hiring a lot of people fast. Of the two versions, the one where you get a lot of customers fast is of course preferable. But even that may be overrated. The idea is to get there first and get all the users, leaving none for competitors. But I think in most businesses the advantages of being first to market are not so overwhelmingly great. Google is again a case in point. When they appeared it seemed as if search was a mature market, dominated by big players who'd spent millions to build their brands: Yahoo, Lycos, Excite, Infoseek, Altavista, Inktomi. Surely 1998 was a little late to arrive at the party. But as the founders of Google knew, brand is worth next to nothing in the search business. You can come along at any point and make something better, and users will gradually seep over to you. As if to emphasize the point, Google never did any advertising.
当我思考创业公司必须做的事情时,差点列出第四条:尽快推出第一版产品。但我决定不写,因为这已经隐含在“做客户想要的东西”中。唯一能做出客户想要的产品的方法,就是先做出原型给他们看,然后根据反馈改进。
另一种方法我称之为“万福玛丽亚”策略。你为产品制定详尽计划,雇佣工程师团队开发(这样做的人倾向于用“工程师”称呼黑客),然后一年后发现自己花了两百万美元开发出没人要的东西。这在泡沫时期并不少见,尤其常见于商务人士掌管的公司,他们认为软件开发是件可怕的事,因此必须精心规划。
They're like dealers; they sell the stuff, but they know better than to use it themselves. The competitors Google buried would have done better to spend those millions improving their software. Future startups should learn from that mistake. Unless you're in a market where products are as undifferentiated as cigarettes or vodka or laundry detergent, spending a lot on brand advertising is a sign of breakage. And few if any Web businesses are so undifferentiated. The dating sites are running big ad campaigns right now, which is all the more evidence they're ripe for the picking. (Fee, fie, fo, fum, I smell a company run by marketing guys.) We were compelled by circumstances to grow slowly, and in retrospect it was a good thing. The founders all learned to do every job in the company. As well as writing software, I had to do sales and customer support. At sales I was not very good. I was persistent, but I didn't have the smoothness of a good salesman. My message to potential customers was: you'd be stupid not to sell online, and if you sell online you'd be stupid to use anyone else's software. Both statements were true, but that's not the way to convince people. I was great at customer support though. Imagine talking to a customer support person who not only knew everything about the product, but would apologize abjectly if there was a bug, and then fix it immediately, while you were on the phone with them. Customers loved us. And we loved them, because when you're growing slow by word of mouth, your first batch of users are the ones who were smart enough to find you by themselves. There is nothing more valuable, in the early stages of a startup, than smart users. If you listen to them, they'll tell you exactly how to make a winning product. And not only will they give you this advice for free, they'll pay you. We officially launched in early 1996. By the end of that year we had about 70 users.
我们从未考虑过这种方法。作为Lisp黑客,我来自快速原型的传统。我不会声称(至少在这里不会)这是编写所有程序的正确方式,但它绝对是创业公司开发软件的正确方式。在创业公司中,你的初始计划几乎必然有某些错误,而你的首要任务应该是找出错在哪里。唯一的方法就是尝试实现它们。
和大多数创业公司一样,我们在过程中改变了计划。起初我们以为客户会是网络咨询公司。结果他们不喜欢我们,因为我们的软件太易用,而且我们托管网站。这让客户解雇他们变得太容易。我们还以为能签下许多目录公司,因为在线销售是他们现有业务的自然延伸。但在1996年,这很难推销。我们接触的目录公司中层管理者将网络视为额外负担,而非机遇。
Since this was the era of "get big fast," I worried about how small and obscure we were. But in fact we were doing exactly the right thing. Once you get big (in users or employees) it gets hard to change your product. That year was effectively a laboratory for improving our software. By the end of it, we were so far ahead of our competitors that they never had a hope of catching up. And since all the hackers had spent many hours talking to users, we understood online commerce way better than anyone else. That's the key to success as a startup. There is nothing more important than understanding your business. You might think that anyone in a business must, ex officio, understand it. Far from it. Google's secret weapon was simply that they understood search. I was working for Yahoo when Google appeared, and Yahoo didn't understand search. I know because I once tried to convince the powers that be that we had to make search better, and I got in reply what was then the party line about it: that Yahoo was no longer a mere "search engine." Search was now only a small percentage of our page views, less than one month's growth, and now that we were established as a "media company," or "portal," or whatever we were, search could safely be allowed to wither and drop off, like an umbilical cord. Well, a small fraction of page views they may be, but they are an important fraction, because they are the page views that Web sessions start with. I think Yahoo gets that now. Google understands a few other things most Web companies still don't. The most important is that you should put users before advertisers, even though the advertisers are paying and users aren't. One of my favorite bumper stickers reads "if the people lead, the leaders will follow." Paraphrased for the Web, this becomes "get all the users, and the advertisers will follow." More generally, design your product to please users first, and then think about how to make money from it.
我们确实签下了一些较有冒险精神的目录公司,包括Frederick's of Hollywood,这让我们获得了处理服务器高负载的宝贵经验。但我们的大多数用户是小型个体商户,他们将网络视为创业机会。有些有实体店,但许多只存在于线上。于是我们转向专注这些用户。不再专注于网络咨询公司和目录公司需要的功能,而是努力让软件更易用。
我从中学到了宝贵的一课:让技术易于使用值得付出极大努力。黑客太熟悉电脑,以至于他们不知道软件对普通人来说有多可怕。斯蒂芬·霍金的编辑告诉他,书中每增加一个方程式,销量就会减半。当你致力于让技术更易用时,你是在推动曲线上升而非下降。易用性提升10%不仅会让销量增加10%,更可能让销量翻倍。
如何了解客户需求?观察他们。贸易展是绝佳场所之一。贸易展作为获取新客户的渠道并不划算,但作为市场调研却很有价值。我们不只是做固定演示,而是向人们展示如何建立真正可用的商店。这意味着我们能观察他们如何使用软件,并和他们讨论需求。
If you don't put users first, you leave a gap for competitors who do. To make something users love, you have to understand them. And the bigger you are, the harder that is. So I say "get big slow." The slower you burn through your funding, the more time you have to learn. The other reason to spend money slowly is to encourage a culture of cheapness. That's something Yahoo did understand. David Filo's title was "Chief Yahoo," but he was proud that his unofficial title was "Cheap Yahoo." Soon after we arrived at Yahoo, we got an email from Filo, who had been crawling around our directory hierarchy, asking if it was really necessary to store so much of our data on expensive RAID drives. I was impressed by that. Yahoo's market cap then was already in the billions, and they were still worrying about wasting a few gigs of disk space. When you get a couple million dollars from a VC firm, you tend to feel rich. It's important to realize you're not. A rich company is one with large revenues. This money isn't revenue. It's money investors have given you in the hope you'll be able to generate revenues. So despite those millions in the bank, you're still poor. For most startups the model should be grad student, not law firm. Aim for cool and cheap, not expensive and impressive. For us the test of whether a startup understood this was whether they had Aeron chairs. The Aeron came out during the Bubble and was very popular with startups. Especially the type, all too common then, that was like a bunch of kids playing house with money supplied by VCs. We had office chairs so cheap that the arms all fell off. This was slightly embarrassing at the time, but in retrospect the grad-studenty atmosphere of our office was another of those things we did right without knowing it. Our offices were in a wooden triple-decker in Harvard Square. It had been an apartment until about the 1970s, and there was still a claw-footed bathtub in the bathroom.
无论创办哪种创业公司,创始人理解用户需求可能都需要突破自我。唯一不需要研究用户就能开发的软件,是那些你自己就是典型用户的软件。但这正是倾向于开源的类型:操作系统、编程语言、编辑器等。因此,如果你为了赚钱而开发技术,你的用户很可能和你不是一类人。事实上,你可以利用这点来生成创业点子:那些和你不同的人需要技术做什么?
大多数人想到创业公司时,会想到苹果或谷歌这样的公司。这些家喻户晓的大众消费品牌。但每有一个这样的创业公司,就有二十家在利基市场运营或低调扎根于基础设施的公司。因此,如果你创办一家成功的创业公司,很可能就是其中之一。
It must once have been inhabited by someone fairly eccentric, because a lot of the chinks in the walls were stuffed with aluminum foil, as if to protect against cosmic rays. When eminent visitors came to see us, we were a bit sheepish about the low production values. But in fact that place was the perfect space for a startup. We felt like our role was to be impudent underdogs instead of corporate stuffed shirts, and that is exactly the spirit you want. An apartment is also the right kind of place for developing software. Cube farms suck for that, as you've probably discovered if you've tried it. Ever notice how much easier it is to hack at home than at work? So why not make work more like home? When you're looking for space for a startup, don't feel that it has to look professional. Professional means doing good work, not elevators and glass walls. I'd advise most startups to avoid corporate space at first and just rent an apartment. You want to live at the office in a startup, so why not have a place designed to be lived in as your office? Besides being cheaper and better to work in, apartments tend to be in better locations than office buildings. And for a startup location is very important. The key to productivity is for people to come back to work after dinner. Those hours after the phone stops ringing are by far the best for getting work done. Great things happen when a group of employees go out to dinner together, talk over ideas, and then come back to their offices to implement them. So you want to be in a place where there are a lot of restaurants around, not some dreary office park that's a wasteland after 6:00 PM. Once a company shifts over into the model where everyone drives home to the suburbs for dinner, however late, you've lost something extraordinarily valuable. God help you if you actually start in that mode.
换句话说,如果你尝试创办那种必须成为大众消费品牌的公司,成功的几率会更低。最佳机会在利基市场。由于创业公司通过提供比现有更好的东西赚钱,最佳机会存在于现状最糟糕的领域。很难找到比企业IT部门更糟糕的地方。你无法想象企业在软件上花了多少钱,却换来一堆垃圾。这种不平衡意味着机会。
如果你想找创业点子,最有价值的事情之一是找一家中型非科技公司,花几周观察他们如何使用电脑。大多数优秀黑客对这些地方的恐怖程度一无所知,就像富裕的美国人对巴西贫民窟的生活一无所知一样。
If I were going to start a startup today, there are only three places I'd consider doing it: on the Red Line near Central, Harvard, or Davis Squares (Kendall is too sterile); in Palo Alto on University or California Aves; and in Berkeley immediately north or south of campus. These are the only places I know that have the right kind of vibe. The most important way to not spend money is by not hiring people. I may be an extremist, but I think hiring people is the worst thing a company can do. To start with, people are a recurring expense, which is the worst kind. They also tend to cause you to grow out of your space, and perhaps even move to the sort of uncool office building that will make your software worse. But worst of all, they slow you down: instead of sticking your head in someone's office and checking out an idea with them, eight people have to have a meeting about it. So the fewer people you can hire, the better. During the Bubble a lot of startups had the opposite policy. They wanted to get "staffed up" as soon as possible, as if you couldn't get anything done unless there was someone with the corresponding job title. That's big company thinking. Don't hire people to fill the gaps in some a priori org chart. The only reason to hire someone is to do something you'd like to do but can't. If hiring unnecessary people is expensive and slows you down, why do nearly all companies do it? I think the main reason is that people like the idea of having a lot of people working for them. This weakness often extends right up to the CEO. If you ever end up running a company, you'll find the most common question people ask is how many employees you have. This is their way of weighing you. It's not just random people who ask this; even reporters do. And they're going to be a lot more impressed if the answer is a thousand than if it's ten. This is ridiculous, really.
从小公司开始写软件,因为向他们销售更容易。向大公司销售产品价值巨大,以至于那些向他们销售垃圾产品的公司投入大量时间和金钱来做这件事。尽管你能用一半脑力就比Oracle做得更好,但你无法比Oracle的销售员更会推销。因此,如果你想通过更好的技术取胜,瞄准小客户。[4]
无论如何,小客户是市场中更具战略价值的部分。在科技行业,低端总是吞噬高端。让廉价产品变得更强大,比让强大产品变得更便宜容易。因此,那些起初作为廉价简单选项的产品,往往会逐渐变得更强大,直到像涨潮的水一样将“高端”产品逼到天花板。Sun对大型机这样做了,英特尔正在对Sun这样做。微软Word对Interleaf和Framemaker这样的桌面出版软件这样做了。大众市场数码相机正在对专业昂贵机型这样做。Avid对专业视频编辑系统制造商这样做了,现在苹果正在对Avid这样做。亨利·福特对他之前的汽车制造商也这样做了。如果你打造简单、廉价的选择,不仅初期更容易销售,还能占据征服剩余市场的最佳位置。
让别人在你下方飞行非常危险。如果你拥有最便宜、最简单的产品,你将占据低端市场。如果没有,你就会成为拥有这类产品者的靶子。
If two companies have the same revenues, it's the one with fewer employees that's more impressive. When people used to ask me how many people our startup had, and I answered "twenty," I could see them thinking that we didn't count for much. I used to want to add "but our main competitor, whose ass we regularly kick, has a hundred and forty, so can we have credit for the larger of the two numbers?" As with office space, the number of your employees is a choice between seeming impressive, and being impressive. Any of you who were nerds in high school know about this choice. Keep doing it when you start a company. Should You? But should you start a company? Are you the right sort of person to do it? If you are, is it worth it? More people are the right sort of person to start a startup than realize it. That's the main reason I wrote this. There could be ten times more startups than there are, and that would probably be a good thing. I was, I now realize, exactly the right sort of person to start a startup. But the idea terrified me at first. I was forced into it because I was a Lisp hacker. The company I'd been consulting for seemed to be running into trouble, and there were not a lot of other companies using Lisp. Since I couldn't bear the thought of programming in another language (this was 1995, remember, when "another language" meant C++) the only option seemed to be to start a new company using Lisp. I realize this sounds far-fetched, but if you're a Lisp hacker you'll know what I mean. And if the idea of starting a startup frightened me so much that I only did it out of necessity, there must be a lot of people who would be good at it but who are too intimidated to try. So who should start a startup? Someone who is a good hacker, between about 23 and 38, and who wants to solve the money problem in one shot instead of getting paid gradually over a conventional working life.
为了实现这一切,你需要钱。有些创业公司是自筹资金的(比如微软),但大多数不是。我认为从投资者那里拿钱是明智的。要自筹资金,你必须从咨询公司起步,而很难从咨询公司转型为产品公司。
从财务角度看,创业公司就像一门通过/不通过的课程。通过创业致富的方法是最大化公司成功的机会,而不是最大化你保留的股份。因此,如果能用股份换取提高成功几率的东西,这可能是明智之举。
I can't say precisely what a good hacker is. At a first rate university this might include the top half of computer science majors. Though of course you don't have to be a CS major to be a hacker; I was a philosophy major in college. It's hard to tell whether you're a good hacker, especially when you're young. Fortunately the process of starting startups tends to select them automatically. What drives people to start startups is (or should be) looking at existing technology and thinking, don't these guys realize they should be doing x, y, and z? And that's also a sign that one is a good hacker. I put the lower bound at 23 not because there's something that doesn't happen to your brain till then, but because you need to see what it's like in an existing business before you try running your own. The business doesn't have to be a startup. I spent a year working for a software company to pay off my college loans. It was the worst year of my adult life, but I learned, without realizing it at the time, a lot of valuable lessons about the software business. In this case they were mostly negative lessons: don't have a lot of meetings; don't have chunks of code that multiple people own; don't have a sales guy running the company; don't make a high-end product; don't let your code get too big; don't leave finding bugs to QA people; don't go too long between releases; don't isolate developers from users; don't move from Cambridge to Route 128; and so on. [8] But negative lessons are just as valuable as positive ones. Perhaps even more valuable: it's hard to repeat a brilliant performance, but it's straightforward to avoid errors. [9] The other reason it's hard to start a company before 23 is that people won't take you seriously. VCs won't trust you, and will try to reduce you to a mascot as a condition of funding. Customers will worry you're going to flake out and leave them stranded.
对大多数黑客来说,寻找投资者似乎是个可怕而神秘的过程。实际上它只是枯燥乏味。我会简要概述这个过程。
首先你需要几万美元作为开发原型期间的费用。这被称为种子资金。由于涉及金额较小,筹集种子资金相对容易——至少能快速得到肯定或否定的答复。
Even you yourself, unless you're very unusual, will feel your age to some degree; you'll find it awkward to be the boss of someone much older than you, and if you're 21, hiring only people younger rather limits your options. Some people could probably start a company at 18 if they wanted to. Bill Gates was 19 when he and Paul Allen started Microsoft. (Paul Allen was 22, though, and that probably made a difference.) So if you're thinking, I don't care what he says, I'm going to start a company now, you may be the sort of person who could get away with it. The other cutoff, 38, has a lot more play in it. One reason I put it there is that I don't think many people have the physical stamina much past that age. I used to work till 2:00 or 3:00 AM every night, seven days a week. I don't know if I could do that now. Also, startups are a big risk financially. If you try something that blows up and leaves you broke at 26, big deal; a lot of 26 year olds are broke. By 38 you can't take so many risks-- especially if you have kids. My final test may be the most restrictive. Do you actually want to start a startup? What it amounts to, economically, is compressing your working life into the smallest possible space. Instead of working at an ordinary rate for 40 years, you work like hell for four. And maybe end up with nothing-- though in that case it probably won't take four years. During this time you'll do little but work, because when you're not working, your competitors will be. My only leisure activities were running, which I needed to do to keep working anyway, and about fifteen minutes of reading a night. I had a girlfriend for a total of two months during that three year period. Every couple weeks I would take a few hours off to visit a used bookshop or go to a friend's house for dinner. I went to visit my family twice. Otherwise I just worked. Working was often fun, because the people I worked with were some of my best friends.
通常种子资金来自被称为“天使”的富人。他们往往本身通过科技致富。在种子阶段,投资者不期望你有详尽的商业计划。大多数人知道应该快速决定。基于半页协议在一周内拿到支票并不罕见。
我们通过朋友Julian提供的1万美元种子资金创办了Viaweb。但他给我们的远不止钱。他曾是CEO和公司律师,因此给了我们许多宝贵的商业建议,还完成了我们公司成立的所有法律工作。此外,他还把我们介绍给了两位天使投资人之一,他们提供了下一轮资金。
有些天使投资人,尤其是有技术背景的,可能只需要演示和你计划做什么的口头描述。但许多人会要一份商业计划,哪怕只是为了记住自己投资了什么。
Sometimes it was even technically interesting. But only about 10% of the time. The best I can say for the other 90% is that some of it is funnier in hindsight than it seemed then. Like the time the power went off in Cambridge for about six hours, and we made the mistake of trying to start a gasoline powered generator inside our offices. I won't try that again. I don't think the amount of bullshit you have to deal with in a startup is more than you'd endure in an ordinary working life. It's probably less, in fact; it just seems like a lot because it's compressed into a short period. So mainly what a startup buys you is time. That's the way to think about it if you're trying to decide whether to start one. If you're the sort of person who would like to solve the money problem once and for all instead of working for a salary for 40 years, then a startup makes sense. For a lot of people the conflict is between startups and graduate school. Grad students are just the age, and just the sort of people, to start software startups. You may worry that if you do you'll blow your chances of an academic career. But it's possible to be part of a startup and stay in grad school, especially at first. Two of our three original hackers were in grad school the whole time, and both got their degrees. There are few sources of energy so powerful as a procrastinating grad student. If you do have to leave grad school, in the worst case it won't be for too long. If a startup fails, it will probably fail quickly enough that you can return to academic life. And if it succeeds, you may find you no longer have such a burning desire to be an assistant professor. If you want to do it, do it. Starting a startup is not the great mystery it seems from outside. It's not something you have to know about "business" to do. Build something users love, and spend less than you make.
我们的天使投资人要了商业计划,回想起来,我惊讶它曾让我如此焦虑。“商业计划”中有“商业”这个词,所以我以为必须读一本关于商业计划的书才能写出来。其实不然。在这个阶段,大多数投资者只期望看到你计划做什么、如何赚钱的简要描述,以及创始人的简历。如果你坐下来写下你们彼此讨论的内容,这就足够了。这不需要超过几个小时,而且你可能会发现,把一切写下来会让你对下一步有更多想法。
为了让天使投资人能开出支票,你需要某种形式的公司。单纯注册公司并不难。问题在于,公司要存在,你必须决定谁是创始人,以及各自持有多少股份。如果有两位条件相同、对业务投入相同的创始人,这很简单。但如果有多位贡献程度不同的人,分配股份比例可能很困难。而且一旦分配,往往就固定不变了。
How hard is that? Notes [1] Google's revenues are about two billion a year, but half comes from ads on other sites. [2] One advantage startups have over established companies is that there are no discrimination laws about starting businesses. For example, I would be reluctant to start a startup with a woman who had small children, or was likely to have them soon. But you're not allowed to ask prospective employees if they plan to have kids soon. Believe it or not, under current US law, you're not even allowed to discriminate on the basis of intelligence. Whereas when you're starting a company, you can discriminate on any basis you want about who you start it with. [3] Learning to hack is a lot cheaper than business school, because you can do it mostly on your own. For the price of a Linux box, a copy of K&R, and a few hours of advice from your neighbor's fifteen year old son, you'll be well on your way. [4] Corollary: Avoid starting a startup to sell things to the biggest company of all, the government. Yes, there are lots of opportunities to sell them technology. But let someone else start those startups. [5] A friend who started a company in Germany told me they do care about the paperwork there, and that there's more of it. Which helps explain why there are not more startups in Germany. [6] At the seed stage our valuation was in principle $100,000, because Julian got 10% of the company. But this is a very misleading number, because the money was the least important of the things Julian gave us. [7] The same goes for companies that seem to want to acquire you. There will be a few that are only pretending to in order to pick your brains. But you can never tell for sure which these are, so the best approach is to seem entirely open, but to fail to mention a few critical technical secrets. [8] I was as bad an employee as this place was a company.
我没有解决这个问题的技巧。只能说,努力把它做对。我有一条经验法则来判断分配是否合理:当每个人都觉得自己得到的略少,自己付出的比股份应得的更多时,股份分配就是最优的。
当然,成立公司不仅仅是注册:还有保险、营业执照、失业补偿、与国税局的各种手续。我甚至不确定完整清单是什么,因为我们,呃,跳过了所有这些。1996年底获得实际融资后,我们聘请了一位出色的CFO,他事后补办了所有手续。事实证明,如果你在创业时没有完成所有应做事项,不会有人来逮捕你。这也是好事,否则许多创业公司永远无法起步。[5]
I apologize to anyone who had to work with me there. [9] You could probably write a book about how to succeed in business by doing everything in exactly the opposite way from the DMV. Thanks to Trevor Blackwell, Sarah Harlin, Jessica Livingston, and Robert Morris for reading drafts of this essay, and to Steve Melendez and Gregory Price for inviting me to speak.
| Domain Name Search | | | Turkish Translation | Hebrew Translation | | | Russian Translation | Chinese Translation | | | French Translation | Japanese Translation | | | Arabic Translation.
延迟成立公司可能有风险,因为一位或多位创始人可能决定分拆出去创办另一家做同样事情的公司。这确实会发生。因此,在成立公司时,除了分配股份,还应让所有创始人签署协议,声明所有人的创意都属于这家公司,并且这家公司将是每个人的唯一工作。
[如果这是电影,此时会响起不祥的音乐。]
趁此机会,你应该问问他们还
January 2005 _(I wrote this talk for a high school. I never actually gave it, because the school authorities vetoed the plan to invite me.)_ When I said I was speaking at a high school, my friends were curious. What will you say to high school students? So I asked them, what do you wish someone had told you in high school? Their answers were remarkably similar. So I'm going to tell you what we all wish someone had told us. I'll start by telling you something you don't have to know in high school: what you want to do with your life. People are always asking you this, so you think you're supposed to have an answer. But adults ask this mainly as a conversation starter. They want to know what sort of person you are, and this question is just to get you talking. They ask it the way you might poke a hermit crab in a tide pool, to see what it does. If I were back in high school and someone asked about my plans, I'd say that my first priority was to learn what the options were. You don't need to be in a rush to choose your life's work. What you need to do is discover what you like. You have to work on stuff you like if you want to be good at what you do. It might seem that nothing would be easier than deciding what you like, but it turns out to be hard, partly because it's hard to get an accurate picture of most jobs. Being a doctor is not the way it's portrayed on TV. Fortunately you can also watch real doctors, by volunteering in hospitals. [1] But there are other jobs you can't learn about, because no one is doing them yet. Most of the work I've done in the last ten years didn't exist when I was in high school. The world changes fast, and the rate at which it changes is itself speeding up. In such a world it's not a good idea to have fixed plans. And yet every May, speakers all over the country fire up the Standard Graduation Speech, the theme of which is: don't give up on your dreams.
(这篇演讲稿是为高中准备的。由于校方否决了邀请我的计划,我最终未能发表。)
当我说要去高中演讲时,朋友们都很好奇:你会对高中生说些什么?于是我反问他们:你们希望当年有人告诉高中时的自己什么?他们的回答惊人地相似。所以今天我要说的,正是我们共同希望当年有人能点醒我们的事。
首先我要告诉你们一个高中阶段不必纠结的问题:人生目标。大人们总爱问这个问题,让你误以为必须给出答案。但其实他们多半只是没话找话,真正想了解的是你的个性,提问不过是引你开口的借口,就像戳潮池里的寄居蟹,只想看它如何反应。
I know what they mean, but this is a bad way to put it, because it implies you're supposed to be bound by some plan you made early on. The computer world has a name for this: premature optimization. And it is synonymous with disaster. These speakers would do better to say simply, don't give up. What they really mean is, don't get demoralized. Don't think that you can't do what other people can. And I agree you shouldn't underestimate your potential. People who've done great things tend to seem as if they were a race apart. And most biographies only exaggerate this illusion, partly due to the worshipful attitude biographers inevitably sink into, and partly because, knowing how the story ends, they can't help streamlining the plot till it seems like the subject's life was a matter of destiny, the mere unfolding of some innate genius. In fact I suspect if you had the sixteen year old Shakespeare or Einstein in school with you, they'd seem impressive, but not totally unlike your other friends. Which is an uncomfortable thought. If they were just like us, then they had to work very hard to do what they did. And that's one reason we like to believe in genius. It gives us an excuse for being lazy. If these guys were able to do what they did only because of some magic Shakespeareness or Einsteinness, then it's not our fault if we can't do something as good. I'm not saying there's no such thing as genius. But if you're trying to choose between two theories and one gives you an excuse for being lazy, the other one is probably right. So far we've cut the Standard Graduation Speech down from "don't give up on your dreams" to "what someone else can do, you can do." But it needs to be cut still further. There is _some_ variation in natural ability. Most people overestimate its role, but it does exist.
若重返高中被问及规划,我会说首要任务是探索可能性。不必急于选定终身职业,你需要的是发现自己的兴趣所在。唯有热爱,方能卓越。
听起来发现兴趣再简单不过,实则不然——部分源于多数职业的真实面貌难以窥见。医生职业绝非电视剧呈现的那般光鲜。好在你可以通过医院志愿活动观察真实的医生[1]。
更棘手的是,有些职业尚未诞生。我过去十年从事的工作,在我高中时根本不存在。世界瞬息万变,变化速率本身还在加快。这种环境下,固守既定计划绝非明智之举。
If I were talking to a guy four feet tall whose ambition was to play in the NBA, I'd feel pretty stupid saying, you can do anything if you really try. [2] We need to cut the Standard Graduation Speech down to, "what someone else with your abilities can do, you can do; and don't underestimate your abilities." But as so often happens, the closer you get to the truth, the messier your sentence gets. We've taken a nice, neat (but wrong) slogan, and churned it up like a mud puddle. It doesn't make a very good speech anymore. But worse still, it doesn't tell you what to do anymore. Someone with your abilities? What are your abilities? Upwind I think the solution is to work in the other direction. Instead of working back from a goal, work forward from promising situations. This is what most successful people actually do anyway. In the graduation-speech approach, you decide where you want to be in twenty years, and then ask: what should I do now to get there? I propose instead that you don't commit to anything in the future, but just look at the options available now, and choose those that will give you the most promising range of options afterward. It's not so important what you work on, so long as you're not wasting your time. Work on things that interest you and increase your options, and worry later about which you'll take. Suppose you're a college freshman deciding whether to major in math or economics. Well, math will give you more options: you can go into almost any field from math. If you major in math it will be easy to get into grad school in economics, but if you major in economics it will be hard to get into grad school in math. Flying a glider is a good metaphor here. Because a glider doesn't have an engine, you can't fly into the wind without losing a lot of altitude. If you let yourself get far downwind of good places to land, your options narrow uncomfortably. As a rule you want to stay upwind.
然而每年五月,全国毕业典礼演讲者都在重复标准陈词:"别放弃梦想"。我懂其善意,但表述糟糕——它暗示你该被早年规划束缚。计算机领域称这种现象为"过早优化",堪称灾难之源。不如直接说"别放弃"更妥帖。
他们真正想说的是:别丧失斗志,别自认不如人。我完全赞同不该低估潜力。那些成就伟业者看似天赋异禀,实则多数传记夸大了这种错觉。部分源于传记作者不可避免的崇拜心理,部分因为知晓结局后,他们总不自觉将传主人生简化为天命所归。其实若与十六岁的莎士比亚或爱因斯坦同窗,他们虽令人印象深刻,但与你其他朋友并无本质不同。
这个事实令人不安:若天才与我们无异,则他们的成就必源于非凡努力。这正是我们热衷"天才论"的原因——它为懒惰提供借口。若那些成就只因神秘的"莎士比亚基因"或"爱因斯坦特质",那我们碌碌无为便情有可原。
并非否认天才存在。但当两个理论摆面前,一个为懒惰开脱时,选另一个多半没错。
So I propose that as a replacement for "don't give up on your dreams." Stay upwind. How do you do that, though? Even if math is upwind of economics, how are you supposed to know that as a high school student? Well, you don't, and that's what you need to find out. Look for smart people and hard problems. Smart people tend to clump together, and if you can find such a clump, it's probably worthwhile to join it. But it's not straightforward to find these, because there is a lot of faking going on. To a newly arrived undergraduate, all university departments look much the same. The professors all seem forbiddingly intellectual and publish papers unintelligible to outsiders. But while in some fields the papers are unintelligible because they're full of hard ideas, in others they're deliberately written in an obscure way to seem as if they're saying something important. This may seem a scandalous proposition, but it has been experimentally verified, in the famous _Social Text_ affair. Suspecting that the papers published by literary theorists were often just intellectual-sounding nonsense, a physicist deliberately wrote a paper full of intellectual-sounding nonsense, and submitted it to a literary theory journal, which published it. The best protection is always to be working on hard problems. Writing novels is hard. Reading novels isn't. Hard means worry: if you're not worrying that something you're making will come out badly, or that you won't be able to understand something you're studying, then it isn't hard enough. There has to be suspense. Well, this seems a grim view of the world, you may think. What I'm telling you is that you should worry? Yes, but it's not as bad as it sounds. It's exhilarating to overcome worries. You don't see faces much happier than people winning gold medals. And you know why they're so happy? Relief. I'm not saying this is the only way to be happy.
至此,我们把标准毕业演讲从"别放弃梦想"精简为"别人能,你也能"。但还需进一步修正:天赋差异确实存在。多数人高估其作用,但它客观存在。若对身高1米2却梦想进NBA的孩子说"努力就能成",我会自感愚蠢[2]。
最终版本应是:"与同等资质者能做到的,你也能做到;且别低估自身资质。"但接近真相的代价往往是语句不再光鲜。我们把漂亮口号搅成了泥潭,既不宜演讲,更缺乏实操指导。"同等资质"究竟指什么?
解方在于逆向思维:不从目标倒推,而从当下机遇顺延。这恰是多数成功者的真实路径。
Just that some kinds of worry are not as bad as they sound. Ambition In practice, "stay upwind" reduces to "work on hard problems." And you can start today. I wish I'd grasped that in high school. Most people like to be good at what they do. In the so-called real world this need is a powerful force. But high school students rarely benefit from it, because they're given a fake thing to do. When I was in high school, I let myself believe that my job was to be a high school student. And so I let my need to be good at what I did be satisfied by merely doing well in school. If you'd asked me in high school what the difference was between high school kids and adults, I'd have said it was that adults had to earn a living. Wrong. It's that adults take responsibility for themselves. Making a living is only a small part of it. Far more important is to take intellectual responsibility for oneself. If I had to go through high school again, I'd treat it like a day job. I don't mean that I'd slack in school. Working at something as a day job doesn't mean doing it badly. It means not being defined by it. I mean I wouldn't think of myself as a high school student, just as a musician with a day job as a waiter doesn't think of himself as a waiter. [3] And when I wasn't working at my day job I'd start trying to do real work. When I ask people what they regret most about high school, they nearly all say the same thing: that they wasted so much time. If you're wondering what you're doing now that you'll regret most later, that's probably it. [4] Some people say this is inevitable — that high school students aren't capable of getting anything done yet. But I don't think this is true. And the proof is that you're bored. You probably weren't bored when you were eight. When you're eight it's called "playing" instead of "hanging out," but it's the same thing. And when I was eight, I was rarely bored.
毕业演讲思维要你设定二十年后的目标,再反推现在该做什么。我建议相反:别承诺未来,只评估当下选项,选择能最大限度拓展未来可能性的路径。
具体做什么不重要,只要不虚度光阴。先投身感兴趣且能拓展可能性的领域,选择留待日后。假设你是大一新生,在数学与经济学间犹豫。数学能打开更多门:几乎所有领域都欢迎数学背景。数学专业转经济研究生易如反掌,反之则举步维艰。
滑翔机是个绝妙隐喻:无动力装置意味着逆风飞行会急速坠落。若让自己顺风飘离安全着陆点,选择将令人不安地收窄。原则就是保持逆风优势。因此我提议用"保持逆风"替代"别放弃梦想"。
Give me a back yard and a few other kids and I could play all day. The reason this got stale in middle school and high school, I now realize, is that I was ready for something else. Childhood was getting old. I'm not saying you shouldn't hang out with your friends — that you should all become humorless little robots who do nothing but work. Hanging out with friends is like chocolate cake. You enjoy it more if you eat it occasionally than if you eat nothing but chocolate cake for every meal. No matter how much you like chocolate cake, you'll be pretty queasy after the third meal of it. And that's what the malaise one feels in high school is: mental queasiness. [5] You may be thinking, we have to do more than get good grades. We have to have _extracurricular activities._ But you know perfectly well how bogus most of these are. Collecting donations for a charity is an admirable thing to do, but it's not _hard._ It's not getting something done. What I mean by getting something done is learning how to write well, or how to program computers, or what life was really like in preindustrial societies, or how to draw the human face from life. This sort of thing rarely translates into a line item on a college application. Corruption It's dangerous to design your life around getting into college, because the people you have to impress to get into college are not a very discerning audience. At most colleges, it's not the professors who decide whether you get in, but admissions officers, and they are nowhere near as smart. They're the NCOs of the intellectual world. They can't tell how smart you are. The mere existence of prep schools is proof of that. Few parents would pay so much for their kids to go to a school that didn't improve their admissions prospects. Prep schools openly say this is one of their aims.
但如何践行?高中生怎知数学比经济学更具逆风优势?答案是你本不知,这正是需要探索的。寻找聪明人与难题。智者常聚,找到这类群体便值得加入。但这非易事,因伪装者众。
新生眼中,所有院系别无二致:教授皆高深莫测,论文对外行如天书。但某些领域论文艰深因思想深邃,另一些则刻意晦涩以显得重要。这听似惊世骇俗,但《社会文本》事件已实验验证:物理学家故意用学术黑话拼凑伪论文,竟被文学理论期刊录用。
最佳防御是永远攻坚。写小说难,读小说易。"难"意味着焦虑——若你不担心作品失败或无法理解研究对象,说明难度不够。必须保持悬疑感。
你或许认为这世界观太过严苛。我在劝人自寻烦恼?不错,但没听来那么糟。战胜忧虑令人振奋。奥运金牌得主的笑脸最灿烂,你知道为什么吗?如释重负。
But what that means, if you stop to think about it, is that they can hack the admissions process: that they can take the very same kid and make him seem a more appealing candidate than he would if he went to the local public school. [6] Right now most of you feel your job in life is to be a promising college applicant. But that means you're designing your life to satisfy a process so mindless that there's a whole industry devoted to subverting it. No wonder you become cynical. The malaise you feel is the same that a producer of reality TV shows or a tobacco industry executive feels. And you don't even get paid a lot. So what do you do? What you should not do is rebel. That's what I did, and it was a mistake. I didn't realize exactly what was happening to us, but I smelled a major rat. And so I just gave up. Obviously the world sucked, so why bother? When I discovered that one of our teachers was herself using Cliff's Notes, it seemed par for the course. Surely it meant nothing to get a good grade in such a class. In retrospect this was stupid. It was like someone getting fouled in a soccer game and saying, hey, you fouled me, that's against the rules, and walking off the field in indignation. Fouls happen. The thing to do when you get fouled is not to lose your cool. Just keep playing. By putting you in this situation, society has fouled you. Yes, as you suspect, a lot of the stuff you learn in your classes is crap. And yes, as you suspect, the college admissions process is largely a charade. But like many fouls, this one was unintentional. [7] So just keep playing. Rebellion is almost as stupid as obedience. In either case you let yourself be defined by what they tell you to do. The best plan, I think, is to step onto an orthogonal vector. Don't just do what they tell you, and don't just refuse to. Instead treat school as a day job. As day jobs go, it's pretty sweet.
非说这是唯一快乐之道。只是某些忧虑没想象中可怕。
实践中,"保持逆风"即"攻坚克难"。今日便可开始。多希望我高中就懂这道理。
多数人渴望精通本职。现实世界中这需求是强大动力。但高中生鲜能受益,因其被赋予虚假任务。当年我自欺欺人地把"当好学生"视为工作,仅用学业成绩满足成就需求。
You're done at 3 o'clock, and you can even work on your own stuff while you're there. Curiosity And what's your real job supposed to be? Unless you're Mozart, your first task is to figure that out. What are the great things to work on? Where are the imaginative people? And most importantly, what are you interested in? The word "aptitude" is misleading, because it implies something innate. The most powerful sort of aptitude is a consuming interest in some question, and such interests are often acquired tastes. A distorted version of this idea has filtered into popular culture under the name "passion." I recently saw an ad for waiters saying they wanted people with a "passion for service." The real thing is not something one could have for waiting on tables. And passion is a bad word for it. A better name would be curiosity. Kids are curious, but the curiosity I mean has a different shape from kid curiosity. Kid curiosity is broad and shallow; they ask why at random about everything. In most adults this curiosity dries up entirely. It has to: you can't get anything done if you're always asking why about everything. But in ambitious adults, instead of drying up, curiosity becomes narrow and deep. The mud flat morphs into a well. Curiosity turns work into play. For Einstein, relativity wasn't a book full of hard stuff he had to learn for an exam. It was a mystery he was trying to solve. So it probably felt like less work to him to invent it than it would seem to someone now to learn it in a class. One of the most dangerous illusions you get from school is the idea that doing great things requires a lot of discipline. Most subjects are taught in such a boring way that it's only by discipline that you can flog yourself through them. So I was surprised when, early in college, I read a quote by Wittgenstein saying that he had no self-discipline and had never been able to deny himself anything, not even a cup of coffee.
若高中时问我学生与成人区别,我会说成人需谋生。大错。实则是成人自我负责。谋生仅是小部分,更重要的是智力层面的自我担当。
若能重历高中,我会视其为日间工作。非指敷衍了事,而是不被其定义。就像服务生兼职的乐手不自认服务生[3]。课余时间则开始真正的事业。
当问人们高中最后悔什么,答案高度一致:虚度光阴。若疑惑当下所为会否成为未来最大遗憾,这多半就是[4]。
Now I know a number of people who do great work, and it's the same with all of them. They have little discipline. They're all terrible procrastinators and find it almost impossible to make themselves do anything they're not interested in. One still hasn't sent out his half of the thank-you notes from his wedding, four years ago. Another has 26,000 emails in her inbox. I'm not saying you can get away with zero self-discipline. You probably need about the amount you need to go running. I'm often reluctant to go running, but once I do, I enjoy it. And if I don't run for several days, I feel ill. It's the same with people who do great things. They know they'll feel bad if they don't work, and they have enough discipline to get themselves to their desks to start working. But once they get started, interest takes over, and discipline is no longer necessary. Do you think Shakespeare was gritting his teeth and diligently trying to write Great Literature? Of course not. He was having fun. That's why he's so good. If you want to do good work, what you need is a great curiosity about a promising question. The critical moment for Einstein was when he looked at Maxwell's equations and said, what the hell is going on here? It can take years to zero in on a productive question, because it can take years to figure out what a subject is really about. To take an extreme example, consider math. Most people think they hate math, but the boring stuff you do in school under the name "mathematics" is not at all like what mathematicians do. The great mathematician G. H. Hardy said he didn't like math in high school either. He only took it up because he was better at it than the other students. Only later did he realize math was interesting — only later did he start to ask questions instead of merely answering them correctly.
有人说这不可避免——高中生尚无能力成事。我不同意。证据正是你的无聊感。八岁时你鲜感无聊,那时叫"玩耍"而非"闲逛",本质却同。八岁的我能与伙伴在后院嬉戏终日。
如今我明白,初中起感到乏味是因准备迎接新阶段。童年期已显老态。
非劝你断绝社交。朋友相处如巧克力蛋糕——偶尔享用比方顿顿大餐更愉悦。再爱蛋糕,连吃三顿也会反胃。高中那种倦怠感正是精神层面的反胃[5]。
你或许想:除成绩外还需课外活动。但心知肚明多数活动多虚假。慈善募捐虽高尚,但不具挑战性,不算真成就。我指的成就是掌握写作、编程、了解前工业社会真相或人像素描。这些鲜能转化为大学申请表的条目。
When a friend of mine used to grumble because he had to write a paper for school, his mother would tell him: find a way to make it interesting. That's what you need to do: find a question that makes the world interesting. People who do great things look at the same world everyone else does, but notice some odd detail that's compellingly mysterious. And not only in intellectual matters. Henry Ford's great question was, why do cars have to be a luxury item? What would happen if you treated them as a commodity? Franz Beckenbauer's was, in effect, why does everyone have to stay in his position? Why can't defenders score goals too? Now If it takes years to articulate great questions, what do you do now, at sixteen? Work toward finding one. Great questions don't appear suddenly. They gradually congeal in your head. And what makes them congeal is experience. So the way to find great questions is not to search for them — not to wander about thinking, what great discovery shall I make? You can't answer that; if you could, you'd have made it. The way to get a big idea to appear in your head is not to hunt for big ideas, but to put in a lot of time on work that interests you, and in the process keep your mind open enough that a big idea can take roost. Einstein, Ford, and Beckenbauer all used this recipe. They all knew their work like a piano player knows the keys. So when something seemed amiss to them, they had the confidence to notice it. Put in time how and on what? Just pick a project that seems interesting: to master some chunk of material, or to make something, or to answer some question. Choose a project that will take less than a month, and make it something you have the means to finish. Do something hard enough to stretch you, but only just, especially at first. If you're deciding between two projects, choose whichever seems most fun. If one blows up in your face, start another.
围绕大学申请设计人生是危险的,因为录取决策者鉴赏力有限。多数学校由招生官非教授决定录取,而前者智力水平远不及后者。他们是知识界的士官,无力辨识真才。预科学校的存在即是明证——若无助升学,家长怎愿重金投入?预科学校公然将此列为目标,意味着他们能破解录取规则:让同一学生在他们手中比在公立学校更耀眼[6]。
此刻你们多数人视"成为有前途的申请者"为人生的任务。这意味着你们在为一个可被专业机构轻易破解的愚蠢流程设计人生。难怪你们变得 cynical。这种不适感与真人秀制片人或烟草公司高管无异。而你们甚至没有高薪补偿。
该如何应对?切忌叛逆。我曾如此,实属不智。当年虽未彻底看透体制,但嗅到严重腐坏。于是索性放弃——既然世界如此糟糕,何必努力?当发现老师自己也在用《Cliff笔记》时,更觉荒诞——这种课拿高分有何意义?
Repeat till, like an internal combustion engine, the process becomes self-sustaining, and each project generates the next one. (This could take years.) It may be just as well not to do a project "for school," if that will restrict you or make it seem like work. Involve your friends if you want, but not too many, and only if they're not flakes. Friends offer moral support (few startups are started by one person), but secrecy also has its advantages. There's something pleasing about a secret project. And you can take more risks, because no one will know if you fail. Don't worry if a project doesn't seem to be on the path to some goal you're supposed to have. Paths can bend a lot more than you think. So let the path grow out the project. The most important thing is to be excited about it, because it's by doing that you learn. Don't disregard unseemly motivations. One of the most powerful is the desire to be better than other people at something. Hardy said that's what got him started, and I think the only unusual thing about him is that he admitted it. Another powerful motivator is the desire to do, or know, things you're not supposed to. Closely related is the desire to do something audacious. Sixteen year olds aren't supposed to write novels. So if you try, anything you achieve is on the plus side of the ledger; if you fail utterly, you're doing no worse than expectations. [8] Beware of bad models. Especially when they excuse laziness. When I was in high school I used to write "existentialist" short stories like ones I'd seen by famous writers. My stories didn't have a lot of plot, but they were very deep. And they were less work to write than entertaining ones would have been. I should have known that was a danger sign. And in fact I found my stories pretty boring; what excited me was the idea of writing serious, intellectual stuff like the famous writers. Now I have enough experience to realize that those famous writers actually sucked.
回首方知愚蠢。这就像足球赛中被犯规后愤然离场:犯规本就难免,明智之举是保持冷静继续比赛。社会通过这种体制对你犯规。没错,课堂所学多糟粕;大学录取多作秀。但如多数犯规,这非蓄意为之[7]。所以继续比赛吧。
叛逆与盲从同样愚蠢——两者都让他人定义你。最佳策略是选择正交向量:既不盲从也不硬抗,而是把学校当临时工作。平心而论,这份工相当轻松:下午三点下班,甚至能边工作边做自己的事。
那么真正的事业是什么?除非你是莫扎特,否则首要任务是找到它。哪些是值得攻坚的领域?富有想象力的人聚集何处?最关键的是:你对什么感兴趣?"天资"一词易生误导,它强调先天属性。而最强大的资质是对某个问题的炽热兴趣——这种兴趣往往需要后天培养。
Plenty of famous people do; in the short term, the quality of one's work is only a small component of fame. I should have been less worried about doing something that seemed cool, and just done something I liked. That's the actual road to coolness anyway. A key ingredient in many projects, almost a project on its own, is to find good books. Most books are bad. Nearly all textbooks are bad. [9] So don't assume a subject is to be learned from whatever book on it happens to be closest. You have to search actively for the tiny number of good books. The important thing is to get out there and do stuff. Instead of waiting to be taught, go out and learn. Your life doesn't have to be shaped by admissions officers. It could be shaped by your own curiosity. It is for all ambitious adults. And you don't have to wait to start. In fact, you don't have to wait to be an adult. There's no switch inside you that magically flips when you turn a certain age or graduate from some institution. You start being an adult when you decide to take responsibility for your life. You can do that at any age. [10] This may sound like bullshit. I'm just a minor, you may think, I have no money, I have to live at home, I have to do what adults tell me all day long. Well, most adults labor under restrictions just as cumbersome, and they manage to get things done. If you think it's restrictive being a kid, imagine having kids. The only real difference between adults and high school kids is that adults realize they need to get things done, and high school kids don't. That realization hits most people around 23. But I'm letting you in on the secret early. So get to work.
该理念的扭曲版本以"激情"之名渗入流行文化。最近我看到服务生招聘广告要求"对服务有激情"。真正的事业激情不可能存在于端盘子这种事上。"激情"并非合适词汇,更好的称呼是"好奇心"。
孩子充满好奇,但我要说的好奇与孩童式好奇形态迥异。孩童好奇广而浅,随机发问;多数成人则完全丧失好奇——必须如此:若事事追问,将一事无成。但抱负远大者的好奇会转化为窄而深的形态,如同泥滩蜕变为水井。
好奇化苦役为乐事。对爱因斯坦而言,相对论非考试必背的艰涩课本,而是待解的谜题。因此他创造理论所需的心力,或许比现今学生课堂学习所费更少。
学校灌输的最危险错觉之一是"成大事需要高度自律"。多数科目教法枯燥,唯靠自律才能勉强啃下。因此大学初读维特根斯坦名言"我毫无自律,从不肯拒绝自己任何事,哪怕一杯咖啡"时,我大为震惊。
Maybe you can be the first generation whose greatest regret from high school isn't how much time you wasted. Notes [1] A doctor friend warns that even this can give an inaccurate picture. "Who knew how much time it would take up, how little autonomy one would have for endless years of training, and how unbelievably annoying it is to carry a beeper?" [2] His best bet would probably be to become dictator and intimidate the NBA into letting him play. So far the closest anyone has come is Secretary of Labor. [3] A day job is one you take to pay the bills so you can do what you really want, like play in a band, or invent relativity. Treating high school as a day job might actually make it easier for some students to get good grades. If you treat your classes as a game, you won't be demoralized if they seem pointless. However bad your classes, you need to get good grades in them to get into a decent college. And that _is_ worth doing, because universities are where a lot of the clumps of smart people are these days. [4] The second biggest regret was caring so much about unimportant things. And especially about what other people thought of them. I think what they really mean, in the latter case, is caring what random people thought of them. Adults care just as much what other people think, but they get to be more selective about the other people. I have about thirty friends whose opinions I care about, and the opinion of the rest of the world barely affects me. The problem in high school is that your peers are chosen for you by accidents of age and geography, rather than by you based on respect for their judgement. [5] The key to wasting time is distraction. Without distractions it's too obvious to your brain that you're not doing anything with it, and you start to feel uncomfortable.
如今我认识众多成就斐然者,他们共性就是缺乏纪律。全是拖延高手,对不感兴趣之事几乎无法启动。有人婚礼谢卡四年未寄,有人邮箱积压两万六千封未读。
非说零自律可行。你需要的自律量约等于跑步所需:虽常不情愿,但一旦开始便享受其中;数日不跑则浑身不适。成大事者亦如此——知不工作会难受,并有足够自律坐到书桌前。但一旦开始,兴趣接管,便不再需要纪律。
你以为莎士比亚是咬紧牙关、呕心沥血创作伟大文学?当然不。他乐在其中,正因如此杰出。
If you want to measure how dependent you've become on distractions, try this experiment: set aside a chunk of time on a weekend and sit alone and think. You can have a notebook to write your thoughts down in, but nothing else: no friends, TV, music, phone, IM, email, Web, games, books, newspapers, or magazines. Within an hour most people will feel a strong craving for distraction. [6] I don't mean to imply that the only function of prep schools is to trick admissions officers. They also generally provide a better education. But try this thought experiment: suppose prep schools supplied the same superior education but had a tiny (.001) negative effect on college admissions. How many parents would still send their kids to them? It might also be argued that kids who went to prep schools, because they've learned more, _are_ better college candidates. But this seems empirically false. What you learn in even the best high school is rounding error compared to what you learn in college. Public school kids arrive at college with a slight disadvantage, but they start to pull ahead in the sophomore year. (I'm not saying public school kids are smarter than preppies, just that they are within any given college. That follows necessarily if you agree prep schools improve kids' admissions prospects.) [7] Why does society foul you? Indifference, mainly. There are simply no outside forces pushing high school to be good. The air traffic control system works because planes would crash otherwise. Businesses have to deliver because otherwise competitors would take their customers. But no planes crash if your school sucks, and it has no competitors. High school isn't evil; it's random; but random is pretty bad. [8] And then of course there is money. It's not a big factor in high school, because you can't do much that anyone wants. But a lot of great things were created mainly to make money.
若想成就卓越,你需要的是对关键问题的强烈好奇。爱因斯坦的关键时刻,是凝视麦克斯韦方程组时发出"这到底怎么回事"的疑问。
锁定关键问题或需数年,因理解领域本质同样耗时。极端例子如数学——多数人自认厌恶数学,但学校冠以"数学"之名的枯燥内容与数学家工作毫无相似。
大数学家哈代坦言高中时也不喜数学,专攻仅因比同学擅长。直到后来才发觉数学之趣——开始提问而非仅正确答题。
Samuel Johnson said "no man but a blockhead ever wrote except for money." (Many hope he was exaggerating.) [9] Even college textbooks are bad. When you get to college, you'll find that (with a few stellar exceptions) the textbooks are not written by the leading scholars in the field they describe. Writing college textbooks is unpleasant work, done mostly by people who need the money. It's unpleasant because the publishers exert so much control, and there are few things worse than close supervision by someone who doesn't understand what you're doing. This phenomenon is apparently even worse in the production of high school textbooks. [10] Your teachers are always telling you to behave like adults. I wonder if they'd like it if you did. You may be loud and disorganized, but you're very docile compared to adults. If you actually started acting like adults, it would be just as if a bunch of adults had been transposed into your bodies. Imagine the reaction of an FBI agent or taxi driver or reporter to being told they had to ask permission to go the bathroom, and only one person could go at a time. To say nothing of the things you're taught. If a bunch of actual adults suddenly found themselves trapped in high school, the first thing they'd do is form a union and renegotiate all the rules with the administration. Thanks to Ingrid Bassett, Trevor Blackwell, Rich Draves, Dan Giffin, Sarah Harlin, Jessica Livingston, Jackie McDonough, Robert Morris, Mark Nitzberg, Lisa Randall, and Aaron Swartz for reading drafts of this, and to many others for talking to me about high school.
| Why Nerds are Unpopular | | | Japanese Translation | Russian Translation | | | Georgian Translation.
当朋友抱怨学校论文时,其母总说:"想办法让它有趣。"这正是你该做的:找到让世界生动的问题。伟人眼中世界与他人无异,但他们注意到某些 compellingly mysterious 的古怪细节。
不仅智力领域如此。亨利·福特的关键问题是:为何汽车必是奢侈品?若视其为大宗商品会怎样?贝肯鲍尔则问:为何球员必须固守位置?后卫为何不能进球?
若关键问题需数年酝酿,十六岁的你能做什么?朝着发现问题的方向努力。伟大问题不会突然显现,而是在脑中逐渐凝结——凝结剂正是经验。因此寻找之法非刻意搜寻,不是边闲逛边想"我该做什么伟大发现"。这无解——若能解答,你早已发现。
让伟大想法降临的方法,不是追逐宏
[](https://s.turbifycdn.com/aah/paulgraham/it-s-charisma-stupid-11.gif) November 2004, corrected June 2006 Occam's razor says we should prefer the simpler of two explanations. I begin by reminding readers of this principle because I'm about to propose a theory that will offend both liberals and conservatives. But Occam's razor means, in effect, that if you want to disagree with it, you have a hell of a coincidence to explain. Theory: In US presidential elections, the more charismatic candidate wins. People who write about politics, whether on the left or the right, have a consistent bias: they take politics seriously. When one candidate beats another they look for political explanations. The country is shifting to the left, or the right. And that sort of shift can certainly be the result of a presidential election, which makes it easy to believe it was the cause. But when I think about why I voted for Clinton over the first George Bush, it wasn't because I was shifting to the left. Clinton just seemed more dynamic. He seemed to want the job more. Bush seemed old and tired. I suspect it was the same for a lot of voters. Clinton didn't represent any national shift leftward. [1] He was just more charismatic than George Bush or (God help us) Bob Dole. In 2000 we practically got a controlled experiment to prove it: Gore had Clinton's policies, but not his charisma, and he suffered proportionally. [2] Same story in 2004. Kerry was smarter and more articulate than Bush, but rather a stiff. And Kerry lost. As I looked further back, I kept finding the same pattern. Pundits said Carter beat Ford because the country distrusted the Republicans after Watergate. And yet it also happened that Carter was famous for his big grin and folksy ways, and Ford for being a boring klutz. Four years later, pundits said the country had lurched to the right.
[](https://s.turbifycdn.com/aah/paulgraham/it-s-charisma-stupid-11.gif)
2004年11月,2006年6月修订
奥卡姆剃刀原则指出,当存在两种解释时,我们应倾向于更简单的那种。我首先提醒读者这一原则,因为我即将提出一个会同时冒犯自由派和保守派的理论。但奥卡姆剃刀实际上意味着:如果你想反驳这个理论,就必须解释一个惊人的巧合。
理论:在美国总统选举中,更具魅力的候选人会获胜。
无论是左派还是右派,政治评论家都有一个共同的偏见:他们过于严肃地看待政治。当一位候选人击败另一位时,他们总在寻找政治层面的解释——国家正在向左或向右倾斜。这种倾斜确实可能是选举的结果,但人们很容易误将其视为原因。
当我回想自己当年投票给克林顿而非老布什时,并非因为我的立场转向左派。仅仅因为克林顿显得更有活力,更渴望这份工作,而布什看起来老态龙钟。我猜许多选民也是如此。
But Reagan, a former actor, also happened to be even more charismatic than Carter (whose grin was somewhat less cheery after four stressful years in office). In 1984 the charisma gap between Reagan and Mondale was like that between Clinton and Dole, with similar results. The first George Bush managed to win in 1988, though he would later be vanquished by one of the most charismatic presidents ever, because in 1988 he was up against the notoriously uncharismatic Michael Dukakis. These are the elections I remember personally, but apparently the same pattern played out in 1964 and 1972. The most recent counterexample appears to be 1968, when Nixon beat the more charismatic Hubert Humphrey. But when you examine that election, it tends to support the charisma theory more than contradict it. As Joe McGinnis recounts in his famous book _The Selling of the President 1968_ , Nixon knew he had less charisma than Humphrey, and thus simply refused to debate him on TV. He knew he couldn't afford to let the two of them be seen side by side. Now a candidate probably couldn't get away with refusing to debate. But in 1968 the custom of televised debates was still evolving. In effect, Nixon won in 1968 because voters were never allowed to see the real Nixon. All they saw were carefully scripted campaign spots. Oddly enough, the most recent true counterexample is probably 1960. Though this election is usually given as an example of the power of TV, Kennedy apparently would not have won without fraud by party machines in Illinois and Texas. But TV was still young in 1960; only 87% of households had it. [3] Undoubtedly TV helped Kennedy, so historians are correct in regarding this election as a watershed. TV required a new kind of candidate. There would be no more Calvin Coolidges. The charisma theory may also explain why Democrats tend to lose presidential elections. The core of the Democrats' ideology seems to be a belief in government.
克林顿并不代表国家整体左转[1],他只是比乔治·布什(或上帝保佑的鲍勃·多尔)更有魅力。2000年我们几乎得到了一个对照实验来证明这一点:戈尔继承了克林顿的政策,却缺乏他的魅力,结果遭受了相应的失败[2]。2004年历史重演——克里比布什更聪明、更雄辩,却僵硬呆板,最终败选。
当我回溯更早的选举,同样的模式不断重现。评论家声称卡特击败福特是因为水门事件后民众不信任共和党。但不可忽视的是:卡特以灿烂笑容和亲民作风闻名,福特则因笨拙无趣著称。四年后,专家宣称国家突然右转,但演员出身的里根恰好比卡特(经过四年高压任期后笑容已不那么灿烂)更具魅力。1984年里根与蒙代尔的魅力差距堪比克林顿与多尔,结果如出一辙。老布什在1988年勉强获胜(尽管后来败给史上最具魅力的总统之一),只因当年他的对手是出了名缺乏魅力的杜卡基斯。
这些是我亲身经历的选举,但1964和1972年显然也遵循相同规律。最近的例外似乎是1968年尼克松击败更有魅力的汉弗莱。但细究之下,这场选举反而佐证了魅力理论。正如乔·麦金尼斯在《1968年总统的推销》中所述,尼克松深知自己魅力不及对手,因此干脆拒绝电视辩论。他明白绝不能给选民同时比较两人的机会。
如今候选人已无法逃避辩论,但在1968年电视辩论传统尚未成型。尼克松的胜利本质上是因为选民从未见识真实的他——人们只看到精心设计的竞选广告。
最令人意外的真正反例或许是1960年。虽然这场选举常被作为电视影响力的典型案例,但若无伊利诺伊州和得克萨斯州的选举舞弊,肯尼迪很可能败选。不过1960年电视仍属新兴媒介(覆盖率仅87%)[3]。电视确实助力肯尼迪,因此历史学家将其视为分水岭是正确的——电视时代需要新型候选人,卡尔文·柯立芝式的总统从此绝迹。
魅力理论或许也能解释民主党为何屡败总统选举。民主党意识形态的核心似乎是对政府的信仰,这种特质容易吸引认真但乏味的人。杜卡基斯、戈尔和克里在这方面相似得如同兄弟。对民主党而言幸运的是,他们的筛选机制偶尔能漏出克林顿这样的例外,即便附带丑闻[4]。
Perhaps this tends to attract people who are earnest, but dull. Dukakis, Gore, and Kerry were so similar in that respect that they might have been brothers. Good thing for the Democrats that their screen lets through an occasional Clinton, even if some scandal results. [4] One would like to believe elections are won and lost on issues, if only fake ones like Willie Horton. And yet, if they are, we have a remarkable coincidence to explain. In every presidential election since TV became widespread, the apparently more charismatic candidate has won. Surprising, isn't it, that voters' opinions on the issues have lined up with charisma for 11 elections in a row? The political commentators who come up with shifts to the left or right in their morning-after analyses are like the financial reporters stuck writing stories day after day about the random fluctuations of the stock market. Day ends, market closes up or down, reporter looks for good or bad news respectively, and writes that the market was up on news of Intel's earnings, or down on fears of instability in the Middle East. Suppose we could somehow feed these reporters false information about market closes, but give them all the other news intact. Does anyone believe they would notice the anomaly, and not simply write that stocks were up (or down) on whatever good (or bad) news there was that day? That they would say, hey, wait a minute, how can stocks be up with all this unrest in the Middle East? I'm not saying that issues don't matter to voters. Of course they do. But the major parties know so well which issues matter how much to how many voters, and adjust their message so precisely in response, that they tend to split the difference on the issues, leaving the election to be decided by the one factor they can't control: charisma. If the Democrats had been running a candidate as charismatic as Clinton in the 2004 election, he'd have won.
人们宁愿相信选举成败取决于议题(哪怕是威利·霍顿这类虚构议题)。但若真如此,我们就必须解释一个惊人的巧合:自电视普及以来,每届总统选举都是表面更具魅力的候选人获胜。连续11届选举中,选民的议题立场竟都与候选人魅力完美吻合,这不奇怪吗?
那些在选后分析中炮制"左转右转"论的政治评论家,就像日复一日编造股市随机波动故事的财经记者。收盘后,记者会根据涨跌分别寻找利好或利空消息,宣称"因英特尔盈利股市上涨"或"因中东动荡担忧股市下跌"。假设我们篡改收盘数据却保留其他新闻,这些记者真能发现异常吗?难道他们会说"等等,中东乱局下股市怎么可能上涨"?
我并非否认议题对选民的重要性。但两大党对"哪些议题影响多少选民"了如指掌,他们会精准调整政纲,最终在议题上势均力敌,使得选举结果取决于唯一不可控因素:魅力。
如果2004年民主党推出克林顿般魅力的候选人,他本可获胜。届时我们读到的将是"这场选举是对伊拉克战争的公投",而非"民主党与中美洲福音派基督徒脱节"。
1992年大选期间,克林顿竞选办公室挂着巨幅标语:"问题是经济,笨蛋"。或许真相比他们想象的更简单。
人们对魅力理论褒贬不一。有人认为绝无可能,有人觉得显而易见——这或许是理论恰处于两者之间的理想位置。
And we'd be reading that the election was a referendum on the war in Iraq, instead of that the Democrats are out of touch with evangelical Christians in middle America. During the 1992 election, the Clinton campaign staff had a big sign in their office saying "It's the economy, stupid." Perhaps it was even simpler than they thought. Postscript Opinions seem to be divided about the charisma theory. Some say it's impossible, others say it's obvious. This seems a good sign. Perhaps it's in the sweet spot midway between. As for it being impossible, I reply: here's the data; here's the theory; theory explains data 100%. To a scientist, at least, that means it deserves attention, however implausible it seems. You can't believe voters are so superficial that they just choose the most charismatic guy? My theory doesn't require that. I'm not proposing that charisma is the only factor, just that it's the only one _left_ after the efforts of the two parties cancel one another out. As for the theory being obvious, as far as I know, no one has proposed it before. Election forecasters are proud when they can achieve the same results with much more complicated models. Finally, to the people who say that the theory is probably true, but rather depressing: it's not so bad as it seems. The phenomenon is like a pricing anomaly; once people realize it's there, it will disappear. Once both parties realize it's a waste of time to nominate uncharismatic candidates, they'll tend to nominate only the most charismatic ones. And if the candidates are equally charismatic, charisma will cancel out, and elections will be decided on issues, as political commentators like to think they are now. Notes [1] As Clinton himself discovered to his surprise when, in one of his first acts as president, he tried to shift the military leftward.
对"不可能"论者,我的回应是:数据在此,理论在此,理论100%解释数据。至少在科学家看来,无论多不可思议,这都值得关注。
你无法相信选民竟肤浅到只看魅力?我的理论无需如此极端。我并非主张魅力是唯一因素,只是说当两党在其他方面相互抵消后,魅力成为决定性变量。
至于"显而易见"的评价,据我所知此前从未有人明确提出该理论。选举预测专家总以复杂模型得出相同结果为荣。
最后,对那些认同理论但感到沮丧的人:情况没想象中糟糕。这种现象如同定价异常——一旦被察觉就会消失。当两党都意识到提名乏味候选人是徒劳时,自然会选择最具魅力者。若候选人魅力相当,选举终将如评论家们设想的那样由议题决定。
[1] 克林顿上任后试图推动军队左转时,惊讶地发现这并非国家意志。经历激烈斗争后,他仅以体面妥协收场。
[2] 戈尔确实赢得普选票。但政客深知选举人票决定胜负,因此全力争夺后者。若布什当年主攻普选票,结果或许不同。(感谢judgmentalist指出)
After a bruising fight he escaped with a face-saving compromise. [2] True, Gore won the popular vote. But politicians know the electoral vote decides the election, so that's what they campaign for. If Bush had been campaigning for the popular vote he would presumably have got more of it. (Thanks to judgmentalist for this point.) [3] Source: Nielsen Media Research. Of the remaining 13%, 11 didn't have TV because they couldn't afford it. I'd argue that the missing 11% were probably also the 11% most susceptible to charisma. [4] One implication of this theory is that parties shouldn't be too quick to reject candidates with skeletons in their closets. Charismatic candidates will tend to have more skeletons than squeaky clean dullards, but in practice that doesn't seem to lose elections. The current Bush, for example, probably did more drugs in his twenties than any preceding president, and yet managed to get elected with a base of evangelical Christians. All you have to do is say you've reformed, and stonewall about the details. Thanks to Trevor Blackwell, Maria Daniels, Jessica Livingston, Jackie McDonough, and Robert Morris for reading drafts of this, and to Eric Raymond for pointing out that I was wrong about 1968. [](http://reddit.com) Comment on this essay.
| What Charisma Is | | | Politics and the Art of Acting | Japanese Translation.
[3] 数据来源:尼尔森媒体研究。未覆盖的13%家庭中,11%因经济困难无力购买电视。我认为这11%恰是最易受魅力影响的群体。
[4] 该理论的启示是:政党不应仓排除有污点的候选人。有魅力者往往比"干净"的平庸者更多黑历史,但实践中这似乎不影响胜选。例如小布什青年时期的吸毒史远超历任总统,却仍能赢得福音派基督徒支持——只需宣称已改过自新并对细节避而不谈。
致谢 特雷弗·布莱克韦尔、玛丽亚·丹尼尔斯、杰西卡·利文斯顿、杰基·麦克多诺和罗伯特·莫里斯审阅了本文草稿,埃里克·雷蒙德纠正了我对1968年选举的错误认知。
[](http://reddit.com) 评论本文
| 何为魅力
| | | 政治与表演艺术
| 日语译本
[](https://s.turbifycdn.com/aah/paulgraham/made-in-usa-11.gif) November 2004 _(This is a new essay for the Japanese edition ofHackers & Painters. It tries to explain why Americans make some things well and others badly.)_ A few years ago an Italian friend of mine travelled by train from Boston to Providence. She had only been in America for a couple weeks and hadn't seen much of the country yet. She arrived looking astonished. "It's so _ugly!"_ People from other rich countries can scarcely imagine the squalor of the man-made bits of America. In travel books they show you mostly natural environments: the Grand Canyon, whitewater rafting, horses in a field. If you see pictures with man-made things in them, it will be either a view of the New York skyline shot from a discreet distance, or a carefully cropped image of a seacoast town in Maine. How can it be, visitors must wonder. How can the richest country in the world look like this? Oddly enough, it may not be a coincidence. Americans are good at some things and bad at others. We're good at making movies and software, and bad at making cars and cities. And I think we may be good at what we're good at for the same reason we're bad at what we're bad at. We're impatient. In America, if you want to do something, you don't worry that it might come out badly, or upset delicate social balances, or that people might think you're getting above yourself. If you want to do something, as Nike says, _just do it._ This works well in some fields and badly in others. I suspect it works in movies and software because they're both messy processes. "Systematic" is the last word I'd use to describe the way good programmers write software. Code is not something they assemble painstakingly after careful planning, like the pyramids.
[](https://s.turbifycdn.com/aah/paulgraham/made-in-usa-11.gif)
(本文是为日文版《黑客与画家》撰写的新文章,试图解释美国人在某些领域表现出色而在其他领域表现糟糕的原因。)
几年前,我的一位意大利朋友乘火车从波士顿前往普罗维登斯。她刚来美国两周,对这个国家还不太了解。抵达时,她一脸震惊:“这里太丑了!”
来自其他富裕国家的人几乎无法想象美国人造环境的破败。旅游书籍展示的多是自然景观:大峡谷、激流漂流、田野中的马匹。如果照片中出现人造物,要么是从谨慎距离拍摄的纽约天际线,要么是经过精心裁剪的缅因州海滨小镇画面。
游客们一定感到困惑:世界上最富裕的国家怎么会是这样?
It's something they plunge into, working fast and constantly changing their minds, like a charcoal sketch. In software, paradoxical as it sounds, good craftsmanship means working fast. If you work slowly and meticulously, you merely end up with a very fine implementation of your initial, mistaken idea. Working slowly and meticulously is premature optimization. Better to get a prototype done fast, and see what new ideas it gives you. It sounds like making movies works a lot like making software. Every movie is a Frankenstein, full of imperfections and usually quite different from what was originally envisioned. But interesting, and finished fairly quickly. I think we get away with this in movies and software because they're both malleable mediums. Boldness pays. And if at the last minute two parts don't quite fit, you can figure out some hack that will at least conceal the problem. Not so with cars, or cities. They are all too physical. If the car business worked like software or movies, you'd surpass your competitors by making a car that weighed only fifty pounds, or folded up to the size of a motorcycle when you wanted to park it. But with physical products there are more constraints. You don't win by dramatic innovations so much as by good taste and attention to detail. The trouble is, the very word "taste" sounds slightly ridiculous to American ears. It seems pretentious, or frivolous, or even effeminate. Blue staters think it's "subjective," and red staters think it's for sissies. So anyone in America who really cares about design will be sailing upwind. Twenty years ago we used to hear that the problem with the US car industry was the workers. We don't hear that any more now that Japanese companies are building cars in the US. The problem with American cars is bad design. You can see that just by looking at them. All that extra sheet metal on the AMC Matador wasn't added by the workers.
奇怪的是,这或许并非巧合。美国人擅长某些事,却在另一些事上表现糟糕。我们擅长制作电影和软件,却不擅长制造汽车和城市规划。我认为,我们擅长的原因可能正是我们不擅长的原因——我们缺乏耐心。在美国,如果你想做某事,不会担心结果糟糕、破坏微妙的社会平衡,或被人认为狂妄自大。正如耐克所说,想做就做。
这种方式在某些领域行之有效,在其他领域则不然。我认为它在电影和软件领域有效,因为这两个过程都充满混乱。“系统性”是我最不会用来描述优秀程序员编写软件方式的词。代码不是像金字塔那样经过精心规划后费力组装的东西,而是像炭笔画一样快速投入、不断修改的产物。
在软件中,听起来矛盾,但优秀的工艺意味着快速工作。如果缓慢而细致地工作,最终只会完美实现最初错误的想法。缓慢而细致是过早的优化。快速完成原型并观察新想法更为重要。
电影制作似乎与软件开发类似。每部电影都是弗兰肯斯坦,充满瑕疵且通常与最初设想大相径庭。但它有趣且完成迅速。
我认为电影和软件能够容忍这种方式,因为它们都是可塑性强的媒介。大胆有回报。如果在最后一刻两部分无法完美契合,至少可以找到临时方案掩盖问题。
汽车或城市则不然。它们过于实体化。如果汽车行业像软件或电影一样运作,你会通过制造仅重50磅或可折叠成摩托车大小的汽车超越竞争对手。但实体产品有更多限制。胜利不在于戏剧性创新,而在于良好的品味和对细节的关注。
The problem with this car, as with American cars today, is that it was designed by marketing people instead of designers. Why do the Japanese make better cars than us? Some say it's because their culture encourages cooperation. That may come into it. But in this case it seems more to the point that their culture prizes design and craftsmanship. For centuries the Japanese have made finer things than we have in the West. When you look at swords they made in 1200, you just can't believe the date on the label is right. Presumably their cars fit together more precisely than ours for the same reason their joinery always has. They're obsessed with making things well. Not us. When we make something in America, our aim is just to get the job done. Once we reach that point, we take one of two routes. We can stop there, and have something crude but serviceable, like a Vise-grip. Or we can improve it, which usually means encrusting it with gratuitous ornament. When we want to make a car "better," we stick tail fins on it, or make it longer, or make the windows smaller, depending on the current fashion. Ditto for houses. In America you can have either a flimsy box banged together out of two by fours and drywall, or a McMansion-- a flimsy box banged together out of two by fours and drywall, but larger, more dramatic-looking, and full of expensive fittings. Rich people don't get better design or craftsmanship; they just get a larger, more conspicuous version of the standard house. We don't especially prize design or craftsmanship here. What we like is speed, and we're willing to do something in an ugly way to get it done fast. In some fields, like software or movies, this is a net win. But it's not just that software and movies are malleable mediums. In those businesses, the designers (though they're not generally called that) have more power.
问题在于,“品味”一词在美国人听来有些可笑。它显得矫饰、轻浮甚至女性化。蓝州人认为它“主观”,红州人认为它属于懦夫。因此,真正关心设计的美国人都逆风而行。
二十年前,我们常听说美国汽车业的问题是工人。如今日本公司在美国建厂后,这种说法消失了。美国汽车的问题是糟糕的设计,一眼可见。
AMC Matador上多余的金属板不是工人添加的。这款车的问题与当今美国汽车一样,是由营销人员而非设计师设计的。
为什么日本人制造的汽车比我们好?有人说是因为他们的文化鼓励合作。这可能是部分原因。但更关键的是,他们的文化重视设计和工艺。
几个世纪以来,日本人制作的物品比西方更精致。看到他们1200年制作的刀剑时,你很难相信标签上的日期。他们的汽车比我们的更精密,原因与他们的木工技艺一脉相承——他们痴迷于精益求精。
我们则不然。在美国制造某物时,目标只是完成任务。完成后,我们有两种选择:要么止步于粗糙但可用的产品(如老虎钳),要么通过添加多余装饰来“改进”。想让汽车“更好”?根据时尚添加尾翼、加长车身或缩小车窗。
Software companies, at least successful ones, tend to be run by programmers. And in the film industry, though producers may second-guess directors, the director controls most of what appears on the screen. And so American software and movies, and Japanese cars, all have this in common: the people in charge care about design-- the former because the designers are in charge, and the latter because the whole culture cares about design. I think most Japanese executives would be horrified at the idea of making a bad car. Whereas American executives, in their hearts, still believe the most important thing about a car is the image it projects. Make a good car? What's "good?" It's so _subjective._ If you want to know how to design a car, ask a focus group. Instead of relying on their own internal design compass (like Henry Ford did), American car companies try to make what marketing people think consumers want. But it isn't working. American cars continue to lose market share. And the reason is that the customer doesn't want what he thinks he wants. Letting focus groups design your cars for you only wins in the short term. In the long term, it pays to bet on good design. The focus group may say they want the meretricious feature du jour, but what they want even more is to imitate sophisticated buyers, and they, though a small minority, really do care about good design. Eventually the pimps and drug dealers notice that the doctors and lawyers have switched from Cadillac to Lexus, and do the same. Apple is an interesting counterexample to the general American trend. If you want to buy a nice CD player, you'll probably buy a Japanese one. But if you want to buy an MP3 player, you'll probably buy an iPod. What happened? Why doesn't Sony dominate MP3 players? Because Apple is in the consumer electronics business now, and unlike other American companies, they're obsessed with good design. Or more precisely, their CEO is.
房屋也是如此。在美国,你可以选择用2x4木材和石膏板拼凑的脆弱盒子,或是McMansion——更大的、外观更夸张、装满昂贵配件的脆弱盒子。富人的房屋并非设计或工艺更好,只是更大、更显眼的标准版本。
我们并不特别重视设计或工艺。我们喜欢速度,并愿意以丑陋的方式快速完成任务。在软件或电影等领域,这是净收益。
但不仅因为软件和电影是可塑性强的媒介。在这些行业中,设计师(尽管通常不这么称呼)拥有更多权力。软件公司(至少成功的那些)往往由程序员管理。电影行业中,导演控制银幕上的大部分内容。因此,美国软件和电影与日本汽车的共同点是:负责人关心设计——前者因为设计师掌权,后者因为整个文化重视设计。
我认为大多数日本高管会对制造糟糕汽车的想法感到恐惧,而美国高管内心仍认为汽车最重要的是其投射的形象。制造好车?什么是“好”?这太主观了。想知道如何设计汽车?问问焦点小组。
美国汽车公司不依赖内部设计指南(如亨利·福特那样),而是试图制造营销人员认为消费者想要的产品。但这行不通。美国汽车市场份额持续下降,原因是消费者并不真正知道自己想要什么。
I just got an iPod, and it's not just nice. It's _surprisingly_ nice. For it to surprise me, it must be satisfying expectations I didn't know I had. No focus group is going to discover those. Only a great designer can. Cars aren't the worst thing we make in America. Where the just-do-it model fails most dramatically is in our cities-- or rather, exurbs. If real estate developers operated on a large enough scale, if they built whole towns, market forces would compel them to build towns that didn't suck. But they only build a couple office buildings or suburban streets at a time, and the result is so depressing that the inhabitants consider it a great treat to fly to Europe and spend a couple weeks living what is, for people there, just everyday life. [1] But the just-do-it model does have advantages. It seems the clear winner for generating wealth and technical innovations (which are practically the same thing). I think speed is the reason. It's hard to create wealth by making a commodity. The real value is in things that are new, and if you want to be the first to make something, it helps to work fast. For better or worse, the just-do-it model is fast, whether you're Dan Bricklin writing the prototype of VisiCalc in a weekend, or a real estate developer building a block of shoddy condos in a month. If I had to choose between the just-do-it model and the careful model, I'd probably choose just-do-it. But do we have to choose? Could we have it both ways? Could Americans have nice places to live without undermining the impatient, individualistic spirit that makes us good at software? Could other countries introduce more individualism into their technology companies and research labs without having it metastasize as strip malls? I'm optimistic. It's harder to say about other countries, but in the US, at least, I think we can have both. Apple is an encouraging example.
让焦点小组设计汽车只能在短期内获胜。长期来看,押注优秀设计才有回报。焦点小组可能想要华而不实的流行功能,但他们更想模仿品味成熟的买家——尽管是少数,这些人真正关心好设计。最终,皮条客和毒贩会注意到医生和律师从凯迪拉克转向雷克萨斯,并效仿之。
苹果是美国普遍趋势的反例。如果想买好的CD播放器,你可能会选日本产品。但如果是MP3播放器,你可能会选iPod。为什么索尼不主导MP3播放器市场?因为苹果现在涉足消费电子行业,且与其他美国公司不同,他们痴迷于优秀设计。更准确地说,他们的CEO是。
我刚拿到iPod,它不仅好,而且好得令人惊讶。能让我惊讶,说明它满足了我未曾意识到的期望。焦点小组无法发现这些,只有伟大的设计师才能。
汽车并非我们在美国制造的最糟糕产品。“做就对了”模式最失败的是我们的城市——或更准确地说,远郊。如果房地产开发商规模足够大,能建造整个城镇,市场力量会迫使他们建造不糟糕的城镇。但他们一次只建几栋办公楼或郊区街道,结果令人沮丧,以至于居民将飞往欧洲生活几周视为享受——尽管对当地人来说这只是日常生活。[1]
但“做就对了”模式确有优势。在创造财富和技术创新(两者几乎是一回事)方面,它显然是赢家。我认为速度是关键。通过制造商品很难创造财富,真正的价值在于新事物。如果想成为第一个做出某物的人,快速工作至关重要。无论好坏,“做就对了”模式速度很快——无论是Dan Bricklin用一个周末写出VisiCalc原型,还是房地产开发商一个月内建起劣质公寓楼。
如果必须在“做就对了”和“谨慎”模式间选择,我可能会选前者。但我们必须二选一吗?能否兼得?美国人能否拥有宜居环境而不损害让我们擅长软件的不耐烦、个人主义精神?其他国家能否在科技公司和实验室引入更多个人主义而不让其扩散为 strip mall?我持乐观态度。其他国家难以断言,但在美国,我认为我们可以两者兼得。
They've managed to preserve enough of the impatient, hackerly spirit you need to write software. And yet when you pick up a new Apple laptop, well, it doesn't seem American. It's too perfect. It seems as if it must have been made by a Swedish or a Japanese company. In many technologies, version 2 has higher resolution. Why not in design generally? I think we'll gradually see national characters superseded by occupational characters: hackers in Japan will be allowed to behave with a willfulness that would now seem unJapanese, and products in America will be designed with an insistence on taste that would now seem unAmerican. Perhaps the most successful countries, in the future, will be those most willing to ignore what are now considered national characters, and do each kind of work in the way that works best. Race you. Notes [1] Japanese cities are ugly too, but for different reasons. Japan is prone to earthquakes, so buildings are traditionally seen as temporary; there is no grand tradition of city planning like the one Europeans inherited from Rome. The other cause is the notoriously corrupt relationship between the government and construction companies. Thanks to Trevor Blackwell, Barry Eisler, Sarah Harlin, Shiro Kawai, Jessica Livingston, Jackie McDonough, Robert Morris, and Eric Raymond for reading drafts of this.
| American Gothic | | | The John Rain Books.
苹果是个鼓舞人心的例子。他们保留了编写软件所需的不耐烦、黑客精神。然而拿起一台新的苹果笔记本电脑时,它感觉不太像美国产品——它太完美了,仿佛出自瑞典或日本公司之手。
在许多技术中,版本2分辨率更高。为何设计不能普遍如此?我认为我们将逐渐看到职业性格取代民族性格:日本的黑客将被允许表现出如今看来不像日本人的任性,美国的产品将设计得注重品味——如今这似乎不像美国人。未来最成功的国家或许是那些最愿忽视所谓民族性格、以最佳方式完成每项工作的国家。我们比比看。
注释 [1] 日本城市也很丑,但原因不同。日本地震频发,传统上建筑被视为临时物;没有欧洲从罗马继承的城市规划传统。另一原因是政府与建筑公司间众所周知的腐败关系。
致谢 感谢Trevor Blackwell、Barry Eisler、Sarah Harlin、Shiro Kawai、Jessica Livingston、Jackie McDonough、Robert Morris和Eric Raymond阅读本文草稿。
| 美国哥特式
| | | 约翰·雷恩系列小说
[](https://s.turbifycdn.com/aah/paulgraham/bradley-s-ghost-16.gif) November 2004 A lot of people are writing now about why Kerry lost. Here I want to examine a more specific question: why were the exit polls so wrong? In Ohio, which Kerry ultimately lost 49-51, exit polls gave him a 52-48 victory. And this wasn't just random error. In every swing state they overestimated the Kerry vote. In Florida, which Bush ultimately won 52-47, exit polls predicted a dead heat. (These are not early numbers. They're from about midnight eastern time, long after polls closed in Ohio and Florida. And yet by the next afternoon the exit poll numbers online corresponded to the returns. The only way I can imagine this happening is if those in charge of the exit polls cooked the books after seeing the actual returns. But that's another issue.) What happened? The source of the problem may be a variant of the Bradley Effect. This term was invented after Tom Bradley, the black mayor of Los Angeles, lost an election for governor of California despite a comfortable lead in the polls. Apparently voters were afraid to say they planned to vote against him, lest their motives be (perhaps correctly) suspected. It seems likely that something similar happened in exit polls this year. In theory, exit polls ought to be very accurate. You're not asking people what they would do. You're asking what they just did. How can you get errors asking that? Because some people don't respond. To get a truly random sample, pollsters ask, say, every 20th person leaving the polling place who they voted for. But not everyone wants to answer. And the pollsters can't simply ignore those who won't, or their sample isn't random anymore. So what they do, apparently, is note down the age and race and sex of the person, and guess from that who they voted for. This works so long as there is no _correlation_ between who people vote for and whether they're willing to talk about it.
[](https://s.turbifycdn.com/aah/paulgraham/bradley-s-ghost-16.gif) 2004年11月 如今许多人都在探讨克里败选的原因。在此我想研究一个更具体的问题:为何出口民调如此失准? 在俄亥俄州,克里最终以49比51落败,出口民调却显示他将以52比48胜出。这并非随机误差——所有摇摆州的出口民调都高估了克里的得票率。在布什最终以52比47赢下的佛罗里达州,出口民调曾预测双方势均力敌。 (这些并非早期数据。它们来自东部时间午夜时分,远在俄亥俄和佛罗里达投票结束之后。然而次日午后,网络上的出口民调数据已与最终结果吻合。唯一可能的解释是负责出口民调的人员在见到实际结果后篡改了数据——但这属于另一个议题。) 究竟发生了什么?问题的根源或许是"布拉德利效应"的变体。这个术语诞生于洛杉矶黑人市长汤姆·布拉德利竞选加州州长时,他在民调领先的情况下意外落败。显然选民不敢坦言打算投票反对他,唯恐自己的动机(或许确实如此)遭到质疑。 今年出口民调很可能出现了类似现象。理论上出口民调应极为精准——你不是在询问人们的投票意向,而是在确认他们刚刚完成的投票行为。 这种调查为何会出错?因为部分受访者拒绝回答。为获得真正随机样本,民调机构会每隔20人询问其投票选择。但并非所有人都愿意作答。若简单忽略拒答者,样本就不再随机。因此实际操作中,调查员会记录受访者的年龄、种族和性别,据此推测其投票倾向。 只要投票选择与受访意愿无关,这种方法就有效。但今年二者可能产生了关联——或许有相当数量的布什选民不愿表明立场。 为何如此?因为美国民众比他们愿意承认的更为保守。当前美国精英阶层奉行的是NPR(美国公共广播)价值观。正如共和党与民主党都认同的,普通民众在社会观念上更为保守。有些人公然炫耀自己与精英观点相左,另一些人则对此感到不安,就像担心暴露不良餐桌礼仪。 例如按照当前NPR价值观,任何可能被视为贬损同性恋的言论都被打上"恐同"标签。然而大量美国民众信仰虔诚,而《圣经》对同性恋立场鲜明。他们该如何自处?许多人选择保留真实观点但保持沉默。 他们清楚自己的信仰,也明白"应该"持有的立场。因此当陌生人(比如民调员)询问他们对同性婚姻等议题的看法时,未必会吐露心声。 当精英价值观偏向自由主义时,民调往往会低估普通选民的保守程度。这在我看来是解释今年出口民调严重失准的主流理论。NPR价值观宣称应该投票给克里,于是所有克里支持者都自豪地告知民调员自己的选择——没有人会为投票给克里感到心虚。
But this year there may have been. It may be that a significant number of those who voted for Bush didn't want to say so. Why not? Because people in the US are more conservative than they're willing to admit. The values of the elite in this country, at least at the moment, are NPR values. The average person, as I think both Republicans and Democrats would agree, is more socially conservative. But while some openly flaunt the fact that they don't share the opinions of the elite, others feel a little nervous about it, as if they had bad table manners. For example, according to current NPR values, you can't say anything that might be perceived as disparaging towards homosexuals. To do so is "homophobic." And yet a large number of Americans are deeply religious, and the Bible is quite explicit on the subject of homosexuality. What are they to do? I think what many do is keep their opinions, but keep them to themselves. They know what they believe, but they also know what they're supposed to believe. And so when a stranger (for example, a pollster) asks them their opinion about something like gay marriage, they will not always say what they really think. When the values of the elite are liberal, polls will tend to underestimate the conservativeness of ordinary voters. This seems to me the leading theory to explain why the exit polls were so far off this year. NPR values said one ought to vote for Kerry. So all the people who voted for Kerry felt virtuous for doing so, and were eager to tell pollsters they had. No one who voted for Kerry did it as an act of quiet defiance.
| Support for a Woman President | | | Japanese Translation.
If you liked this, you may also like _Hackers & Painters_.
如果你喜欢这篇文章,可能也会喜欢《黑客与画家》。
October 2004 As E. B. White said, "good writing is rewriting." I didn't realize this when I was in school. In writing, as in math and science, they only show you the finished product. You don't see all the false starts. This gives students a misleading view of how things get made. Part of the reason it happens is that writers don't want people to see their mistakes. But I'm willing to let people see an early draft if it will show how much you have to rewrite to beat an essay into shape. Below is the oldest version I can find of The Age of the Essay (probably the second or third day), with text that ultimately survived in red and text that later got deleted in gray. There seem to be several categories of cuts: things I got wrong, things that seem like bragging, flames, digressions, stretches of awkward prose, and unnecessary words. I discarded more from the beginning. That's not surprising; it takes a while to hit your stride. There are more digressions at the start, because I'm not sure where I'm heading. The amount of cutting is about average. I probably write three to four words for every one that appears in the final version of an essay. (Before anyone gets mad at me for opinions expressed here, remember that anything you see here that's not in the final version is obviously something I chose not to publish, often because I disagree with it.) Recently a friend said that what he liked about my essays was that they weren't written the way we'd been taught to write essays in school. You remember: topic sentence, introductory paragraph, supporting paragraphs, conclusion. It hadn't occurred to me till then that those horrible things we had to write in school were even connected to what I was doing now. But sure enough, I thought, they did call them "essays," didn't they? Well, they're not.
正如E.B.怀特所言:"好文章是改出来的。"我在学校时并不明白这一点。无论是写作、数学还是科学,人们只会向你展示最终成品。你看不到所有失败的尝试。这让学生对创作过程产生了误解。
部分原因在于作家不愿让人看到自己的错误。但如果能让人们明白一篇文章需要反复修改才能成形,我愿意展示早期草稿。
以下是我能找到的《散文的时代》最原始版本(约第二或第三天撰写),最终保留的文本标红,删除部分标灰。删减内容大致可分为几类:错误观点、自夸之词、过激言论、离题内容、生硬表达及冗余文字。
开头部分删改最多。这并不意外——进入状态需要时间。开头常有更多离题内容,因为当时我还不确定方向。
Those things you have to write in school are not only not essays, they're one of the most pointless of all the pointless hoops you have to jump through in school. And I worry that they not only teach students the wrong things about writing, but put them off writing entirely. So I'm going to give the other side of the story: what an essay really is, and how you write one. Or at least, how I write one. Students be forewarned: if you actually write the kind of essay I describe, you'll probably get bad grades. But knowing how it's really done should at least help you to understand the feeling of futility you have when you're writing the things they tell you to. The most obvious difference between real essays and the things one has to write in school is that real essays are not exclusively about English literature. It's a fine thing for schools to teach students how to write. But for some bizarre reason (actually, a very specific bizarre reason that I'll explain in a moment), the teaching of writing has gotten mixed together with the study of literature. And so all over the country, students are writing not about how a baseball team with a small budget might compete with the Yankees, or the role of color in fashion, or what constitutes a good dessert, but about symbolism in Dickens. With obvious results. Only a few people really care about symbolism in Dickens. The teacher doesn't. The students don't. Most of the people who've had to write PhD disserations about Dickens don't. And certainly Dickens himself would be more interested in an essay about color or baseball. How did things get this way? To answer that we have to go back almost a thousand years. Between about 500 and 1000, life was not very good in Europe. The term "dark ages" is presently out of fashion as too judgemental (the period wasn't dark; it was just _different_ ), but if this label didn't already exist, it would seem an inspired metaphor.
这样的删改量很常见。我每写一篇最终定稿的散文,大概要写三到四个字的草稿。
(若有人因本文观点感到不悦,请记住:任何未出现在终稿的内容,显然是我选择不发表的——通常因为我自己也不同意那些观点。)
最近有朋友说,他喜欢我的散文,因为它们与我们在学校学的写作方式截然不同。还记得吗?主题句、开篇段、论证段、结论段。直到那时我才意识到,我们在学校被迫写的那些可怕东西,居然与我现在的写作有关联。但转念一想,它们确实也被称为"散文",不是吗?
其实不然。学校里要求写的东西不仅不是真正的散文,还是所有无用功中最无意义的一种。我担心它们不仅教会学生错误的写作观念,还会彻底扼杀他们对写作的兴趣。
What little original thought there was took place in lulls between constant wars and had something of the character of the thoughts of parents with a new baby. The most amusing thing written during this period, Liudprand of Cremona's Embassy to Constantinople, is, I suspect, mostly inadvertantly so. Around 1000 Europe began to catch its breath. And once they had the luxury of curiosity, one of the first things they discovered was what we call "the classics." Imagine if we were visited by aliens. If they could even get here they'd presumably know a few things we don't. Immediately Alien Studies would become the most dynamic field of scholarship: instead of painstakingly discovering things for ourselves, we could simply suck up everything they'd discovered. So it was in Europe in 1200. When classical texts began to circulate in Europe, they contained not just new answers, but new questions. (If anyone proved a theorem in christian Europe before 1200, for example, there is no record of it.) For a couple centuries, some of the most important work being done was intellectual archaelogy. Those were also the centuries during which schools were first established. And since reading ancient texts was the essence of what scholars did then, it became the basis of the curriculum. By 1700, someone who wanted to learn about physics didn't need to start by mastering Greek in order to read Aristotle. But schools change slower than scholarship: the study of ancient texts had such prestige that it remained the backbone of education until the late 19th century. By then it was merely a tradition. It did serve some purposes: reading a foreign language was difficult, and thus taught discipline, or at least, kept students busy; it introduced students to cultures quite different from their own; and its very uselessness made it function (like white gloves) as a social bulwark.
因此,我要讲述另一面:什么是真正的散文,以及如何写作。至少,我是如何写作的。学生们请注意:如果你真的按我描述的方式写作,可能会得低分。但了解真正的写作方式,至少能帮你理解被迫写作时的无力感。
真正的散文与学校作文最明显的区别在于:前者不只讨论英国文学。学校教授写作本是好事。但由于某些奇怪原因(实际上我稍后会解释这个具体原因),写作教学与文学研究被混为一谈。于是全国学生写的不是"小预算棒球队如何对抗洋基队",不是"色彩在时尚中的作用",也不是"何为优质甜点",而是"狄更斯作品中的象征主义"。
结果显而易见。没几个人真正关心狄更斯的象征手法。老师不关心,学生不关心,多数被迫写狄更斯博士论文的人也不关心。当然,狄更斯本人对色彩或棒球的散文会更感兴趣。
为何会变成这样?要回答这个问题,我们得回溯近千年。约公元500至1000年间,欧洲生活并不美好。"黑暗时代"一词如今因带有评判色彩而不再流行(那个时代并不黑暗,只是不同),但如果这个标签尚未存在,它倒像是个绝妙隐喻。仅有的原创思想诞生于连绵战火的间隙,带着初为父母者特有的思考特质。这时期最有趣的作品——克雷莫纳的柳德普兰德所著《君士坦丁堡使团记》,我猜其趣味性多半是意外产生的。
But it certainly wasn't true, and hadn't been true for centuries, that students were serving apprenticeships in the hottest area of scholarship. Classical scholarship had also changed. In the early era, philology actually mattered. The texts that filtered into Europe were all corrupted to some degree by the errors of translators and copyists. Scholars had to figure out what Aristotle said before they could figure out what he meant. But by the modern era such questions were answered as well as they were ever going to be. And so the study of ancient texts became less about ancientness and more about texts. The time was then ripe for the question: if the study of ancient texts is a valid field for scholarship, why not modern texts? The answer, of course, is that the raison d'etre of classical scholarship was a kind of intellectual archaelogy that does not need to be done in the case of contemporary authors. But for obvious reasons no one wanted to give that answer. The archaeological work being mostly done, it implied that the people studying the classics were, if not wasting their time, at least working on problems of minor importance. And so began the study of modern literature. There was some initial resistance, but it didn't last long. The limiting reagent in the growth of university departments is what parents will let undergraduates study. If parents will let their children major in x, the rest follows straightforwardly. There will be jobs teaching x, and professors to fill them. The professors will establish scholarly journals and publish one another's papers. Universities with x departments will subscribe to the journals. Graduate students who want jobs as professors of x will write dissertations about it.
公元1000年左右,欧洲开始喘息。当人们终于有余裕好奇时,最先发现的便是所谓的"古典著作"。想象外星人造访地球。既然能到达这里,他们肯定知晓我们不知道的事。"外星研究"会立即成为最热门的学术领域:我们不必辛苦探索,只需吸收他们的发现。1200年的欧洲正是如此。当古典文本开始流传,它们带来的不仅是新答案,更是新问题。(例如,若有人在1200年前的基督教欧洲证明过定理,也毫无记载。)
此后几个世纪,最重要的学术工作是思想考古。也正是在这些世纪里,学校首次建立。既然阅读古籍是学者的核心工作,它自然成为课程基础。
到1700年,想研究物理的人已无需先掌握希腊语来阅读亚里士多德。但学校变革慢于学术发展:古籍研究因声望卓著,直到19世纪末仍是教育支柱。此时它已沦为传统。它确实有些作用:阅读外语能培养纪律性(或至少让学生忙碌);让学生接触异域文化;其无用性本身(如同白手套)成为社会阶层的壁垒。但几个世纪以来,学生根本不是在热门领域当学徒。
古典学术也发生了变化。早期语文学确实重要。传入欧洲的文本都因翻译和抄写错误存在讹误。学者须先确定亚里士多德的原意,才能理解其思想。但到现代,这些问题已基本解决。于是古籍研究不再注重"古",而更关注"文本"。
It may take a good long while for the more prestigious universities to cave in and establish departments in cheesier xes, but at the other end of the scale there are so many universities competing to attract students that the mere establishment of a discipline requires little more than the desire to do it. High schools imitate universities. And so once university English departments were established in the late nineteenth century, the 'riting component of the 3 Rs was morphed into English. With the bizarre consequence that high school students now had to write about English literature-- to write, without even realizing it, imitations of whatever English professors had been publishing in their journals a few decades before. It's no wonder if this seems to the student a pointless exercise, because we're now three steps removed from real work: the students are imitating English professors, who are imitating classical scholars, who are merely the inheritors of a tradition growing out of what was, 700 years ago, fascinating and urgently needed work. Perhaps high schools should drop English and just teach writing. The valuable part of English classes is learning to write, and that could be taught better by itself. Students learn better when they're interested in what they're doing, and it's hard to imagine a topic less interesting than symbolism in Dickens. Most of the people who write about that sort of thing professionally are not really interested in it. (Though indeed, it's been a while since they were writing about symbolism; now they're writing about gender.) I have no illusions about how eagerly this suggestion will be adopted. Public schools probably couldn't stop teaching English even if they wanted to; they're probably required to by law. But here's a related suggestion that goes with the grain instead of against it: that universities establish a writing major.
此时自然产生一个问题:若古籍研究是正当学术领域,为何现代文本不行?答案当然是:古典学术存在的理由是一种思想考古,而当代作家无需这种考古。但出于显而易见的原因,没人愿意承认这点——这等于说研究古典的学者若非浪费时间,至少也是在研究次要问题。
于是现代文学研究开始了。初期虽有阻力,但未持续太久。大学科系发展的限制因素是家长允许子女修读什么专业。只要家长同意子女主修x专业,后续发展水到渠成:会出现x专业的教职,学者会填充这些职位,创办学术期刊,相互发表论文。设有x专业的大学会订阅这些期刊。想成为x专业教授的研究生会撰写相关论文。顶尖大学可能需要很长时间才会妥协设立较"low"的专业,但另一端有太多大学争夺生源,建立一个学科几乎只需意愿即可。
中学模仿大学。因此19世纪末大学英语系建立后,"3R"中的"写作"('Riting)就被英语取代。于是出现荒谬结果:中学生必须写关于英国文学的文章——在浑然不觉中模仿几十年前英语教授在期刊发表的文章。难怪学生觉得这是无用功,因为我们已离真正的工作隔了三层:学生在模仿英语教授,教授在模仿古典学者,而古典学者只是七百年前那场激动人心且亟需的工作传统的继承者。
或许中学应该取消英语课,只教写作。英语课最有价值的部分是学习写作,单独教授效果更好。学生对感兴趣的内容学得更好,而很难想象还有比"狄更斯的象征手法"更无聊的话题。多数专业研究这类话题的人其实并不感兴趣。(虽然他们早就不研究象征手法了——现在研究性别问题了。)
我对这个建议能被采纳不抱幻想。公立学校可能想取消英语课也做不到;法律可能要求开设。但有个顺势而为的相关建议:大学设立写作专业。现在主修英语的学生,多数会改修写作——这对他们更有益。
Many of the students who now major in English would major in writing if they could, and most would be better off. It will be argued that it is a good thing for students to be exposed to their literary heritage. Certainly. But is that more important than that they learn to write well? And are English classes even the place to do it? After all, the average public high school student gets zero exposure to his artistic heritage. No disaster results. The people who are interested in art learn about it for themselves, and those who aren't don't. I find that American adults are no better or worse informed about literature than art, despite the fact that they spent years studying literature in high school and no time at all studying art. Which presumably means that what they're taught in school is rounding error compared to what they pick up on their own. Indeed, English classes may even be harmful. In my case they were effectively aversion therapy. Want to make someone dislike a book? Force him to read it and write an essay about it. And make the topic so intellectually bogus that you could not, if asked, explain why one ought to write about it. I love to read more than anything, but by the end of high school I never read the books we were assigned. I was so disgusted with what we were doing that it became a point of honor with me to write nonsense at least as good at the other students' without having more than glanced over the book to learn the names of the characters and a few random events in it. I hoped this might be fixed in college, but I found the same problem there. It was not the teachers. It was English. We were supposed to read novels and write essays about them. About what, and why? That no one seemed to be able to explain.
有人会辩称让学生接触文学遗产是好事。确实。但这比学会写作更重要吗?英语课是合适场所吗?毕竟普通公立高中生对艺术遗产的接触为零,并未造成灾难。对艺术感兴趣的人会自学,不感兴趣的人不会。我发现美国成年人对文学与艺术的了解程度相当,尽管他们在中学花多年学习文学,却从未学过艺术。这意味着学校教授的内容与他们自学相比可忽略不计。
事实上,英语课可能有害。对我而言,它们简直是厌恶疗法。想让某人讨厌一本书?强迫他读并写相关文章。让题目假大空到你被问及时都无法解释为何要写它。我比谁都爱阅读,但到高中毕业时,我从不读指定书目。我对这种作业深恶痛绝,以至于以"不读书却能写出与其他同学相当的无聊文章"为荣——只需瞥一眼书,记住人物名字和几个随机事件。
我期待大学能改善,却发现同样问题。问题不在老师,而在"英语"本身。我们要读小说并写相关文章。写什么?为什么?似乎没人能解释。最终通过试错,我发现老师想让我们假装故事真实发生过,根据角色言行(线索越隐晦越好)分析其动机。涉及阶级动机会得高分(如今涉及性别与性取向想必也一样)。我学会了炮制这类文字拿A,但再也没选过英语课。
那些被如此糟蹋的书,就像中学时被蹂躏的书一样,在我心中永远留下污点。唯一安慰是英语课偏爱亨利·詹姆斯等浮夸乏味的作家——他们本就该被钉在耻辱柱上。IRS判定某项扣除是否合理的标准之一是:如果某事有趣,就不算工作。缺乏学术自信的领域依赖类似原则。阅读P.G.伍德豪斯、伊夫林·沃或雷蒙德·钱德勒显然太愉悦,不像正经工作——正如在英语进化到需要费力理解莎士比亚之前,读莎剧也不像正经工作。[sh] 因此优秀作家(三百年后仍再版的作家)较少被笨拙自封的导游败坏名声。
Eventually by trial and error I found that what the teacher wanted us to do was pretend that the story had really taken place, and to analyze based on what the characters said and did (the subtler clues, the better) what their motives must have been. One got extra credit for motives having to do with class, as I suspect one must now for those involving gender and sexuality. I learned how to churn out such stuff well enough to get an A, but I never took another English class. And the books we did these disgusting things to, like those we mishandled in high school, I find still have black marks against them in my mind. The one saving grace was that English courses tend to favor pompous, dull writers like Henry James, who deserve black marks against their names anyway. One of the principles the IRS uses in deciding whether to allow deductions is that, if something is fun, it isn't work. Fields that are intellectually unsure of themselves rely on a similar principle. Reading P.G. Wodehouse or Evelyn Waugh or Raymond Chandler is too obviously pleasing to seem like serious work, as reading Shakespeare would have been before English evolved enough to make it an effort to understand him. [sh] And so good writers (just you wait and see who's still in print in 300 years) are less likely to have readers turned against them by clumsy, self-appointed tour guides. The other big difference between a real essay and the things they make you write in school is that a real essay doesn't take a position and then defend it. That principle, like the idea that we ought to be writing about literature, turns out to be another intellectual hangover of long forgotten origins. It's often mistakenly believed that medieval universities were mostly seminaries. In fact they were more law schools. And at least in our tradition lawyers are advocates: they are trained to be able to take either side of an argument and make as good a case for it as they can.
真正散文与学校作文另一重大区别是:前者不会先立论后辩护。这个原则与"应写文学"的观念一样,都是被遗忘历史遗留的思想包袱。人们常误以为中世纪大学主要是神学院。其实它们更像法学院。至少在我们的传统中,律师是辩护者:他们被训练能为任何立场辩护。
无论这是否可取(对检察官可能不可取),它渗透了早期大学的氛围。讲座后最常见的讨论形式是辩论。这个观念至少名义上保存在现代论文答辩(thesis defense)中——"thesis"一词本身就体现这点。多数人将thesis与dissertation混用,但最初thesis是采取的立场,dissertation是辩护论证。
我并非抱怨这两个词的混用。在我看来,"thesis"原始意义消失得越快越好。对多数研究生而言,将工作重塑为单一论点如同方枘圆凿。至于辩论,显然弊大于利。在法律纠纷中为双方辩护可能是必要之恶,但绝非寻求真理的最佳方式——我想律师会首先承认这点。
然而这个原则深深植根于中学所教的"散文"结构中。主题句是预先选定的论点,论证段是交锋,结论——呃,结论是什么?我中学时一直不确定。若论点已充分表达,何必重述?理论上,真正好散文的结论只需"证毕"。但若了解这类"散文"的起源,就明白结论从何而来——它是给陪审团的结案陈词。
Whether or not this is a good idea (in the case of prosecutors, it probably isn't), it tended to pervade the atmosphere of early universities. After the lecture the most common form of discussion was the disputation. This idea is at least nominally preserved in our present-day thesis defense\-- indeed, in the very word thesis. Most people treat the words thesis and dissertation as interchangeable, but originally, at least, a thesis was a position one took and the dissertation was the argument by which one defended it. I'm not complaining that we blur these two words together. As far as I'm concerned, the sooner we lose the original sense of the word thesis, the better. For many, perhaps most, graduate students, it is stuffing a square peg into a round hole to try to recast one's work as a single thesis. And as for the disputation, that seems clearly a net lose. Arguing two sides of a case may be a necessary evil in a legal dispute, but it's not the best way to get at the truth, as I think lawyers would be the first to admit. And yet this principle is built into the very structure of the essays they teach you to write in high school. The topic sentence is your thesis, chosen in advance, the supporting paragraphs the blows you strike in the conflict, and the conclusion--- uh, what it the conclusion? I was never sure about that in high school. If your thesis was well expressed, what need was there to restate it? In theory it seemed that the conclusion of a really good essay ought not to need to say any more than QED. But when you understand the origins of this sort of "essay", you can see where the conclusion comes from. It's the concluding remarks to the jury. What other alternative is there? To answer that we have to reach back into history again, though this time not so far. To Michel de Montaigne, inventor of the essay. He was doing something quite different from what a lawyer does, and the difference is embodied in the name.
还有其他选择吗?要回答这个问题,我们需要再次回溯历史——这次不用太久。回到散文发明者米歇尔·德·蒙田。他做的事与律师截然不同,这种差异体现在名称中。"Essayer"是法语动词,意为"尝试"(与我们的"assay"同源),"essai"即尝试。散文是你为弄清某事而写的东西。
弄清什么?你还不知道。因此你不能从论点开始——因为你没有论点,可能永远不会有。散文不以陈述开头,而以问题开头。真正的散文中,你不会先立论后辩护。你看见半开的门,推门而入探索内部。
如果只为弄清事情,为何要写下来?坐着思考不行吗?这正是蒙田的伟大发现:表达有助于形成思想。"有助于"这个词太弱了。我散文中90%的内容是动笔时才想到的。这就是我写作的原因。
因此散文与学校作文还有一点不同:在学校,你理论上是在向他人解释;在最佳情况下(如果你条理清晰),你只是把想法写下来。而真正的散文是为自己而写。是大声思考。
Essayer is the French verb meaning "to try" (the cousin of our word assay), and an "essai" is an effort. An essay is something you write in order to figure something out. Figure out what? You don't know yet. And so you can't begin with a thesis, because you don't have one, and may never have one. An essay doesn't begin with a statement, but with a question. In a real essay, you don't take a position and defend it. You see a door that's ajar, and you open it and walk in to see what's inside. If all you want to do is figure things out, why do you need to write anything, though? Why not just sit and think? Well, there precisely is Montaigne's great discovery. Expressing ideas helps to form them. Indeed, helps is far too weak a word. 90% of what ends up in my essays was stuff I only thought of when I sat down to write them. That's why I write them. So there's another difference between essays and the things you have to write in school. In school you are, in theory, explaining yourself to someone else. In the best case---if you're really organized---you're just writing it _down._ In a real essay you're writing for yourself. You're thinking out loud. But not quite. Just as inviting people over forces you to clean up your apartment, writing something that you know other people will read forces you to think well. So it does matter to have an audience. The things I've written just for myself are no good. Indeed, they're bad in a particular way: they tend to peter out. When I run into difficulties, I notice that I tend to conclude with a few vague questions and then drift off to get a cup of tea. This seems a common problem. It's practically the standard ending in blog entries--- with the addition of a "heh" or an emoticon, prompted by the all too accurate sense that something is missing. And indeed, a lot of published essays peter out in this same way. Particularly the sort written by the staff writers of newsmagazines.
但也不尽然。正如邀请客人能迫使你打扫房间,写给别人看的东西能迫使你思考得更清晰。因此读者确实重要。我仅为自己所写的东西都不好。它们有种特别的糟糕:容易虎头蛇尾。遇到困难时,我常以几个模糊问题草草收场,然后溜去喝茶。
这似乎是个普遍问题。博客文章常这样结尾——加上"嘿"或表情符号,因为作者清楚感觉缺了点什么。
许多发表的散文也如此收尾。尤其是新闻杂志专职作者写的类型。外聘作者常提供"辩护立场"类社论,直奔预定结论。但专职作者觉得必须写得更"平衡",结果往往含糊不清。由于为大众杂志写作,他们从最具争议性问题入手,又因面向大众而畏缩退缩。支持还是反对同性婚姻?这群人这样说,那群人那样说。有一点是肯定的:这个问题很复杂。(但别怪我们。我们没下结论。)
仅有问题不够。散文必须提供答案。当然并非总能做到。有时你从 promising 的问题开始却一无所获。这类文章不发表。它们就像没有结论的实验。发表的东西应告诉读者他原先不知道的事。
但具体告诉什么不重要,只要有趣。我常被批评行文散漫。在"辩护立场"写作中这是缺陷——那种写作不关心真理。你已知目的地,只想直奔而去,冲破障碍,挥手掠过沼泽。但散文不是这样。散文应追寻真理。若不散漫反倒可疑。
Outside writers tend to supply editorials of the defend-a-position variety, which make a beeline toward a rousing (and foreordained) conclusion. But the staff writers feel obliged to write something more balanced, which in practice ends up meaning blurry. Since they're writing for a popular magazine, they start with the most radioactively controversial questions, from which (because they're writing for a popular magazine) they then proceed to recoil from in terror. Gay marriage, for or against? This group says one thing. That group says another. One thing is certain: the question is a complex one. (But don't get mad at us. We didn't draw any conclusions.) Questions aren't enough. An essay has to come up with answers. They don't always, of course. Sometimes you start with a promising question and get nowhere. But those you don't publish. Those are like experiments that get inconclusive results. Something you publish ought to tell the reader something he didn't already know. But _what_ you tell him doesn't matter, so long as it's interesting. I'm sometimes accused of meandering. In defend-a-position writing that would be a flaw. There you're not concerned with truth. You already know where you're going, and you want to go straight there, blustering through obstacles, and hand-waving your way across swampy ground. But that's not what you're trying to do in an essay. An essay is supposed to be a search for truth. It would be suspicious if it didn't meander. The Meander is a river in Asia Minor (aka Turkey). As you might expect, it winds all over the place. But does it do this out of frivolity? Quite the opposite. Like all rivers, it's rigorously following the laws of physics. The path it has discovered, winding as it is, represents the most economical route to the sea. The river's algorithm is simple. At each step, flow down. For the essayist this translates to: flow interesting. Of all the places to go next, choose whichever seems most interesting.
米安德河(Meander)在小亚细亚(今土耳其)。如你所料,它蜿蜒曲折。但这是轻浮之举吗?恰恰相反。与所有河流一样,它严格遵循物理定律。它发现的路径虽曲折,却是通往大海的最经济路线。
河流的算法很简单:每一步都向下流。对散文作者而言,这意味着:流向有趣之处。在所有可去的方向中,选择最有趣的那个。
这个比喻我稍加发挥。散文作者不能像河流那样毫无远见。实际上你(或我)的做法介于河流与罗马筑路者之间。我对方向有大体规划,据此选择下一个话题。本文关于写作,所以我偶尔会拉回这个方向,但它并非我预想中那类关于写作的散文。
注意"爬山算法"(这个算法的名称)也会带来麻烦。有时像河流一样,你会撞上绝壁。我的做法与河流相同:回溯。本文某处,我沿着某条思路写到无话可说。必须退回n段,另辟蹊径。为作说明,我将废弃分支留作脚注。
I'm pushing this metaphor a bit. An essayist can't have quite as little foresight as a river. In fact what you do (or what I do) is somewhere between a river and a roman road-builder. I have a general idea of the direction I want to go in, and I choose the next topic with that in mind. This essay is about writing, so I do occasionally yank it back in that direction, but it is not all the sort of essay I thought I was going to write about writing. Note too that hill-climbing (which is what this algorithm is called) can get you in trouble. Sometimes, just like a river, you run up against a blank wall. What I do then is just what the river does: backtrack. At one point in this essay I found that after following a certain thread I ran out of ideas. I had to go back n paragraphs and start over in another direction. For illustrative purposes I've left the abandoned branch as a footnote. Err on the side of the river. An essay is not a reference work. It's not something you read looking for a specific answer, and feel cheated if you don't find it. I'd much rather read an essay that went off in an unexpected but interesting direction than one that plodded dutifully along a prescribed course. So what's interesting? For me, interesting means surprise. Design, as Matz has said, should follow the principle of least surprise. A button that looks like it will make a machine stop should make it stop, not speed up. Essays should do the opposite. Essays should aim for maximum surprise. I was afraid of flying for a long time and could only travel vicariously. When friends came back from faraway places, it wasn't just out of politeness that I asked them about their trip. I really wanted to know. And I found that the best way to get information out of them was to ask what surprised them. How was the place different from what they expected? This is an extremely useful question.
宁可像河流般犯错。散文不是工具书。读者不会为寻找特定答案而读,找不到就觉受骗。我宁愿读一篇偏离预期但有趣的散文,也不要一篇按部就班的沉闷文章。
那么什么是"有趣"?对我而言,有趣意味着意外。正如Matz所说,设计应遵循最少意外原则。看似停止按钮就该停止机器,而非加速。散文应反其道而行。散文应追求最大意外。
我曾长期害怕飞行,只能神游。当朋友从远方归来,我问他们旅行见闻不仅是出于礼貌——我真心想知道。我发现获取信息的最佳方式是问:什么让你意外?那里与你想的有何不同?这是个极其有用的问题。即使对最不善于观察的人,也能挖出他们不自知的信息。
事实上你可以实时问这个问题。现在我去新地方时,会记下让我意外的事物。有时我甚至提前有意识地想象那个地方,以便与现实对比。
You can ask it of even the most unobservant people, and it will extract information they didn't even know they were recording. Indeed, you can ask it in real time. Now when I go somewhere new, I make a note of what surprises me about it. Sometimes I even make a conscious effort to visualize the place beforehand, so I'll have a detailed image to diff with reality. Surprises are facts you didn't already know. But they're more than that. They're facts that contradict things you thought you knew. And so they're the most valuable sort of fact you can get. They're like a food that's not merely healthy, but counteracts the unhealthy effects of things you've already eaten. How do you find surprises? Well, therein lies half the work of essay writing. (The other half is expressing yourself well.) You can at least use yourself as a proxy for the reader. You should only write about things you've thought about a lot. And anything you come across that surprises you, who've thought about the topic a lot, will probably surprise most readers. For example, in a recent essay I pointed out that because you can only judge computer programmers by working with them, no one knows in programming who the heroes should be. I certainly didn't realize this when I started writing the essay, and even now I find it kind of weird. That's what you're looking for. So if you want to write essays, you need two ingredients: you need a few topics that you think about a lot, and you need some ability to ferret out the unexpected. What should you think about? My guess is that it doesn't matter. Almost everything is interesting if you get deeply enough into it. The one possible exception are things like working in fast food, which have deliberately had all the variation sucked out of them. In retrospect, was there anything interesting about working in Baskin-Robbins? Well, it was interesting to notice how important color was to the customers.
意外是你原先不知道的事实。但不止如此。它们是与你认知相悖的事实。因此是最宝贵的事实。它们像不仅能保健,还能抵消已摄入有害物质的食物。
如何发现意外?这占了散文写作一半功夫。(另一半是好好表达。)你至少可以把自己当作读者的替身。只写你深思熟虑过的话题。任何让深思过的你感到意外的事物,多半也会让多数读者意外。
例如在最近一篇散文中,我指出:由于只能通过共事判断程序员水平,编程界无人知晓谁是英雄。动笔时我完全没意识到这点,即使现在也觉得有点怪。这就是你要寻找的东西。
因此想写散文需要两种原料:几个常思考的话题,以及发掘意外的能力。
Kids a certain age would point into the case and say that they wanted yellow. Did they want French Vanilla or Lemon? They would just look at you blankly. They wanted yellow. And then there was the mystery of why the perennial favorite Pralines n' Cream was so appealing. I'm inclined now to think it was the salt. And the mystery of why Passion Fruit tasted so disgusting. People would order it because of the name, and were always disappointed. It should have been called In-sink-erator Fruit. And there was the difference in the way fathers and mothers bought ice cream for their kids. Fathers tended to adopt the attitude of benevolent kings bestowing largesse, and mothers that of harried bureaucrats, giving in to pressure against their better judgement. So, yes, there does seem to be material, even in fast food. What about the other half, ferreting out the unexpected? That may require some natural ability. I've noticed for a long time that I'm pathologically observant. .... [That was as far as I'd gotten at the time.] Notes [sh] In Shakespeare's own time, serious writing meant theological discourses, not the bawdy plays acted over on the other side of the river among the bear gardens and whorehouses. The other extreme, the work that seems formidable from the moment it's created (indeed, is deliberately intended to be) is represented by Milton. Like the Aeneid, Paradise Lost is a rock imitating a butterfly that happened to get fossilized. Even Samuel Johnson seems to have balked at this, on the one hand paying Milton the compliment of an extensive biography, and on the other writing of Paradise Lost that "none who read it ever wished it longer.".
该思考什么?我想这不重要。几乎所有事物深入探究都很有趣。唯一例外可能是快餐店工作这种被刻意剔除所有变化的事物。回想起来,在Baskin-Robbins工作有什么趣事?注意到色彩对顾客的重要性很有趣。某年龄段的孩子会指着冰柜说要黄色。他们要的是法式香草还是柠檬味?只会茫然看着你——他们要黄色。还有常年热销的山核桃奶油口味为何诱人?我现在倾向认为是盐分。以及为何百香果味如此难吃?人们因名字点它,总是失望。该改名叫"厨余粉碎机果味"。还有父母给孩子买冰淇淋的差异:父亲像施恩的仁慈国王,母亲像被迫妥协的疲惫官僚。所以即使在快餐业也有素材可写。
另一半能力——发掘意外呢?这可能需要些天赋。我早就发现自己有种病态的观察力......
[当时我只写到这里。]
[sh] 莎士比亚时代,严肃写作指神学论述,而非河对岸熊园妓院旁上演的粗俗戏剧。
另一极端是弥尔顿的作品——从诞生起就令人生畏(实为刻意为之)。《失乐园》如同《埃涅阿斯纪》,是化作蝴蝶的岩石恰好被石化。连塞缪尔·约翰逊都对此却步:他一面为弥尔顿撰写详实传记致敬,一面评价《失乐园》"没有一个读者希望它更长"。
[](https://s.turbifycdn.com/aah/paulgraham/the-age-of-the-essay-11.gif) September 2004 Remember the essays you had to write in high school? Topic sentence, introductory paragraph, supporting paragraphs, conclusion. The conclusion being, say, that Ahab in _Moby Dick_ was a Christ-like figure. Oy. So I'm going to try to give the other side of the story: what an essay really is, and how you write one. Or at least, how I write one. Mods The most obvious difference between real essays and the things one has to write in school is that real essays are not exclusively about English literature. Certainly schools should teach students how to write. But due to a series of historical accidents the teaching of writing has gotten mixed together with the study of literature. And so all over the country students are writing not about how a baseball team with a small budget might compete with the Yankees, or the role of color in fashion, or what constitutes a good dessert, but about symbolism in Dickens. With the result that writing is made to seem boring and pointless. Who cares about symbolism in Dickens? Dickens himself would be more interested in an essay about color or baseball. How did things get this way? To answer that we have to go back almost a thousand years. Around 1100, Europe at last began to catch its breath after centuries of chaos, and once they had the luxury of curiosity they rediscovered what we call "the classics." The effect was rather as if we were visited by beings from another solar system. These earlier civilizations were so much more sophisticated that for the next several centuries the main work of European scholars, in almost every field, was to assimilate what they knew. During this period the study of ancient texts acquired great prestige. It seemed the essence of what scholars did.
[](https://s.turbifycdn.com/aah/paulgraham/the-age-of-the-essay-11.gif)
还记得高中时被迫写的那些作文吗?主题句、开篇段落、论证段落、结论段落。结论无外乎类似"《白鲸记》中的亚哈船长是基督式人物"这样的陈词滥调。
唉。现在我要讲述故事的另一面:什么是真正的随笔,以及如何创作。至少,是我的创作方式。
真正随笔与学校作文最显著的区别在于,前者绝不局限于英国文学。学校当然应该教授写作,但由于一系列历史偶然,写作教学与文学研究被混为一谈。于是全美学生写的不是"小预算棒球队如何对抗洋基队",不是"色彩在时尚中的角色",不是"甜点的精髓",而是"狄更斯作品中的象征主义"。
As European scholarship gained momentum it became less and less important; by 1350 someone who wanted to learn about science could find better teachers than Aristotle in his own era. [1] But schools change slower than scholarship. In the 19th century the study of ancient texts was still the backbone of the curriculum. The time was then ripe for the question: if the study of ancient texts is a valid field for scholarship, why not modern texts? The answer, of course, is that the original raison d'etre of classical scholarship was a kind of intellectual archaeology that does not need to be done in the case of contemporary authors. But for obvious reasons no one wanted to give that answer. The archaeological work being mostly done, it implied that those studying the classics were, if not wasting their time, at least working on problems of minor importance. And so began the study of modern literature. There was a good deal of resistance at first. The first courses in English literature seem to have been offered by the newer colleges, particularly American ones. Dartmouth, the University of Vermont, Amherst, and University College, London taught English literature in the 1820s. But Harvard didn't have a professor of English literature until 1876, and Oxford not till 1885. (Oxford had a chair of Chinese before it had one of English.) [2] What tipped the scales, at least in the US, seems to have been the idea that professors should do research as well as teach. This idea (along with the PhD, the department, and indeed the whole concept of the modern university) was imported from Germany in the late 19th century. Beginning at Johns Hopkins in 1876, the new model spread rapidly. Writing was one of the casualties. Colleges had long taught English composition.
结果写作变得乏味而无意义。谁在乎狄更斯的象征主义?狄更斯本人会对色彩或棒球的随笔更感兴趣。
这种局面如何形成?我们需要回溯近千年。约公元1100年,欧洲在历经数世纪动荡后终于喘息,当人们重获求知奢侈,便重新发现了"古典文明"。其冲击不亚于外星文明造访。这些古代文明如此精妙,以至于此后数百年间,欧洲学者几乎所有领域的工作就是消化这些知识。
这一时期,古籍研究获得崇高地位,几乎成为学术研究的代名词。随着欧洲学术发展,其重要性逐渐降低——到1350年,想学习科学的人已能找到比亚里士多德更优秀的导师[1]。但教育体系变革总是滞后。19世纪,古籍研究仍是课程核心。
此时一个疑问自然浮现:既然古籍研究是正当学术领域,为何现代文本不能是?真实答案当然是古典学术最初存在的理由——某种知识考古——对当代作家根本不适用。但出于显而易见的原因,没人愿意承认这点。这等于宣告古典研究者若非虚度光阴,至少也是在研究次要问题。
于是现代文学研究诞生了。最初遭遇巨大阻力,最早开设英国文学课程的似乎都是新兴学院,尤其是美国院校。达特茅斯、佛蒙特大学、阿默斯特学院和伦敦大学学院在1820年代开始教授英国文学。但哈佛直到1876年才有英国文学教授,牛津更迟至1885年(牛津设立中文教席比英文还早)[2]。
But how do you do research on composition? The professors who taught math could be required to do original math, the professors who taught history could be required to write scholarly articles about history, but what about the professors who taught rhetoric or composition? What should they do research on? The closest thing seemed to be English literature. [3] And so in the late 19th century the teaching of writing was inherited by English professors. This had two drawbacks: (a) an expert on literature need not himself be a good writer, any more than an art historian has to be a good painter, and (b) the subject of writing now tends to be literature, since that's what the professor is interested in. High schools imitate universities. The seeds of our miserable high school experiences were sown in 1892, when the National Education Association "formally recommended that literature and composition be unified in the high school course." [4] The 'riting component of the 3 Rs then morphed into English, with the bizarre consequence that high school students now had to write about English literature-- to write, without even realizing it, imitations of whatever English professors had been publishing in their journals a few decades before. It's no wonder if this seems to the student a pointless exercise, because we're now three steps removed from real work: the students are imitating English professors, who are imitating classical scholars, who are merely the inheritors of a tradition growing out of what was, 700 years ago, fascinating and urgently needed work. No Defense The other big difference between a real essay and the things they make you write in school is that a real essay doesn't take a position and then defend it. That principle, like the idea that we ought to be writing about literature, turns out to be another intellectual hangover of long forgotten origins.
在美国,扭转局面的关键因素是"教授应兼顾教学与研究"的理念。这种理念(连同博士学位、院系制度及现代大学概念)于19世纪末从德国引进。1876年始于约翰·霍普金斯大学的新模式迅速普及。
写作教学成为牺牲品。大学长期开设英语写作课,但如何对写作开展研究?数学教授可被要求做原创数学,历史教授可撰写学术论文,但修辞学或写作教授该研究什么?最接近的选择似乎是英国文学[3]。
于是19世纪末,写作教学被移交给了文学教授。这带来双重弊端:(a)文学专家未必擅长写作,就像艺术史家不必是优秀画家;(b)写作主题自然倾向文学,因为这是教授的兴趣所在。
中学模仿大学。我们悲惨的中学写作体验根源在1892年,当时全美教育协会"正式建议将文学与写作融合为中学课程"[4]。3R(读写算)中的"写"逐渐异化为"英语课",导致中学生被迫撰写关于英国文学的作文——他们甚至没意识到,自己不过在模仿几十年前文学教授期刊文章的拙劣仿作。
难怪学生觉得这种练习毫无意义——我们已与现实写作隔了三重屏障:学生模仿文学教授,教授模仿古典学者,而古典学者只是七百年前那场激动人心的知识考古的继承者。
It's often mistakenly believed that medieval universities were mostly seminaries. In fact they were more law schools. And at least in our tradition lawyers are advocates, trained to take either side of an argument and make as good a case for it as they can. Whether cause or effect, this spirit pervaded early universities. The study of rhetoric, the art of arguing persuasively, was a third of the undergraduate curriculum. [5] And after the lecture the most common form of discussion was the disputation. This is at least nominally preserved in our present-day thesis defense: most people treat the words thesis and dissertation as interchangeable, but originally, at least, a thesis was a position one took and the dissertation was the argument by which one defended it. Defending a position may be a necessary evil in a legal dispute, but it's not the best way to get at the truth, as I think lawyers would be the first to admit. It's not just that you miss subtleties this way. The real problem is that you can't change the question. And yet this principle is built into the very structure of the things they teach you to write in high school. The topic sentence is your thesis, chosen in advance, the supporting paragraphs the blows you strike in the conflict, and the conclusion-- uh, what is the conclusion? I was never sure about that in high school. It seemed as if we were just supposed to restate what we said in the first paragraph, but in different enough words that no one could tell. Why bother? But when you understand the origins of this sort of "essay," you can see where the conclusion comes from. It's the concluding remarks to the jury. Good writing should be convincing, certainly, but it should be convincing because you got the right answers, not because you did a good job of arguing. When I give a draft of an essay to friends, there are two things I want to know: which parts bore them, and which seem unconvincing.
真正随笔与学校作文另一关键区别在于:前者不会先确立观点再为之辩护。这个原则与"必须写文学"一样,都是被遗忘历史的精神遗存。
人们常误以为中世纪大学主要是神学院,实则是法学院。至少在我们的传统中,律师是辩论家,训练有素地为任何立场辩护。无论因果,这种精神弥漫早期大学。说服性论证艺术——修辞学,占本科课程三分之一[5]。课后最常见讨论形式是辩论,这种形式至少名义上保留在今天的论文答辩中:多数人将thesis与dissertation混用,但最初thesis指所持立场,dissertation是为之辩护的论证。
在法律争议中,立场辩护或许是必要之恶,但绝非寻求真理的最佳方式——我想律师会率先承认这点。问题不仅在于会忽略微妙之处,更在于无法改变议题。
然而这个原则却深植于中学作文结构:主题句是预先选定的论点,论证段落是交锋中的攻势,结论则是——呃,结论是什么?我中学时始终没弄明白。似乎只需用不同词汇重述首段内容而不被识破即可。何必多此一举?但若了解这类"作文"的渊源,就会明白结论从何而来——那是给陪审团的结案陈词。
优秀写作当然要有说服力,但应因正确结论而令人信服,而非依靠诡辩。当我把随笔草稿给朋友看时,只关心两点:哪些部分无聊,哪些部分牵强。无聊处通常删减即可,但不会用更巧妙的论证修补牵强处,而是重新探讨问题。
The boring bits can usually be fixed by cutting. But I don't try to fix the unconvincing bits by arguing more cleverly. I need to talk the matter over. At the very least I must have explained something badly. In that case, in the course of the conversation I'll be forced to come up a with a clearer explanation, which I can just incorporate in the essay. More often than not I have to change what I was saying as well. But the aim is never to be convincing per se. As the reader gets smarter, convincing and true become identical, so if I can convince smart readers I must be near the truth. The sort of writing that attempts to persuade may be a valid (or at least inevitable) form, but it's historically inaccurate to call it an essay. An essay is something else. Trying To understand what a real essay is, we have to reach back into history again, though this time not so far. To Michel de Montaigne, who in 1580 published a book of what he called "essais." He was doing something quite different from what lawyers do, and the difference is embodied in the name. _Essayer_ is the French verb meaning "to try" and an _essai_ is an attempt. An essay is something you write to try to figure something out. Figure out what? You don't know yet. And so you can't begin with a thesis, because you don't have one, and may never have one. An essay doesn't begin with a statement, but with a question. In a real essay, you don't take a position and defend it. You notice a door that's ajar, and you open it and walk in to see what's inside. If all you want to do is figure things out, why do you need to write anything, though? Why not just sit and think? Well, there precisely is Montaigne's great discovery. Expressing ideas helps to form them. Indeed, helps is far too weak a word. Most of what ends up in my essays I only thought of when I sat down to write them. That's why I write them.
至少说明我解释得糟糕。讨论过程中,我会被迫想出更清晰的解释,直接纳入文章。更多时候需要修改原有观点。但目标从来不是说服本身。读者越聪明,"可信"与"真实"就越重合,若能说服聪明读者,说明已接近真理。
试图说服的写作或许是合理(或不可避免)的形式,但称之为"随笔"实为历史误读。随笔是另一回事。
要理解真正随笔,我们需要再次回望历史(这次不必太久远)——看向1580年出版《随笔集》的米歇尔·德·蒙田。他实践的与律师截然不同,这种差异体现在名称中:Essayer是法语"尝试"动词,essai即尝试。随笔是你为厘清问题而写的探索。
探索什么?你尚不知道。因此不能从论点开始——因为你没有论点,或许永远不会有。随笔不以论断开篇,而以疑问起笔。真正随笔中,你不捍卫立场,而是注意到微启的门扉,推门而入探查内里。
若只为思考,何必写作?静坐冥想不行吗?这正是蒙田的伟大发现:表达能塑造思想。"帮助"这个词都太弱——我最终写进随笔的多数内容,都是动笔时才想到的。这正是我写作的原因。
In the things you write in school you are, in theory, merely explaining yourself to the reader. In a real essay you're writing for yourself. You're thinking out loud. But not quite. Just as inviting people over forces you to clean up your apartment, writing something that other people will read forces you to think well. So it does matter to have an audience. The things I've written just for myself are no good. They tend to peter out. When I run into difficulties, I find I conclude with a few vague questions and then drift off to get a cup of tea. Many published essays peter out in the same way. Particularly the sort written by the staff writers of newsmagazines. Outside writers tend to supply editorials of the defend-a-position variety, which make a beeline toward a rousing (and foreordained) conclusion. But the staff writers feel obliged to write something "balanced." Since they're writing for a popular magazine, they start with the most radioactively controversial questions, from which-- because they're writing for a popular magazine-- they then proceed to recoil in terror. Abortion, for or against? This group says one thing. That group says another. One thing is certain: the question is a complex one. (But don't get mad at us. We didn't draw any conclusions.) The River Questions aren't enough. An essay has to come up with answers. They don't always, of course. Sometimes you start with a promising question and get nowhere. But those you don't publish. Those are like experiments that get inconclusive results. An essay you publish ought to tell the reader something he didn't already know. But _what_ you tell him doesn't matter, so long as it's interesting. I'm sometimes accused of meandering. In defend-a-position writing that would be a flaw. There you're not concerned with truth. You already know where you're going, and you want to go straight there, blustering through obstacles, and hand-waving your way across swampy ground.
学校写作理论上只是向读者解释,真正随笔却是为自己而写。是思考的具象化。
但又不尽然。如同邀请客人能迫使你打扫房间,为他人写作能迫使你完善思考。因此读者确实重要。那些只为自己写的东西往往虎头蛇尾——遇到困难时,我常以几个模糊问题草草收场,然后飘去泡茶。
许多公开发表的随笔同样如此,尤其是新闻杂志专职撰稿人的作品。外聘作家常提供辩护型社论,直奔预定结论;而专职作家觉得必须"平衡"。由于面向大众刊物,他们从最具争议的话题切入——又因面向大众刊物——随即惊恐退缩。"支持或反对堕胎?甲团体说X,乙团体说Y。唯一确定的是:问题很复杂。(但别怪我们,我们不下结论)"
仅有疑问不够。随笔应当给出答案——当然并非总能做到。有时你带着 promising question 启程却一无所获。这类文章不会发表,就像没有结论的实验。发表的随笔应告诉读者他未知之事。
但具体内容无关紧要,只要有趣即可。我常被批评行文散漫。在辩护型写作中这确是缺陷——那种写作不关心真理,你已知目的地,只想一路强攻沼泽。但随笔不同,它本应是真理的追寻。若不见迂回反倒可疑。
But that's not what you're trying to do in an essay. An essay is supposed to be a search for truth. It would be suspicious if it didn't meander. The Meander (aka Menderes) is a river in Turkey. As you might expect, it winds all over the place. But it doesn't do this out of frivolity. The path it has discovered is the most economical route to the sea. [6] The river's algorithm is simple. At each step, flow down. For the essayist this translates to: flow interesting. Of all the places to go next, choose the most interesting. One can't have quite as little foresight as a river. I always know generally what I want to write about. But not the specific conclusions I want to reach; from paragraph to paragraph I let the ideas take their course. This doesn't always work. Sometimes, like a river, one runs up against a wall. Then I do the same thing the river does: backtrack. At one point in this essay I found that after following a certain thread I ran out of ideas. I had to go back seven paragraphs and start over in another direction. Fundamentally an essay is a train of thought-- but a cleaned-up train of thought, as dialogue is cleaned-up conversation. Real thought, like real conversation, is full of false starts. It would be exhausting to read. You need to cut and fill to emphasize the central thread, like an illustrator inking over a pencil drawing. But don't change so much that you lose the spontaneity of the original. Err on the side of the river. An essay is not a reference work. It's not something you read looking for a specific answer, and feel cheated if you don't find it. I'd much rather read an essay that went off in an unexpected but interesting direction than one that plodded dutifully along a prescribed course. Surprise So what's interesting? For me, interesting means surprise. Interfaces, as Geoffrey James has said, should follow the principle of least astonishment.
米安德河(又名门德雷斯河)是土耳其的河流。如名所示,它百转千回。但这非因轻浮——它找到的是入海最经济的路径[6]。
河流的算法很简单:每一步都向下流淌。对随笔作者而言,这转化为:向有趣处流淌。在所有可能的方向中,选择最有趣的。人虽不能像河流般毫无预见,我总知道大致方向,但从不会预设具体结论——段与段间,我任由思想流淌。
这并非总奏效。有时如河流撞上墙壁,我的对策也如河流:回溯。本文某处,我沿某条思路走到死胡同,不得不退回七段另辟蹊径。
根本上,随笔是思维的轨迹——但如对话是加工的交谈,它是加工的思绪。真实思考如真实交谈,充满试错,直接呈现将令人疲惫。你需要删减填充以突出主线,如同画家用墨水描摹铅笔草图。但切勿过度修饰而丧失原始 spontaneity。
宁可像河流般自由。随笔不是工具书,读者不该带着特定问题来索求答案。相比四平八稳的规训之作,我宁愿读意外频出却妙趣横生的文章。
A button that looks like it will make a machine stop should make it stop, not speed up. Essays should do the opposite. Essays should aim for maximum surprise. I was afraid of flying for a long time and could only travel vicariously. When friends came back from faraway places, it wasn't just out of politeness that I asked what they saw. I really wanted to know. And I found the best way to get information out of them was to ask what surprised them. How was the place different from what they expected? This is an extremely useful question. You can ask it of the most unobservant people, and it will extract information they didn't even know they were recording. Surprises are things that you not only didn't know, but that contradict things you thought you knew. And so they're the most valuable sort of fact you can get. They're like a food that's not merely healthy, but counteracts the unhealthy effects of things you've already eaten. How do you find surprises? Well, therein lies half the work of essay writing. (The other half is expressing yourself well.) The trick is to use yourself as a proxy for the reader. You should only write about things you've thought about a lot. And anything you come across that surprises you, who've thought about the topic a lot, will probably surprise most readers. For example, in a recent essay I pointed out that because you can only judge computer programmers by working with them, no one knows who the best programmers are overall. I didn't realize this when I began that essay, and even now I find it kind of weird. That's what you're looking for. So if you want to write essays, you need two ingredients: a few topics you've thought about a lot, and some ability to ferret out the unexpected. What should you think about? My guess is that it doesn't matter-- that anything can be interesting if you get deeply enough into it.
那么何为有趣?对我而言,有趣意味着意外。正如杰弗里·詹姆斯所说,界面应遵循"最小意外原则"——看似停止的按钮就该停止而非加速。随笔正相反,应追求最大意外。
我曾长期恐飞,只能神游。当朋友远行归来,我问见闻绝非客套——我真心想知道。而最佳提问方式是:什么让你意外?与预期有何不同?这问题极有效,即使最不 observant 的人,也能榨出他们不自知的记忆。
意外不仅是未知,更是对已知的颠覆。因此是最珍贵的事实,像不仅能养生更能中和垃圾食品毒性的食材。
如何发现意外?这本身就是随笔写作的半壁江山(另一半是良好表达)。秘诀是以己度人:只写你深思过的话题。连深思者都感到意外之处,多半也能让读者意外。
例如最近某篇随笔中,我指出由于只能通过共事评判程序员,无人知晓谁是世界最佳。动笔时我并未意识到这点,即便现在仍觉诡异——这正是你要寻找的。
One possible exception might be things that have deliberately had all the variation sucked out of them, like working in fast food. In retrospect, was there anything interesting about working at Baskin-Robbins? Well, it was interesting how important color was to the customers. Kids a certain age would point into the case and say that they wanted yellow. Did they want French Vanilla or Lemon? They would just look at you blankly. They wanted yellow. And then there was the mystery of why the perennial favorite Pralines 'n' Cream was so appealing. (I think now it was the salt.) And the difference in the way fathers and mothers bought ice cream for their kids: the fathers like benevolent kings bestowing largesse, the mothers harried, giving in to pressure. So, yes, there does seem to be some material even in fast food. I didn't notice those things at the time, though. At sixteen I was about as observant as a lump of rock. I can see more now in the fragments of memory I preserve of that age than I could see at the time from having it all happening live, right in front of me. Observation So the ability to ferret out the unexpected must not merely be an inborn one. It must be something you can learn. How do you learn it? To some extent it's like learning history. When you first read history, it's just a whirl of names and dates. Nothing seems to stick. But the more you learn, the more hooks you have for new facts to stick onto-- which means you accumulate knowledge at an exponential rate. Once you remember that Normans conquered England in 1066, it will catch your attention when you hear that other Normans conquered southern Italy at about the same time. Which will make you wonder about Normandy, and take note when a third book mentions that Normans were not, like most of what is now called France, tribes that flowed in as the Roman empire collapsed, but Vikings (norman = north man) who arrived four centuries later in 911.
因此想写随笔需要两种原料:若干深思过的话题,以及发掘意外的能力。
该思考什么?我认为题材不限——任何事物深入探究都会有趣。可能的例外是被刻意剔除所有变数的事物,比如快餐店工作。回想起来,Baskin-Robbins打工有何趣味?颜色对顾客的重要性很有趣:某年龄段孩子会指着冰柜说要"黄色"。要法式香草还是柠檬?他们茫然——只要黄色。还有常年畅销山核桃糖霜的魔力(我现在想是盐分作用)。父母买冰淇淋的差异也耐人寻味:父亲像施恩的仁慈君王,母亲则像妥协于压力的疲惫者。瞧,快餐店也有素材。
不过当时我并未留意这些。十六岁时我的观察力如同顽石。如今从记忆碎片中看到的,远比当年亲历时更多。
因此发掘意外的能力不应只是天赋,更应是可习得的技能。如何学习?
某种程度上像学历史。初读历史时,只是名字与年代的漩涡,难以记忆。但知识越多,新事实的挂钩就越多——这意味着知识呈指数积累。一旦记住诺曼人1066年征服英格兰,就会留意到同时期另批诺曼人征服南意大利,进而好奇诺曼底渊源,当第三本书提到诺曼人非罗马崩溃时涌入的部落(如现代法国多数居民),而是四世纪后(911年)到来的维京人(Norman即北方人),你会格外注意。这又让你更易记住都柏林也是维京人840年代建立的。以此类推,不断平方。
Which makes it easier to remember that Dublin was also established by Vikings in the 840s. Etc, etc squared. Collecting surprises is a similar process. The more anomalies you've seen, the more easily you'll notice new ones. Which means, oddly enough, that as you grow older, life should become more and more surprising. When I was a kid, I used to think adults had it all figured out. I had it backwards. Kids are the ones who have it all figured out. They're just mistaken. When it comes to surprises, the rich get richer. But (as with wealth) there may be habits of mind that will help the process along. It's good to have a habit of asking questions, especially questions beginning with Why. But not in the random way that three year olds ask why. There are an infinite number of questions. How do you find the fruitful ones? I find it especially useful to ask why about things that seem wrong. For example, why should there be a connection between humor and misfortune? Why do we find it funny when a character, even one we like, slips on a banana peel? There's a whole essay's worth of surprises there for sure. If you want to notice things that seem wrong, you'll find a degree of skepticism helpful. I take it as an axiom that we're only achieving 1% of what we could. This helps counteract the rule that gets beaten into our heads as children: that things are the way they are because that is how things have to be. For example, everyone I've talked to while writing this essay felt the same about English classes-- that the whole process seemed pointless. But none of us had the balls at the time to hypothesize that it was, in fact, all a mistake. We all thought there was just something we weren't getting. I have a hunch you want to pay attention not just to things that seem wrong, but things that seem wrong in a humorous way. I'm always pleased when I see someone laugh as they read a draft of an essay. But why should I be? I'm aiming for good ideas.
收集意外是类似过程。异常见闻越多,新异常越易被发现。这意味着(吊诡的是)随着年龄增长,生活应越来越令人惊讶。儿时我总以为大人洞悉一切,事实正相反——孩子才觉得一切尽在掌握,只是错得离谱。
在意外领域,富者愈富。但(如财富般)有些思维习惯能加速这个过程。保持提问习惯很有益,尤其是"为什么"开头的问题——但别像三岁孩子般随机发问。问题无穷无尽,如何找到 fruitful 的那些?
我发现对看似异常之事追问"为什么"特别有效。例如:为何幽默与不幸相关?为何角色(即使讨喜的)踩香蕉皮滑倒会引发笑声?这里肯定藏着一整篇随笔的意外素材。
若要觉察异常,适度怀疑精神很有助益。我有个信条:我们只实现了1%的潜力。这能抵消儿时被灌输的教条:事物现状即其必然形态。例如本文访谈的所有人都对英语课有同感——整个过程毫无意义。但当时没人敢说这根本是个错误,我们都以为只是自己没领悟奥秘。
我有种直觉:你不仅要关注看似异常的事物,更要关注那些滑稽的异常。当读者笑着放下我的随笔草稿时,我总很愉悦。但为何?我的目标是好想法,为何好想法要好笑?联系或许在于意外——意外让人发笑,而意外正是我想传递的。
Why should good ideas be funny? The connection may be surprise. Surprises make us laugh, and surprises are what one wants to deliver. I write down things that surprise me in notebooks. I never actually get around to reading them and using what I've written, but I do tend to reproduce the same thoughts later. So the main value of notebooks may be what writing things down leaves in your head. People trying to be cool will find themselves at a disadvantage when collecting surprises. To be surprised is to be mistaken. And the essence of cool, as any fourteen year old could tell you, is _nil admirari._ When you're mistaken, don't dwell on it; just act like nothing's wrong and maybe no one will notice. One of the keys to coolness is to avoid situations where inexperience may make you look foolish. If you want to find surprises you should do the opposite. Study lots of different things, because some of the most interesting surprises are unexpected connections between different fields. For example, jam, bacon, pickles, and cheese, which are among the most pleasing of foods, were all originally intended as methods of preservation. And so were books and paintings. Whatever you study, include history-- but social and economic history, not political history. History seems to me so important that it's misleading to treat it as a mere field of study. Another way to describe it is _all the data we have so far._ Among other things, studying history gives one confidence that there are good ideas waiting to be discovered right under our noses. Swords evolved during the Bronze Age out of daggers, which (like their flint predecessors) had a hilt separate from the blade. Because swords are longer the hilts kept breaking off.
我把意外记录在笔记本,虽从不重读利用,但同样想法常会再现。因此笔记的主要价值或许是书写过程对思维的塑造。
想扮酷的人在收集意外时会处于劣势。感到意外意味着犯错,而酷的精髓(任何十四岁孩子都会告诉你)是"不动声色"。犯错时别纠结,假装无事发生,或许无人察觉。
扮酷的关键是避免暴露无知的场合。若想发现意外就该反其道而行:广泛涉猎,因为最有趣的意外常是跨领域的隐秘联结。如果果酱、培根、泡菜和奶酪(顶级美味)最初都是为保存而发明。书籍和绘画也是。
无论研究什么,都要包含历史——但选社会经济史而非政治史。历史在我看来重要到不能仅视为学科,它是"我们迄今拥有的全部数据"。
除其他好处外,研读历史能给人信心:好想法就在我们眼皮底下。青铜时代剑由匕首演化而来,其柄与刃分离(如燧石匕首)。因剑身较长,剑柄常断裂。但历经五百年才有人想到整体铸造。
But it took five hundred years before someone thought of casting hilt and blade as one piece. Disobedience Above all, make a habit of paying attention to things you're not supposed to, either because they're "inappropriate," or not important, or not what you're supposed to be working on. If you're curious about something, trust your instincts. Follow the threads that attract your attention. If there's something you're really interested in, you'll find they have an uncanny way of leading back to it anyway, just as the conversation of people who are especially proud of something always tends to lead back to it. For example, I've always been fascinated by comb-overs, especially the extreme sort that make a man look as if he's wearing a beret made of his own hair. Surely this is a lowly sort of thing to be interested in-- the sort of superficial quizzing best left to teenage girls. And yet there is something underneath. The key question, I realized, is how does the comber-over not see how odd he looks? And the answer is that he got to look that way _incrementally._ What began as combing his hair a little carefully over a thin patch has gradually, over 20 years, grown into a monstrosity. Gradualness is very powerful. And that power can be used for constructive purposes too: just as you can trick yourself into looking like a freak, you can trick yourself into creating something so grand that you would never have dared to _plan_ such a thing. Indeed, this is just how most good software gets created. You start by writing a stripped-down kernel (how hard can it be?) and gradually it grows into a complete operating system. Hence the next leap: could you do the same thing in painting, or in a novel? See what you can extract from a frivolous question? If there's one piece of advice I would give about writing essays, it would be: don't do as you're told. Don't believe what you're supposed to.
最重要的是,养成关注"不该关注"之物的习惯——或因它们"不合时宜",或因看似不重要,或因与手头工作无关。若对某事好奇,相信直觉,追随吸引你的线索。若真有挚爱领域,你会发现这些线索总有灵性地回归其中,就像特别骄傲之人总能把话题绕回自己的成就。
例如我一直痴迷于"地方支援中央"发型,尤其是那种让男人像顶着自己头发做的贝雷帽的极端案例。这兴趣似乎很低级——该留给青春期少女的肤浅癖好。但背后确有深意。关键问题是:梳这种发型的人为何看不出自己多怪异?答案是他是逐渐变成这样的。最初只是小心遮盖稀疏处,经过20年渐变,终成怪物。渐变力量惊人。这种力量也可用于建设性目的:正如你能把自己骗成怪胎,也能骗自己创造出不敢设想的大作。事实上,多数优秀软件正是这样诞生的:先写个简化内核(能有多难?),逐渐成长完整操作系统。由此延伸:绘画或小说能否如法炮制?
看,一个轻浮问题能榨出多少洞见?若要我给一条随笔写作建议,那就是:别听话。别轻信教条。别写读者预期的文章——从预期中学不到东西。别用学校教的方式写作。
最重要的不服从是坚持写随笔。幸运的是,这种不服从正呈现蔓延之势。过去只有少数官方认可的作家能写随笔。杂志很少刊登,且评判标准更看重作者而非内容;杂志可能刊登无名作家的出色小说,但若刊登关于X的随笔,作者必须年过四十且头衔含X。这造成困境:正因是圈内人,许多话反而不能说。
互联网正在改变这点。任何人都能在网上发表随笔,评判标准(本应如此)是内容而非作者。"你有什么资格写X?"——你的资格就是你所写的。
Don't write the essay readers expect; one learns nothing from what one expects. And don't write the way they taught you to in school. The most important sort of disobedience is to write essays at all. Fortunately, this sort of disobedience shows signs of becoming rampant. It used to be that only a tiny number of officially approved writers were allowed to write essays. Magazines published few of them, and judged them less by what they said than who wrote them; a magazine might publish a story by an unknown writer if it was good enough, but if they published an essay on x it had to be by someone who was at least forty and whose job title had x in it. Which is a problem, because there are a lot of things insiders can't say precisely because they're insiders. The Internet is changing that. Anyone can publish an essay on the Web, and it gets judged, as any writing should, by what it says, not who wrote it. Who are you to write about x? You are whatever you wrote. Popular magazines made the period between the spread of literacy and the arrival of TV the golden age of the short story. The Web may well make this the golden age of the essay. And that's certainly not something I realized when I started writing this. Notes [1] I'm thinking of Oresme (c. 1323-82). But it's hard to pick a date, because there was a sudden drop-off in scholarship just as Europeans finished assimilating classical science. The cause may have been the plague of 1347; the trend in scientific progress matches the population curve. [2] Parker, William R. "Where Do College English Departments Come From?" _College English_ 28 (1966-67), pp. 339-351. Reprinted in Gray, Donald J. (ed). _The Department of English at Indiana University Bloomington 1868-1970._ Indiana University Publications. Daniels, Robert V. _The University of Vermont: The First Two Hundred Years._ University of Vermont, 1991.
大众杂志使读写能力普及后、电视普及前成为短篇小说的黄金时代。网络很可能使当下成为随笔的黄金时代。这当然不是我动笔时就意识到的。
[1] 我想到奥雷姆(约1323-82年)。但很难确定具体时间点,因为欧洲刚消化完古典科学,学术水平就突然下滑。原因可能是1347年的瘟疫——科学进展曲线与人口曲线吻合。
[2] 威廉·R·帕克《大学英语系从何而来?》,载于《大学英语》第28卷(1966-67年),第339-351页。重印于唐纳德·J·格雷编《印第安纳大学布鲁明顿分校英语系1868-1970》。
罗伯特·V·丹尼尔斯《佛蒙特大学:前两百年》。
弗里德里希·M·穆勒致《Pall Mall公报》书信(1886/87年),重印于艾伦·培根编《英语研究的十九世纪历史》。
Mueller, Friedrich M. Letter to the _Pall Mall Gazette._ 1886/87. Reprinted in Bacon, Alan (ed). _The Nineteenth-Century History of English Studies._ Ashgate, 1998. [3] I'm compressing the story a bit. At first literature took a back seat to philology, which (a) seemed more serious and (b) was popular in Germany, where many of the leading scholars of that generation had been trained. In some cases the writing teachers were transformed _in situ_ into English professors. Francis James Child, who had been Boylston Professor of Rhetoric at Harvard since 1851, became in 1876 the university's first professor of English. [4] Parker, _op. cit._ , p. 25. [5] The undergraduate curriculum or _trivium_ (whence "trivial") consisted of Latin grammar, rhetoric, and logic. Candidates for masters' degrees went on to study the _quadrivium_ of arithmetic, geometry, music, and astronomy. Together these were the seven liberal arts. The study of rhetoric was inherited directly from Rome, where it was considered the most important subject. It would not be far from the truth to say that education in the classical world meant training landowners' sons to speak well enough to defend their interests in political and legal disputes. [6] Trevor Blackwell points out that this isn't strictly true, because the outside edges of curves erode faster. Thanks to Ken Anderson, Trevor Blackwell, Sarah Harlin, Jessica Livingston, Jackie McDonough, and Robert Morris for reading drafts of this.
| Russian Translation | | | Spanish Translation | Japanese Translation | | | Hungarian Translation | Traditional Chinese Translation.
[3] 我略压缩了过程。最初文学让位于语文学,因为(a)显得更严肃,(b)在德国盛行——那代顶尖学者多受训于德国。
有些写作教师就地转为英语教授。1851年起任哈佛博伊尔斯顿修辞学教授的弗朗西斯·詹姆斯·柴尔德,1876年成为该校首位英语教授。
[4] 帕克,前引书,第25页。
[5] 本科课程(trivium,即"琐碎"词源)包括拉丁语法、修辞学和逻辑学。硕士候选人继续学习算术、几何、音乐和天文四艺(quadrivium),合称七艺。
修辞学直接承袭自罗马,被视为最重要学科。可以说古典世界的教育本质是训练地主子弟在政治法律争议中有效辩护。
If you liked this, you may also like _Hackers & Painters_.
[](https://s.turbifycdn.com/aah/paulgraham/what-the-bubble-got-right-11.gif) September 2004 _(This essay is derived from an invited talk at ICFP 2004.)_ I had a front row seat for the Internet Bubble, because I worked at Yahoo during 1998 and 1999. One day, when the stock was trading around $200, I sat down and calculated what I thought the price should be. The answer I got was $12. I went to the next cubicle and told my friend Trevor. "Twelve!" he said. He tried to sound indignant, but he didn't quite manage it. He knew as well as I did that our valuation was crazy. Yahoo was a special case. It was not just our price to earnings ratio that was bogus. Half our earnings were too. Not in the Enron way, of course. The finance guys seemed scrupulous about reporting earnings. What made our earnings bogus was that Yahoo was, in effect, the center of a Ponzi scheme. Investors looked at Yahoo's earnings and said to themselves, here is proof that Internet companies can make money. So they invested in new startups that promised to be the next Yahoo. And as soon as these startups got the money, what did they do with it? Buy millions of dollars worth of advertising on Yahoo to promote their brand. Result: a capital investment in a startup this quarter shows up as Yahoo earnings next quarter—stimulating another round of investments in startups. As in a Ponzi scheme, what seemed to be the returns of this system were simply the latest round of investments in it. What made it not a Ponzi scheme was that it was unintentional. At least, I think it was. The venture capital business is pretty incestuous, and there were presumably people in a position, if not to create this situation, to realize what was happening and to milk it. A year later the game was up. Starting in January 2000, Yahoo's stock price began to crash, ultimately losing 95% of its value.
(此为Paul Graham《泡沫中的正确之处》第1部分,共2部分)
2004年9月 (本文改编自2004年ICFP大会特邀演讲)
我在互联网泡沫期间拥有绝佳观察席位——1998至1999年间,我正任职于雅虎。某天当股价徘徊在200美元时,我计算了理论合理估值,结果是12美元。我告诉邻座同事Trevor这个数字,"十二!"他试图表现愤怒,但演技拙劣。我们都心知肚明:这个估值荒谬至极。
雅虎是个特例。不仅市盈率虚高,连半数盈利都是幻象。当然不像安然那样财务造假——财务人员似乎严格遵循会计准则。问题在于雅虎实质上是庞氏骗局的中心:投资者看到雅虎盈利,便认定互联网公司能赚钱,于是注资新创企业指望再造雅虎。而这些初创公司拿到钱后做了什么?斥资数百万美元在雅虎投放品牌广告。结果:本季度的风险投资,下季度就转化为雅虎的营收——进而刺激新一轮创业投资。
如同庞氏骗局,系统看似产生的回报不过是新注入的资金。区别在于这并非刻意为之——至少我认为如此。当然风投圈关系错综复杂,或许有人即使未主动设局,也深谙此道并从中渔利。
Notice, though, that even with all the fat trimmed off its market cap, Yahoo was still worth a lot. Even at the morning-after valuations of March and April 2001, the people at Yahoo had managed to create a company worth about $8 billion in just six years. The fact is, despite all the nonsense we heard during the Bubble about the "new economy," there was a core of truth. You need that to get a really big bubble: you need to have something solid at the center, so that even smart people are sucked in. (Isaac Newton and Jonathan Swift both lost money in the South Sea Bubble of 1720.) Now the pendulum has swung the other way. Now anything that became fashionable during the Bubble is ipso facto unfashionable. But that's a mistake—an even bigger mistake than believing what everyone was saying in 1999. Over the long term, what the Bubble got right will be more important than what it got wrong. 1\. Retail VC After the excesses of the Bubble, it's now considered dubious to take companies public before they have earnings. But there is nothing intrinsically wrong with that idea. Taking a company public at an early stage is simply retail VC: instead of going to venture capital firms for the last round of funding, you go to the public markets. By the end of the Bubble, companies going public with no earnings were being derided as "concept stocks," as if it were inherently stupid to invest in them. But investing in concepts isn't stupid; it's what VCs do, and the best of them are far from stupid. The stock of a company that doesn't yet have earnings is worth _something._ It may take a while for the market to learn how to value such companies, just as it had to learn to value common stocks in the early 20th century. But markets are good at solving that kind of problem. I wouldn't be surprised if the market ultimately did a better job than VCs do now. Going public early will not be the right plan for every company.
一年后游戏终结。2000年1月起雅虎股价崩盘,最终蒸发95%市值。但值得注意的是,即便挤尽泡沫,雅虎依然价值不菲。2001年3-4月清醒估值时期,雅虎用六年时间创造了80亿美元市值。
事实是,尽管泡沫期充斥着关于"新经济"的荒谬论调,其核心确有真知。重大泡沫往往需要坚实内核,才能连智者都深陷其中(艾萨克·牛顿和乔纳森·斯威夫特都在1720年南海泡沫中损失惨重)。
如今钟摆反向摆动。任何泡沫期盛行的事物都被自动打上过时标签。这比1999年的盲目跟风更为谬误。长远来看,泡沫的正确洞见将比其谬误影响更为深远。
1. 大众化风投 泡沫破灭后,盈利前上市被视为可疑行为。但这个理念本身并无问题。早期上市本质上是将风投大众化:用公开市场融资替代传统风投的最后轮次。
泡沫末期,无盈利上市公司被嘲为"概念股",仿佛投资概念本身愚蠢。但概念投资恰是风投本职,最优秀的从业者绝非愚人。
And it can of course be disruptive—by distracting the management, or by making the early employees suddenly rich. But just as the market will learn how to value startups, startups will learn how to minimize the damage of going public. 2\. The Internet The Internet genuinely is a big deal. That was one reason even smart people were fooled by the Bubble. Obviously it was going to have a huge effect. Enough of an effect to triple the value of Nasdaq companies in two years? No, as it turned out. But it was hard to say for certain at the time. [1] The same thing happened during the Mississippi and South Sea Bubbles. What drove them was the invention of organized public finance (the South Sea Company, despite its name, was really a competitor of the Bank of England). And that did turn out to be a big deal, in the long run. Recognizing an important trend turns out to be easier than figuring out how to profit from it. The mistake investors always seem to make is to take the trend too literally. Since the Internet was the big new thing, investors supposed that the more Internettish the company, the better. Hence such parodies as Pets.Com. In fact most of the money to be made from big trends is made indirectly. It was not the railroads themselves that made the most money during the railroad boom, but the companies on either side, like Carnegie's steelworks, which made the rails, and Standard Oil, which used railroads to get oil to the East Coast, where it could be shipped to Europe. I think the Internet will have great effects, and that what we've seen so far is nothing compared to what's coming. But most of the winners will only indirectly be Internet companies; for every Google there will be ten JetBlues. 3\. Choices Why will the Internet have great effects? The general argument is that new forms of communication always do.
未盈利公司的股票确有价值。市场需要时间学习估值方法,如同20世纪初学习普通股定价。但市场擅长解决这类问题,未来表现超越现有风投体系也不足为奇。
早期上市并非适合所有企业,当然可能带来干扰——分散管理层注意力或让早期员工暴富。但随着市场学会估值,企业也将学会最小化上市负面影响。
2. 互联网 互联网确实是革命性存在。这正是连智者都被泡沫迷惑的原因——其巨大影响毋庸置疑,但能否两年内让纳斯达克市值翻三倍?事实证明不能。但当时难下断言。[1]
类似情形曾出现在密西西比和南海泡沫中。驱动因素是公共金融体系的诞生(南海公司实为英格兰银行竞争者)。长远来看,这确实是重大变革。
识别趋势总比从中盈利容易。投资者常犯的错误是机械理解趋势——既然互联网是新事物,便认为越"互联网化"的公司越优质,由此催生了Pets.com等荒诞案例。
They happen rarely (till industrial times there were just speech, writing, and printing), but when they do, they always cause a big splash. The specific argument, or one of them, is the Internet gives us more choices. In the "old" economy, the high cost of presenting information to people meant they had only a narrow range of options to choose from. The tiny, expensive pipeline to consumers was tellingly named "the channel." Control the channel and you could feed them what you wanted, on your terms. And it was not just big corporations that depended on this principle. So, in their way, did labor unions, the traditional news media, and the art and literary establishments. Winning depended not on doing good work, but on gaining control of some bottleneck. There are signs that this is changing. Google has over 82 million unique users a month and annual revenues of about three billion dollars. [2] And yet have you ever seen a Google ad? Something is going on here. Admittedly, Google is an extreme case. It's very easy for people to switch to a new search engine. It costs little effort and no money to try a new one, and it's easy to see if the results are better. And so Google doesn't _have_ to advertise. In a business like theirs, being the best is enough. The exciting thing about the Internet is that it's shifting everything in that direction. The hard part, if you want to win by making the best stuff, is the beginning. Eventually everyone will learn by word of mouth that you're the best, but how do you survive to that point? And it is in this crucial stage that the Internet has the most effect. First, the Internet lets anyone find you at almost zero cost. Second, it dramatically speeds up the rate at which reputation spreads by word of mouth. Together these mean that in many fields the rule will be: Build it, and they will come. Make something great and put it online. That is a big change from the recipe for winning in the past century. 4\.
事实上重大趋势的财富往往间接产生。铁路繁荣期最赚钱的不是铁路公司,而是卡内基钢铁(生产铁轨)和标准石油(利用铁路运油)等周边企业。
互联网的影响将远超现有认知,但赢家多数是间接受益者:每个谷歌背后会有十个捷蓝航空。
3. 选择权 互联网为何影响深远?宏观而言,新型通信方式总会引发变革。工业时代前仅有三类(语言、文字、印刷),但每次出现都掀起巨浪。
具体而言,互联网赋予我们更多选择。传统经济中,高昂的信息展示成本导致选择有限。狭小昂贵的传播渠道被意味深长地称为"频道"。控制频道就能按自身条件灌输信息。不仅大企业依赖此道,工会、传统媒体、艺术文学机构亦然——成功不靠优质产出,而在控制瓶颈环节。
变革正在发生。谷歌月活用户超8200万,年收入约30亿美元[2],但你见过谷歌广告吗?这暗示着深刻变化。
Youth The aspect of the Internet Bubble that the press seemed most taken with was the youth of some of the startup founders. This too is a trend that will last. There is a huge standard deviation among 26 year olds. Some are fit only for entry level jobs, but others are ready to rule the world if they can find someone to handle the paperwork for them. A 26 year old may not be very good at managing people or dealing with the SEC. Those require experience. But those are also commodities, which can be handed off to some lieutenant. The most important quality in a CEO is his vision for the company's future. What will they build next? And in that department, there are 26 year olds who can compete with anyone. In 1970 a company president meant someone in his fifties, at least. If he had technologists working for him, they were treated like a racing stable: prized, but not powerful. But as technology has grown more important, the power of nerds has grown to reflect it. Now it's not enough for a CEO to have someone smart he can ask about technical matters. Increasingly, he has to be that person himself. As always, business has clung to old forms. VCs still seem to want to install a legitimate-looking talking head as the CEO. But increasingly the founders of the company are the real powers, and the grey-headed man installed by the VCs more like a music group's manager than a general. 5\. Informality In New York, the Bubble had dramatic consequences: suits went out of fashion. They made one seem old. So in 1998 powerful New York types were suddenly wearing open-necked shirts and khakis and oval wire-rimmed glasses, just like guys in Santa Clara. The pendulum has swung back a bit, driven in part by a panicked reaction by the clothing industry. But I'm betting on the open-necked shirts. And this is not as frivolous a question as it might seem. Clothes are important, as all nerds can sense, though they may not realize it consciously.
当然谷歌是极端案例。转换搜索引擎成本极低,结果优劣立判。因此谷歌无需广告——在它们的领域,卓越即足够。
互联网的激动人心之处,在于推动所有领域朝此方向发展。以质取胜的难点在于初期——虽然口碑终将传播,但如何熬过成长期?互联网在此关键阶段作用显著:首先,零成本触达用户;其次,极大加速口碑传播。这意味着许多领域将遵循"建成自来"法则:创造伟大产品并上线,这与上世纪的成功法则截然不同。
4. 年轻力量 媒体最热衷报道的是创业者的年轻特质。这同样是持久趋势。26岁人群存在巨大差异:有的仅胜任初级工作,有的已具备统治世界能力(若有人处理文书工作)。
26岁者或许不善管理或应对SEC,这些需要经验积累——但经验可交由副手处理。CEO的核心素质是愿景规划,在这方面某些26岁者能与任何人比肩。
1970年代总裁意味着至少50岁。技术团队如同赛马:受重视但无实权。随着技术重要性提升,极客话语权相应增长。如今CEO不仅需要技术智囊,更需自身具备技术判断力。
If you're a nerd, you can understand how important clothes are by asking yourself how you'd feel about a company that made you wear a suit and tie to work. The idea sounds horrible, doesn't it? In fact, horrible far out of proportion to the mere discomfort of wearing such clothes. A company that made programmers wear suits would have something deeply wrong with it. And what would be wrong would be that how one presented oneself counted more than the quality of one's ideas. _That's_ the problem with formality. Dressing up is not so much bad in itself. The problem is the receptor it binds to: dressing up is inevitably a substitute for good ideas. It is no coincidence that technically inept business types are known as "suits." Nerds don't just happen to dress informally. They do it too consistently. Consciously or not, they dress informally as a prophylactic measure against stupidity. 6\. Nerds Clothing is only the most visible battleground in the war against formality. Nerds tend to eschew formality of any sort. They're not impressed by one's job title, for example, or any of the other appurtenances of authority. Indeed, that's practically the definition of a nerd. I found myself talking recently to someone from Hollywood who was planning a show about nerds. I thought it would be useful if I explained what a nerd was. What I came up with was: someone who doesn't expend any effort on marketing himself. A nerd, in other words, is someone who concentrates on substance. So what's the connection between nerds and technology? Roughly that you can't fool mother nature. In technical matters, you have to get the right answers. If your software miscalculates the path of a space probe, you can't finesse your way out of trouble by saying that your code is patriotic, or avant-garde, or any of the other dodges people use in nontechnical fields.
商业世界仍固守旧制。风投仍倾向安插"正统"代言人担任CEO。但实际权力日益归于创始人,风投指派的"银发经理"更似乐队经纪人而非将军。
5. 非正式文化 泡沫期间纽约发生戏剧性变化:西装过时了。1998年纽约权贵突然换上开领衫、卡其裤和椭圆金属框眼镜,宛如硅谷人士。
服装业的恐慌反应使钟摆略有回摆。但我仍看好开领衫。这并非肤浅议题——极客们虽未必明言,但都感知服饰的重要性。
想象被要求穿正装上班的感受?这种不适远超衣着本身。强制程序员穿西装的公司必然存在深层问题。
问题核心在于形式重于实质。正装本身无过,错在其绑定对象——正装总成为思想的替代品。技术低能的商业人士被称为"西装客"绝非偶然。
极客们坚持便装非偶然。无论自觉与否,这是抵御愚蠢的防疫措施。
And as technology becomes increasingly important in the economy, nerd culture is rising with it. Nerds are already a lot cooler than they were when I was a kid. When I was in college in the mid-1980s, "nerd" was still an insult. People who majored in computer science generally tried to conceal it. Now women ask me where they can meet nerds. (The answer that springs to mind is "Usenix," but that would be like drinking from a firehose.) I have no illusions about why nerd culture is becoming more accepted. It's not because people are realizing that substance is more important than marketing. It's because the nerds are getting rich. But that is not going to change. 7\. Options What makes the nerds rich, usually, is stock options. Now there are moves afoot to make it harder for companies to grant options. To the extent there's some genuine accounting abuse going on, by all means correct it. But don't kill the golden goose. Equity is the fuel that drives technical innovation. Options are a good idea because (a) they're fair, and (b) they work. Someone who goes to work for a company is (one hopes) adding to its value, and it's only fair to give them a share of it. And as a purely practical measure, people work a _lot_ harder when they have options. I've seen that first hand. The fact that a few crooks during the Bubble robbed their companies by granting themselves options doesn't mean options are a bad idea. During the railroad boom, some executives enriched themselves by selling watered stock—by issuing more shares than they said were outstanding. But that doesn't make common stock a bad idea. Crooks just use whatever means are available. If there is a problem with options, it's that they reward slightly the wrong thing. Not surprisingly, people do what you pay them to. If you pay them by the hour, they'll work a lot of hours.
6. 极客精神 服饰仅是反形式主义战争的最前线。极客们规避一切形式化事物——头衔等权威象征对他们无效。
这近乎极客的定义。我曾向好莱坞制片人解释:极客是不在自我营销上浪费精力的人。
换言之,极客专注实质。其与技术的关系在于:自然法则无法欺骗。技术领域必须正确——若软件算错太空探测器轨道,无法用"爱国代码"或"前卫艺术"等借口开脱。
随着技术经济地位提升,极客文化正在崛起。极客已比我童年时酷得多——1980年代中期"极客"仍是贬义词,计算机专业学生常隐瞒身份。如今女性会询问何处结识极客(瞬间想到Usenix会议,但那如同用消防栓喝水)。
我对极客文化受接纳不抱幻想——非因世人认识实质重于营销,而是极客正在致富。这趋势不会逆转。
If you pay them by the volume of work done, they'll get a lot of work done (but only as you defined work). And if you pay them to raise the stock price, which is what options amount to, they'll raise the stock price. But that's not quite what you want. What you want is to increase the actual value of the company, not its market cap. Over time the two inevitably meet, but not always as quickly as options vest. Which means options tempt employees, if only unconsciously, to "pump and dump"—to do things that will make the company _seem_ valuable. I found that when I was at Yahoo, I couldn't help thinking, "how will this sound to investors?" when I should have been thinking "is this a good idea?" So maybe the standard option deal needs to be tweaked slightly. Maybe options should be replaced with something tied more directly to earnings. It's still early days. 8\. Startups What made the options valuable, for the most part, is that they were options on the stock of startups. Startups were not of course a creation of the Bubble, but they were more visible during the Bubble than ever before. One thing most people did learn about for the first time during the Bubble was the startup created with the intention of selling it. Originally a startup meant a small company that hoped to grow into a big one. But increasingly startups are evolving into a vehicle for developing technology on spec. As I wrote in Hackers & Painters, employees seem to be most productive when they're paid in proportion to the wealth they generate. And the advantage of a startup—indeed, almost its raison d'etre—is that it offers something otherwise impossible to obtain: a way of _measuring_ that. In many businesses, it just makes more sense for companies to get technology by buying startups rather than developing it in house. You pay more, but there is less risk, and risk is what big companies don't want.
7. 期权激励 极客致富通常依靠股票期权。当前有收紧期权授予的趋势。若存在财务滥用,理应规范——但勿杀金鹅。股权是技术创新的燃料。
期权合理因其(a)公平(b)有效。员工创造价值就应分享回报。实践表明,期权能极大提升工作动力——我亲眼见证。
泡沫期少数骗子通过期权自肥,不意味着期权制度本身错误。铁路繁荣期有人通过掺水股渔利,但普通股仍是伟大发明。骗子总会利用现有手段。
期权制度的潜在缺陷是激励略微错位——人们总会追逐奖励标准:按时计酬就耗时间;按量计酬就冲量;期权实质是激励抬升股价,员工自会设法推高股价。
但企业真正需要的是提升实际价值而非市值。二者终将趋同,但未必与期权兑现期吻合。这诱惑员工(哪怕无意识)进行"拉高出货"——让公司看似而非真正有价值。我在雅虎时常不自觉地思考"投资者会怎么看",而非"这主意是否真好"。
It makes the guys developing the technology more accountable, because they only get paid if they build the winner. And you end up with better technology, created faster, because things are made in the innovative atmosphere of startups instead of the bureaucratic atmosphere of big companies. Our startup, Viaweb, was built to be sold. We were open with investors about that from the start. And we were careful to create something that could slot easily into a larger company. That is the pattern for the future. 9\. California The Bubble was a California phenomenon. When I showed up in Silicon Valley in 1998, I felt like an immigrant from Eastern Europe arriving in America in 1900. Everyone was so cheerful and healthy and rich. It seemed a new and improved world. The press, ever eager to exaggerate small trends, now gives one the impression that Silicon Valley is a ghost town. Not at all. When I drive down 101 from the airport, I still feel a buzz of energy, as if there were a giant transformer nearby. Real estate is still more expensive than just about anywhere else in the country. The people still look healthy, and the weather is still fabulous. The future is there. (I say "there" because I moved back to the East Coast after Yahoo. I still wonder if this was a smart idea.) What makes the Bay Area superior is the attitude of the people. I notice that when I come home to Boston. The first thing I see when I walk out of the airline terminal is the fat, grumpy guy in charge of the taxi line. I brace myself for rudeness: _remember, you're back on the East Coast now._ The atmosphere varies from city to city, and fragile organisms like startups are exceedingly sensitive to such variation. If it hadn't already been hijacked as a new euphemism for liberal, the word to describe the atmosphere in the Bay Area would be "progressive." People there are trying to build the future.
或许标准期权方案需调整,改为更直接绑定实际收益的机制。一切尚在探索中。
8. 初创企业 期权价值多源自初创企业股票。初创企业非泡沫产物,但在泡沫期能见度达历史顶峰。
泡沫期让大众首次认知"为出售而创"的初创模式。传统初创指希望成长的小公司,但新型初创日益成为技术开发的投机载体。
正如我在《黑客与画家》所述,当报酬与创造价值挂钩时,员工效率最高。初创企业的存在意义,正是提供大企业无法实现的衡量机制。
对多数企业,收购初创企业比自主研发更合理——虽成本更高但风险更低,而大企业最忌风险。这种模式让技术开发者更负责(只有成功才能获利),且技术更优、产出更快(因诞生于初创的创新氛围而非大企业的官僚环境)。
Boston has MIT and Harvard, but it also has a lot of truculent, unionized employees like the police who recently held the Democratic National Convention for ransom, and a lot of people trying to be Thurston Howell. Two sides of an obsolete coin. Silicon Valley may not be the next Paris or London, but it is at least the next Chicago. For the next fifty years, that's where new wealth will come from. 10\. Productivity During the Bubble, optimistic analysts used to justify high price to earnings ratios by saying that technology was going to increase productivity dramatically. They were wrong about the specific companies, but not so wrong about the underlying principle. I think one of the big trends we'll see in the coming century is a huge increase in productivity. Or more precisely, a huge increase in variation in productivity. Technology is a lever. It doesn't add; it multiplies. If the present range of productivity is 0 to 100, introducing a multiple of 10 increases the range from 0 to 1000. One upshot of which is that the companies of the future may be surprisingly small. I sometimes daydream about how big you could grow a company (in revenues) without ever having more than ten people. What would happen if you outsourced everything except product development? If you tried this experiment, I think you'd be surprised at how far you could get. As Fred Brooks pointed out, small groups are intrinsically more productive, because the internal friction in a group grows as the square of its size. Till quite recently, running a major company meant managing an army of workers. Our standards about how many employees a company should have are still influenced by old patterns. Startups are perforce small, because they can't afford to hire a lot of people.
我们的Viaweb就是为出售而建。从融资伊始就向投资者明确这点,并精心设计以便并购整合。这将是未来主流模式。
9. 加州效应 泡沫是加州现象。1998年初抵硅谷时,我像1900年从东欧赴美的移民——人人健康富有、朝气蓬勃,宛如升级版新世界。
媒体热衷夸大趋势,如今给人硅谷已成鬼城的错觉。绝非如此。当我沿101公路从机场驶出,仍能感受到能量脉动,仿佛巨型变压器在侧。房价仍居全美前列,人们依然健康,天气照例完美。未来在那里(我说"那里"是因收购后我搬回了东海岸,至今仍怀疑这是否明智)。
湾区优势在于人的态度。每次回到波士顿,航站楼外出租车队伍前肥胖暴躁的管理员就提醒我:记住,你回到东海岸了。
城市氛围各异,初创企业这类脆弱生命体对此极度敏感。若非被挪用为"自由派"代名词,"进步"本是最贴切描述。那里的人们在创造未来。波士顿虽有MIT和哈佛,但也有众多好斗的工会成员(如近期勒索民主党全国代表大会的警察[链接])和诸多模仿Thurston Howell的复古人士——这枚古币的两面。
But I think it's a big mistake for companies to loosen their belts as revenues increase. The question is not whether you can afford the extra salaries. Can you afford the loss in productivity that comes from making the company bigger? The prospect of technological leverage will of course raise the specter of unemployment. I'm surprised people still worry about this. After centuries of supposedly job-killing innovations, the number of jobs is within ten percent of the number of people who want them. This can't be a coincidence. There must be some kind of balancing mechanism. What's New When one looks over these trends, is there any overall theme? There does seem to be: that in the coming century, good ideas will count for more. That 26 year olds with good ideas will increasingly have an edge over 50 year olds with powerful connections. That doing good work will matter more than dressing up—or advertising, which is the same thing for companies. That people will be rewarded a bit more in proportion to the value of what they create. If so, this is good news indeed. Good ideas always tend to win eventually. The problem is, it can take a very long time. It took decades for relativity to be accepted, and the greater part of a century to establish that central planning didn't work. So even a small increase in the rate at which good ideas win would be a momentous change—big enough, probably, to justify a name like the "new economy." Notes [1] Actually it's hard to say now. As Jeremy Siegel points out, if the value of a stock is its future earnings, you can't tell if it was overvalued till you see what the earnings turn out to be. While certain famous Internet stocks were almost certainly overvalued in 1999, it is still hard to say for sure whether, e.g., the Nasdaq index was.
硅谷或许成不了下一个巴黎或伦敦,但至少会是下一个芝加哥。未来五十年的新财富将源自那里。
10. 生产率跃升 泡沫期乐观分析师常以生产率暴涨解释高市盈率。他们对具体公司判断错误,但核心理念未必全错。我认为新世纪将见证生产率的巨大分化。
技术是乘数而非加数。若当前生产率区间为0-100,技术引入10倍乘数后将变为0-1000。
这预示未来公司的规模可能惊人地小。我常幻想:能否用不超过10人的团队创造巨额营收?若将除产品开发外所有环节外包,实验结果会令人惊讶。正如Fred Brooks指出,小团队本质更高效——内部摩擦随规模呈平方增长。
直至最近,大公司仍意味着管理庞大人群。我们对公司规模的认知仍受旧模式影响。初创企业因资金限制被迫精简,但我认为营收增长后盲目扩员是重大错误——问题不在能否负担薪资,而在能否承受规模带来的效率损失。
Siegel, Jeremy J. "What Is an Asset Price Bubble? An Operational Definition." _European Financial Management,_ 9:1, 2003. [2] The number of users comes from a 6/03 Nielsen study quoted on Google's site. (You'd think they'd have something more recent.) The revenue estimate is based on revenues of $1.35 billion for the first half of 2004, as reported in their IPO filing. Thanks to Chris Anderson, Trevor Blackwell, Sarah Harlin, Jessica Livingston, and Robert Morris for reading drafts of this.
| The Long Tail | | | Russian Translation | Japanese Translation.
技术杠杆可能引发失业担忧。但历经数百年"消灭岗位"的创新后,职位数量与求职者始终相差不到10%。这绝非巧合,必存在某种平衡机制。
新范式 这些趋势是否存在共同主题?似乎存在:新世纪里,好点子将更受重视。26岁的创意者相对50岁的人脉者优势渐增;实干比包装重要(广告即企业的包装);回报与创造价值的关联度将提升。
若是如此,实乃佳讯。好创意终将胜出,但往往耗时太久——相对论数十年才被接纳,计划经济近一世纪才被证伪。因此哪怕好创意胜率的小幅提升,都将是重大变革,或许足以冠以"新经济"之名。
注释: [1] 实际至今难下定论。如Jeremy Siegel指出,若股票价值是未来收益,需待收益显现才能判断是否高估。虽某些著名互联网股在1999年明显高估,但纳指整体是否泡沫仍难断言。(引自Jeremy J. Siegel《何为资产价格泡沫?操作定义》)
[2] 用户数据来自谷歌官网引用的2003年6月尼尔森研究(奇怪未更新)。收入依据2004上半年13.5亿美元(招股书披露)估算。
致谢:Chris Anderson、Trevor Blackwell、Sarah Harlin、Jessica Livingston和Robert Morris的审阅。
August 2004 In a recent talk I said something that upset a lot of people: that you could get smarter programmers to work on a Python project than you could to work on a Java project. I didn't mean by this that Java programmers are dumb. I meant that Python programmers are smart. It's a lot of work to learn a new programming language. And people don't learn Python because it will get them a job; they learn it because they genuinely like to program and aren't satisfied with the languages they already know. Which makes them exactly the kind of programmers companies should want to hire. Hence what, for lack of a better name, I'll call the Python paradox: if a company chooses to write its software in a comparatively esoteric language, they'll be able to hire better programmers, because they'll attract only those who cared enough to learn it. And for programmers the paradox is even more pronounced: the language to learn, if you want to get a good job, is a language that people don't learn merely to get a job. Only a few companies have been smart enough to realize this so far. But there is a kind of selection going on here too: they're exactly the companies programmers would most like to work for. Google, for example. When they advertise Java programming jobs, they also want Python experience. A friend of mine who knows nearly all the widely used languages uses Python for most of his projects. He says the main reason is that he likes the way source code looks. That may seem a frivolous reason to choose one language over another. But it is not so frivolous as it sounds: when you program, you spend more time reading code than writing it. You push blobs of source code around the way a sculptor does blobs of clay. So a language that makes source code ugly is maddening to an exacting programmer, as clay full of lumps would be to a sculptor. At the mention of ugly source code, people will of course think of Perl.
2004年8月 在最近的一次演讲中,我说了一些让很多人感到不安的话:相比Java项目,你能为Python项目招募到更聪明的程序员。 我并不是说Java程序员不聪明。我的意思是Python程序员很聪明。学习一门新编程语言需要付出大量努力。人们学习Python并不是因为它能帮他们找到工作;他们学习它是因为他们真心热爱编程,并且对已经掌握的语言感到不满足。 而这正是公司应该想要雇佣的那种程序员。因此,由于缺乏更好的名称,我将其称为“Python悖论”:如果一家公司选择用一种相对冷门的语言编写软件,他们将能够雇佣到更好的程序员,因为他们只会吸引那些真正愿意学习它的人。对于程序员来说,这个悖论更加明显:如果你想找到一份好工作,应该学习的语言是那些人们不仅仅为了找工作而学习的语言。 到目前为止,只有少数公司足够聪明地意识到了这一点。但这里也存在一种选择:它们恰恰是程序员最愿意为之工作的公司。例如谷歌。当他们招聘Java程序员时,也会要求有Python经验。 我的一位朋友几乎精通所有广泛使用的语言,但他大部分项目都使用Python。他说主要原因是他喜欢源代码的呈现方式。这看起来可能是一个轻率的理由来选择一门语言而非另一门。但它并不像听起来那么轻率:在编程时,你阅读代码的时间比编写代码的时间更多。你像雕塑家摆弄黏土块一样摆弄源代码块。因此,一门让源代码变得丑陋的语言会让严谨的程序员感到恼火,就像满是疙瘩的黏土会让雕塑家感到恼火一样。 提到丑陋的源代码,人们当然会想到Perl。但Perl表面上的丑陋并不是我所说的那种。真正的丑陋不是看起来刺眼的语法,而是不得不用错误的概念构建程序。Perl可能看起来像一个骂骂咧咧的卡通人物,但在某些情况下,它在概念上超越了Python。 至少目前如此。当然,这两种语言都在不断发展。但它们与Ruby(以及Icon、Joy、J、Lisp和Smalltalk)有一个共同点:它们是由真正关心编程的人创建和使用的。而这些往往是那些做得很好的人。
土耳其语翻译 | 日语翻译 葡萄牙语翻译 | 意大利语翻译 波兰语翻译 | 罗马尼亚语翻译 俄语翻译 | 西班牙语翻译 法语翻译 | 泰卢固语翻译
But the superficial ugliness of Perl is not the sort I mean. Real ugliness is not harsh-looking syntax, but having to build programs out of the wrong concepts. Perl may look like a cartoon character swearing, but there are cases where it surpasses Python conceptually. So far, anyway. Both languages are of course moving targets. But they share, along with Ruby (and Icon, and Joy, and J, and Lisp, and Smalltalk) the fact that they're created by, and used by, people who really care about programming. And those tend to be the ones who do it well.
Turkish Translation | Japanese Translation Portuguese Translation | Italian Translation Polish Translation | Romanian Translation Russian Translation | Spanish Translation French Translation | Telugu Translation.
If you liked this, you may also like _Hackers & Painters_.
如果你喜欢这篇文章,可能也会喜欢《黑客与画家》。
Want to start a startup? Get funded by Y Combinator.
July 2004 _(This essay is derived from a talk at Oscon 2004.)_ A few months ago I finished a new book, and in reviews I keep noticing words like "provocative'' and "controversial.'' To say nothing of "idiotic.'' I didn't mean to make the book controversial. I was trying to make it efficient. I didn't want to waste people's time telling them things they already knew. It's more efficient just to give them the diffs. But I suppose that's bound to yield an alarming book. Edisons There's no controversy about which idea is most controversial: the suggestion that variation in wealth might not be as big a problem as we think. I didn't say in the book that variation in wealth was in itself a good thing. I said in some situations it might be a sign of good things. A throbbing headache is not a good thing, but it can be a sign of a good thing-- for example, that you're recovering consciousness after being hit on the head. Variation in wealth can be a sign of variation in productivity. (In a society of one, they're identical.) And _that_ is almost certainly a good thing: if your society has no variation in productivity, it's probably not because everyone is Thomas Edison. It's probably because you have no Thomas Edisons. In a low-tech society you don't see much variation in productivity. If you have a tribe of nomads collecting sticks for a fire, how much more productive is the best stick gatherer going to be than the worst? A factor of two? Whereas when you hand people a complex tool like a computer, the variation in what they can do with it is enormous. That's not a new idea. Fred Brooks wrote about it in 1974, and the study he quoted was published in 1968. But I think he underestimated the variation between programmers.
He wrote about productivity in lines of code: the best programmers can solve a given problem in a tenth the time. But what if the problem isn't given? In programming, as in many fields, the hard part isn't solving problems, but deciding what problems to solve. Imagination is hard to measure, but in practice it dominates the kind of productivity that's measured in lines of code. Productivity varies in any field, but there are few in which it varies so much. The variation between programmers is so great that it becomes a difference in kind. I don't think this is something intrinsic to programming, though. In every field, technology magnifies differences in productivity. I think what's happening in programming is just that we have a lot of technological leverage. But in every field the lever is getting longer, so the variation we see is something that more and more fields will see as time goes on. And the success of companies, and countries, will depend increasingly on how they deal with it. If variation in productivity increases with technology, then the contribution of the most productive individuals will not only be disproportionately large, but will actually grow with time. When you reach the point where 90% of a group's output is created by 1% of its members, you lose big if something (whether Viking raids, or central planning) drags their productivity down to the average. If we want to get the most out of them, we need to understand these especially productive people. What motivates them? What do they need to do their jobs? How do you recognize them? How do you get them to come and work for you? And then of course there's the question, how do you become one? More than Money I know a handful of super-hackers, so I sat down and thought about what they have in common. Their defining quality is probably that they really love to program. Ordinary programmers write code to pay the bills.
Great hackers think of it as something they do for fun, and which they're delighted to find people will pay them for. Great programmers are sometimes said to be indifferent to money. This isn't quite true. It is true that all they really care about is doing interesting work. But if you make enough money, you get to work on whatever you want, and for that reason hackers _are_ attracted by the idea of making really large amounts of money. But as long as they still have to show up for work every day, they care more about what they do there than how much they get paid for it. Economically, this is a fact of the greatest importance, because it means you don't have to pay great hackers anything like what they're worth. A great programmer might be ten or a hundred times as productive as an ordinary one, but he'll consider himself lucky to get paid three times as much. As I'll explain later, this is partly because great hackers don't know how good they are. But it's also because money is not the main thing they want. What do hackers want? Like all craftsmen, hackers like good tools. In fact, that's an understatement. Good hackers find it unbearable to use bad tools. They'll simply refuse to work on projects with the wrong infrastructure. At a startup I once worked for, one of the things pinned up on our bulletin board was an ad from IBM. It was a picture of an AS400, and the headline read, I think, "hackers despise it.'' [1] When you decide what infrastructure to use for a project, you're not just making a technical decision. You're also making a social decision, and this may be the more important of the two. For example, if your company wants to write some software, it might seem a prudent choice to write it in Java. But when you choose a language, you're also choosing a community. The programmers you'll be able to hire to work on a Java project won't be as smart as the ones you could get to work on a project written in Python.
And the quality of your hackers probably matters more than the language you choose. Though, frankly, the fact that good hackers prefer Python to Java should tell you something about the relative merits of those languages. Business types prefer the most popular languages because they view languages as standards. They don't want to bet the company on Betamax. The thing about languages, though, is that they're not just standards. If you have to move bits over a network, by all means use TCP/IP. But a programming language isn't just a format. A programming language is a medium of expression. I've read that Java has just overtaken Cobol as the most popular language. As a standard, you couldn't wish for more. But as a medium of expression, you could do a lot better. Of all the great programmers I can think of, I know of only one who would voluntarily program in Java. And of all the great programmers I can think of who don't work for Sun, on Java, I know of zero. Great hackers also generally insist on using open source software. Not just because it's better, but because it gives them more control. Good hackers insist on control. This is part of what makes them good hackers: when something's broken, they need to fix it. You want them to feel this way about the software they're writing for you. You shouldn't be surprised when they feel the same way about the operating system. A couple years ago a venture capitalist friend told me about a new startup he was involved with. It sounded promising. But the next time I talked to him, he said they'd decided to build their software on Windows NT, and had just hired a very experienced NT developer to be their chief technical officer. When I heard this, I thought, these guys are doomed.
One, the CTO couldn't be a first rate hacker, because to become an eminent NT developer he would have had to use NT voluntarily, multiple times, and I couldn't imagine a great hacker doing that; and two, even if he was good, he'd have a hard time hiring anyone good to work for him if the project had to be built on NT. [2] The Final Frontier After software, the most important tool to a hacker is probably his office. Big companies think the function of office space is to express rank. But hackers use their offices for more than that: they use their office as a place to think in. And if you're a technology company, their thoughts are your product. So making hackers work in a noisy, distracting environment is like having a paint factory where the air is full of soot. The cartoon strip Dilbert has a lot to say about cubicles, and with good reason. All the hackers I know despise them. The mere prospect of being interrupted is enough to prevent hackers from working on hard problems. If you want to get real work done in an office with cubicles, you have two options: work at home, or come in early or late or on a weekend, when no one else is there. Don't companies realize this is a sign that something is broken? An office environment is supposed to be something that _helps_ you work, not something you work despite. Companies like Cisco are proud that everyone there has a cubicle, even the CEO. But they're not so advanced as they think; obviously they still view office space as a badge of rank. Note too that Cisco is famous for doing very little product development in house. They get new technology by buying the startups that created it-- where presumably the hackers did have somewhere quiet to work. One big company that understands what hackers need is Microsoft. I once saw a recruiting ad for Microsoft with a big picture of a door. Work for us, the premise was, and we'll give you a place to work where you can actually get work done.
想创业吗? 获得 Y Combinator 的资助。
2004年7月 _(本文改编自2004年Oscon大会的演讲。)_ 几个月前我完成了一本新书,而在书评中我不断看到诸如“挑衅性”和“争议性”这样的字眼。更别提“愚蠢”了。 我并非有意让这本书引发争议。我只是想让它更高效。我不想浪费读者的时间去讲述他们早已知道的事情。直接呈现差异会更有效率。但我想这注定会写出一本令人不安的书。 爱迪生们 最具争议的观点毫无争议:财富差异可能并不像我们想象的那么严重。 我在书中并未说财富差异本身是好事。我说在某些情况下,它可能是好事的征兆。剧烈的头痛不是好事,但它可能是好事的征兆——比如你在头部受击后正在恢复意识。 财富差异可能是生产力差异的体现。(在一个人的社会中,两者是相同的。)而后者几乎肯定是好事:如果你的社会中没有生产力差异,很可能不是因为人人都是托马斯·爱迪生,而是因为你根本没有托马斯·爱迪生。 在低技术社会中,你看不到太大的生产力差异。如果一个游牧部落的人在收集生火的树枝,最擅长收集树枝的人会比最差的人效率高多少?两倍?而当你给人们一个复杂的工具,比如计算机时,他们能用它做的事情差异是巨大的。 这不是新观点。弗雷德·布鲁克斯在1974年就写过,而他引用的研究发表于1968年。但我认为他低估了程序员之间的差异。他写的是代码行数的生产力:最好的程序员能用十分之一的时间解决给定的问题。但如果问题不是给定的呢?在编程中,就像在许多领域一样,困难的部分不是解决问题,而是决定解决什么问题。想象力很难衡量,但在实践中,它主导了以代码行数衡量的生产力。 生产力在任何领域都有差异,但很少有领域像编程这样差异巨大。程序员之间的差异如此之大,以至于变成了质的区别。我不认为这是编程特有的。在每个领域,技术都放大了生产力的差异。我认为编程中发生的情况只是因为我们有大量的技术杠杆。但在每个领域,杠杆都在变长,所以随着时间的推移,越来越多的领域会看到这种差异。而公司和国家的成功将越来越取决于他们如何处理它。 如果生产力的差异随着技术而增加,那么最有生产力的个体的贡献不仅会不成比例地大,而且实际上会随着时间的推移而增长。当你达到一个群体90%的产出由1%的成员创造时,如果某些因素(无论是维京人的袭击还是中央计划)将他们的生产力拖到平均水平,你会损失惨重。 如果我们想充分利用他们,就需要了解这些特别有生产力的人。什么激励着他们?他们工作需要什么?你如何识别他们?如何让他们来为你工作?当然还有问题,如何成为他们中的一员? 不仅仅是金钱 我认识一些超级黑客,所以我坐下来思考他们的共同点。他们的决定性特质可能是他们真的热爱编程。普通程序员写代码是为了谋生。伟大的黑客认为这是他们为了乐趣而做的事情,并且很高兴发现有人会为此付钱给他们。 伟大的程序员有时被认为对金钱漠不关心。这不完全正确。他们真正关心的确实是做有趣的工作。但如果你赚了足够的钱,你就可以做任何你想做的工作,因此黑客确实会被赚大钱的想法吸引。但只要他们仍然需要每天上班,他们就更关心在那里做什么,而不是能拿多少钱。 从经济学的角度来看,这是一个极其重要的事实,因为这意味着你不需要支付伟大黑客与他们价值相当的报酬。一个伟大的程序员可能比普通程序员高效十倍或一百倍,但他会认为自己很幸运能拿到三倍的薪水。正如我稍后会解释的,部分原因是伟大的黑客不知道他们有多优秀。但也因为金钱不是他们主要想要的东西。 黑客想要什么?像所有工匠一样,黑客喜欢好工具。实际上,这还轻描淡写了。优秀的黑客觉得使用糟糕的工具是无法忍受的。他们会直接拒绝在错误的基础设施上工作。 在我曾经工作过的一家初创公司,我们的公告板上钉着一则IBM的广告。那是一张AS400的照片,标题大概是“黑客鄙视它”。[1] 当你决定为一个项目使用什么基础设施时,你不仅是在做一个技术决定,也是在做一个社会决定,而后者可能比前者更重要。例如,如果你的公司想写一些软件,用Java写似乎是一个谨慎的选择。但当你选择一种语言时,你也在选择一个社区。你能雇来从事Java项目的程序员不会像你能雇来从事Python项目的人那样聪明。而你的黑客的质量可能比你选择的语言更重要。不过,坦率地说,优秀的黑客更喜欢Python而不是Java,这应该能告诉你这两种语言的相对优劣。 商业人士更喜欢最流行的语言,因为他们将语言视为标准。他们不想把公司押在Betamax上。但语言不仅仅是标准。如果你必须通过网络传输数据,一定要使用TCP/IP。但编程语言不仅仅是一种格式。编程语言是一种表达媒介。 我读到Java刚刚超过Cobol成为最流行的语言。作为一个标准,你不能再奢求更多了。但作为一种表达媒介,你可以做得更好。在我能想到的所有伟大程序员中,我只知道一个会自愿用Java编程的人。而在我能想到的所有不为Sun公司从事Java工作的伟大程序员中,我知道的为零。 伟大的黑客通常也坚持使用开源软件。不仅因为它更好,还因为它给了他们更多的控制权。优秀的黑客坚持控制权。这是他们成为优秀黑客的部分原因:当某些东西坏了,他们需要修复它。你希望他们对为你编写的软件有这种感觉。当他们觉得操作系统也应该如此时,你不应该感到惊讶。 几年前,一位风险投资家朋友告诉我他参与的一家新初创公司。听起来很有前途。但下次我和他交谈时,他说他们决定在Windows NT上构建软件,并刚刚聘请了一位非常有经验的NT开发人员担任首席技术官。当我听到这个消息时,我想,这些人完蛋了。首先,这位首席技术官不可能是一流的黑客,因为要成为著名的NT开发人员,他必须多次自愿使用NT,而我无法想象一个伟大的黑客会这样做;其次,即使他很优秀,如果项目必须在NT上构建,他也很难雇到任何优秀的人为他工作。[2] 最后的边疆 除了软件,对黑客来说最重要的工具可能是他的办公室。大公司认为办公空间的功能是表达等级。但黑客使用办公室不仅仅是为了这个:他们把办公室当作思考的地方。如果你是一家科技公司,他们的思想就是你的产品。所以让黑客在嘈杂、分散注意力的环境中工作,就像在空气中充满煤灰的油漆厂工作一样。 漫画《呆伯特》对隔间有很多话要说,而且有充分的理由。我认识的所有黑客都鄙视它们。仅仅是可能被打断的念头就足以阻止黑客解决难题。如果你想在一个有隔间的办公室里完成真正的工作,你有两个选择:在家工作,或者在别人不在的时候早来、晚来或周末来。公司难道没有意识到这是一个问题的征兆吗?办公环境应该是帮助你工作的东西,而不是你勉强工作的东西。 像思科这样的公司以每个人(包括CEO)都有一个隔间为荣。但他们并没有他们想象的那么先进;显然他们仍然将办公空间视为等级的象征。还要注意的是,思科以很少进行内部产品开发而闻名。他们通过收购创造了新技术的初创公司来获取新技术——在那里,黑客们确实有安静的地方工作。 微软是一家了解黑客需求的大公司。我曾经看到微软的一则招聘广告,上面有一扇门的大图。前提是:为我们工作,我们会给你一个可以真正完成工作的地方。你知道,微软在大公司中很突出,因为他们能够在内部开发软件。也许不够好,但足够好。 如果公司希望黑客高效工作,他们应该看看黑客在家做什么。在家里,黑客可以自己安排事情,以便完成最多的工作。当黑客在家工作时,他们不会在嘈杂、开放的空间工作;他们在有门的房间里工作。他们在舒适、邻里般的地方工作,周围有人,有地方可以散步,当他们需要思考时,而不是在玻璃盒子里,周围是成片的停车场。他们有一张沙发,当他们感到疲倦时可以小睡一会儿,而不是坐在办公桌前假装工作。没有一群人在黄金编程时间每晚用吸尘器轰鸣而过。没有会议,或者更糟的公司团建或团队建设活动。当你看看他们在电脑上做什么时,你会发现这强化了我之前关于工具的说法。他们可能不得不在工作中使用Java和Windows,但在家里,他们可以自由选择时,你更可能发现他们使用Perl和Linux。 事实上,关于Cobol或Java是最流行语言的统计数据可能会产生误导。如果我们想知道什么工具是最好的,我们应该看看黑客在可以自由选择时会选择什么——也就是说,在他们自己的项目中。当你问这个问题时,你会发现开源操作系统已经占据了主导市场份额,而排名第一的语言可能是Perl。 有趣 除了好工具,黑客还想要有趣的项目。什么让一个项目有趣?显然,像隐形飞机或特效软件这样性感的应用会很有趣。但任何应用如果提出了新颖的技术挑战,都可能变得有趣。因此,很难预测黑客会喜欢哪些问题,因为有些问题只有在从事它们的人发现了一种新的解决方案时才变得有趣。在ITA(Orbitz内部软件的开发者)之前,从事航空公司票价搜索的人可能认为这是可以想象的最无聊的应用之一。但ITA通过以更雄心勃勃的方式重新定义问题使其变得有趣。 我认为谷歌也发生了同样的事情。当谷歌成立时,所谓门户网站的普遍看法是搜索既无聊又不重要。但谷歌的人并不认为搜索无聊,这就是他们做得如此出色的原因。 这是管理者可以有所作为的领域。就像父母对孩子说:“我打赌你不能在十分钟内打扫完整个房间”一样,一个好的管理者有时可以通过将问题重新定义为更有趣的问题来激励团队。史蒂夫·乔布斯似乎特别擅长这一点,部分原因仅仅是因为他有高标准。在Mac之前有很多小型、廉价的电脑。他将问题重新定义为:制造一个漂亮的电脑。这可能比任何胡萝卜或大棒更能激励开发者。 他们确实做到了。当Mac第一次出现时,你甚至不需要打开它就知道它会很好;你可以从机箱上看出来。几周前,我在剑桥的街上走着,在某个人的垃圾中看到了一个看起来像Mac手提箱的东西。我往里看,发现了一台Mac SE。我把它带回家,插上电源,它启动了。快乐的Macintosh笑脸,然后是Finder。天哪,它太简单了。就像……谷歌。 黑客喜欢为有高标准的人工作。但仅仅严格是不够的。你必须坚持正确的事情。这通常意味着你自己也必须是一个黑客。我偶尔会看到关于如何管理程序员的文章。实际上应该有两篇文章:一篇是关于如果你是程序员自己该怎么做,另一篇是关于如果你不是程序员该怎么做。而第二篇可能可以压缩成两个字:放弃。 问题不在于日常管理。真正优秀的黑客实际上是自我管理的。问题是,如果你不是一个黑客,你无法分辨谁是优秀的黑客。类似的问题解释了为什么美国汽车如此丑陋。我称之为“设计悖论”。你可能会认为,只要雇一个伟大的设计师来设计,你就能让你的产品变得漂亮。但如果你自己没有好的品味,你怎么能认出一个好的设计师呢?从定义上讲,你无法从他的作品集中看出来。你也不能根据他赢得的奖项或他做过的工作来判断,因为在设计领域,就像在大多数领域一样,这些往往是由时尚和人际关系驱动的,实际能力排在第三位。没有办法绕过它:如果你不知道什么是美,你就无法管理一个旨在生产美丽事物的过程。美国汽车丑陋是因为美国汽车公司的掌舵人品味糟糕。 在这个国家,许多人认为品味是一种难以捉摸甚至轻浮的东西。它两者都不是。为了推动设计,管理者必须是公司产品最苛刻的用户。如果你真的有好的品味,你可以像史蒂夫·乔布斯那样,让满足你成为优秀人才喜欢解决的问题。 烦人的小问题 很容易说什么样的问题是无趣的:那些不是解决几个大而清晰的问题,而是必须解决许多烦人的小问题的问题。最糟糕的项目之一是为一个充满bug的软件编写接口。另一个是根据个别客户复杂且定义不清的需求定制某些东西。对黑客来说,这类项目就像千刀万剐。 烦人的小问题的特点是,你从中学不到任何东西。编写编译器很有趣,因为它教会你什么是编译器。但为一个充满bug的软件编写接口不会教会你任何东西,因为bug是随机的。[3] 所以,优秀黑客避免烦人的小问题不仅仅是出于挑剔。更多的是自我保护的问题。处理烦人的小问题会让你变得愚蠢。优秀黑客避免它,就像模特避免芝士汉堡一样。 当然,有些问题本身就有这种特点。由于供求关系,它们的报酬特别高。因此,一家能找到方法让优秀黑客处理枯燥问题的公司将非常成功。你会怎么做? 初创公司是一个这样的地方。在我们的初创公司,罗伯特·莫里斯担任系统管理员。这就像让滚石乐队在成人礼上表演。你无法雇佣这种人才。但人们会为公司做任何苦差事,只要他们是创始人。[4] 更大的公司通过划分公司来解决这个问题。他们通过建立一个单独的研发部门来吸引聪明人,员工不必直接处理客户的烦人小问题。[5] 在这种模式下,研究部门就像一个矿山。他们产生新想法;也许公司的其他部门能够利用它们。 你可能不需要走这么远。自底向上编程提出了另一种划分公司的方法:让聪明人担任工具制造者。如果你的公司制作x类软件,让一个小组构建编写该类软件的工具,另一个小组使用这些工具编写应用程序。这样,你或许能让聪明人编写99%的代码,同时让他们几乎像在传统研究部门一样与用户隔离。工具制造者会有用户,但他们只是公司自己的开发人员。[6] 如果微软采用这种方法,他们的软件就不会有这么多安全漏洞,因为编写实际应用程序的不那么聪明的人不会做像分配内存这样的底层工作。他们不是直接用C编写Word,而是用Word语言的大乐高积木拼在一起。(我相信,技术术语是Duplo。) 聚集 除了有趣的问题,优秀黑客喜欢的还有其他的优秀黑客。伟大的黑客往往会聚集在一起——有时非常壮观,比如在施乐帕克研究中心。所以你吸引优秀黑客的能力与你为他们创造的环境的好坏不成线性比例。聚集的趋势意味着它更像是环境的平方。所以赢家通吃。在任何时候,只有大约十到二十个地方是黑客最想去工作的,如果你不是其中之一,你不仅会有更少的伟大黑客,你会有零个。 拥有伟大黑客本身并不足以让一家公司成功。这对谷歌和ITA很有效,它们是现在的热点,但它对思维机器公司或施乐没有帮助。Sun曾经风光过一段时间,但他们的商业模式是下行的。在这种情况下,即使是最好的黑客也救不了你。 不过,我认为在其他条件相同的情况下,能够吸引伟大黑客的公司将具有巨大的优势。有些人会不同意这一点。当我们在20世纪90年代拜访风险投资公司时,有几家告诉我们,软件公司不是通过编写伟大的软件获胜,而是通过品牌、主导渠道和做正确的交易。 他们似乎真的相信这一点,我想我知道为什么。我认为许多风险投资家寻找的,至少是无意识地,是下一个微软。当然,如果微软是你的榜样,你不应该寻找希望通过编写伟大软件获胜的公司。但风险投资家寻找下一个微软是错误的,因为没有一家初创公司能成为下一个微软,除非另一家公司准备在适当的时刻弯腰成为下一个IBM。 以微软为榜样是错误的,因为他们的整个文化都源于那一次幸运的突破。微软是一个糟糕的数据点。如果你抛开他们,你会发现好产品确实倾向于在市场上获胜。风险投资家应该寻找的是下一个苹果,或下一个谷歌。 我认为比尔·盖茨知道这一点。他对谷歌的担忧不是他们品牌的力量,而是他们有更好的黑客。[7] 认可 那么谁是伟大的黑客?当你遇到一个时,你怎么知道?事实证明这非常困难。即使是黑客也无法分辨。我现在非常确定我的朋友特雷弗·布莱克威尔是一个伟大的黑客。你可能在Slashdot上读过他如何制作自己的赛格威。这个项目的显著之处在于,他在一天内写完了所有软件(顺便说一下,用的是Python)。 对特雷弗来说,这是家常便饭。但当我第一次见到他时,我以为他是个彻头彻尾的白痴。他站在罗伯特·莫里斯的办公室里对他喋喋不休地说着什么,我记得我站在他身后疯狂地向罗伯特打手势,让他把这个疯子赶出办公室,这样我们就可以去吃午饭了。罗伯特说他一开始也看错了特雷弗。显然,当罗伯特第一次见到他时,特雷弗刚刚开始一个新计划,涉及将生活的方方面面记录在一叠索引卡上,他走到哪里都带着这些卡片。他刚从加拿大来,带着浓重的加拿大口音和鲻鱼头。 问题更加复杂的是,尽管黑客以社交迟钝著称,但有时他们会花很大力气让自己看起来聪明。我在研究生院时,偶尔会去MIT人工智能实验室转转。一开始有点吓人。那里的每个人都说得很快。但过了一段时间,我学会了快速说话的技巧。你不需要想得更快;只要用两倍的词来说每件事。 在这种信号的噪音中,很难在遇到优秀黑客时认出他们。即使是现在,我也无法分辨。你也不能从他们的简历中看出来。似乎评判一个黑客的唯一方法是与他合作做点什么。 这就是高科技区域只出现在大学周围的原因。这里的活性成分不是教授,而是学生。初创公司在大学周围成长,因为大学将前途无量的年轻人聚集在一起,让他们在相同的项目上工作。聪明的人会知道其他聪明的人是谁,然后一起策划他们自己的新项目。 因为你无法通过合作以外的方式判断一个伟大的黑客,黑客自己也不知道他们有多优秀。这在大多数领域都是如此。我发现,那些在某方面非常出色的人,与其说他们确信自己的伟大,不如说他们对为什么其他人看起来如此无能感到困惑。 但对黑客来说,知道自己有多优秀尤其困难,因为很难比较他们的工作。这在大多数其他领域更容易。在百米赛跑中,你可以在10秒内知道谁最快。即使在数学领域,似乎也有一个普遍的共识,哪些问题难以解决,什么构成了一个好的解决方案。但黑客就像写作。谁能说哪部小说更好?当然不是作者。 至少,其他黑客可以分辨。这是因为,与小说家不同,黑客在项目上合作。当你通过网络向某人抛出几个难题时,你很快就能知道他们回应的力度。但黑客无法观察自己的工作。所以如果你问一个伟大的黑客他有多优秀,他几乎肯定会回答,我不知道。他不是在谦虚。他真的不知道。 我们谁都不知道,除了那些我们真正合作过的人。这让我们处于一个奇怪的境地:我们不知道该崇拜谁。那些成名的黑客往往因为公关的随机事件而成名。有时我需要举一个伟大黑客的例子,而我从来不知道该用谁。首先想到的名字总是我认识的人,但用他们似乎很蹩脚。所以,我想,也许我应该说理查德·斯托曼,或林纳斯·托瓦兹.
And you know, Microsoft is remarkable among big companies in that they are able to develop software in house. Not well, perhaps, but well enough. If companies want hackers to be productive, they should look at what they do at home. At home, hackers can arrange things themselves so they can get the most done. And when they work at home, hackers don't work in noisy, open spaces; they work in rooms with doors. They work in cosy, neighborhoody places with people around and somewhere to walk when they need to mull something over, instead of in glass boxes set in acres of parking lots. They have a sofa they can take a nap on when they feel tired, instead of sitting in a coma at their desk, pretending to work. There's no crew of people with vacuum cleaners that roars through every evening during the prime hacking hours. There are no meetings or, God forbid, corporate retreats or team-building exercises. And when you look at what they're doing on that computer, you'll find it reinforces what I said earlier about tools. They may have to use Java and Windows at work, but at home, where they can choose for themselves, you're more likely to find them using Perl and Linux. Indeed, these statistics about Cobol or Java being the most popular language can be misleading. What we ought to look at, if we want to know what tools are best, is what hackers choose when they can choose freely-- that is, in projects of their own. When you ask that question, you find that open source operating systems already have a dominant market share, and the number one language is probably Perl. Interesting Along with good tools, hackers want interesting projects. What makes a project interesting? Well, obviously overtly sexy applications like stealth planes or special effects software would be interesting to work on. But any application can be interesting if it poses novel technical challenges.
So it's hard to predict which problems hackers will like, because some become interesting only when the people working on them discover a new kind of solution. Before ITA (who wrote the software inside Orbitz), the people working on airline fare searches probably thought it was one of the most boring applications imaginable. But ITA made it interesting by redefining the problem in a more ambitious way. I think the same thing happened at Google. When Google was founded, the conventional wisdom among the so-called portals was that search was boring and unimportant. But the guys at Google didn't think search was boring, and that's why they do it so well. This is an area where managers can make a difference. Like a parent saying to a child, I bet you can't clean up your whole room in ten minutes, a good manager can sometimes redefine a problem as a more interesting one. Steve Jobs seems to be particularly good at this, in part simply by having high standards. There were a lot of small, inexpensive computers before the Mac. He redefined the problem as: make one that's beautiful. And that probably drove the developers harder than any carrot or stick could. They certainly delivered. When the Mac first appeared, you didn't even have to turn it on to know it would be good; you could tell from the case. A few weeks ago I was walking along the street in Cambridge, and in someone's trash I saw what appeared to be a Mac carrying case. I looked inside, and there was a Mac SE. I carried it home and plugged it in, and it booted. The happy Macintosh face, and then the finder. My God, it was so simple. It was just like ... Google. Hackers like to work for people with high standards. But it's not enough just to be exacting. You have to insist on the right things. Which usually means that you have to be a hacker yourself. I've seen occasional articles about how to manage programmers.
Really there should be two articles: one about what to do if you are yourself a programmer, and one about what to do if you're not. And the second could probably be condensed into two words: give up. The problem is not so much the day to day management. Really good hackers are practically self-managing. The problem is, if you're not a hacker, you can't tell who the good hackers are. A similar problem explains why American cars are so ugly. I call it the _design paradox._ You might think that you could make your products beautiful just by hiring a great designer to design them. But if you yourself don't have good taste, how are you going to recognize a good designer? By definition you can't tell from his portfolio. And you can't go by the awards he's won or the jobs he's had, because in design, as in most fields, those tend to be driven by fashion and schmoozing, with actual ability a distant third. There's no way around it: you can't manage a process intended to produce beautiful things without knowing what beautiful is. American cars are ugly because American car companies are run by people with bad taste. Many people in this country think of taste as something elusive, or even frivolous. It is neither. To drive design, a manager must be the most demanding user of a company's products. And if you have really good taste, you can, as Steve Jobs does, make satisfying you the kind of problem that good people like to work on. Nasty Little Problems It's pretty easy to say what kinds of problems are not interesting: those where instead of solving a few big, clear, problems, you have to solve a lot of nasty little ones. One of the worst kinds of projects is writing an interface to a piece of software that's full of bugs. Another is when you have to customize something for an individual client's complex and ill-defined needs. To hackers these kinds of projects are the death of a thousand cuts.
The distinguishing feature of nasty little problems is that you don't learn anything from them. Writing a compiler is interesting because it teaches you what a compiler is. But writing an interface to a buggy piece of software doesn't teach you anything, because the bugs are random. [3] So it's not just fastidiousness that makes good hackers avoid nasty little problems. It's more a question of self-preservation. Working on nasty little problems makes you stupid. Good hackers avoid it for the same reason models avoid cheeseburgers. Of course some problems inherently have this character. And because of supply and demand, they pay especially well. So a company that found a way to get great hackers to work on tedious problems would be very successful. How would you do it? One place this happens is in startups. At our startup we had Robert Morris working as a system administrator. That's like having the Rolling Stones play at a bar mitzvah. You can't hire that kind of talent. But people will do any amount of drudgery for companies of which they're the founders. [4] Bigger companies solve the problem by partitioning the company. They get smart people to work for them by establishing a separate R&D department where employees don't have to work directly on customers' nasty little problems. [5] In this model, the research department functions like a mine. They produce new ideas; maybe the rest of the company will be able to use them. You may not have to go to this extreme. Bottom-up programming suggests another way to partition the company: have the smart people work as toolmakers. If your company makes software to do x, have one group that builds tools for writing software of that type, and another that uses these tools to write the applications. This way you might be able to get smart people to write 99% of your code, but still keep them almost as insulated from users as they would be in a traditional research department.
The toolmakers would have users, but they'd only be the company's own developers. [6] If Microsoft used this approach, their software wouldn't be so full of security holes, because the less smart people writing the actual applications wouldn't be doing low-level stuff like allocating memory. Instead of writing Word directly in C, they'd be plugging together big Lego blocks of Word-language. (Duplo, I believe, is the technical term.) Clumping Along with interesting problems, what good hackers like is other good hackers. Great hackers tend to clump together-- sometimes spectacularly so, as at Xerox Parc. So you won't attract good hackers in linear proportion to how good an environment you create for them. The tendency to clump means it's more like the square of the environment. So it's winner take all. At any given time, there are only about ten or twenty places where hackers most want to work, and if you aren't one of them, you won't just have fewer great hackers, you'll have zero. Having great hackers is not, by itself, enough to make a company successful. It works well for Google and ITA, which are two of the hot spots right now, but it didn't help Thinking Machines or Xerox. Sun had a good run for a while, but their business model is a down elevator. In that situation, even the best hackers can't save you. I think, though, that all other things being equal, a company that can attract great hackers will have a huge advantage. There are people who would disagree with this. When we were making the rounds of venture capital firms in the 1990s, several told us that software companies didn't win by writing great software, but through brand, and dominating channels, and doing the right deals. They really seemed to believe this, and I think I know why. I think what a lot of VCs are looking for, at least unconsciously, is the next Microsoft.
And of course if Microsoft is your model, you shouldn't be looking for companies that hope to win by writing great software. But VCs are mistaken to look for the next Microsoft, because no startup can be the next Microsoft unless some other company is prepared to bend over at just the right moment and be the next IBM. It's a mistake to use Microsoft as a model, because their whole culture derives from that one lucky break. Microsoft is a bad data point. If you throw them out, you find that good products do tend to win in the market. What VCs should be looking for is the next Apple, or the next Google. I think Bill Gates knows this. What worries him about Google is not the power of their brand, but the fact that they have better hackers. [7] Recognition So who are the great hackers? How do you know when you meet one? That turns out to be very hard. Even hackers can't tell. I'm pretty sure now that my friend Trevor Blackwell is a great hacker. You may have read on Slashdot how he made his own Segway. The remarkable thing about this project was that he wrote all the software in one day (in Python, incidentally). For Trevor, that's par for the course. But when I first met him, I thought he was a complete idiot. He was standing in Robert Morris's office babbling at him about something or other, and I remember standing behind him making frantic gestures at Robert to shoo this nut out of his office so we could go to lunch. Robert says he misjudged Trevor at first too. Apparently when Robert first met him, Trevor had just begun a new scheme that involved writing down everything about every aspect of his life on a stack of index cards, which he carried with him everywhere. He'd also just arrived from Canada, and had a strong Canadian accent and a mullet.
书呆子的复仇(第6部分,共9部分)
The problem is compounded by the fact that hackers, despite their reputation for social obliviousness, sometimes put a good deal of effort into seeming smart. When I was in grad school I used to hang around the MIT AI Lab occasionally. It was kind of intimidating at first. Everyone there spoke so fast. But after a while I learned the trick of speaking fast. You don't have to think any faster; just use twice as many words to say everything. With this amount of noise in the signal, it's hard to tell good hackers when you meet them. I can't tell, even now. You also can't tell from their resumes. It seems like the only way to judge a hacker is to work with him on something. And this is the reason that high-tech areas only happen around universities. The active ingredient here is not so much the professors as the students. Startups grow up around universities because universities bring together promising young people and make them work on the same projects. The smart ones learn who the other smart ones are, and together they cook up new projects of their own. Because you can't tell a great hacker except by working with him, hackers themselves can't tell how good they are. This is true to a degree in most fields. I've found that people who are great at something are not so much convinced of their own greatness as mystified at why everyone else seems so incompetent. But it's particularly hard for hackers to know how good they are, because it's hard to compare their work. This is easier in most other fields. In the hundred meters, you know in 10 seconds who's fastest. Even in math there seems to be a general consensus about which problems are hard to solve, and what constitutes a good solution. But hacking is like writing. Who can say which of two novels is better? Certainly not the authors. With hackers, at least, other hackers can tell. That's because, unlike novelists, hackers collaborate on projects.
When you get to hit a few difficult problems over the net at someone, you learn pretty quickly how hard they hit them back. But hackers can't watch themselves at work. So if you ask a great hacker how good he is, he's almost certain to reply, I don't know. He's not just being modest. He really doesn't know. And none of us know, except about people we've actually worked with. Which puts us in a weird situation: we don't know who our heroes should be. The hackers who become famous tend to become famous by random accidents of PR. Occasionally I need to give an example of a great hacker, and I never know who to use. The first names that come to mind always tend to be people I know personally, but it seems lame to use them. So, I think, maybe I should say Richard Stallman, or Linus Torvalds, or Alan Kay, or someone famous like that. But I have no idea if these guys are great hackers. I've never worked with them on anything. If there is a Michael Jordan of hacking, no one knows, including him. Cultivation Finally, the question the hackers have all been wondering about: how do you become a great hacker? I don't know if it's possible to make yourself into one. But it's certainly possible to do things that make you stupid, and if you can make yourself stupid, you can probably make yourself smart too. The key to being a good hacker may be to work on what you like. When I think about the great hackers I know, one thing they have in common is the extreme difficulty of making them work on anything they don't want to. I don't know if this is cause or effect; it may be both. To do something well you have to love it. So to the extent you can preserve hacking as something you love, you're likely to do it well. Try to keep the sense of wonder you had about programming at age 14. If you're worried that your current job is rotting your brain, it probably is.
The best hackers tend to be smart, of course, but that's true in a lot of fields. Is there some quality that's unique to hackers? I asked some friends, and the number one thing they mentioned was curiosity. I'd always supposed that all smart people were curious-- that curiosity was simply the first derivative of knowledge. But apparently hackers are particularly curious, especially about how things work. That makes sense, because programs are in effect giant descriptions of how things work. Several friends mentioned hackers' ability to concentrate-- their ability, as one put it, to "tune out everything outside their own heads.'' I've certainly noticed this. And I've heard several hackers say that after drinking even half a beer they can't program at all. So maybe hacking does require some special ability to focus. Perhaps great hackers can load a large amount of context into their head, so that when they look at a line of code, they see not just that line but the whole program around it. John McPhee wrote that Bill Bradley's success as a basketball player was due partly to his extraordinary peripheral vision. "Perfect'' eyesight means about 47 degrees of vertical peripheral vision. Bill Bradley had 70; he could see the basket when he was looking at the floor. Maybe great hackers have some similar inborn ability. (I cheat by using a very dense language, which shrinks the court.) This could explain the disconnect over cubicles. Maybe the people in charge of facilities, not having any concentration to shatter, have no idea that working in a cubicle feels to a hacker like having one's brain in a blender. (Whereas Bill, if the rumors of autism are true, knows all too well.) One difference I've noticed between great hackers and smart people in general is that hackers are more politically incorrect.
To the extent there is a secret handshake among good hackers, it's when they know one another well enough to express opinions that would get them stoned to death by the general public. And I can see why political incorrectness would be a useful quality in programming. Programs are very complex and, at least in the hands of good programmers, very fluid. In such situations it's helpful to have a habit of questioning assumptions. Can you cultivate these qualities? I don't know. But you can at least not repress them. So here is my best shot at a recipe. If it is possible to make yourself into a great hacker, the way to do it may be to make the following deal with yourself: you never have to work on boring projects (unless your family will starve otherwise), and in return, you'll never allow yourself to do a half-assed job. All the great hackers I know seem to have made that deal, though perhaps none of them had any choice in the matter. Notes [1] In fairness, I have to say that IBM makes decent hardware. I wrote this on an IBM laptop. [2] They did turn out to be doomed. They shut down a few months later. [3] I think this is what people mean when they talk about the "meaning of life." On the face of it, this seems an odd idea. Life isn't an expression; how could it have meaning? But it can have a quality that feels a lot like meaning. In a project like a compiler, you have to solve a lot of problems, but the problems all fall into a pattern, as in a signal. Whereas when the problems you have to solve are random, they seem like noise. [4] Einstein at one point worked designing refrigerators. (He had equity.) [5] It's hard to say exactly what constitutes research in the computer world, but as a first approximation, it's software that doesn't have users. I don't think it's publication that makes the best hackers want to work in research departments.
I think it's mainly not having to have a three hour meeting with a product manager about problems integrating the Korean version of Word 13.27 with the talking paperclip. [6] Something similar has been happening for a long time in the construction industry. When you had a house built a couple hundred years ago, the local builders built everything in it. But increasingly what builders do is assemble components designed and manufactured by someone else. This has, like the arrival of desktop publishing, given people the freedom to experiment in disastrous ways, but it is certainly more efficient. [7] Google is much more dangerous to Microsoft than Netscape was. Probably more dangerous than any other company has ever been. Not least because they're determined to fight. On their job listing page, they say that one of their "core values'' is "Don't be evil.'' From a company selling soybean oil or mining equipment, such a statement would merely be eccentric. But I think all of us in the computer world recognize who that is a declaration of war on. Thanks to Jessica Livingston, Robert Morris, and Sarah Harlin for reading earlier versions of this talk.
| Audio of talk | | | The Python Paradox | Japanese Translation | | | Russian Translation | Italian Translation | | | Spanish Translation.
If you liked this, you may also like _Hackers & Painters_.
If you liked this, you may also like _Hackers & Painters_.
Want to start a startup? Get funded by Y Combinator.
May 2004 _(This essay was originally published inHackers & Painters.) _ If you wanted to get rich, how would you do it? I think your best bet would be to start or join a startup. That's been a reliable way to get rich for hundreds of years. The word "startup" dates from the 1960s, but what happens in one is very similar to the venture-backed trading voyages of the Middle Ages. Startups usually involve technology, so much so that the phrase "high-tech startup" is almost redundant. A startup is a small company that takes on a hard technical problem. Lots of people get rich knowing nothing more than that. You don't have to know physics to be a good pitcher. But I think it could give you an edge to understand the underlying principles. Why do startups have to be small? Will a startup inevitably stop being a startup as it grows larger? And why do they so often work on developing new technology? Why are there so many startups selling new drugs or computer software, and none selling corn oil or laundry detergent? The Proposition Economically, you can think of a startup as a way to compress your whole working life into a few years. Instead of working at a low intensity for forty years, you work as hard as you possibly can for four. This pays especially well in technology, where you earn a premium for working fast. Here is a brief sketch of the economic proposition. If you're a good hacker in your mid twenties, you can get a job paying about $80,000 per year. So on average such a hacker must be able to do at least $80,000 worth of work per year for the company just to break even.
You could probably work twice as many hours as a corporate employee, and if you focus you can probably get three times as much done in an hour. [1] You should get another multiple of two, at least, by eliminating the drag of the pointy-haired middle manager who would be your boss in a big company. Then there is one more multiple: how much smarter are you than your job description expects you to be? Suppose another multiple of three. Combine all these multipliers, and I'm claiming you could be 36 times more productive than you're expected to be in a random corporate job. [2] If a fairly good hacker is worth $80,000 a year at a big company, then a smart hacker working very hard without any corporate bullshit to slow him down should be able to do work worth about $3 million a year. Like all back-of-the-envelope calculations, this one has a lot of wiggle room. I wouldn't try to defend the actual numbers. But I stand by the structure of the calculation. I'm not claiming the multiplier is precisely 36, but it is certainly more than 10, and probably rarely as high as 100. If $3 million a year seems high, remember that we're talking about the limit case: the case where you not only have zero leisure time but indeed work so hard that you endanger your health. Startups are not magic. They don't change the laws of wealth creation. They just represent a point at the far end of the curve. There is a conservation law at work here: if you want to make a million dollars, you have to endure a million dollars' worth of pain. For example, one way to make a million dollars would be to work for the Post Office your whole life, and save every penny of your salary. Imagine the stress of working for the Post Office for fifty years. In a startup you compress all this stress into three or four years. You do tend to get a certain bulk discount if you buy the economy-size pain, but you can't evade the fundamental conservation law.
If starting a startup were easy, everyone would do it. Millions, not Billions If $3 million a year seems high to some people, it will seem low to others. Three _million?_ How do I get to be a billionaire, like Bill Gates? So let's get Bill Gates out of the way right now. It's not a good idea to use famous rich people as examples, because the press only write about the very richest, and these tend to be outliers. Bill Gates is a smart, determined, and hardworking man, but you need more than that to make as much money as he has. You also need to be very lucky. There is a large random factor in the success of any company. So the guys you end up reading about in the papers are the ones who are very smart, totally dedicated, _and_ win the lottery. Certainly Bill is smart and dedicated, but Microsoft also happens to have been the beneficiary of one of the most spectacular blunders in the history of business: the licensing deal for DOS. No doubt Bill did everything he could to steer IBM into making that blunder, and he has done an excellent job of exploiting it, but if there had been one person with a brain on IBM's side, Microsoft's future would have been very different. Microsoft at that stage had little leverage over IBM. They were effectively a component supplier. If IBM had required an exclusive license, as they should have, Microsoft would still have signed the deal. It would still have meant a lot of money for them, and IBM could easily have gotten an operating system elsewhere. Instead IBM ended up using all its power in the market to give Microsoft control of the PC standard. From that point, all Microsoft had to do was execute. They never had to bet the company on a bold decision. All they had to do was play hardball with licensees and copy more innovative products reasonably promptly. If IBM hadn't made this mistake, Microsoft would still have been a successful company, but it could not have grown so big so fast.
Bill Gates would be rich, but he'd be somewhere near the bottom of the Forbes 400 with the other guys his age. There are a lot of ways to get rich, and this essay is about only one of them. This essay is about how to make money by creating wealth and getting paid for it. There are plenty of other ways to get money, including chance, speculation, marriage, inheritance, theft, extortion, fraud, monopoly, graft, lobbying, counterfeiting, and prospecting. Most of the greatest fortunes have probably involved several of these. The advantage of creating wealth, as a way to get rich, is not just that it's more legitimate (many of the other methods are now illegal) but that it's more _straightforward._ You just have to do something people want. Money Is Not Wealth If you want to create wealth, it will help to understand what it is. Wealth is not the same thing as money. [3] Wealth is as old as human history. Far older, in fact; ants have wealth. Money is a comparatively recent invention. Wealth is the fundamental thing. Wealth is stuff we want: food, clothes, houses, cars, gadgets, travel to interesting places, and so on. You can have wealth without having money. If you had a magic machine that could on command make you a car or cook you dinner or do your laundry, or do anything else you wanted, you wouldn't need money. Whereas if you were in the middle of Antarctica, where there is nothing to buy, it wouldn't matter how much money you had. Wealth is what you want, not money. But if wealth is the important thing, why does everyone talk about making money? It is a kind of shorthand: money is a way of moving wealth, and in practice they are usually interchangeable. But they are not the same thing, and unless you plan to get rich by counterfeiting, talking about _making money_ can make it harder to understand how to make money. Money is a side effect of specialization.
In a specialized society, most of the things you need, you can't make for yourself. If you want a potato or a pencil or a place to live, you have to get it from someone else. How do you get the person who grows the potatoes to give you some? By giving him something he wants in return. But you can't get very far by trading things directly with the people who need them. If you make violins, and none of the local farmers wants one, how will you eat? The solution societies find, as they get more specialized, is to make the trade into a two-step process. Instead of trading violins directly for potatoes, you trade violins for, say, silver, which you can then trade again for anything else you need. The intermediate stuff-- the _medium of exchange_ \-- can be anything that's rare and portable. Historically metals have been the most common, but recently we've been using a medium of exchange, called the _dollar_ , that doesn't physically exist. It works as a medium of exchange, however, because its rarity is guaranteed by the U.S. Government. The advantage of a medium of exchange is that it makes trade work. The disadvantage is that it tends to obscure what trade really means. People think that what a business does is make money. But money is just the intermediate stage-- just a shorthand-- for whatever people want. What most businesses really do is make wealth. They do something people want. [4] The Pie Fallacy A surprising number of people retain from childhood the idea that there is a fixed amount of wealth in the world. There is, in any normal family, a fixed amount of _money_ at any moment. But that's not the same thing. When wealth is talked about in this context, it is often described as a pie. "You can't make the pie larger," say politicians. When you're talking about the amount of money in one family's bank account, or the amount available to a government from one year's tax revenue, this is true.
If one person gets more, someone else has to get less. I can remember believing, as a child, that if a few rich people had all the money, it left less for everyone else. Many people seem to continue to believe something like this well into adulthood. This fallacy is usually there in the background when you hear someone talking about how x percent of the population have y percent of the wealth. If you plan to start a startup, then whether you realize it or not, you're planning to disprove the Pie Fallacy. What leads people astray here is the abstraction of money. Money is not wealth. It's just something we use to move wealth around. So although there may be, in certain specific moments (like your family, this month) a fixed amount of money available to trade with other people for things you want, there is not a fixed amount of wealth in the world. _You can make more wealth._ Wealth has been getting created and destroyed (but on balance, created) for all of human history. Suppose you own a beat-up old car. Instead of sitting on your butt next summer, you could spend the time restoring your car to pristine condition. In doing so you create wealth. The world is-- and you specifically are-- one pristine old car the richer. And not just in some metaphorical way. If you sell your car, you'll get more for it. In restoring your old car you have made yourself richer. You haven't made anyone else poorer. So there is obviously not a fixed pie. And in fact, when you look at it this way, you wonder why anyone would think there was. [5] Kids know, without knowing they know, that they can create wealth. If you need to give someone a present and don't have any money, you make one. But kids are so bad at making things that they consider home-made presents to be a distinct, inferior, sort of thing to store-bought ones-- a mere expression of the proverbial thought that counts.
And indeed, the lumpy ashtrays we made for our parents did not have much of a resale market. Craftsmen The people most likely to grasp that wealth can be created are the ones who are good at making things, the craftsmen. Their hand-made objects become store-bought ones. But with the rise of industrialization there are fewer and fewer craftsmen. One of the biggest remaining groups is computer programmers. A programmer can sit down in front of a computer and _create wealth_. A good piece of software is, in itself, a valuable thing. There is no manufacturing to confuse the issue. Those characters you type are a complete, finished product. If someone sat down and wrote a web browser that didn't suck (a fine idea, by the way), the world would be that much richer. [5b] Everyone in a company works together to create wealth, in the sense of making more things people want. Many of the employees (e.g. the people in the mailroom or the personnel department) work at one remove from the actual making of stuff. Not the programmers. They literally think the product, one line at a time. And so it's clearer to programmers that wealth is something that's made, rather than being distributed, like slices of a pie, by some imaginary Daddy. It's also obvious to programmers that there are huge variations in the rate at which wealth is created. At Viaweb we had one programmer who was a sort of monster of productivity. I remember watching what he did one long day and estimating that he had added several hundred thousand dollars to the market value of the company. A great programmer, on a roll, could create a million dollars worth of wealth in a couple weeks. A mediocre programmer over the same period will generate zero or even negative wealth (e.g. by introducing bugs). This is why so many of the best programmers are libertarians. In our world, you sink or swim, and there are no excuses.
(以下为直接翻译结果,保留HTML格式)
When those far removed from the creation of wealth-- undergraduates, reporters, politicians-- hear that the richest 5% of the people have half the total wealth, they tend to think _injustice!_ An experienced programmer would be more likely to think _is that all?_ The top 5% of programmers probably write 99% of the good software. Wealth can be created without being sold. Scientists, till recently at least, effectively donated the wealth they created. We are all richer for knowing about penicillin, because we're less likely to die from infections. Wealth is whatever people want, and not dying is certainly something we want. Hackers often donate their work by writing open source software that anyone can use for free. I am much the richer for the operating system FreeBSD, which I'm running on the computer I'm using now, and so is Yahoo, which runs it on all their servers. What a Job Is In industrialized countries, people belong to one institution or another at least until their twenties. After all those years you get used to the idea of belonging to a group of people who all get up in the morning, go to some set of buildings, and do things that they do not, ordinarily, enjoy doing. Belonging to such a group becomes part of your identity: name, age, role, institution. If you have to introduce yourself, or someone else describes you, it will be as something like, John Smith, age 10, a student at such and such elementary school, or John Smith, age 20, a student at such and such college. When John Smith finishes school he is expected to get a job. And what getting a job seems to mean is joining another institution. Superficially it's a lot like college. You pick the companies you want to work for and apply to join them. If one likes you, you become a member of this new group. You get up in the morning and go to a new set of buildings, and do things that you do not, ordinarily, enjoy doing.
There are a few differences: life is not as much fun, and you get paid, instead of paying, as you did in college. But the similarities feel greater than the differences. John Smith is now John Smith, 22, a software developer at such and such corporation. In fact John Smith's life has changed more than he realizes. Socially, a company looks much like college, but the deeper you go into the underlying reality, the more different it gets. What a company does, and has to do if it wants to continue to exist, is earn money. And the way most companies make money is by creating wealth. Companies can be so specialized that this similarity is concealed, but it is not only manufacturing companies that create wealth. A big component of wealth is location. Remember that magic machine that could make you cars and cook you dinner and so on? It would not be so useful if it delivered your dinner to a random location in central Asia. If wealth means what people want, companies that move things also create wealth. Ditto for many other kinds of companies that don't make anything physical. Nearly all companies exist to do something people want. And that's what you do, as well, when you go to work for a company. But here there is another layer that tends to obscure the underlying reality. In a company, the work you do is averaged together with a lot of other people's. You may not even be aware you're doing something people want. Your contribution may be indirect. But the company as a whole must be giving people something they want, or they won't make any money. And if they are paying you x dollars a year, then on average you must be contributing at least x dollars a year worth of work, or the company will be spending more than it makes, and will go out of business. Someone graduating from college thinks, and is told, that he needs to get a job, as if the important thing were becoming a member of an institution.
A more direct way to put it would be: you need to start doing something people want. You don't need to join a company to do that. All a company is is a group of people working together to do something people want. It's doing something people want that matters, not joining the group. [6] For most people the best plan probably is to go to work for some existing company. But it is a good idea to understand what's happening when you do this. A job means doing something people want, averaged together with everyone else in that company. Working Harder That averaging gets to be a problem. I think the single biggest problem afflicting large companies is the difficulty of assigning a value to each person's work. For the most part they punt. In a big company you get paid a fairly predictable salary for working fairly hard. You're expected not to be obviously incompetent or lazy, but you're not expected to devote your whole life to your work. It turns out, though, that there are economies of scale in how much of your life you devote to your work. In the right kind of business, someone who really devoted himself to work could generate ten or even a hundred times as much wealth as an average employee. A programmer, for example, instead of chugging along maintaining and updating an existing piece of software, could write a whole new piece of software, and with it create a new source of revenue. Companies are not set up to reward people who want to do this. You can't go to your boss and say, I'd like to start working ten times as hard, so will you please pay me ten times as much? For one thing, the official fiction is that you are already working as hard as you can. But a more serious problem is that the company has no way of measuring the value of your work. Salesmen are an exception. It's easy to measure how much revenue they generate, and they're usually paid a percentage of it.
If a salesman wants to work harder, he can just start doing it, and he will automatically get paid proportionally more. There is one other job besides sales where big companies can hire first-rate people: in the top management jobs. And for the same reason: their performance can be measured. The top managers are held responsible for the performance of the entire company. Because an ordinary employee's performance can't usually be measured, he is not expected to do more than put in a solid effort. Whereas top management, like salespeople, have to actually come up with the numbers. The CEO of a company that tanks cannot plead that he put in a solid effort. If the company does badly, he's done badly. A company that could pay all its employees so straightforwardly would be enormously successful. Many employees would work harder if they could get paid for it. More importantly, such a company would attract people who wanted to work especially hard. It would crush its competitors. Unfortunately, companies can't pay everyone like salesmen. Salesmen work alone. Most employees' work is tangled together. Suppose a company makes some kind of consumer gadget. The engineers build a reliable gadget with all kinds of new features; the industrial designers design a beautiful case for it; and then the marketing people convince everyone that it's something they've got to have. How do you know how much of the gadget's sales are due to each group's efforts? Or, for that matter, how much is due to the creators of past gadgets that gave the company a reputation for quality? There's no way to untangle all their contributions. Even if you could read the minds of the consumers, you'd find these factors were all blurred together. If you want to go faster, it's a problem to have your work tangled together with a large number of other people's.
In a large group, your performance is not separately measurable-- and the rest of the group slows you down. Measurement and Leverage To get rich you need to get yourself in a situation with two things, measurement and leverage. You need to be in a position where your performance can be measured, or there is no way to get paid more by doing more. And you have to have leverage, in the sense that the decisions you make have a big effect. Measurement alone is not enough. An example of a job with measurement but not leverage is doing piecework in a sweatshop. Your performance is measured and you get paid accordingly, but you have no scope for decisions. The only decision you get to make is how fast you work, and that can probably only increase your earnings by a factor of two or three. An example of a job with both measurement and leverage would be lead actor in a movie. Your performance can be measured in the gross of the movie. And you have leverage in the sense that your performance can make or break it. CEOs also have both measurement and leverage. They're measured, in that the performance of the company is their performance. And they have leverage in that their decisions set the whole company moving in one direction or another. I think everyone who gets rich by their own efforts will be found to be in a situation with measurement and leverage. Everyone I can think of does: CEOs, movie stars, hedge fund managers, professional athletes. A good hint to the presence of leverage is the possibility of failure. Upside must be balanced by downside, so if there is big potential for gain there must also be a terrifying possibility of loss. CEOs, stars, fund managers, and athletes all live with the sword hanging over their heads; the moment they start to suck, they're out. If you're in a job that feels safe, you are not going to get rich, because if there is no danger there is almost certainly no leverage.
But you don't have to become a CEO or a movie star to be in a situation with measurement and leverage. All you need to do is be part of a small group working on a hard problem. Smallness = Measurement If you can't measure the value of the work done by individual employees, you can get close. You can measure the value of the work done by small groups. One level at which you can accurately measure the revenue generated by employees is at the level of the whole company. When the company is small, you are thereby fairly close to measuring the contributions of individual employees. A viable startup might only have ten employees, which puts you within a factor of ten of measuring individual effort. Starting or joining a startup is thus as close as most people can get to saying to one's boss, I want to work ten times as hard, so please pay me ten times as much. There are two differences: you're not saying it to your boss, but directly to the customers (for whom your boss is only a proxy after all), and you're not doing it individually, but along with a small group of other ambitious people. It will, ordinarily, be a group. Except in a few unusual kinds of work, like acting or writing books, you can't be a company of one person. And the people you work with had better be good, because it's their work that yours is going to be averaged with. A big company is like a giant galley driven by a thousand rowers. Two things keep the speed of the galley down. One is that individual rowers don't see any result from working harder. The other is that, in a group of a thousand people, the average rower is likely to be pretty average. If you took ten people at random out of the big galley and put them in a boat by themselves, they could probably go faster. They would have both carrot and stick to motivate them. An energetic rower would be encouraged by the thought that he could have a visible effect on the speed of the boat.
And if someone was lazy, the others would be more likely to notice and complain. But the real advantage of the ten-man boat shows when you take the ten _best_ rowers out of the big galley and put them in a boat together. They will have all the extra motivation that comes from being in a small group. But more importantly, by selecting that small a group you can get the best rowers. Each one will be in the top 1%. It's a much better deal for them to average their work together with a small group of their peers than to average it with everyone. That's the real point of startups. Ideally, you are getting together with a group of other people who also want to work a lot harder, and get paid a lot more, than they would in a big company. And because startups tend to get founded by self-selecting groups of ambitious people who already know one another (at least by reputation), the level of measurement is more precise than you get from smallness alone. A startup is not merely ten people, but ten people like you. Steve Jobs once said that the success or failure of a startup depends on the first ten employees. I agree. If anything, it's more like the first five. Being small is not, in itself, what makes startups kick butt, but rather that small groups can be select. You don't want small in the sense of a village, but small in the sense of an all-star team. The larger a group, the closer its average member will be to the average for the population as a whole. So all other things being equal, a very able person in a big company is probably getting a bad deal, because his performance is dragged down by the overall lower performance of the others. Of course, all other things often are not equal: the able person may not care about money, or may prefer the stability of a large company.
想创业? 获得Y Combinator的资助。
2004年5月 _(本文最初发表于《黑客与画家》Hackers & Painters。)_ 如果你想致富,该怎么做?我认为最好的选择是创办或加入一家创业公司。几个世纪以来,这始终是可靠的致富途径。"创业公司"一词源于20世纪60年代,但其本质与中世纪那些由风险资本支持的贸易航行极为相似。 创业公司通常涉及技术,以至于"高科技创业公司"几乎成了冗余表达。创业公司就是致力于解决棘手技术问题的小公司。 许多人仅凭这一点就致富了。你不需要懂物理也能成为优秀的投球手。但我认为,理解底层原理会让你更具优势。为什么创业公司必须是小公司?随着规模扩大,创业公司是否必然会失去创业特质?为什么它们总在开发新技术?为什么有那么多创业公司销售新药或计算机软件,却没有一家卖玉米油或洗衣粉? 命题 从经济角度看,你可以把创业公司视为将整个职业生涯压缩到短短几年的方式。与其以低强度工作四十年,不如全力以赴工作四年。这在技术领域尤其划算,因为快速工作能带来溢价。 以下是经济命题的简要说明:假设你是一名25岁左右的优秀黑客,年薪约8万美元。这样的黑客平均每年至少要为公司创造8万美元的价值才能收支平衡。你或许能比普通企业员工多工作两倍时间,如果专注,每小时效率可能提高三倍。[1] 再乘以至少两倍——因为摆脱了大公司里那些指手画脚的中层管理者。还有另一个乘数:你比岗位要求的聪明多少?假设再乘以三。综合这些因素,我认为你的生产力可能达到普通公司职位的36倍。[2] 如果一名优秀黑客在大公司值8万美元年薪,那么一个聪明黑客在不被公司官僚拖累的情况下拼命工作,每年应能创造约300万美元的价值。 如同所有粗略估算,这个数字有很大浮动空间。我不会为具体数字辩护,但坚持计算框架。乘数不一定是精确的36,但肯定超过10,也很少达到100。 如果一年300万美元看起来太高,请记住我们讨论的是极限情况:不仅没有闲暇,甚至要拼命工作到危及健康。 创业公司并非魔法,它没有改变财富创造的规律,只是代表了曲线远端的一个点。这里存在守恒定律:想赚100万美元,就得承受价值100万美元的痛苦。比如,你可以选择在邮局工作一辈子,省下每一分钱来攒够100万。想象在邮局忍受50年压力的感觉。创业则是将所有这些压力压缩到三四年。批量购买痛苦确实能享受折扣,但无法逃避根本的守恒定律。如果创业很容易,所有人都会去做。 百万而非十亿 对某些人来说,一年300万很高,但对另一些人则显得太低。300万?怎样才能像比尔·盖茨那样成为亿万富翁? 让我们先放下比尔·盖茨的例子。用著名富豪当榜样并不明智,因为媒体只报道最顶尖的富豪,而他们往往是异常值。比尔·盖茨聪明、坚定且勤奋,但仅凭这些无法积累他那样的财富,还需要极大的运气。 任何公司的成功都有很大的随机因素。因此,你最终在报纸上读到的人,都是那些极其聪明、完全投入且中了彩票的家伙。比尔确实聪明勤奋,但微软也恰好受益于商业史上最惊人的失误之一:DOS的授权协议。尽管比尔竭尽全力引导IBM犯下这个错误,并出色地利用了它,但如果IBM那边有哪怕一个明白人,微软的命运将截然不同。当时的微软对IBM几乎没有议价能力,他们本质上是个组件供应商。如果IBM要求独占授权(本该如此),微软仍会签约。这对他们仍意味巨额收入,而IBM本可轻松从别处获得操作系统。 结果IBM用尽市场力量,反而让微软控制了PC标准。此后微软只需执行即可,再无需为公司命运押注大胆决策,只需强硬对待被许可方,并及时复制更具创新性的产品。 如果IBM没犯这个错,微软仍会是成功的公司,但不会如此迅速地壮大。比尔·盖茨会富有,但只会与其他同龄人一起排在福布斯400强的末尾。 致富途径很多,本文只讨论其中一种:通过创造财富并获取报酬来赚钱。其他方式包括运气、投机、婚姻、继承、盗窃、勒索、欺诈、垄断、贪污、游说、伪造和勘探。多数巨额财富可能涉及其中多项。 创造财富作为致富方式的优势,不仅在于其更合法(许多其他方法现已非法),更在于其直接性。你只需做人们需要的事。 金钱≠财富 要创造财富,需先理解其本质。财富不同于金钱。[3] 财富与人类历史一样古老,事实上更古老——蚂蚁也有财富。金钱则是相对近期的发明。 财富是根本。财富是我们需要的东西:食物、衣服、房子、汽车、小工具、去有趣的地方旅行等。没有金钱也能拥有财富。假设有台魔法机器能按需为你造车、做饭、洗衣或做任何事,你就不需要钱。而如果你身处南极,无处购物,有多少钱都毫无意义。 财富才是你想要的,而非金钱。但如果财富如此重要,为何人人谈论赚钱?这是一种简写:金钱是转移财富的手段,实践中二者通常可互换。但它们并非同一事物,除非你打算靠伪造致富,否则谈论"赚钱"会妨碍理解生财之道。 金钱是专业化的副产品。在专业化社会里,多数所需之物无法自己生产。想要土豆、铅笔或住所,必须从他人那里获取。 如何让种土豆的人给你一些?用他想要的东西交换。但直接与需求方交易很难走远。如果你制作小提琴,而当地农民没人需要,你如何吃饭? 随着社会日趋专业化,解决方案是将交易分为两步:先用小提琴换取白银,再用白银换其他所需。中间物——交换媒介——可以是任何稀有且便携的东西。历史上金属最常见,但近来我们使用一种物理上不存在的交换媒介——美元。它之所以能作为交换媒介,是因为其稀有性由美国政府担保。 交换媒介的优点是促成交易,缺点是容易掩盖交易的真正意义。人们以为企业做的就是赚钱。但金钱只是中间阶段——只是人们所需之物的简写。多数企业实际创造的是财富,它们做人们需要的事。[4] 馅饼谬误 令人惊讶的是,许多人从小保留了一种观念:世界上的财富总量是固定的。任何普通家庭在特定时刻的金钱数量确实是固定的,但二者不同。 在此语境下讨论财富时,常被比作馅饼。"你无法把馅饼做大",政客们说。当谈论一个家庭银行账户的金额或政府一年税收时,这没错。若某人多得,他人必少得。 我记得小时候相信,如果少数富人占有所有钱,其他人得到的就少了。许多人似乎直到成年仍持类似观点。当你听到"x%人口占有y%财富"时,这种谬误通常潜伏在背景中。若你计划创业,无论是否意识到,你都打算反驳这个馅饼谬误。 让人误入歧途的是金钱的抽象性。金钱不是财富,只是转移财富的工具。因此,尽管在某些特定时刻(如你家本月)可用于交换所需之物的金钱量固定,但世界上的财富总量并非固定。你可以创造更多财富。整个人类历史中,财富始终在被创造和毁灭(但总体是创造)。 假设你有一辆破旧的老车。与其明年夏天无所事事,不如花时间将其修复如新。这样你就创造了财富。世界——具体而言是你——多了一辆完好的老车。这不只是比喻:如果你卖车,会得到更多钱。 通过修复旧车,你让自己更富有,但没让任何人更穷。显然不存在固定馅饼。事实上,这样想时,你会奇怪为何有人觉得存在。[5] 孩子们无意识地明白自己能创造财富。如果需要送人礼物又没钱,就亲手做一个。但孩子们手艺太差,自制礼物被视为与商店买的不同且低劣——只是俗话"礼轻情意重"的表现。确实,我们为父母制作的凹凸不平的烟灰缸几乎没有转售价值。 手艺人 最可能理解财富可被创造的人,是那些擅长制作的手艺人。他们的手工制品变成了商店商品。但随着工业化兴起,手艺人越来越少。目前最大的群体之一是程序员。 程序员可以坐在电脑前直接创造财富。一个好的软件本身就是有价值的东西。没有制造环节混淆问题,你输入的字符就是完整成品。如果有人写出不烂的网页浏览器(顺便说,这想法不错),世界就会更富有。[5b] 公司里每个人都共同创造财富——即制作更多人们需要的东西。许多员工(如收发室或人事部)与实际制作隔了一层。程序员则不然,他们逐行构建产品。因此程序员更清楚财富是被创造的,而非像分馅饼那样由某个想象中的"爸爸"分配。 程序员也清楚财富创造速率差异巨大。在Viaweb,我们有个生产力惊人的程序员。我记得观察他某天的工作,估计他为公司增加了数十万美元市值。一个进入状态的高手程序员,两周就能创造价值百万美元的财富。而平庸程序员同期可能产出为零甚至负财富(比如引入漏洞)。 这就是为何许多顶尖程序员是自由主义者。在我们的世界,成王败寇,没有借口。那些远离财富创造的人——本科生、记者、政客——听说最富有的5%人口拥有半数财富时,往往认为"不公!"而有经验的程序员更可能想"就这?"顶尖5%的程序员可能写出了99%的优秀软件。 财富可不经出售就被创造。至少直到最近,科学家们实际上捐赠了他们创造的财富。知道青霉素让我们都更富有,因为我们更不易死于感染。财富就是人们想要的东西,不想死当然是我们想要的。黑客常通过编写开源软件捐赠劳动,供人免费使用。FreeBSD操作系统让我富有得多,我现在用的电脑就运行它,雅虎所有服务器也用这个系统。 工作的本质 在工业化国家,人们至少二十岁前都属于某个机构。经过这些年,你已习惯这样的观念:属于某个群体,大家早晨起床,去某些建筑,做通常并不享受的事。成为这种群体的一部分成了你身份的一部分:姓名、年龄、角色、机构。介绍自己或被描述时,你会是"约翰·史密斯,10岁,某小学学生"或"约翰·史密斯,20岁,某大学学生"。 约翰·史密斯毕业后应该"找工作"。而找工作似乎意味着加入另一个机构。表面看很像大学:挑选想去的公司申请加入。如果一家公司喜欢你,你就成为这个新群体的一员。早晨起床去新建筑,做通常并不享受的事。有些区别:生活没那么有趣,而且你获得报酬而非像大学时那样付钱。但相似感大于差异感。约翰·史密斯现在是"约翰·史密斯,22岁,某公司软件开发者"。 实际上约翰·史密斯的生活变化比他意识到的更大。社交上,公司看起来很像大学,但越是深入底层现实,差异就越大。 公司所做的——也是其存续必须做的——是赚钱。而多数公司赚钱的方式是创造财富。公司可能高度专业化,掩盖了这点,但创造财富的不只是制造公司。位置是财富的重要组成部分。记得那台能造车、做饭等的魔法机器吗?如果它把晚餐送到中亚随机地点,就没那么有用了。如果财富意味着人们所需,那么搬运物品的公司也创造财富。其他许多不制造实物的公司亦然。几乎所有公司都为做人们需要的事而存在。 这也是你为公司工作时做的事。但这里有另一层掩盖了底层现实:在公司里,你的工作与许多其他人的工作被平均。你甚至可能没意识到自己在做人们需要的事,贡献可能是间接的。但公司整体必须提供人们所需,否则赚不到钱。如果他们每年付你x美元,平均而言你每年必须贡献至少价值x美元的工作,否则公司将入不敷出,走向倒闭。 大学毕业生被告知需要"找工作",仿佛重要的是成为机构成员。更直接的说法是:你需要开始做人们需要的事。为此不必加入公司。公司只是一群人共同做人们需要的事。重要的是做人们需要的事,而非加入群体。[6] 对多数人,最佳方案可能是为现有公司工作。但有必要理解这么做的实质。工作意味着做人们需要的事,与公司里其他人取平均。 更努力工作 这种平均成了问题。我认为大公司最大的问题是难以衡量每个人的工作价值。多数情况下他们选择回避。在大公司,你努力工作获得相当可预测的薪水。公司期望你不明显无能或懒惰,但不期望全身心投入工作。 然而,事实证明,在投入工作的生命比例上存在规模经济。在合适的业务中,真正全身心投入的人能创造普通员工十倍甚至百倍的财富。例如程序员可以不满足于维护更新现有软件,而是编写全新软件,创造新收入来源。 公司并不设置来奖励想这么做的人。你不能对老板说:"我想十倍努力工作,请付我十倍薪水。"一方面,官方说法是你已在全力工作。更严重的问题是公司无法衡量你工作的价值。 销售是例外。他们创造的收入容易衡量,通常按比例获得报酬。如果销售想更努力,直接去做就会自动获得更多报酬。 除销售外,大公司还能在一类职位雇佣一流人才:高层管理。原因相同:绩效可衡量。高层管理者对整个公司绩效负责。由于普通员工绩效通常无法衡量,公司只期望他们稳定努力。而高层如销售,必须拿出数字。公司垮台的CEO不能辩称自己已尽力。公司表现差就是他的失败。 能如此直接支付所有员工的公司将极为成功。许多员工若因努力工作获得报酬,会更努力。更重要的是,这种公司将吸引特别想努力工作的人,碾压竞争对手。 不幸的是,公司无法像对待销售那样支付所有人。销售独立工作,多数员工的工作交织在一起。假设公司生产某种消费电子产品:工程师打造可靠且功能新颖的产品;工业设计师设计精美外壳;营销人员说服人们这是必需品。你如何知道销售额有多少归功于哪组人?或有多少归功于过去产品建立的质量声誉?无法厘清所有贡献。即使能读懂消费者心思,也会发现这些因素全部模糊交织。 如果想更快,工作与大量他人交织是个问题。在大群体中,你的绩效无法单独衡量——且群体其他人会拖慢你。 可衡量性与杠杆效应 要致富,你需要置身于具备两点的情境:可衡量性与杠杆效应。你需要处于绩效可被衡量的位置,否则无法通过多做获得更多报酬。你还必须有杠杆效应,即你的决策能产生重大影响。 仅有可衡量性不够。血汗工厂的计件工作有可衡量性但无杠杆效应。绩效被衡量并相应获得报酬,但你没有决策空间。唯一能做的决策是工作速度,这可能只能让收入增加两三倍。 兼具可衡量性与杠杆效应的例子是电影主演。绩效可由票房衡量,且你有杠杆效应——表演能成就或毁掉电影。 CEO也兼具二者。他们被衡量,因为公司表现即其表现;他们有杠杆效应,因为决策让整个公司朝某个方向前进。 我认为所有白手起家的富人都会处于兼具可衡量性与杠杆效应的情境。我能想到的所有人都如此:CEO、明星、对冲基金经理、职业运动员。杠杆效应的强烈暗示是失败的可能性。收益必有风险平衡,因此若有巨大获利潜力,也必有可怕的损失可能。CEO、明星、基金经理和运动员都生活在头顶悬剑中;一旦开始糟糕,他们就出局。如果你处于感觉安全的工作,就不会致富,因为无危险几乎必然无杠杆效应。 但你不必成为CEO或明星就能处于兼具二者的情境。只需加入致力于难题的小团队。 小=可衡量性 如果无法衡量单个员工的工作价值,可以接近。你可以衡量小团队的工作价值。 能准确衡量员工创造收入的层级是整个公司。公司越小时,你就越接近衡量个人贡献。一个可行的创业公司可能只有十名员工,让你在十倍范围内衡量个人努力。 因此,创办或加入创业公司是多数人最接近对老板说"我想十倍努力工作,请付我十倍薪水"的方式。区别有两点:你不是对老板说,而是直接对客户说(毕竟老板只是代理);你不是单独做,而是与其他有雄心的少数人一起。 通常需要一个团队。除表演或写书等少数特殊工作外,一人无法成公司。同事最好优秀,因为你的工作将与他们的平均。 大公司像由千名桨手驱动的大船。两件事让船速下降:一是单个桨手努力工作看不到结果;二是在千人中,普通桨手很可能相当普通。 如果随机从大船抽出十人放入小船,他们可能更快。他们有胡萝卜加大棒作为动力:活力充沛的桨手会因自己对船速的可见影响而受鼓舞;如果有人懒惰,其他人更容易注意到并抱怨。 但十人小船的真正优势在于:当你从大船选出十名最佳桨手放入小船时,他们不仅有小群体带来的额外动力,更重要的是,通过如此精选,你能得到顶尖桨手。每个人都处于前1%。与同级别小群体平均工作成果,远比与所有人平均好得多。 这才是创业公司的真正意义。理想情况下,你与一群同样想比在大公司更努力、获得更多报酬的人共事。由于创业公司往往由自我筛选的雄心群体(至少通过声誉了解彼此)创立,可衡量性比仅靠小规模更精确。创业公司不只是十个人,而是十个像你这样的人。 史蒂夫·乔布斯曾说创业公司的成败取决于前十名员工。我同意。如果有什么区别,更像是前五名。小规模本身不是创业公司成功的原因,而是小群体可以精选。你要的不是村庄式的小,而是全明星团队式的小。 群体越大,其普通成员就越接近整体人群的平均水平。因此其他条件相同时,大公司中能力极强的人很可能吃亏,因为其表现被其他人较低的整体表现拖累。当然,其他条件常不相同:能人可能不在乎钱,或更喜欢大公司的稳定。但真正在乎钱的能人,通常会选择与小群同级别的人共事。 技术=杠杆效应 创业公司让任何人都能处于兼具可衡量性与杠杆效应的情境。可衡量性来自小规模,杠杆效应则来自通过发明新技术赚钱。 什么是技术?是技法,是我们做事的方式。当你发现新方法时,其价值会乘以使用人数。这是俗话说的"授人以渔而非鱼"。这是创业公司与餐馆或理发店的区别。你一次只能为一个顾客煎蛋或剪发,而若解决许多人关心的技术问题,就能帮助所有.
But a very able person who does care about money will ordinarily do better to go off and work with a small group of peers. Technology = Leverage Startups offer anyone a way to be in a situation with measurement and leverage. They allow measurement because they're small, and they offer leverage because they make money by inventing new technology. What is technology? It's _technique_. It's the way we all do things. And when you discover a new way to do things, its value is multiplied by all the people who use it. It is the proverbial fishing rod, rather than the fish. That's the difference between a startup and a restaurant or a barber shop. You fry eggs or cut hair one customer at a time. Whereas if you solve a technical problem that a lot of people care about, you help everyone who uses your solution. That's leverage. If you look at history, it seems that most people who got rich by creating wealth did it by developing new technology. You just can't fry eggs or cut hair fast enough. What made the Florentines rich in 1200 was the discovery of new techniques for making the high-tech product of the time, fine woven cloth. What made the Dutch rich in 1600 was the discovery of shipbuilding and navigation techniques that enabled them to dominate the seas of the Far East. Fortunately there is a natural fit between smallness and solving hard problems. The leading edge of technology moves fast. Technology that's valuable today could be worthless in a couple years. Small companies are more at home in this world, because they don't have layers of bureaucracy to slow them down. Also, technical advances tend to come from unorthodox approaches, and small companies are less constrained by convention. Big companies can develop technology. They just can't do it quickly. Their size makes them slow and prevents them from rewarding employees for the extraordinary effort required.
So in practice big companies only get to develop technology in fields where large capital requirements prevent startups from competing with them, like microprocessors, power plants, or passenger aircraft. And even in those fields they depend heavily on startups for components and ideas. It's obvious that biotech or software startups exist to solve hard technical problems, but I think it will also be found to be true in businesses that don't seem to be about technology. McDonald's, for example, grew big by designing a system, the McDonald's franchise, that could then be reproduced at will all over the face of the earth. A McDonald's franchise is controlled by rules so precise that it is practically a piece of software. Write once, run everywhere. Ditto for Wal-Mart. Sam Walton got rich not by being a retailer, but by designing a new kind of store. Use difficulty as a guide not just in selecting the overall aim of your company, but also at decision points along the way. At Viaweb one of our rules of thumb was _run upstairs._ Suppose you are a little, nimble guy being chased by a big, fat, bully. You open a door and find yourself in a staircase. Do you go up or down? I say up. The bully can probably run downstairs as fast as you can. Going upstairs his bulk will be more of a disadvantage. Running upstairs is hard for you but even harder for him. What this meant in practice was that we deliberately sought hard problems. If there were two features we could add to our software, both equally valuable in proportion to their difficulty, we'd always take the harder one. Not just because it was more valuable, but _because it was harder._ We delighted in forcing bigger, slower competitors to follow us over difficult ground. Like guerillas, startups prefer the difficult terrain of the mountains, where the troops of the central government can't follow. I can remember times when we were just exhausted after wrestling all day with some horrible technical problem.
And I'd be delighted, because something that was hard for us would be impossible for our competitors. This is not just a good way to run a startup. It's what a startup is. Venture capitalists know about this and have a phrase for it: _barriers to entry._ If you go to a VC with a new idea and ask him to invest in it, one of the first things he'll ask is, how hard would this be for someone else to develop? That is, how much difficult ground have you put between yourself and potential pursuers? [7] And you had better have a convincing explanation of why your technology would be hard to duplicate. Otherwise as soon as some big company becomes aware of it, they'll make their own, and with their brand name, capital, and distribution clout, they'll take away your market overnight. You'd be like guerillas caught in the open field by regular army forces. One way to put up barriers to entry is through patents. But patents may not provide much protection. Competitors commonly find ways to work around a patent. And if they can't, they may simply violate it and invite you to sue them. A big company is not afraid to be sued; it's an everyday thing for them. They'll make sure that suing them is expensive and takes a long time. Ever heard of Philo Farnsworth? He invented television. The reason you've never heard of him is that his company was not the one to make money from it. [8] The company that did was RCA, and Farnsworth's reward for his efforts was a decade of patent litigation. Here, as so often, the best defense is a good offense. If you can develop technology that's simply too hard for competitors to duplicate, you don't need to rely on other defenses. Start by picking a hard problem, and then at every decision point, take the harder choice. [9] The Catch(es) If it were simply a matter of working harder than an ordinary employee and getting paid proportionately, it would obviously be a good deal to start a startup.
Up to a point it would be more fun. I don't think many people like the slow pace of big companies, the interminable meetings, the water-cooler conversations, the clueless middle managers, and so on. Unfortunately there are a couple catches. One is that you can't choose the point on the curve that you want to inhabit. You can't decide, for example, that you'd like to work just two or three times as hard, and get paid that much more. When you're running a startup, your competitors decide how hard you work. And they pretty much all make the same decision: as hard as you possibly can. The other catch is that the payoff is only on average proportionate to your productivity. There is, as I said before, a large random multiplier in the success of any company. So in practice the deal is not that you're 30 times as productive and get paid 30 times as much. It is that you're 30 times as productive, and get paid between zero and a thousand times as much. If the mean is 30x, the median is probably zero. Most startups tank, and not just the dogfood portals we all heard about during the Internet Bubble. It's common for a startup to be developing a genuinely good product, take slightly too long to do it, run out of money, and have to shut down. A startup is like a mosquito. A bear can absorb a hit and a crab is armored against one, but a mosquito is designed for one thing: to score. No energy is wasted on defense. The defense of mosquitos, as a species, is that there are a lot of them, but this is little consolation to the individual mosquito. Startups, like mosquitos, tend to be an all-or-nothing proposition. And you don't generally know which of the two you're going to get till the last minute. Viaweb came close to tanking several times. Our trajectory was like a sine wave. Fortunately we got bought at the top of the cycle, but it was damned close.
While we were visiting Yahoo in California to talk about selling the company to them, we had to borrow a conference room to reassure an investor who was about to back out of a new round of funding that we needed to stay alive. The all-or-nothing aspect of startups was not something we wanted. Viaweb's hackers were all extremely risk-averse. If there had been some way just to work super hard and get paid for it, without having a lottery mixed in, we would have been delighted. We would have much preferred a 100% chance of $1 million to a 20% chance of $10 million, even though theoretically the second is worth twice as much. Unfortunately, there is not currently any space in the business world where you can get the first deal. The closest you can get is by selling your startup in the early stages, giving up upside (and risk) for a smaller but guaranteed payoff. We had a chance to do this, and stupidly, as we then thought, let it slip by. After that we became comically eager to sell. For the next year or so, if anyone expressed the slightest curiosity about Viaweb we would try to sell them the company. But there were no takers, so we had to keep going. It would have been a bargain to buy us at an early stage, but companies doing acquisitions are not looking for bargains. A company big enough to acquire startups will be big enough to be fairly conservative, and within the company the people in charge of acquisitions will be among the more conservative, because they are likely to be business school types who joined the company late. They would rather overpay for a safe choice. So it is easier to sell an established startup, even at a large premium, than an early-stage one. Get Users I think it's a good idea to get bought, if you can. Running a business is different from growing one. It is just as well to let a big company take over once you reach cruising altitude. It's also financially wiser, because selling allows you to diversify.
What would you think of a financial advisor who put all his client's assets into one volatile stock? How do you get bought? Mostly by doing the same things you'd do if you didn't intend to sell the company. Being profitable, for example. But getting bought is also an art in its own right, and one that we spent a lot of time trying to master. Potential buyers will always delay if they can. The hard part about getting bought is getting them to act. For most people, the most powerful motivator is not the hope of gain, but the fear of loss. For potential acquirers, the most powerful motivator is the prospect that one of their competitors will buy you. This, as we found, causes CEOs to take red-eyes. The second biggest is the worry that, if they don't buy you now, you'll continue to grow rapidly and will cost more to acquire later, or even become a competitor. In both cases, what it all comes down to is users. You'd think that a company about to buy you would do a lot of research and decide for themselves how valuable your technology was. Not at all. What they go by is the number of users you have. In effect, acquirers assume the customers know who has the best technology. And this is not as stupid as it sounds. Users are the only real proof that you've created wealth. Wealth is what people want, and if people aren't using your software, maybe it's not just because you're bad at marketing. Maybe it's because you haven't made what they want. Venture capitalists have a list of danger signs to watch out for. Near the top is the company run by techno-weenies who are obsessed with solving interesting technical problems, instead of making users happy. In a startup, you're not just trying to solve problems. You're trying to solve problems _that users care about._ So I think you should make users the test, just as acquirers do. Treat a startup as an optimization problem in which performance is measured by number of users.
As anyone who has tried to optimize software knows, the key is measurement. When you try to guess where your program is slow, and what would make it faster, you almost always guess wrong. Number of users may not be the perfect test, but it will be very close. It's what acquirers care about. It's what revenues depend on. It's what makes competitors unhappy. It's what impresses reporters, and potential new users. Certainly it's a better test than your a priori notions of what problems are important to solve, no matter how technically adept you are. Among other things, treating a startup as an optimization problem will help you avoid another pitfall that VCs worry about, and rightly-- taking a long time to develop a product. Now we can recognize this as something hackers already know to avoid: premature optimization. Get a version 1.0 out there as soon as you can. Until you have some users to measure, you're optimizing based on guesses. The ball you need to keep your eye on here is the underlying principle that wealth is what people want. If you plan to get rich by creating wealth, you have to know what people want. So few businesses really pay attention to making customers happy. How often do you walk into a store, or call a company on the phone, with a feeling of dread in the back of your mind? When you hear "your call is important to us, please stay on the line," do you think, oh good, now everything will be all right? A restaurant can afford to serve the occasional burnt dinner. But in technology, you cook one thing and that's what everyone eats. So any difference between what people want and what you deliver is multiplied. You please or annoy customers wholesale. The closer you can get to what they want, the more wealth you generate. Wealth and Power Making wealth is not the only way to get rich. For most of human history it has not even been the most common.
书呆子的复仇(第6部分,共9部分)
Until a few centuries ago, the main sources of wealth were mines, slaves and serfs, land, and cattle, and the only ways to acquire these rapidly were by inheritance, marriage, conquest, or confiscation. Naturally wealth had a bad reputation. Two things changed. The first was the rule of law. For most of the world's history, if you did somehow accumulate a fortune, the ruler or his henchmen would find a way to steal it. But in medieval Europe something new happened. A new class of merchants and manufacturers began to collect in towns. [10] Together they were able to withstand the local feudal lord. So for the first time in our history, the bullies stopped stealing the nerds' lunch money. This was naturally a great incentive, and possibly indeed the main cause of the second big change, industrialization. A great deal has been written about the causes of the Industrial Revolution. But surely a necessary, if not sufficient, condition was that people who made fortunes be able to enjoy them in peace. [11] One piece of evidence is what happened to countries that tried to return to the old model, like the Soviet Union, and to a lesser extent Britain under the labor governments of the 1960s and early 1970s. Take away the incentive of wealth, and technical innovation grinds to a halt. Remember what a startup is, economically: a way of saying, I want to work faster. Instead of accumulating money slowly by being paid a regular wage for fifty years, I want to get it over with as soon as possible. So governments that forbid you to accumulate wealth are in effect decreeing that you work slowly. They're willing to let you earn $3 million over fifty years, but they're not willing to let you work so hard that you can do it in two. They are like the corporate boss that you can't go to and say, I want to work ten times as hard, so please pay me ten times a much. Except this is not a boss you can escape by starting your own company.
The problem with working slowly is not just that technical innovation happens slowly. It's that it tends not to happen at all. It's only when you're deliberately looking for hard problems, as a way to use speed to the greatest advantage, that you take on this kind of project. Developing new technology is a pain in the ass. It is, as Edison said, one percent inspiration and ninety-nine percent perspiration. Without the incentive of wealth, no one wants to do it. Engineers will work on sexy projects like fighter planes and moon rockets for ordinary salaries, but more mundane technologies like light bulbs or semiconductors have to be developed by entrepreneurs. Startups are not just something that happened in Silicon Valley in the last couple decades. Since it became possible to get rich by creating wealth, everyone who has done it has used essentially the same recipe: measurement and leverage, where measurement comes from working with a small group, and leverage from developing new techniques. The recipe was the same in Florence in 1200 as it is in Santa Clara today. Understanding this may help to answer an important question: why Europe grew so powerful. Was it something about the geography of Europe? Was it that Europeans are somehow racially superior? Was it their religion? The answer (or at least the proximate cause) may be that the Europeans rode on the crest of a powerful new idea: allowing those who made a lot of money to keep it. Once you're allowed to do that, people who want to get rich can do it by generating wealth instead of stealing it. The resulting technological growth translates not only into wealth but into military power. The theory that led to the stealth plane was developed by a Soviet mathematician. But because the Soviet Union didn't have a computer industry, it remained for them a theory; they didn't have hardware capable of executing the calculations fast enough to design an actual airplane.
In that respect the Cold War teaches the same lesson as World War II and, for that matter, most wars in recent history. Don't let a ruling class of warriors and politicians squash the entrepreneurs. The same recipe that makes individuals rich makes countries powerful. Let the nerds keep their lunch money, and you rule the world. Notes [1] One valuable thing you tend to get only in startups is _uninterruptability_. Different kinds of work have different time quanta. Someone proofreading a manuscript could probably be interrupted every fifteen minutes with little loss of productivity. But the time quantum for hacking is very long: it might take an hour just to load a problem into your head. So the cost of having someone from personnel call you about a form you forgot to fill out can be huge. This is why hackers give you such a baleful stare as they turn from their screen to answer your question. Inside their heads a giant house of cards is tottering. The mere possibility of being interrupted deters hackers from starting hard projects. This is why they tend to work late at night, and why it's next to impossible to write great software in a cubicle (except late at night). One great advantage of startups is that they don't yet have any of the people who interrupt you. There is no personnel department, and thus no form nor anyone to call you about it. [2] Faced with the idea that people working for startups might be 20 or 30 times as productive as those working for large companies, executives at large companies will naturally wonder, how could I get the people working for me to do that? The answer is simple: pay them to. Internally most companies are run like Communist states.
If you believe in free markets, why not turn your company into one? Hypothesis: A company will be maximally profitable when each employee is paid in proportion to the wealth they generate. [3] Until recently even governments sometimes didn't grasp the distinction between money and wealth. Adam Smith ( _Wealth of Nations_ , v:i) mentions several that tried to preserve their "wealth" by forbidding the export of gold or silver. But having more of the medium of exchange would not make a country richer; if you have more money chasing the same amount of material wealth, the only result is higher prices. [4] There are many senses of the word "wealth," not all of them material. I'm not trying to make a deep philosophical point here about which is the true kind. I'm writing about one specific, rather technical sense of the word "wealth." What people will give you money for. This is an interesting sort of wealth to study, because it is the kind that prevents you from starving. And what people will give you money for depends on them, not you. When you're starting a business, it's easy to slide into thinking that customers want what you do. During the Internet Bubble I talked to a woman who, because she liked the outdoors, was starting an "outdoor portal." You know what kind of business you should start if you like the outdoors? One to recover data from crashed hard disks. What's the connection? None at all. Which is precisely my point. If you want to create wealth (in the narrow technical sense of not starving) then you should be especially skeptical about any plan that centers on things you like doing. That is where your idea of what's valuable is least likely to coincide with other people's. [5] In the average car restoration you probably do make everyone else microscopically poorer, by doing a small amount of damage to the environment. While environmental costs should be taken into account, they don't make wealth a zero-sum game.
For example, if you repair a machine that's broken because a part has come unscrewed, you create wealth with no environmental cost. [5b] This essay was written before Firefox. [6] Many people feel confused and depressed in their early twenties. Life seemed so much more fun in college. Well, of course it was. Don't be fooled by the surface similarities. You've gone from guest to servant. It's possible to have fun in this new world. Among other things, you now get to go behind the doors that say "authorized personnel only." But the change is a shock at first, and all the worse if you're not consciously aware of it. [7] When VCs asked us how long it would take another startup to duplicate our software, we used to reply that they probably wouldn't be able to at all. I think this made us seem naive, or liars. [8] Few technologies have one clear inventor. So as a rule, if you know the "inventor" of something (the telephone, the assembly line, the airplane, the light bulb, the transistor) it is because their company made money from it, and the company's PR people worked hard to spread the story. If you don't know who invented something (the automobile, the television, the computer, the jet engine, the laser), it's because other companies made all the money. [9] This is a good plan for life in general. If you have two choices, choose the harder. If you're trying to decide whether to go out running or sit home and watch TV, go running. Probably the reason this trick works so well is that when you have two choices and one is harder, the only reason you're even considering the other is laziness. You know in the back of your mind what's the right thing to do, and this trick merely forces you to acknowledge it. [10] It is probably no accident that the middle class first appeared in northern Italy and the low countries, where there were no strong central governments.
These two regions were the richest of their time and became the twin centers from which Renaissance civilization radiated. If they no longer play that role, it is because other places, like the United States, have been truer to the principles they discovered. [11] It may indeed be a sufficient condition. But if so, why didn't the Industrial Revolution happen earlier? Two possible (and not incompatible) answers: (a) It did. The Industrial Revolution was one in a series. (b) Because in medieval towns, monopolies and guild regulations initially slowed the development of new means of production. [](http://reddit.com) Comment on this essay.
| Russian Translation | | | Arabic Translation | Spanish Translation.
You'll find this essay and 14 others in _Hackers & Painters_.
You'll find this essay and 14 others in _Hackers & Painters_.
May 2004 When people care enough about something to do it well, those who do it best tend to be far better than everyone else. There's a huge gap between Leonardo and second-rate contemporaries like Borgognone. You see the same gap between Raymond Chandler and the average writer of detective novels. A top-ranked professional chess player could play ten thousand games against an ordinary club player without losing once. Like chess or painting or writing novels, making money is a very specialized skill. But for some reason we treat this skill differently. No one complains when a few people surpass all the rest at playing chess or writing novels, but when a few people make more money than the rest, we get editorials saying this is wrong. Why? The pattern of variation seems no different than for any other skill. What causes people to react so strongly when the skill is making money? I think there are three reasons we treat making money as different: the misleading model of wealth we learn as children; the disreputable way in which, till recently, most fortunes were accumulated; and the worry that great variations in income are somehow bad for society. As far as I can tell, the first is mistaken, the second outdated, and the third empirically false. Could it be that, in a modern democracy, variation in income is actually a sign of health? The Daddy Model of Wealth When I was five I thought electricity was created by electric sockets. I didn't realize there were power plants out there generating it. Likewise, it doesn't occur to most kids that wealth is something that has to be generated. It seems to be something that flows from parents. Because of the circumstances in which they encounter it, children tend to misunderstand wealth. They confuse it with money. They think that there is a fixed amount of it.
当人们对某件事足够用心并做到极致时,顶尖者与其他人之间的差距往往大得惊人。达·芬奇与二流同代人如博尔戈尼奥内之间横亘着天堑;雷蒙德·钱德勒与普通侦探小说作家之间亦是如此。一位顶级职业棋手与普通俱乐部棋手对弈万局也未必会输一次。
赚钱如同下棋、绘画或写小说,是高度专业化的技能。但奇怪的是,人们对待这项技能的态度却截然不同。当少数人在棋艺或写作上远超众人时无人抱怨,可若有人赚得比旁人多,社论便会指责这不公。
为何如此?收入差异的模式与其他技能并无二致。为何当这项技能是赚钱时,人们反应如此激烈?
And they think of it as something that's distributed by authorities (and so should be distributed equally), rather than something that has to be created (and might be created unequally). In fact, wealth is not money. Money is just a convenient way of trading one form of wealth for another. Wealth is the underlying stuff—the goods and services we buy. When you travel to a rich or poor country, you don't have to look at people's bank accounts to tell which kind you're in. You can _see_ wealth—in buildings and streets, in the clothes and the health of the people. Where does wealth come from? People make it. This was easier to grasp when most people lived on farms, and made many of the things they wanted with their own hands. Then you could see in the house, the herds, and the granary the wealth that each family created. It was obvious then too that the wealth of the world was not a fixed quantity that had to be shared out, like slices of a pie. If you wanted more wealth, you could make it. This is just as true today, though few of us create wealth directly for ourselves (except for a few vestigial domestic tasks). Mostly we create wealth for other people in exchange for money, which we then trade for the forms of wealth we want. [1] Because kids are unable to create wealth, whatever they have has to be given to them. And when wealth is something you're given, then of course it seems that it should be distributed equally. [2] As in most families it is. The kids see to that. "Unfair," they cry, when one sibling gets more than another. In the real world, you can't keep living off your parents. If you want something, you either have to make it, or do something of equivalent value for someone else, in order to get them to give you enough money to buy it. In the real world, wealth is (except for a few specialists like thieves and speculators) something you have to create, not something that's distributed by Daddy.
我认为有三个原因:童年被灌输的误导性财富观念;历史上多数财富积累的不光彩手段;以及收入差距有害社会的担忧。但在我看来,第一点是误解,第二点已过时,第三点被事实推翻。在现代民主社会,收入差距或许恰恰是健康的表现?
财富的"父亲分配模型"
五岁时我以为电是插座产生的,不知另有发电厂。同样,孩子很少意识到财富需要被创造,他们以为财富像从父母那里流出的自来水。
成长环境使孩子对财富产生三重误解:将财富与金钱混淆;认为财富总量固定;视财富为权威分配之物(故应均分),而非创造所得(可能不均)。
And since the ability and desire to create it vary from person to person, it's not made equally. You get paid by doing or making something people want, and those who make more money are often simply better at doing what people want. Top actors make a lot more money than B-list actors. The B-list actors might be almost as charismatic, but when people go to the theater and look at the list of movies playing, they want that extra oomph that the big stars have. Doing what people want is not the only way to get money, of course. You could also rob banks, or solicit bribes, or establish a monopoly. Such tricks account for some variation in wealth, and indeed for some of the biggest individual fortunes, but they are not the root cause of variation in income. The root cause of variation in income, as Occam's Razor implies, is the same as the root cause of variation in every other human skill. In the United States, the CEO of a large public company makes about 100 times as much as the average person. [3] Basketball players make about 128 times as much, and baseball players 72 times as much. Editorials quote this kind of statistic with horror. But I have no trouble imagining that one person could be 100 times as productive as another. In ancient Rome the price of _slaves_ varied by a factor of 50 depending on their skills. [4] And that's without considering motivation, or the extra leverage in productivity that you can get from modern technology. Editorials about athletes' or CEOs' salaries remind me of early Christian writers, arguing from first principles about whether the Earth was round, when they could just walk outside and check. [5] How much someone's work is worth is not a policy question. It's something the market already determines. "Are they really worth 100 of us?" editorialists ask. Depends on what you mean by worth. If you mean worth in the sense of what people will pay for their skills, the answer is yes, apparently.
实则财富≠金钱。金钱只是交换不同形式财富的工具,真正的财富是我们购买的物品与服务。踏入富国或穷国时,无需查看银行账户——建筑、街道、人们的衣着与健康状态都在昭示财富。
财富从何而来?由人创造。在农耕时代这更易理解:每个家庭通过双手创造的财富直观体现在房屋、牲畜和谷仓中。那时人们也明白世界财富非固定馅饼——想要更多,就去创造。
今日依然如此,只是多数人通过为他人创造财富换取金钱,再购买所需。[1]
儿童无力创造财富,所得皆需被给予。当财富是被赐予之物时,"均分"自然成为诉求。[2]家庭中常见孩子抗议:"他分得更多,这不公平!"
A few CEOs' incomes reflect some kind of wrongdoing. But are there not others whose incomes really do reflect the wealth they generate? Steve Jobs saved a company that was in a terminal decline. And not merely in the way a turnaround specialist does, by cutting costs; he had to decide what Apple's next products should be. Few others could have done it. And regardless of the case with CEOs, it's hard to see how anyone could argue that the salaries of professional basketball players don't reflect supply and demand. It may seem unlikely in principle that one individual could really generate so much more wealth than another. The key to this mystery is to revisit that question, are they really worth 100 of us? _Would_ a basketball team trade one of their players for 100 random people? What would Apple's next product look like if you replaced Steve Jobs with a committee of 100 random people? [6] These things don't scale linearly. Perhaps the CEO or the professional athlete has only ten times (whatever that means) the skill and determination of an ordinary person. But it makes all the difference that it's concentrated in one individual. When we say that one kind of work is overpaid and another underpaid, what are we really saying? In a free market, prices are determined by what buyers want. People like baseball more than poetry, so baseball players make more than poets. To say that a certain kind of work is underpaid is thus identical with saying that people want the wrong things. Well, of course people want the wrong things. It seems odd to be surprised by that. And it seems even odder to say that it's _unjust_ that certain kinds of work are underpaid. [7] Then you're saying that it's unjust that people want the wrong things. It's lamentable that people prefer reality TV and corndogs to Shakespeare and steamed vegetables, but unjust? That seems like saying that blue is heavy, or that up is circular.
现实世界无法永远依赖父母。想要某物,要么亲手创造,要么通过为他人提供等值服务换取金钱。除窃贼与投机者外,财富须靠创造而非分配获得。而人的能力与欲望各异,创造自然不均。
报酬源于提供他人所需之物,高收入者往往更擅长此道。一线影星收入远超二线——后者或许同样魅力非凡,但观众就是愿意为巨星额外买单。
当然,满足需求并非致富唯一途径。抢银行、收贿赂、搞垄断也能敛财,这类手段确会造成财富差异(甚至催生顶级富豪),但非收入差距根源。如奥卡姆剃刀原则所示:收入差异的根本原因,与其他人类技能差异别无二致。
美国大公司CEO收入约为普通人100倍[3],篮球运动员128倍,棒球选手72倍。社论常惊恐引用此类数据,但我完全相信个体生产力存在百倍差异。古罗马奴隶价格因技能差异可达50倍[4]——这还未计入现代科技带来的生产力杠杆。
The appearance of the word "unjust" here is the unmistakable spectral signature of the Daddy Model. Why else would this idea occur in this odd context? Whereas if the speaker were still operating on the Daddy Model, and saw wealth as something that flowed from a common source and had to be shared out, rather than something generated by doing what other people wanted, this is exactly what you'd get on noticing that some people made much more than others. When we talk about "unequal distribution of income," we should also ask, where does that income come from? [8] Who made the wealth it represents? Because to the extent that income varies simply according to how much wealth people create, the distribution may be unequal, but it's hardly unjust. Stealing It The second reason we tend to find great disparities of wealth alarming is that for most of human history the usual way to accumulate a fortune was to steal it: in pastoral societies by cattle raiding; in agricultural societies by appropriating others' estates in times of war, and taxing them in times of peace. In conflicts, those on the winning side would receive the estates confiscated from the losers. In England in the 1060s, when William the Conqueror distributed the estates of the defeated Anglo-Saxon nobles to his followers, the conflict was military. By the 1530s, when Henry VIII distributed the estates of the monasteries to his followers, it was mostly political. [9] But the principle was the same. Indeed, the same principle is at work now in Zimbabwe. In more organized societies, like China, the ruler and his officials used taxation instead of confiscation. But here too we see the same principle: the way to get rich was not to create wealth, but to serve a ruler powerful enough to appropriate it. This started to change in Europe with the rise of the middle class.
关于运动员或CEO薪水的社论,让我想起早期基督教作家依据教义争论地球是否平坦——他们本可出门验证。某人劳动价值几何非政策问题,市场早有定论。"他们真抵得上100个普通人?"社论作者质问。若以市场愿意支付的价格衡量,答案显然是肯定的。
少数CEO收入确与不当行为相关,但就没有人配得上其收入吗?史蒂夫·乔布斯将濒临破产的公司起死回生,这不仅是削减成本的扭亏为盈,更需决策下一代产品方向——罕有人能做到。且不论CEO,职业篮球运动员的薪水难道不正是供需关系的体现?
理论上,个体财富创造能力存在巨大差异看似不可思议。破解此谜需重新思考"是否值100人"——篮球队会用明星球员交换100个路人吗?用100个普通人替代乔布斯,苹果下一代产品会怎样?[6]这些事不遵循线性规律。或许顶尖者仅具备常人十倍(姑且这么说)的能力与决心,但集中于单一个体就会产生天壤之别。
当我们说某工作报酬过高或过低时,实际在说什么?自由市场中,价格由买家需求决定。人们更爱棒球而非诗歌,故棒球选手收入更高。声称某工作报酬过低,等同于指责人们需求错误。
Now we think of the middle class as people who are neither rich nor poor, but originally they were a distinct group. In a feudal society, there are just two classes: a warrior aristocracy, and the serfs who work their estates. The middle class were a new, third group who lived in towns and supported themselves by manufacturing and trade. Starting in the tenth and eleventh centuries, petty nobles and former serfs banded together in towns that gradually became powerful enough to ignore the local feudal lords. [10] Like serfs, the middle class made a living largely by creating wealth. (In port cities like Genoa and Pisa, they also engaged in piracy.) But unlike serfs they had an incentive to create a lot of it. Any wealth a serf created belonged to his master. There was not much point in making more than you could hide. Whereas the independence of the townsmen allowed them to keep whatever wealth they created. Once it became possible to get rich by creating wealth, society as a whole started to get richer very rapidly. Nearly everything we have was created by the middle class. Indeed, the other two classes have effectively disappeared in industrial societies, and their names been given to either end of the middle class. (In the original sense of the word, Bill Gates is middle class.) But it was not till the Industrial Revolution that wealth creation definitively replaced corruption as the best way to get rich. In England, at least, corruption only became unfashionable (and in fact only started to be called "corruption") when there started to be other, faster ways to get rich. Seventeenth-century England was much like the third world today, in that government office was a recognized route to wealth. The great fortunes of that time still derived more from what we would now call corruption than from commerce. [11] By the nineteenth century that had changed.
当然,人们总想要"错误"的东西——对此惊讶才显奇怪。若进一步声称某些低薪工作遭遇"不公"[7],则等于宣称"人们需求错误"本身不公正。人们偏爱真人秀和玉米热狗而非莎士比亚与清蒸蔬菜虽可叹,但算不公吗?这如同说"蓝色很重"或"上方是圆形"般荒谬。
"不公正"一词在此出现,暴露出"父亲分配模型"的幽灵。若非受此模型影响——将财富视为来自公共源头需均分之物,而非通过满足他人需求所创——怎会在此语境产生如此怪诞念头?
谈论"收入分配不均"时,我们更该追问:这些收入从何而来?[8]谁创造了对应的财富?若收入差异真实反映财富创造能力,这种不均难言不公。
财富差距令人不安的第二个原因在于:人类历史大部分时期,积累财富的主要方式是掠夺——游牧社会抢牲畜,农耕社会战时强占土地,和平时期征税。
There continued to be bribes, as there still are everywhere, but politics had by then been left to men who were driven more by vanity than greed. Technology had made it possible to create wealth faster than you could steal it. The prototypical rich man of the nineteenth century was not a courtier but an industrialist. With the rise of the middle class, wealth stopped being a zero-sum game. Jobs and Wozniak didn't have to make us poor to make themselves rich. Quite the opposite: they created things that made our lives materially richer. They had to, or we wouldn't have paid for them. But since for most of the world's history the main route to wealth was to steal it, we tend to be suspicious of rich people. Idealistic undergraduates find their unconsciously preserved child's model of wealth confirmed by eminent writers of the past. It is a case of the mistaken meeting the outdated. "Behind every great fortune, there is a crime," Balzac wrote. Except he didn't. What he actually said was that a great fortune with no apparent cause was probably due to a crime well enough executed that it had been forgotten. If we were talking about Europe in 1000, or most of the third world today, the standard misquotation would be spot on. But Balzac lived in nineteenth-century France, where the Industrial Revolution was well advanced. He knew you could make a fortune without stealing it. After all, he did himself, as a popular novelist. [12] Only a few countries (by no coincidence, the richest ones) have reached this stage. In most, corruption still has the upper hand. In most, the fastest way to get wealth is by stealing it. And so when we see increasing differences in income in a rich country, there is a tendency to worry that it's sliding back toward becoming another Venezuela. I think the opposite is happening.
胜利者总在瓜分战利品。1060年代英格兰,征服者威廉将盎格鲁-撒克逊贵族的土地分封给追随者;1530年代亨利八世将修道院地产赏赐亲信——前者是军事征服,后者是政治清洗[9],但本质相同。如今津巴布韦仍在演绎相同剧本。
在中国等更组织化的社会,统治者用征税替代直接掠夺。但核心逻辑未变:致富之道非创造财富,而是效忠能攫取财富的强权。
欧洲中产阶级的兴起改变了游戏规则。如今中产指既不富也不穷的群体,但其最初是作为新兴第三阶级出现的。封建社会中仅有两类人:武士贵族与农奴。中产是聚居城镇、以制造贸易为生的新群体。
I think you're seeing a country a full step ahead of Venezuela. The Lever of Technology Will technology increase the gap between rich and poor? It will certainly increase the gap between the productive and the unproductive. That's the whole point of technology. With a tractor an energetic farmer could plow six times as much land in a day as he could with a team of horses. But only if he mastered a new kind of farming. I've seen the lever of technology grow visibly in my own time. In high school I made money by mowing lawns and scooping ice cream at Baskin-Robbins. This was the only kind of work available at the time. Now high school kids could write software or design web sites. But only some of them will; the rest will still be scooping ice cream. I remember very vividly when in 1985 improved technology made it possible for me to buy a computer of my own. Within months I was using it to make money as a freelance programmer. A few years before, I couldn't have done this. A few years before, there was no such _thing_ as a freelance programmer. But Apple created wealth, in the form of powerful, inexpensive computers, and programmers immediately set to work using it to create more. As this example suggests, the rate at which technology increases our productive capacity is probably exponential, rather than linear. So we should expect to see ever-increasing variation in individual productivity as time goes on. Will that increase the gap between rich and the poor? Depends which gap you mean. Technology should increase the gap in income, but it seems to decrease other gaps. A hundred years ago, the rich led a different _kind_ of life from ordinary people. They lived in houses full of servants, wore elaborately uncomfortable clothes, and travelled about in carriages drawn by teams of horses which themselves required their own houses and servants. Now, thanks to technology, the rich live more like the average person.
11世纪起,破落贵族与解放农奴在城镇集结,逐渐形成抗衡领主的势力。[10]与农奴相似,中产主要通过创造财富谋生(热那亚、比萨等港口城市也兼营海盗),但与农奴不同,他们有强烈创造动力——农奴创造的财富全归领主,超额产出唯有隐藏;而市民能保留所创财富。
当创造财富成为致富途径后,社会总财富开始激增。现代社会的几乎一切都由中产创造。事实上,另两个阶级在工业社会已名存实亡,其名称被转赠给中产的两端。(按本义,比尔·盖茨属中产。)
但直到工业革命,创造财富才彻底取代腐败成为最佳致富途径。至少在英格兰,当更快致富方式出现后,腐败才变得"不体面"(并真正开始被称为"腐败")。
17世纪英格兰如同今日第三世界,政府职位是公认致富途径。彼时巨富多来自我们今天所称的腐败,而非商业。[11]到19世纪情况改变。贿赂虽未绝迹(如今亦然),但从政者更多为虚荣而非贪婪所驱动。技术进步使创造财富快过掠夺,典型富人不再是廷臣而是实业家。
Cars are a good example of why. It's possible to buy expensive, handmade cars that cost hundreds of thousands of dollars. But there is not much point. Companies make more money by building a large number of ordinary cars than a small number of expensive ones. So a company making a mass-produced car can afford to spend a lot more on its design. If you buy a custom-made car, something will always be breaking. The only point of buying one now is to advertise that you can. Or consider watches. Fifty years ago, by spending a lot of money on a watch you could get better performance. When watches had mechanical movements, expensive watches kept better time. Not any more. Since the invention of the quartz movement, an ordinary Timex is more accurate than a Patek Philippe costing hundreds of thousands of dollars. [13] Indeed, as with expensive cars, if you're determined to spend a lot of money on a watch, you have to put up with some inconvenience to do it: as well as keeping worse time, mechanical watches have to be wound. The only thing technology can't cheapen is brand. Which is precisely why we hear ever more about it. Brand is the residue left as the substantive differences between rich and poor evaporate. But what label you have on your stuff is a much smaller matter than having it versus not having it. In 1900, if you kept a carriage, no one asked what year or brand it was. If you had one, you were rich. And if you weren't rich, you took the omnibus or walked. Now even the poorest Americans drive cars, and it is only because we're so well trained by advertising that we can even recognize the especially expensive ones. [14] The same pattern has played out in industry after industry. If there is enough demand for something, technology will make it cheap enough to sell in large volumes, and the mass-produced versions will be, if not better, at least more convenient. [15] And there is nothing the rich like more than convenience.
中产阶级兴起使财富不再零和。乔布斯与沃兹尼亚克致富无需以我们贫困为代价——正相反,他们创造的产品让我们的生活更富足。他们必须如此,否则我们不会买单。
但因历史上致富主要靠掠夺,我们对富人充满戒心。理想主义大学生们无意识保留的童年财富观,恰与过往名作家的论述吻合——这是谬误与过时的相遇。
"每一笔巨额财富背后都有犯罪。"巴尔扎克写道。其实他没这么说过。原意是:无明确来源的巨富,可能源于已被遗忘的完美犯罪。若谈论公元1000年的欧洲或今日多数第三世界,这句误引堪称精准。但巴尔扎克生活在工业革命蓬勃发展的19世纪法国,他清楚致富可不靠偷窃——毕竟他自己作为畅销小说家就做到了。[12]
只有少数国家(巧合的是皆为最富裕国家)达到此阶段。多数地区腐败仍占上风,最快致富方式仍是掠夺。因此当富国收入差距扩大时,人们总担心其滑向委内瑞拉。我认为相反情况正在发生——你看到的其实是领先委内瑞拉整整一个身位的国家。
The rich people I know drive the same cars, wear the same clothes, have the same kind of furniture, and eat the same foods as my other friends. Their houses are in different neighborhoods, or if in the same neighborhood are different sizes, but within them life is similar. The houses are made using the same construction techniques and contain much the same objects. It's inconvenient to do something expensive and custom. The rich spend their time more like everyone else too. Bertie Wooster seems long gone. Now, most people who are rich enough not to work do anyway. It's not just social pressure that makes them; idleness is lonely and demoralizing. Nor do we have the social distinctions there were a hundred years ago. The novels and etiquette manuals of that period read now like descriptions of some strange tribal society. "With respect to the continuance of friendships..." hints _Mrs. Beeton's Book of Household Management_ (1880), "it may be found necessary, in some cases, for a mistress to relinquish, on assuming the responsibility of a household, many of those commenced in the earlier part of her life." A woman who married a rich man was expected to drop friends who didn't. You'd seem a barbarian if you behaved that way today. You'd also have a very boring life. People still tend to segregate themselves somewhat, but much more on the basis of education than wealth. [16] Materially and socially, technology seems to be decreasing the gap between the rich and the poor, not increasing it. If Lenin walked around the offices of a company like Yahoo or Intel or Cisco, he'd think communism had won. Everyone would be wearing the same clothes, have the same kind of office (or rather, cubicle) with the same furnishings, and address one another by their first names instead of by honorifics. Everything would seem exactly as he'd predicted, until he looked at their bank accounts. Oops.
技术会加大贫富差距吗?它必定会扩大生产者与非生产者的差距——这正是技术存在的意义。使用拖拉机的农民每日耕作面积是马耕的六倍,但前提是他必须掌握新型农业技术。
我亲历了技术杠杆的显性增长。高中时我靠修剪草坪和Baskin-Robbins冰淇淋店打工赚钱,这是当时仅有的选择。如今高中生可以编写软件或设计网站——但只有部分人会这么做,其余仍在挖冰淇淋球。
1985年技术进步让我拥有个人电脑的场景历历在目。几个月内我就靠自由编程赚钱。若早几年,这不可能——那时甚至不存在"自由程序员"的职业。苹果公司创造了强大廉价的计算机这种财富形式,程序员们立即着手用它创造更多财富。
此例暗示:技术对生产力的提升可能呈指数而非线性增长。因此我们应预期个体生产力差异将随时间持续扩大。这会加剧贫富差距吗?取决于你指哪种差距。
Is it a problem if technology increases that gap? It doesn't seem to be so far. As it increases the gap in income, it seems to decrease most other gaps. Alternative to an Axiom One often hears a policy criticized on the grounds that it would increase the income gap between rich and poor. As if it were an axiom that this would be bad. It might be true that increased variation in income would be bad, but I don't see how we can say it's _axiomatic._ Indeed, it may even be false, in industrial democracies. In a society of serfs and warlords, certainly, variation in income is a sign of an underlying problem. But serfdom is not the only cause of variation in income. A 747 pilot doesn't make 40 times as much as a checkout clerk because he is a warlord who somehow holds her in thrall. His skills are simply much more valuable. I'd like to propose an alternative idea: that in a modern society, increasing variation in income is a sign of health. Technology seems to increase the variation in productivity at faster than linear rates. If we don't see corresponding variation in income, there are three possible explanations: (a) that technical innovation has stopped, (b) that the people who would create the most wealth aren't doing it, or (c) that they aren't getting paid for it. I think we can safely say that (a) and (b) would be bad. If you disagree, try living for a year using only the resources available to the average Frankish nobleman in 800, and report back to us. (I'll be generous and not send you back to the stone age.) The only option, if you're going to have an increasingly prosperous society without increasing variation in income, seems to be (c), that people will create a lot of wealth without being paid for it.
技术会扩大收入差距,但似乎缩小了其他差距。百年前富人与普通人过着截然不同的生活:仆役成群的宅邸、繁复不适的衣着、需要专属马厩与马夫的马车队。如今技术让富人生活更接近普通人。
汽车是绝佳例证。固然可以花费数十万美元购买手工豪车,但意义不大——厂商通过大规模生产普通车更赚钱,故量产车反而能投入更多设计成本。定制车总会故障连连,如今买它唯一目的是炫富。
手表亦如此。五十年前,昂贵机械表确实走时更准。石英机芯发明后,普通天美时已比数十万美元的百达翡丽更精准。[13]事实上,若执意买机械表,你不得不忍受额外麻烦——既走时不准,还需上弦。
技术唯一无法廉价化的是品牌。这恰是品牌宣传愈演愈烈的原因——当贫富实质差异消失后,品牌成为残留的符号。但物品的标签远不如拥有物品本身重要。1900年若有私人马车,无人会问其年份品牌——拥有即象征富裕。如今最穷的美国人也开车,唯有被广告驯化的我们才能识别特别昂贵的车型。[14]
That Jobs and Wozniak, for example, will cheerfully work 20-hour days to produce the Apple computer for a society that allows them, after taxes, to keep just enough of their income to match what they would have made working 9 to 5 at a big company. Will people create wealth if they can't get paid for it? Only if it's fun. People will write operating systems for free. But they won't install them, or take support calls, or train customers to use them. And at least 90% of the work that even the highest tech companies do is of this second, unedifying kind. All the unfun kinds of wealth creation slow dramatically in a society that confiscates private fortunes. We can confirm this empirically. Suppose you hear a strange noise that you think may be due to a nearby fan. You turn the fan off, and the noise stops. You turn the fan back on, and the noise starts again. Off, quiet. On, noise. In the absence of other information, it would seem the noise is caused by the fan. At various times and places in history, whether you could accumulate a fortune by creating wealth has been turned on and off. Northern Italy in 800, off (warlords would steal it). Northern Italy in 1100, on. Central France in 1100, off (still feudal). England in 1800, on. England in 1974, off (98% tax on investment income). United States in 1974, on. We've even had a twin study: West Germany, on; East Germany, off. In every case, the creation of wealth seems to appear and disappear like the noise of a fan as you switch on and off the prospect of keeping it. There is some momentum involved. It probably takes at least a generation to turn people into East Germans (luckily for England). But if it were merely a fan we were studying, without all the extra baggage that comes from the controversial topic of wealth, no one would have any doubt that the fan was causing the noise.
相同模式在各行业轮番上演。只要需求足够,技术就会将其变得价廉物美,量产版本即使不更优质,至少更便利。[15]而富人最爱的莫过于便利。我认识的富人与朋友开同款车、穿同款衣、用同款家具、吃相同食物。他们的住宅可能位于不同社区或面积不同,但内部生活高度相似——采用相同建筑技术,摆放相同物品。刻意追求昂贵定制反而麻烦。
富人的时间支配也趋同。伯蒂·伍斯特式的闲散早成往事。如今即便足够富有无需工作的人仍在工作,不仅是社会压力使然——无所事事令人孤独消沉。
百年前的社会阶层区分也已消失。当时小说与礼仪手册读来如同异族部落志。"关于友谊的维系..."比顿夫人的《家政管理》(1880年)建议:"女主人或许需要放弃婚前部分社交。"嫁给富人的女性被期待与穷朋友断交。今日如此行事会被视作野蛮人,生活也将无聊透顶。人们仍会自我隔离,但更多基于教育而非财富。[16]
无论物质还是社交层面,技术似乎都在缩小而非扩大贫富差距。若列宁漫步雅虎、英特尔或思科的办公室,会以为共产主义已胜利——人人穿着相同,拥有同样格局(确切说是格子间)的办公室,彼此直呼其名。一切正如他所预言,直到查看银行账户时——哦豁。
If you suppress variations in income, whether by stealing private fortunes, as feudal rulers used to do, or by taxing them away, as some modern governments have done, the result always seems to be the same. Society as a whole ends up poorer. If I had a choice of living in a society where I was materially much better off than I am now, but was among the poorest, or in one where I was the richest, but much worse off than I am now, I'd take the first option. If I had children, it would arguably be immoral not to. It's absolute poverty you want to avoid, not relative poverty. If, as the evidence so far implies, you have to have one or the other in your society, take relative poverty. You need rich people in your society not so much because in spending their money they create jobs, but because of what they have to do to _get_ rich. I'm not talking about the trickle-down effect here. I'm not saying that if you let Henry Ford get rich, he'll hire you as a waiter at his next party. I'm saying that he'll make you a tractor to replace your horse. Notes [1] Part of the reason this subject is so contentious is that some of those most vocal on the subject of wealth—university students, heirs, professors, politicians, and journalists—have the least experience creating it. (This phenomenon will be familiar to anyone who has overheard conversations about sports in a bar.) Students are mostly still on the parental dole, and have not stopped to think about where that money comes from. Heirs will be on the parental dole for life. Professors and politicians live within socialist eddies of the economy, at one remove from the creation of wealth, and are paid a flat rate regardless of how hard they work. And journalists as part of their professional code segregate themselves from the revenue-collecting half of the businesses they work for (the ad sales department).
若技术扩大收入差距是问题吗?迄今未见其害。它在扩大收入差距的同时,缩小了大多数其他差距。
我们常听到某项政策因"扩大贫富收入差距"受批评,仿佛这天然是坏事。收入差异扩大或许有害,但我不认为这该是不证自明的公理。
对工业民主国家而言,这甚至可能是错的。在农奴与军阀社会,收入差距确是根本问题的表征。但农奴制非收入差异唯一成因。747飞行员收入40倍于收银员,非因他是奴役对方的军阀——只是其技能价值更高。
Many of these people never come face to face with the fact that the money they receive represents wealth—wealth that, except in the case of journalists, someone else created earlier. They live in a world in which income _is_ doled out by a central authority according to some abstract notion of fairness (or randomly, in the case of heirs), rather than given by other people in return for something they wanted, so it may seem to them unfair that things don't work the same in the rest of the economy. (Some professors do create a great deal of wealth for society. But the money they're paid isn't a _quid pro quo_. It's more in the nature of an investment.) [2] When one reads about the origins of the Fabian Society, it sounds like something cooked up by the high-minded Edwardian child-heroes of Edith Nesbit's _The Wouldbegoods_. [3] According to a study by the Corporate Library, the median total compensation, including salary, bonus, stock grants, and the exercise of stock options, of S&P 500 CEOs in 2002 was $3.65 million. According to _Sports Illustrated_ , the average NBA player's salary during the 2002-03 season was $4.54 million, and the average major league baseball player's salary at the start of the 2003 season was $2.56 million. According to the Bureau of Labor Statistics, the mean annual wage in the US in 2002 was $35,560. [4] In the early empire the price of an ordinary adult slave seems to have been about 2,000 sestertii (e.g. Horace, _Sat._ ii.7.43). A servant girl cost 600 (Martial vi.66), while Columella (iii.3.8) says that a skilled vine-dresser was worth 8,000. A doctor, P. Decimus Eros Merula, paid 50,000 sestertii for his freedom (Dessau, _Inscriptiones_ 7812). Seneca ( _Ep._ xxvii.7) reports that one Calvisius Sabinus paid 100,000 sestertii apiece for slaves learned in the Greek classics. Pliny ( _Hist.
我提出一个反常识观点:现代社会收入差距扩大是健康标志。技术对生产力差异的加速作用似乎超线性。若未见相应的收入差异,只有三种解释:(a)技术创新停滞;(b)本可创造大量财富者未行动;(c)他们未获相应报酬。
我们可肯定(a)(b)是坏事。若存疑,请尝试仅用公元800年法兰克贵族可获取的资源生活一年(仁慈起见,不送你回石器时代),再向我们汇报。
要在不扩大收入差距的前提下实现社会繁荣,似乎只能选择(c):让人们无偿创造大量财富。这意味着乔布斯和沃兹尼亚克需甘愿每天工作20小时开发苹果电脑,而社会通过征税仅让他们保留相当于大公司朝九晚五工作的收入。
无法获利时人们会创造财富吗?除非乐在其中。人们愿免费编写操作系统,但不会免费安装、接客服电话或培训用户——而即便最高科技公司,至少90%工作属于这类无趣范畴。
Nat._ vii.39) says that the highest price paid for a slave up to his time was 700,000 sestertii, for the linguist (and presumably teacher) Daphnis, but that this had since been exceeded by actors buying their own freedom. Classical Athens saw a similar variation in prices. An ordinary laborer was worth about 125 to 150 drachmae. Xenophon ( _Mem._ ii.5) mentions prices ranging from 50 to 6,000 drachmae (for the manager of a silver mine). For more on the economics of ancient slavery see: Jones, A. H. M., "Slavery in the Ancient World," _Economic History Review_ , 2:9 (1956), 185-199, reprinted in Finley, M. I. (ed.), _Slavery in Classical Antiquity_ , Heffer, 1964. [5] Eratosthenes (276—195 BC) used shadow lengths in different cities to estimate the Earth's circumference. He was off by only about 2%. [6] No, and Windows, respectively. [7] One of the biggest divergences between the Daddy Model and reality is the valuation of hard work. In the Daddy Model, hard work is in itself deserving. In reality, wealth is measured by what one delivers, not how much effort it costs. If I paint someone's house, the owner shouldn't pay me extra for doing it with a toothbrush. It will seem to someone still implicitly operating on the Daddy Model that it is unfair when someone works hard and doesn't get paid much. To help clarify the matter, get rid of everyone else and put our worker on a desert island, hunting and gathering fruit. If he's bad at it he'll work very hard and not end up with much food. Is this unfair? Who is being unfair to him? [8] Part of the reason for the tenacity of the Daddy Model may be the dual meaning of "distribution." When economists talk about "distribution of income," they mean statistical distribution.
当社会没收私人财富时,所有无趣的财富创造都会急剧放缓。这有实证支持:假设你怀疑怪声来自附近风扇,关闭后声音消失,重启后重现——如此反复验证,可断定声源。历史上,能否通过创造财富积累财产如同这个开关:公元800年的北意大利(军阀会掠夺)——关;1100年的北意大利——开;1100年的法国中部(仍处封建)——关;1800年的英格兰——开;1974年的英格兰(投资所得税率98%)——关;1974年的美国——开。我们甚至存在对照组:西德开,东德关。每种情况下,财富创造都随保留预期的开关而起伏。
这其中存在惯性(英格兰幸运地至少需要一代人时间才能变成东德)。但若研究对象仅是风扇而非充满争议的财富话题,无人会怀疑声源成因。
无论是封建主直接掠夺,还是现代政府征税,压制收入差异的结果总相同:社会整体趋于贫困。
若可选择:生活在物质远优于当前但身处底层的社会,或成为最富但物质远逊当前的社会,我会选前者。若有子女,不这么选甚至不道德——需避免的是绝对贫困,而非相对贫困。若证据表明确需二选一,请选相对贫困。
But when you use the phrase frequently, you can't help associating it with the other sense of the word (as in e.g. "distribution of alms"), and thereby subconsciously seeing wealth as something that flows from some central tap. The word "regressive" as applied to tax rates has a similar effect, at least on me; how can anything _regressive_ be good? [9] "From the beginning of the reign Thomas Lord Roos was an assiduous courtier of the young Henry VIII and was soon to reap the rewards. In 1525 he was made a Knight of the Garter and given the Earldom of Rutland. In the thirties his support of the breach with Rome, his zeal in crushing the Pilgrimage of Grace, and his readiness to vote the death-penalty in the succession of spectacular treason trials that punctuated Henry's erratic matrimonial progress made him an obvious candidate for grants of monastic property." Stone, Lawrence, _Family and Fortune: Studies in Aristocratic Finance in the Sixteenth and Seventeenth Centuries_ , Oxford University Press, 1973, p. 166. [10] There is archaeological evidence for large settlements earlier, but it's hard to say what was happening in them. Hodges, Richard and David Whitehouse, _Mohammed, Charlemagne and the Origins of Europe_ , Cornell University Press, 1983. [11] William Cecil and his son Robert were each in turn the most powerful minister of the crown, and both used their position to amass fortunes among the largest of their times. Robert in particular took bribery to the point of treason. "As Secretary of State and the leading advisor to King James on foreign policy, [he] was a special recipient of favour, being offered large bribes by the Dutch not to make peace with Spain, and large bribes by Spain to make peace." (Stone, _op. cit._ , p. 17.) [12] Though Balzac made a lot of money from writing, he was notoriously improvident and was troubled by debts all his life. [13] A Timex will gain or lose about .5 seconds per day.
社会需要富人,主要非因其消费创造就业,而因其致富过程中的作为。此处不谈涓滴效应——非指让亨利·福特致富就能被他聘为宴会侍者,而是指他会发明拖拉机替代你的马匹。
[1] 该话题争议部分源于最热衷讨论财富的人群——大学生、继承人、教授、政客和记者——往往最缺乏创造财富的经验。(酒吧里听人谈论体育就能理解此现象。)
学生多数仍靠父母供养,未曾思考钱从何来;继承人终生依赖家族财富;教授与政客生活在经济体的社会主义涡流中,远离财富创造前线,无论多努力都拿固定薪酬;记者则按职业准则与公司营收部门(广告部)保持隔离。这些群体中许多人从未直面其收入本质——除记者外,他们领取的财富都由他人创造。他们生活在收入由中央权威按某种抽象公平理念(或继承人的随机运气)分配的世界,故当其发现经济体其他部分不按此运作时,便觉不公。
(部分教授确实为社会创造巨大财富,但其报酬非等价交换,更类似投资行为。)
The most accurate mechanical watch, the Patek Philippe 10 Day Tourbillon, is rated at -1.5 to +2 seconds. Its retail price is about $220,000. [14] If asked to choose which was more expensive, a well-preserved 1989 Lincoln Town Car ten-passenger limousine ($5,000) or a 2004 Mercedes S600 sedan ($122,000), the average Edwardian might well guess wrong. [15] To say anything meaningful about income trends, you have to talk about real income, or income as measured in what it can buy. But the usual way of calculating real income ignores much of the growth in wealth over time, because it depends on a consumer price index created by bolting end to end a series of numbers that are only locally accurate, and that don't include the prices of new inventions until they become so common that their prices stabilize. So while we might think it was very much better to live in a world with antibiotics or air travel or an electric power grid than without, real income statistics calculated in the usual way will prove to us that we are only slightly richer for having these things. Another approach would be to ask, if you were going back to the year x in a time machine, how much would you have to spend on trade goods to make your fortune? For example, if you were going back to 1970 it would certainly be less than $500, because the processing power you can get for $500 today would have been worth at least $150 million in 1970. The function goes asymptotic fairly quickly, because for times over a hundred years or so you could get all you needed in present-day trash. In 1800 an empty plastic drink bottle with a screw top would have seemed a miracle of workmanship. [16] Some will say this amounts to the same thing, because the rich have better opportunities for education. That's a valid point. It is still possible, to a degree, to buy your kids' way into top colleges by sending them to private schools that in effect hack the college admissions process.
[2] 读费边社起源时,感觉像伊迪丝·内斯比特《寻宝少年团》里高尚的爱德华时代孩童的构想。
[3] 企业图书馆研究显示:2002年标普500公司CEO薪酬中位数(含工资、奖金、股票赠与与期权行权)为365万美元;《体育画报》数据:2002-03赛季NBA球员平均薪资454万美元,2003赛季MLB球员256万美元;劳工统计局:2002年美国平均年薪35,560美元。
[4] 罗马帝国早期普通成年奴隶价格约2,000塞斯特斯(贺拉斯《讽刺诗》ii.7.43),女仆600塞斯特斯(马提亚尔vi.66),而科卢梅拉(iii.3.8)称熟练葡萄园工值8,000。医生P.德西穆斯·埃罗斯·梅鲁拉为自由支付50,000塞斯特斯(德绍《铭文集》7812)。塞内加(《书信集》xxvii.7)记载卡尔维西乌斯·萨比努斯为通晓希腊经典的奴隶每人支付100,000塞斯特斯。老普林尼(《自然史》vii.39)称达芙妮斯(语言学家兼教师)700,000塞斯特斯的最高奴隶价格记录后被赎身演员打破。
古典雅典奴隶价格差异类似:普通劳力约125-150德拉克马,色诺芬(《回忆录》ii.5)提及银矿监工价格达6,000德拉克马。
According to a 2002 report by the National Center for Education Statistics, about 1.7% of American kids attend private, non-sectarian schools. At Princeton, 36% of the class of 2007 came from such schools. (Interestingly, the number at Harvard is significantly lower, about 28%.) Obviously this is a huge loophole. It does at least seem to be closing, not widening. Perhaps the designers of admissions processes should take a lesson from the example of computer security, and instead of just assuming that their system can't be hacked, measure the degree to which it is.
古奴隶制经济更多参见: 琼斯,《古代世界的奴隶制》,《经济史评论》2:9(1956),收录于芬利主编《古典时代的奴隶制》,赫弗出版社,1964。
[5] 埃拉托斯特尼(前276-195年)通过不同城市影长估算地球周长,误差仅约2%。
[6] 答案分别是"不会"和"变成Windows系统"。
[7] "父亲模型"与现实最大分歧之一是对辛苦工作的估值。该模型认为辛苦本身就该获得回报;现实中
[](https://s.turbifycdn.com/aah/paulgraham/the-word-hacker-11.gif) April 2004 To the popular press, "hacker" means someone who breaks into computers. Among programmers it means a good programmer. But the two meanings are connected. To programmers, "hacker" connotes mastery in the most literal sense: someone who can make a computer do what he wants—whether the computer wants to or not. To add to the confusion, the noun "hack" also has two senses. It can be either a compliment or an insult. It's called a hack when you do something in an ugly way. But when you do something so clever that you somehow beat the system, that's also called a hack. The word is used more often in the former than the latter sense, probably because ugly solutions are more common than brilliant ones. Believe it or not, the two senses of "hack" are also connected. Ugly and imaginative solutions have something in common: they both break the rules. And there is a gradual continuum between rule breaking that's merely ugly (using duct tape to attach something to your bike) and rule breaking that is brilliantly imaginative (discarding Euclidean space). Hacking predates computers. When he was working on the Manhattan Project, Richard Feynman used to amuse himself by breaking into safes containing secret documents. This tradition continues today. When we were in grad school, a hacker friend of mine who spent too much time around MIT had his own lock picking kit. (He now runs a hedge fund, a not unrelated enterprise.) It is sometimes hard to explain to authorities why one would want to do such things. Another friend of mine once got in trouble with the government for breaking into computers. This had only recently been declared a crime, and the FBI found that their usual investigative technique didn't work. Police investigation apparently begins with a motive. The usual motives are few: drugs, money, sex, revenge.
[](https://s.turbifycdn.com/aah/paulgraham/the-word-hacker-11.gif) 2004年4月 对大众媒体而言,“黑客”指入侵计算机的人。在程序员群体中,它则代表优秀的程序员。但这两个含义存在关联。对程序员来说,“黑客”在字面意义上象征着掌控力——能让计算机服从指令的人,无论计算机本身是否情愿。
“hack”这个名词的双重含义更添混乱。它既可以是赞美也可以是贬损。用笨拙方式解决问题时称为hack;但以巧妙方式绕开系统限制同样称为hack。前者使用频率更高,或许因为拙劣方案总比精妙方案更常见。
信不信由你,这两种“hack”也存在联系。粗劣与富有想象力的方案有个共同点:它们都打破规则。从单纯丑陋的违规(用胶带固定自行车零件)到充满智慧的破局(抛弃欧几里得空间),二者之间存在渐变的谱系。
Intellectual curiosity was not one of the motives on the FBI's list. Indeed, the whole concept seemed foreign to them. Those in authority tend to be annoyed by hackers' general attitude of disobedience. But that disobedience is a byproduct of the qualities that make them good programmers. They may laugh at the CEO when he talks in generic corporate newspeech, but they also laugh at someone who tells them a certain problem can't be solved. Suppress one, and you suppress the other. This attitude is sometimes affected. Sometimes young programmers notice the eccentricities of eminent hackers and decide to adopt some of their own in order to seem smarter. The fake version is not merely annoying; the prickly attitude of these posers can actually slow the process of innovation. But even factoring in their annoying eccentricities, the disobedient attitude of hackers is a net win. I wish its advantages were better understood. For example, I suspect people in Hollywood are simply mystified by hackers' attitudes toward copyrights. They are a perennial topic of heated discussion on Slashdot. But why should people who program computers be so concerned about copyrights, of all things? Partly because some companies use _mechanisms_ to prevent copying. Show any hacker a lock and his first thought is how to pick it. But there is a deeper reason that hackers are alarmed by measures like copyrights and patents. They see increasingly aggressive measures to protect "intellectual property" as a threat to the intellectual freedom they need to do their job. And they are right. It is by poking about inside current technology that hackers get ideas for the next generation. No thanks, intellectual homeowners may say, we don't need any outside help. But they're wrong. The next generation of computer technology has often—perhaps more often than not—been developed by outsiders.
黑客行为早于计算机出现。理查德·费曼在曼哈顿计划期间就以撬开存放机密文件的保险柜为乐。这种传统延续至今——我在研究生时期有位沉迷MIT的黑客朋友,他随身携带开锁工具包(如今他经营对冲基金,这行当倒也一脉相承)。
向权威解释这类行为的动机有时很困难。我另一位朋友曾因入侵计算机惹上政府麻烦。当时这刚被列为犯罪,FBI发现常规调查手段失效了。警方破案通常始于动机分析,而常规动机不外乎毒品、金钱、性与报复。求知欲不在FBI的清单上——事实上,这个概念对他们而言相当陌生。
当权者往往反感黑客普遍的反叛精神。但这种反叛正是造就优秀程序员的特质副产品。他们会嘲笑CEO满口企业套话,同样也会嘲笑那些宣称某问题无解的人。压制前者,后者亦将消亡。
In 1977 there was no doubt some group within IBM developing what they expected to be the next generation of business computer. They were mistaken. The next generation of business computer was being developed on entirely different lines by two long-haired guys called Steve in a garage in Los Altos. At about the same time, the powers that be were cooperating to develop the official next generation operating system, Multics. But two guys who thought Multics excessively complex went off and wrote their own. They gave it a name that was a joking reference to Multics: Unix. The latest intellectual property laws impose unprecedented restrictions on the sort of poking around that leads to new ideas. In the past, a competitor might use patents to prevent you from selling a copy of something they made, but they couldn't prevent you from taking one apart to see how it worked. The latest laws make this a crime. How are we to develop new technology if we can't study current technology to figure out how to improve it? Ironically, hackers have brought this on themselves. Computers are responsible for the problem. The control systems inside machines used to be physical: gears and levers and cams. Increasingly, the brains (and thus the value) of products is in software. And by this I mean software in the general sense: i.e. data. A song on an LP is physically stamped into the plastic. A song on an iPod's disk is merely stored on it. Data is by definition easy to copy. And the Internet makes copies easy to distribute. So it is no wonder companies are afraid. But, as so often happens, fear has clouded their judgement. The government has responded with draconian laws to protect intellectual property. They probably mean well. But they may not realize that such laws will do more harm than good.
这种态度有时是刻意为之。年轻程序员注意到顶尖黑客的怪癖后,会刻意模仿以求显得聪明。这种伪装不止惹人厌烦——冒牌货的刺猬态度实际会阻碍创新进程。
但即便算上这些恼人怪癖,黑客的反叛精神仍利大于弊。我多希望人们更理解其价值。
例如好莱坞人士恐怕难以理解黑客对版权的态度。Slashdot上这类争论永不停歇。但为何偏偏是程序员对版权如此执着?部分缘于企业采用防复制技术——给黑客看到锁,他第一反应就是撬开它。但更深层的原因是,版权与专利这类措施让黑客警觉。他们将日益激进的“知识产权”保护视为对其工作必需的思想自由的威胁。他们没错。
Why are programmers so violently opposed to these laws? If I were a legislator, I'd be interested in this mystery—for the same reason that, if I were a farmer and suddenly heard a lot of squawking coming from my hen house one night, I'd want to go out and investigate. Hackers are not stupid, and unanimity is very rare in this world. So if they're all squawking, perhaps there is something amiss. Could it be that such laws, though intended to protect America, will actually harm it? Think about it. There is something very _American_ about Feynman breaking into safes during the Manhattan Project. It's hard to imagine the authorities having a sense of humor about such things over in Germany at that time. Maybe it's not a coincidence. Hackers are unruly. That is the essence of hacking. And it is also the essence of Americanness. It is no accident that Silicon Valley is in America, and not France, or Germany, or England, or Japan. In those countries, people color inside the lines. I lived for a while in Florence. But after I'd been there a few months I realized that what I'd been unconsciously hoping to find there was back in the place I'd just left. The reason Florence is famous is that in 1450, it was New York. In 1450 it was filled with the kind of turbulent and ambitious people you find now in America. (So I went back to America.) It is greatly to America's advantage that it is a congenial atmosphere for the right sort of unruliness—that it is a home not just for the smart, but for smart-alecks. And hackers are invariably smart-alecks. If we had a national holiday, it would be April 1st. It says a great deal about our work that we use the same word for a brilliant or a horribly cheesy solution. When we cook one up we're not always 100% sure which kind it is. But as long as it has the right sort of wrongness, that's a promising sign. It's odd that people think of programming as precise and methodical. _Computers_ are precise and methodical.
正是通过剖析现有技术,黑客才能构想下一代创新。“不必了”,知识产权持有者或许会说,“我们不需要外力协助”。但他们错了。下一代计算机技术往往(甚至多数时候)由局外人开发。
1977年IBM某个团队肯定在研发他们心目中的下一代商用计算机。但他们错了。真正的下一代产品正在洛斯阿尔托斯的车库里,由两个长发史蒂夫以完全不同的思路开发。同期,权威机构正合作开发官方下一代系统Multics。而两位认为Multics过度复杂的年轻人自立门户,写了个戏谑Multics的系统——Unix。
最新知识产权法对催生新思想的探索行为施加了空前限制。过去竞争对手顶多用专利阻止你销售仿制品,但无法阻止你拆解研究。新法律将此定为犯罪。若不能研究现有技术,我们如何开发新技术?
Hacking is something you do with a gleeful laugh. In our world some of the most characteristic solutions are not far removed from practical jokes. IBM was no doubt rather surprised by the consequences of the licensing deal for DOS, just as the hypothetical "adversary" must be when Michael Rabin solves a problem by redefining it as one that's easier to solve. Smart-alecks have to develop a keen sense of how much they can get away with. And lately hackers have sensed a change in the atmosphere. Lately hackerliness seems rather frowned upon. To hackers the recent contraction in civil liberties seems especially ominous. That must also mystify outsiders. Why should we care especially about civil liberties? Why programmers, more than dentists or salesmen or landscapers? Let me put the case in terms a government official would appreciate. Civil liberties are not just an ornament, or a quaint American tradition. Civil liberties make countries rich. If you made a graph of GNP per capita vs. civil liberties, you'd notice a definite trend. Could civil liberties really be a cause, rather than just an effect? I think so. I think a society in which people can do and say what they want will also tend to be one in which the most efficient solutions win, rather than those sponsored by the most influential people. Authoritarian countries become corrupt; corrupt countries become poor; and poor countries are weak. It seems to me there is a Laffer curve for government power, just as for tax revenues. At least, it seems likely enough that it would be stupid to try the experiment and find out. Unlike high tax rates, you can't repeal totalitarianism if it turns out to be a mistake. This is why hackers worry. The government spying on people doesn't literally make programmers write worse code. It just leads eventually to a world in which bad ideas win. And because this is so important to hackers, they're especially sensitive to it.
讽刺的是,黑客自身导致了这个问题。机器控制系统曾由物理部件构成——齿轮、杠杆、凸轮。如今产品的核心价值越来越多体现在软件(广义上即数据)中。黑胶唱片上的歌曲是物理压制的,iPod磁盘上的歌曲只是存储的数据。
数据天生易复制,互联网更让传播易如反掌。企业恐惧情有可原。但恐惧蒙蔽了判断力。政府以严苛法律回应,本意或许是好的。但他们可能没意识到这些法律弊大于利。
为何程序员激烈反对这些法律?若我是立法者,定会探究这个谜团——就像农场主听见鸡舍深夜骚动必定会查看。黑客不愚蠢,而举世共识极为罕见。既然他们齐声抗议,或许真有隐情。
They can sense totalitarianism approaching from a distance, as animals can sense an approaching thunderstorm. It would be ironic if, as hackers fear, recent measures intended to protect national security and intellectual property turned out to be a missile aimed right at what makes America successful. But it would not be the first time that measures taken in an atmosphere of panic had the opposite of the intended effect. There is such a thing as Americanness. There's nothing like living abroad to teach you that. And if you want to know whether something will nurture or squash this quality, it would be hard to find a better focus group than hackers, because they come closest of any group I know to embodying it. Closer, probably, than the men running our government, who for all their talk of patriotism remind me more of Richelieu or Mazarin than Thomas Jefferson or George Washington. When you read what the founding fathers had to say for themselves, they sound more like hackers. "The spirit of resistance to government," Jefferson wrote, "is so valuable on certain occasions, that I wish it always to be kept alive." Imagine an American president saying that today. Like the remarks of an outspoken old grandmother, the sayings of the founding fathers have embarrassed generations of their less confident successors. They remind us where we come from. They remind us that it is the people who break rules that are the source of America's wealth and power. Those in a position to impose rules naturally want them to be obeyed. But be careful what you ask for. You might get it. Thanks to Ken Anderson, Trevor Blackwell, Daniel Giffin, Sarah Harlin, Shiro Kawai, Jessica Livingston, Matz, Jackie McDonough, Robert Morris, Eric Raymond, Guido van Rossum, David Weinberger, and Steven Wolfram for reading drafts of this essay. (The image shows Steves Jobs and Wozniak with a "blue box." Photo by Margret Wozniak.
这些法律本为保护美国,实则可能伤害它?想想看。费曼在曼哈顿计划期间撬保险柜的行为就很美国——很难想象当时德国当局对此会有幽默感。这或许并非巧合。
黑客桀骜不驯。这是黑客精神的本质,也是美国精神的精髓。硅谷诞生于美国而非法德英日绝非偶然——那些国家的人们习惯循规蹈矩。
我在佛罗伦萨住过一阵,数月后意识到自己潜意识追寻的东西其实留在刚离开的地方。佛罗伦萨闻名于世是因1450年它是当时的纽约——充满如今在美国才能见到的那种躁动野心家(所以我回了美国)。
Reproduced by permission of Steve Wozniak.)
| Portuguese Translation | | | Hebrew Translation | Romanian Translation.
美国最大的优势在于它滋养着恰到好处的不守规矩——不仅是聪明人的家园,更是机灵鬼的乐土。黑客无一例外都是机灵鬼。若设立国家节日,该是4月1日。我们用同一个词形容绝妙方案与拙劣把戏,这很说明问题——有时我们自己都分不清做出来的是哪种。但只要具备正确的错误特质,就是好兆头。人们认为编程精确刻板实在奇怪,计算机才精确刻板,而黑客行为总伴随着欢笑声。
我们这个领域最标志性的方案往往与恶作剧相去不远。DOS授权协议的后果想必让IBM大跌眼镜,就像迈克尔·拉宾通过重新定义问题来解题时,假想“对手”的震惊反应。
机灵鬼对分寸感有着敏锐把握。近来黑客们察觉到氛围变化——反叛精神似乎越来越不受待见。
You'll find this essay and 14 others in _Hackers & Painters_.
对黑客而言,近期公民自由的收缩尤为不祥。外人可能不解:为何我们特别在意公民自由?程序员为何比牙医、销售或园艺师更关心这个?
让我用官员能理解的方式说明:公民自由不是装饰品或古怪传统,它让国家富强。若绘制人均GNP与公民自由度的图表,你会发现明确关联。公民自由可能是因而非果?我认为如此。在人们能自由言行
You'll find this essay and 14 others in _Hackers & Painters_.
[](https://s.turbifycdn.com/aah/paulgraham/what-you-can-t-say-11.gif) January 2004 Have you ever seen an old photo of yourself and been embarrassed at the way you looked? _Did we actually dress like that?_ We did. And we had no idea how silly we looked. It's the nature of fashion to be invisible, in the same way the movement of the earth is invisible to all of us riding on it. What scares me is that there are moral fashions too. They're just as arbitrary, and just as invisible to most people. But they're much more dangerous. Fashion is mistaken for good design; moral fashion is mistaken for good. Dressing oddly gets you laughed at. Violating moral fashions can get you fired, ostracized, imprisoned, or even killed. If you could travel back in a time machine, one thing would be true no matter where you went: you'd have to watch what you said. Opinions we consider harmless could have gotten you in big trouble. I've already said at least one thing that would have gotten me in big trouble in most of Europe in the seventeenth century, and did get Galileo in big trouble when he said it � that the earth moves. [1] It seems to be a constant throughout history: In every period, people believed things that were just ridiculous, and believed them so strongly that you would have gotten in terrible trouble for saying otherwise. Is our time any different? To anyone who has read any amount of history, the answer is almost certainly no. It would be a remarkable coincidence if ours were the first era to get everything just right. It's tantalizing to think we believe things that people in the future will find ridiculous. What _would_ someone coming back to visit us in a time machine have to be careful not to say? That's what I want to study here. But I want to do more than just shock everyone with the heresy du jour.
I want to find general recipes for discovering what you can't say, in any era. The Conformist Test Let's start with a test: Do you have any opinions that you would be reluctant to express in front of a group of your peers? If the answer is no, you might want to stop and think about that. If everything you believe is something you're supposed to believe, could that possibly be a coincidence? Odds are it isn't. Odds are you just think what you're told. The other alternative would be that you independently considered every question and came up with the exact same answers that are now considered acceptable. That seems unlikely, because you'd also have to make the same mistakes. Mapmakers deliberately put slight mistakes in their maps so they can tell when someone copies them. If another map has the same mistake, that's very convincing evidence. Like every other era in history, our moral map almost certainly contains a few mistakes. And anyone who makes the same mistakes probably didn't do it by accident. It would be like someone claiming they had independently decided in 1972 that bell-bottom jeans were a good idea. If you believe everything you're supposed to now, how can you be sure you wouldn't also have believed everything you were supposed to if you had grown up among the plantation owners of the pre-Civil War South, or in Germany in the 1930s � or among the Mongols in 1200, for that matter? Odds are you would have. Back in the era of terms like "well-adjusted," the idea seemed to be that there was something wrong with you if you thought things you didn't dare say out loud. This seems backward. Almost certainly, there is something wrong with you if you _don't_ think things you don't dare say out loud. Trouble What can't we say? One way to find these ideas is simply to look at things people do say, and get in trouble for. [2] Of course, we're not just looking for things we can't say.
We're looking for things we can't say that are true, or at least have enough chance of being true that the question should remain open. But many of the things people get in trouble for saying probably do make it over this second, lower threshold. No one gets in trouble for saying that 2 + 2 is 5, or that people in Pittsburgh are ten feet tall. Such obviously false statements might be treated as jokes, or at worst as evidence of insanity, but they are not likely to make anyone mad. The statements that make people mad are the ones they worry might be believed. I suspect the statements that make people maddest are those they worry might be true. If Galileo had said that people in Padua were ten feet tall, he would have been regarded as a harmless eccentric. Saying the earth orbited the sun was another matter. The church knew this would set people thinking. Certainly, as we look back on the past, this rule of thumb works well. A lot of the statements people got in trouble for seem harmless now. So it's likely that visitors from the future would agree with at least some of the statements that get people in trouble today. Do we have no Galileos? Not likely. To find them, keep track of opinions that get people in trouble, and start asking, could this be true? Ok, it may be heretical (or whatever modern equivalent), but might it also be true? Heresy This won't get us all the answers, though. What if no one happens to have gotten in trouble for a particular idea yet? What if some idea would be so radioactively controversial that no one would dare express it in public? How can we find these too? Another approach is to follow that word, heresy.
In every period of history, there seem to have been labels that got applied to statements to shoot them down before anyone had a chance to ask if they were true or not. "Blasphemy", "sacrilege", and "heresy" were such labels for a good part of western history, as in more recent times "indecent", "improper", and "unamerican" have been. By now these labels have lost their sting. They always do. By now they're mostly used ironically. But in their time, they had real force. The word "defeatist", for example, has no particular political connotations now. But in Germany in 1917 it was a weapon, used by Ludendorff in a purge of those who favored a negotiated peace. At the start of World War II it was used extensively by Churchill and his supporters to silence their opponents. In 1940, any argument against Churchill's aggressive policy was "defeatist". Was it right or wrong? Ideally, no one got far enough to ask that. We have such labels today, of course, quite a lot of them, from the all-purpose "inappropriate" to the dreaded "divisive." In any period, it should be easy to figure out what such labels are, simply by looking at what people call ideas they disagree with besides untrue. When a politician says his opponent is mistaken, that's a straightforward criticism, but when he attacks a statement as "divisive" or "racially insensitive" instead of arguing that it's false, we should start paying attention. So another way to figure out which of our taboos future generations will laugh at is to start with the labels. Take a label � "sexist", for example � and try to think of some ideas that would be called that. Then for each ask, might this be true? Just start listing ideas at random? Yes, because they won't really be random. The ideas that come to mind first will be the most plausible ones. They'll be things you've already noticed but didn't let yourself think.
In 1989 some clever researchers tracked the eye movements of radiologists as they scanned chest images for signs of lung cancer. [3] They found that even when the radiologists missed a cancerous lesion, their eyes had usually paused at the site of it. Part of their brain knew there was something there; it just didn't percolate all the way up into conscious knowledge. I think many interesting heretical thoughts are already mostly formed in our minds. If we turn off our self-censorship temporarily, those will be the first to emerge. Time and Space If we could look into the future it would be obvious which of our taboos they'd laugh at. We can't do that, but we can do something almost as good: we can look into the past. Another way to figure out what we're getting wrong is to look at what used to be acceptable and is now unthinkable. Changes between the past and the present sometimes do represent progress. In a field like physics, if we disagree with past generations it's because we're right and they're wrong. But this becomes rapidly less true as you move away from the certainty of the hard sciences. By the time you get to social questions, many changes are just fashion. The age of consent fluctuates like hemlines. We may imagine that we are a great deal smarter and more virtuous than past generations, but the more history you read, the less likely this seems. People in past times were much like us. Not heroes, not barbarians. Whatever their ideas were, they were ideas reasonable people could believe. So here is another source of interesting heresies. Diff present ideas against those of various past cultures, and see what you get. [4] Some will be shocking by present standards. Ok, fine; but which might also be true? You don't have to look into the past to find big differences. In our own time, different societies have wildly varying ideas of what's ok and what isn't.
So you can try diffing other cultures' ideas against ours as well. (The best way to do that is to visit them.) Any idea that's considered harmless in a significant percentage of times and places, and yet is taboo in ours, is a candidate for something we're mistaken about. For example, at the high water mark of political correctness in the early 1990s, Harvard distributed to its faculty and staff a brochure saying, among other things, that it was inappropriate to compliment a colleague or student's clothes. No more "nice shirt." I think this principle is rare among the world's cultures, past or present. There are probably more where it's considered especially polite to compliment someone's clothing than where it's considered improper. Odds are this is, in a mild form, an example of one of the taboos a visitor from the future would have to be careful to avoid if he happened to set his time machine for Cambridge, Massachusetts, 1992. [5] Prigs Of course, if they have time machines in the future they'll probably have a separate reference manual just for Cambridge. This has always been a fussy place, a town of i dotters and t crossers, where you're liable to get both your grammar and your ideas corrected in the same conversation. And that suggests another way to find taboos. Look for prigs, and see what's inside their heads. Kids' heads are repositories of all our taboos. It seems fitting to us that kids' ideas should be bright and clean. The picture we give them of the world is not merely simplified, to suit their developing minds, but sanitized as well, to suit our ideas of what kids ought to think. [6] You can see this on a small scale in the matter of dirty words. A lot of my friends are starting to have children now, and they're all trying not to use words like "fuck" and "shit" within baby's hearing, lest baby start using these words too. But these words are part of the language, and adults use them all the time.
So parents are giving their kids an inaccurate idea of the language by not using them. Why do they do this? Because they don't think it's fitting that kids should use the whole language. We like children to seem innocent. [7] Most adults, likewise, deliberately give kids a misleading view of the world. One of the most obvious examples is Santa Claus. We think it's cute for little kids to believe in Santa Claus. I myself think it's cute for little kids to believe in Santa Claus. But one wonders, do we tell them this stuff for their sake, or for ours? I'm not arguing for or against this idea here. It is probably inevitable that parents should want to dress up their kids' minds in cute little baby outfits. I'll probably do it myself. The important thing for our purposes is that, as a result, a well brought-up teenage kid's brain is a more or less complete collection of all our taboos � and in mint condition, because they're untainted by experience. Whatever we think that will later turn out to be ridiculous, it's almost certainly inside that head. How do we get at these ideas? By the following thought experiment. Imagine a kind of latter-day Conrad character who has worked for a time as a mercenary in Africa, for a time as a doctor in Nepal, for a time as the manager of a nightclub in Miami. The specifics don't matter � just someone who has seen a lot. Now imagine comparing what's inside this guy's head with what's inside the head of a well-behaved sixteen year old girl from the suburbs. What does he think that would shock her? He knows the world; she knows, or at least embodies, present taboos. Subtract one from the other, and the result is what we can't say. Mechanism I can think of one more way to figure out what we can't say: to look at how taboos are created. How do moral fashions arise, and why are they adopted? If we can understand this mechanism, we may be able to see it at work in our own time.
Moral fashions don't seem to be created the way ordinary fashions are. Ordinary fashions seem to arise by accident when everyone imitates the whim of some influential person. The fashion for broad-toed shoes in late fifteenth century Europe began because Charles VIII of France had six toes on one foot. The fashion for the name Gary began when the actor Frank Cooper adopted the name of a tough mill town in Indiana. Moral fashions more often seem to be created deliberately. When there's something we can't say, it's often because some group doesn't want us to. The prohibition will be strongest when the group is nervous. The irony of Galileo's situation was that he got in trouble for repeating Copernicus's ideas. Copernicus himself didn't. In fact, Copernicus was a canon of a cathedral, and dedicated his book to the pope. But by Galileo's time the church was in the throes of the Counter-Reformation and was much more worried about unorthodox ideas. To launch a taboo, a group has to be poised halfway between weakness and power. A confident group doesn't need taboos to protect it. It's not considered improper to make disparaging remarks about Americans, or the English. And yet a group has to be powerful enough to enforce a taboo. Coprophiles, as of this writing, don't seem to be numerous or energetic enough to have had their interests promoted to a lifestyle. I suspect the biggest source of moral taboos will turn out to be power struggles in which one side only barely has the upper hand. That's where you'll find a group powerful enough to enforce taboos, but weak enough to need them. Most struggles, whatever they're really about, will be cast as struggles between competing ideas. The English Reformation was at bottom a struggle for wealth and power, but it ended up being cast as a struggle to preserve the souls of Englishmen from the corrupting influence of Rome. It's easier to get people to fight for an idea.
And whichever side wins, their ideas will also be considered to have triumphed, as if God wanted to signal his agreement by selecting that side as the victor. We often like to think of World War II as a triumph of freedom over totalitarianism. We conveniently forget that the Soviet Union was also one of the winners. I'm not saying that struggles are never about ideas, just that they will always be made to seem to be about ideas, whether they are or not. And just as there is nothing so unfashionable as the last, discarded fashion, there is nothing so wrong as the principles of the most recently defeated opponent. Representational art is only now recovering from the approval of both Hitler and Stalin. [8] Although moral fashions tend to arise from different sources than fashions in clothing, the mechanism of their adoption seems much the same. The early adopters will be driven by ambition: self-consciously cool people who want to distinguish themselves from the common herd. As the fashion becomes established they'll be joined by a second, much larger group, driven by fear. [9] This second group adopt the fashion not because they want to stand out but because they are afraid of standing out. So if you want to figure out what we can't say, look at the machinery of fashion and try to predict what it would make unsayable. What groups are powerful but nervous, and what ideas would they like to suppress? What ideas were tarnished by association when they ended up on the losing side of a recent struggle? If a self-consciously cool person wanted to differentiate himself from preceding fashions (e.g. from his parents), which of their ideas would he tend to reject? What are conventional-minded people afraid of saying? This technique won't find us all the things we can't say. I can think of some that aren't the result of any recent struggle. Many of our taboos are rooted deep in the past.
But this approach, combined with the preceding four, will turn up a good number of unthinkable ideas. Why Some would ask, why would one want to do this? Why deliberately go poking around among nasty, disreputable ideas? Why look under rocks? I do it, first of all, for the same reason I did look under rocks as a kid: plain curiosity. And I'm especially curious about anything that's forbidden. Let me see and decide for myself. Second, I do it because I don't like the idea of being mistaken. If, like other eras, we believe things that will later seem ridiculous, I want to know what they are so that I, at least, can avoid believing them. Third, I do it because it's good for the brain. To do good work you need a brain that can go anywhere. And you especially need a brain that's in the habit of going where it's not supposed to. Great work tends to grow out of ideas that others have overlooked, and no idea is so overlooked as one that's unthinkable. Natural selection, for example. It's so simple. Why didn't anyone think of it before? Well, that is all too obvious. Darwin himself was careful to tiptoe around the implications of his theory. He wanted to spend his time thinking about biology, not arguing with people who accused him of being an atheist. In the sciences, especially, it's a great advantage to be able to question assumptions. The m.o. of scientists, or at least of the good ones, is precisely that: look for places where conventional wisdom is broken, and then try to pry apart the cracks and see what's underneath. That's where new theories come from. A good scientist, in other words, does not merely ignore conventional wisdom, but makes a special effort to break it. Scientists go looking for trouble.
This should be the m.o. of any scholar, but scientists seem much more willing to look under rocks. [10] Why? It could be that the scientists are simply smarter; most physicists could, if necessary, make it through a PhD program in French literature, but few professors of French literature could make it through a PhD program in physics. Or it could be because it's clearer in the sciences whether theories are true or false, and this makes scientists bolder. (Or it could be that, because it's clearer in the sciences whether theories are true or false, you have to be smart to get jobs as a scientist, rather than just a good politician.) Whatever the reason, there seems a clear correlation between intelligence and willingness to consider shocking ideas. This isn't just because smart people actively work to find holes in conventional thinking. I think conventions also have less hold over them to start with. You can see that in the way they dress. It's not only in the sciences that heresy pays off. In any competitive field, you can win big by seeing things that others daren't. And in every field there are probably heresies few dare utter. Within the US car industry there is a lot of hand-wringing now about declining market share. Yet the cause is so obvious that any observant outsider could explain it in a second: they make bad cars. And they have for so long that by now the US car brands are antibrands � something you'd buy a car despite, not because of. Cadillac stopped being the Cadillac of cars in about 1970. And yet I suspect no one dares say this. [11] Otherwise these companies would have tried to fix the problem. Training yourself to think unthinkable thoughts has advantages beyond the thoughts themselves. It's like stretching. When you stretch before running, you put your body into positions much more extreme than any it will assume during the run.
If you can think things so outside the box that they'd make people's hair stand on end, you'll have no trouble with the small trips outside the box that people call innovative. _Pensieri Stretti_ When you find something you can't say, what do you do with it? My advice is, don't say it. Or at least, pick your battles. Suppose in the future there is a movement to ban the color yellow. Proposals to paint anything yellow are denounced as "yellowist", as is anyone suspected of liking the color. People who like orange are tolerated but viewed with suspicion. Suppose you realize there is nothing wrong with yellow. If you go around saying this, you'll be denounced as a yellowist too, and you'll find yourself having a lot of arguments with anti-yellowists. If your aim in life is to rehabilitate the color yellow, that may be what you want. But if you're mostly interested in other questions, being labelled as a yellowist will just be a distraction. Argue with idiots, and you become an idiot. The most important thing is to be able to think what you want, not to say what you want. And if you feel you have to say everything you think, it may inhibit you from thinking improper thoughts. I think it's better to follow the opposite policy. Draw a sharp line between your thoughts and your speech. Inside your head, anything is allowed. Within my head I make a point of encouraging the most outrageous thoughts I can imagine. But, as in a secret society, nothing that happens within the building should be told to outsiders. The first rule of Fight Club is, you do not talk about Fight Club. When Milton was going to visit Italy in the 1630s, Sir Henry Wootton, who had been ambassador to Venice, told him his motto should be _"i pensieri stretti & il viso sciolto."_ Closed thoughts and an open face. Smile at everyone, and don't tell them what you're thinking. This was wise advice.
Milton was an argumentative fellow, and the Inquisition was a bit restive at that time. But I think the difference between Milton's situation and ours is only a matter of degree. Every era has its heresies, and if you don't get imprisoned for them you will at least get in enough trouble that it becomes a complete distraction. I admit it seems cowardly to keep quiet. When I read about the harassment to which the Scientologists subject their critics [12], or that pro-Israel groups are "compiling dossiers" on those who speak out against Israeli human rights abuses [13], or about people being sued for violating the DMCA [14], part of me wants to say, "All right, you bastards, bring it on." The problem is, there are so many things you can't say. If you said them all you'd have no time left for your real work. You'd have to turn into Noam Chomsky. [15] The trouble with keeping your thoughts secret, though, is that you lose the advantages of discussion. Talking about an idea leads to more ideas. So the optimal plan, if you can manage it, is to have a few trusted friends you can speak openly to. This is not just a way to develop ideas; it's also a good rule of thumb for choosing friends. The people you can say heretical things to without getting jumped on are also the most interesting to know. _Viso Sciolto?_ I don't think we need the _viso sciolto_ so much as the _pensieri stretti._ Perhaps the best policy is to make it plain that you don't agree with whatever zealotry is current in your time, but not to be too specific about what you disagree with. Zealots will try to draw you out, but you don't have to answer them. If they try to force you to treat a question on their terms by asking "are you with us or against us?" you can always just answer "neither". Better still, answer "I haven't decided." That's what Larry Summers did when a group tried to put him in this position.
Explaining himself later, he said "I don't do litmus tests." [16] A lot of the questions people get hot about are actually quite complicated. There is no prize for getting the answer quickly. If the anti-yellowists seem to be getting out of hand and you want to fight back, there are ways to do it without getting yourself accused of being a yellowist. Like skirmishers in an ancient army, you want to avoid directly engaging the main body of the enemy's troops. Better to harass them with arrows from a distance. One way to do this is to ratchet the debate up one level of abstraction. If you argue against censorship in general, you can avoid being accused of whatever heresy is contained in the book or film that someone is trying to censor. You can attack labels with meta-labels: labels that refer to the use of labels to prevent discussion. The spread of the term "political correctness" meant the beginning of the end of political correctness, because it enabled one to attack the phenomenon as a whole without being accused of any of the specific heresies it sought to suppress. Another way to counterattack is with metaphor. Arthur Miller undermined the House Un-American Activities Committee by writing a play, "The Crucible," about the Salem witch trials. He never referred directly to the committee and so gave them no way to reply. What could HUAC do, defend the Salem witch trials? And yet Miller's metaphor stuck so well that to this day the activities of the committee are often described as a "witch-hunt." Best of all, probably, is humor. Zealots, whatever their cause, invariably lack a sense of humor. They can't reply in kind to jokes. They're as unhappy on the territory of humor as a mounted knight on a skating rink. Victorian prudishness, for example, seems to have been defeated mainly by treating it as a joke.
Likewise its reincarnation as political correctness. "I am glad that I managed to write 'The Crucible,'" Arthur Miller wrote, "but looking back I have often wished I'd had the temperament to do an absurd comedy, which is what the situation deserved." [17] ABQ A Dutch friend says I should use Holland as an example of a tolerant society. It's true they have a long tradition of comparative open-mindedness. For centuries the low countries were the place to go to say things you couldn't say anywhere else, and this helped to make the region a center of scholarship and industry (which have been closely tied for longer than most people realize). Descartes, though claimed by the French, did much of his thinking in Holland. And yet, I wonder. The Dutch seem to live their lives up to their necks in rules and regulations. There's so much you can't do there; is there really nothing you can't say? Certainly the fact that they value open-mindedness is no guarantee. Who thinks they're not open-minded? Our hypothetical prim miss from the suburbs thinks she's open-minded. Hasn't she been taught to be? Ask anyone, and they'll say the same thing: they're pretty open-minded, though they draw the line at things that are really wrong. (Some tribes may avoid "wrong" as judgemental, and may instead use a more neutral sounding euphemism like "negative" or "destructive".) When people are bad at math, they know it, because they get the wrong answers on tests. But when people are bad at open-mindedness they don't know it. In fact they tend to think the opposite. Remember, it's the nature of fashion to be invisible. It wouldn't work otherwise. Fashion doesn't seem like fashion to someone in the grip of it. It just seems like the right thing to do. It's only by looking from a distance that we see oscillations in people's idea of the right thing to do, and can identify them as fashions. Time gives us such distance for free.
Indeed, the arrival of new fashions makes old fashions easy to see, because they seem so ridiculous by contrast. From one end of a pendulum's swing, the other end seems especially far away. To see fashion in your own time, though, requires a conscious effort. Without time to give you distance, you have to create distance yourself. Instead of being part of the mob, stand as far away from it as you can and watch what it's doing. And pay especially close attention whenever an idea is being suppressed. Web filters for children and employees often ban sites containing pornography, violence, and hate speech. What counts as pornography and violence? And what, exactly, is "hate speech?" This sounds like a phrase out of _1984._ Labels like that are probably the biggest external clue. If a statement is false, that's the worst thing you can say about it. You don't need to say that it's heretical. And if it isn't false, it shouldn't be suppressed. So when you see statements being attacked as x-ist or y-ic (substitute your current values of x and y), whether in 1630 or 2030, that's a sure sign that something is wrong. When you hear such labels being used, ask why. Especially if you hear yourself using them. It's not just the mob you need to learn to watch from a distance. You need to be able to watch your own thoughts from a distance. That's not a radical idea, by the way; it's the main difference between children and adults. When a child gets angry because he's tired, he doesn't know what's happening. An adult can distance himself enough from the situation to say "never mind, I'm just tired." I don't see why one couldn't, by a similar process, learn to recognize and discount the effects of moral fashions. You have to take that extra step if you want to think clearly. But it's harder, because now you're working against social customs instead of with them. Everyone encourages you to grow up to the point where you can discount your own bad moods.
Few encourage you to continue to the point where you can discount society's bad moods. How can you see the wave, when you're the water? Always be questioning. That's the only defence. What can't you say? And why? _ Notes_ Thanks to Sarah Harlin, Trevor Blackwell, Jessica Livingston, Robert Morris, Eric Raymond and Bob van der Zwaan for reading drafts of this essay, and to Lisa Randall, Jackie McDonough, Ryan Stanley and Joel Rainey for conversations about heresy.
Needless to say they bear no blame for opinions expressed in it, and especially for opinions _not_ expressed in it.
| Re: What You Can't Say | | | Labels | Japanese Translation | | | French Translation | German Translation | | | Dutch Translation | Romanian Translation | | | Hebrew Translation | Turkish Translation | | | Chinese Translation | Buttons | | | A Civic Duty to Annoy | The Perils of Obedience | | | Aliens Cause Global Warming | Hays Code | | | Stratagem 32 | Conspiracy Theories | | | Mark Twain: Corn-pone Opinions | A Blacklist for "Excuse Makers" | | | What You Can't Say Will Hurt You.
[](https://s.turbifycdn.com/aah/paulgraham/what-you-can-t-say-11.gif) 2004年1月 你可曾翻看旧照片时被自己当年的模样尴尬到?我们当年真穿成那样吗?确实如此。而我们当时全然不知自己有多滑稽。时尚的本质就是让人视而不见,正如地球上所有人都感受不到大地的运动。 令我恐惧的是,道德同样存在时尚潮流。它们同样武断,同样被多数人视而不见,却危险得多。奇装异服招致嘲笑,违背道德风尚却可能让你失业、遭排挤、入狱甚至丧命。 若乘时光机回到过去,无论哪个时代都需谨言慎行。今天我们视为无害的观点,曾可能招致灭顶之灾。仅"地球会转动"这一句,就足以让17世纪欧洲多数地区的我惹上大麻烦——伽利略因此遭难便是明证[1]。 历史似乎总有恒定规律:每个时代的人都坚信某些荒诞之事,其信念之强烈足以让异议者万劫不复。 我们这个时代会例外吗?但凡读过历史的人都明白答案几乎必然是否定的。若说我们首次完美认知了一切,那才是惊人的巧合。 想到我们笃信之事将被未来视为荒谬,实在令人心痒。乘时光机来访的未来人需对哪些话题三缄其口?这正是本文想探讨的。但我不止想用当下的异端邪说震撼众人,更希望找出任何时代都适用的"禁忌发现法则"。 从众测试 先做个测试:可有在同行面前难以启齿的观点? 若答案是没有,你该停下来深思。若你所有信念都符合社会期待,这真是巧合吗?大概率不是。你很可能只是在复述被告知的答案。 另一种可能是你独立思考每个问题后,恰好得出与当下主流完全一致的结论。这概率微乎其微,因为你必须连错误都复刻得一模一样。地图制作者会故意留些小纰漏来识别抄袭——若另一张地图出现相同错误,便是铁证。 与历史上所有时代相同,我们的道德地图必然存在谬误。而犯相同错误者,绝非偶然。就像某人声称在1972年独立认定喇叭裤是绝妙设计。 若你对当下所有正统观念照单全收,又怎能确信自己若生长在内战前南方种植园、1930年代的德国或1200年的蒙古,不会同样全盘接受当时的正统?大概率你会。 在"适应良好"这类术语盛行的年代,不敢宣之于口的想法被视为心理缺陷。这实在本末倒置。事实上,若你脑中不存在不敢明言的想法,那才真正有问题。 禁忌清单 哪些是当代禁忌?观察那些因言获罪的事件便能窥见一二[2]。 当然,我们不止寻找不可言说之事,更探寻那些被禁却可能属实,或至少值得商榷的观点。多数因言获罪的案例都跨越了这条较低门槛。没人会因声称2+2=5或匹兹堡人身高十尺而惹麻烦——这些明显谬误只会被当作玩笑或精神异常,而非激怒他人。真正令人暴怒的,是那些他们担心有人会相信的言论。而最令人震怒的,恐怕正是那些可能属实的观点。 若伽利略声称帕多瓦居民身高十尺,只会被当作无害怪人。但宣称地球绕日运转则触犯天条——教会深知这将引发思想地震。 回望历史,这条经验法则屡试不爽。许多曾因言获罪的观点如今看来人畜无害。因此未来访客很可能认同当下部分"危险思想"。难道当代没有伽利略?概率微乎其微。 要发现他们,请追踪那些因言获罪的案例,然后自问:这可能是真的吗?好吧,它或许离经叛道(或触犯当代禁忌),但是否存在真实性? 异端标签 此法未必穷尽所有答案。若某观点尚未有人敢公开表述呢?若某思想争议性太强以致无人敢碰呢? 另一条线索是追踪"异端"标签。每个历史时期都存在特定词汇,能在人们思考真伪前就将观点扼杀。西方史上"亵渎""渎神""异端"曾扮演此角,正如近世的"伤风败俗""不合时宜""非美活动"。这些标签如今锋芒尽失——它们总会如此——多被反讽使用。但在当时,它们威力无穷。 比如"失败主义"如今已无特殊政治含义。但在1917年的德国,它是鲁登道夫清洗主和派的武器;二战初期被丘吉尔派广泛用于压制反对声音。1940年,任何反对丘吉尔激进政策的言论都是"失败主义"。其正确与否?最好根本无人深究。 当代同样充斥着此类标签,从万能的"不合时宜"到可怕的"制造分裂"。任何时代,只需观察人们给异见贴的标签(除"错误"外),就能轻易识别禁忌。当政客称对手"制造分裂"而非反驳其谬误时,我们就该警惕了。 因此预测未来将嘲笑的当代禁忌,不妨从标签入手。以"性别歧视"为例,设想哪些观点会被如此指控,然后逐一追问:这可能是真的吗? 需要天马行空罗列观点吗?正是如此,因为它们实际并非随机。最先浮现的念头往往最可信——那些你已察觉却不敢深想的蛛丝马迹。 198年一项巧妙研究追踪放射科医生查看胸片的眼动轨迹[3]。发现即使医生漏诊癌变,其视线常在病灶处停留——部分大脑已察觉异常,只是未上升至意识层面。许多精彩的异端思想早已在我们脑中成形。只要暂时关闭自我审查,它们便会率先浮现。 时空透镜 若能窥见未来,当代哪些禁忌将被嘲笑便一目了然。虽不能至,但观往知来亦不失良策。审视今昔观念变迁,便能发现当下谬误。 某些古今差异确属进步。在物理学等领域,我们与前人分歧是因为站在真理这边。但随着领域软性化,这种确定性迅速衰减。到了社会议题,许多变化仅是风尚使然。比如性同意年龄的波动,简直如裙摆高低般无常。 我们常自诩比古人更智慧高尚,但读史越多,这种幻象就越脆弱。古人与我们并无二致——非英雄亦非野蛮人。他们的信念,都是理性人可能持有的观点。 因此古今观念对比是异端思想的富矿[4]。将当下观念与各历史时期碰撞,某些组合按当代标准必然惊世骇俗。但其中哪些可能属实? 差异不必远求。当代不同社会对"恰当"的定义已天差地别。因此跨文化观念对比同样有效(亲身体验最佳)。若某观点在相当比例时空中被视为无害,唯独在当代成为禁忌,就很可能是我们的认知偏差。 例如政治正确巅峰的1990年代初,哈佛给教职工发放的手册竟将"称赞同事或学生衣着"列为不当行为。"衬衫真好看"成了禁语。纵观古今寰宇,罕有文化将赞美衣着视为失礼,反将其作为特别礼仪的却不少。这很可能是未来时光旅客需在1992年马萨诸塞州剑桥市谨防触碰的温和禁忌范例[5]。 道学先生 若未来真有时光机,剑桥市恐怕需要单独编撰禁忌手册。这个锱铢必较之地,连语法和思想都会在对话中被同步纠正。这提示了另一条发现禁忌的路径:观察卫道士的脑内清单。 孩童头脑是当代禁忌的储藏室。我们理所当然认为孩子该有纯净思想。给他们的世界观不仅因认知水平而简化,更为符合我们对"童真"的期待而消毒[6]。 脏话现象便是微观例证。我许多朋友初为人父母,都严防孩子在旁时说出"操""屎"等字眼。但这些本是语言组成部分,成人日常使用。父母通过自我审查给孩子营造失真的语言环境。为何如此?只因我们认为孩童不该接触完整语言。我们热衷维护"天真无邪"的幻象[7]。 多数成人同样刻意给孩子扭曲的世界观。圣诞老人便是显例。我们都觉得孩子信圣诞老人很可爱——我亦如此。但值得玩味:我们讲述这些,究竟为孩子,还是为自己? 此处我不评判对错。父母给孩子思想"穿童装"或许不可避免——我将来很可能也如此。关键在于:正因如此,教养良好的青少年头脑堪称当代禁忌的完整收藏,且品相崭新——未经现实玷污。那些终将被证明荒谬的观念,几乎必然存于其中。 如何提取这些禁忌?想象一个现代版康拉德式人物:当过非洲雇佣兵,做过尼泊尔医生,混过迈阿密夜店经理——重点是他阅历丰富。现在比较他的头脑与郊区乖顺十六岁少女的头脑。哪些他的认知会震碎她的三观?他通晓世情,她则承载(或化身)当代禁忌。两者相减,便是不可言说之物。 机制溯源 最后一条发现禁忌的路径:研究禁忌的生成机制。道德风尚如何兴起?为何被接纳?理解这点或能洞察当下运作。 道德风尚的诞生迥异于日常时尚。后者常源于对意见领袖的偶然模仿——15世纪末欧洲流行宽头鞋是因法王查理八世有六趾;"盖瑞"这个名字走红是因演员弗兰克·库珀用了印第安纳工业城的名号。而道德风尚往往被刻意制造。当我们被禁止表达,通常是某些群体不愿我们发声。 当群体焦虑时,禁令最严。伽利略的讽刺在于:他因重述哥白尼观点获罪,而哥白尼本人安然无恙——这位教士甚至将著作献给教皇。但到伽利略时代,教会深陷反宗教改革漩涡,对异端思想更为敏感。 要发起禁忌,群体须处于强弱临界点。强者无需禁忌保护——如今贬损美国人或英国人不会被视作失礼。但群体又须足够强势来推行禁忌。比如恋粪癖至今人数不足、行动力欠佳,未能将其癖好升华为生活方式。 我认为道德禁忌最大源头是权力拉锯战中勉强占优的一方——强到能推行禁忌,又弱到需要禁忌。 多数斗争无论实质为何,终被包装为理念之争。英国宗教改革本质是财富权力争夺,却被塑造成"拯救英格兰灵魂免受罗马腐蚀"。毕竟鼓动人们为理念而战更容易。而胜者理念总被视为真理化身,仿佛上帝借胜利昭示认可。 我们常将二战视为自由对极权的胜利,却 conveniently 忘记苏联亦是战胜国之一。 并非说斗争从不关乎理念,而是说它们总被包装成理念之争——无论实质如何。正如没有比过时时尚更土的事物,也没有比刚败北对手的信条更错误的存在。具象艺术至今仍在摆脱希特勒与斯大林共同青睐的阴影[8]。 尽管道德风尚的起源异于服装潮流,其传播机制却惊人相似。早期采纳者受野心驱动——那些刻意标新立异以区分庸众的"酷族"。当时尚确立,第二批更庞大的群体因恐惧加入[9]——他们不为出众,只为免于出众。 因此要预测当代禁忌,可观察时尚机器将制造哪些言论禁区。哪些群体强势却焦虑?他们想压制何种思想?近期斗争中,哪些理念因站错队而被污名化?当刻意求酷者想区别于父辈时尚,会拒斥哪些观念?庸众最恐惧表达什么? 此法不能穷尽所有禁忌。某些禁忌根植远古,与近期斗争无关。但结合前四法,能发掘大量"不可想"之念。 为何探寻 或有人问:为何要挖掘这些恶心不堪的观念?何必翻检这些精神秽物? 首先,这与我儿时翻石头同理——纯粹好奇。我对禁忌尤感好奇。让我亲眼见证,自行判断。 其次,因我不愿被谬误裹挟。若如所有时代那样,我们正信奉着未来看来荒谬的信条,我至少要知晓它们以保持清醒。 第三,这有益思维。卓越工作需要无远弗届的头脑,尤其需要习惯越界的思维习惯。 伟大成果往往源于被忽视的念头,而最被忽视的莫过于"不可想"之物。比如自然选择——如此简洁,为何前人未察?答案昭然若揭。达尔文自己都小心翼翼绕开理论隐含的锋芒。他宁愿研究生物学,也不愿被无神论指控纠缠。 尤其在科学领域,质疑假设的能力至关重要。优秀科学家的方法论正是:寻找传统智慧的裂缝,撬开缝隙一探究竟。新理论由此诞生。 换言之,优秀科学家不仅忽视传统智慧,更主动打破它。他们自找麻烦。这本该是所有学者的方法论,但科学家似乎更愿翻检精神秽物[10]。 为何?或因科学家更聪明——多数物理学家若有必要能拿下法国文学博士,但鲜有法国文学教授能搞定物理学博士;或因科学领域真伪更易辨明,赋予他们更大勇气(或因真伪分明,科学家必须靠真才实学而非政治手腕上位)。 无论原因,智力与接纳惊世骇俗观念的意愿确存关联。这不仅因聪明人主动寻找传统漏洞,更因他们本就较少受陈规束缚——从穿衣风格便可见一斑。 异端思维的红利不限于科学。任何竞争领域,洞察他人不敢见之事都能大获全胜。每个领域都存在少人敢言的异端。当下美国汽车业正为市场份额萎缩焦头烂额,其实原因一目了然——他们造的车太差。积弊日久,如今美国车标已成"负品牌"——人们购车时需克服而非因其选择。凯迪拉克约在1970年就失去了"汽车中的凯迪拉克"地位。但恐怕无人敢言[11],否则早该整改。 训练"非常之思"的好处超越具体观点本身。如同拉伸运动——热身时将身体推向日常不会达到的极限,就能轻松应对所谓的"创新"小突破。若你能构思令人毛骨悚然的离经叛道,那些被称作"跳出框架"的小把戏将不值一提。 缜思 发现不可言说之物后该如何处置?我的建议是:保持缄默。至少,慎选战场。 假设未来掀起"禁黄运动",任何使用黄色的提案都被斥为"黄色主义",连喜好黄色者都遭怀疑。喜欢橙色者虽被容忍但受侧目。若你洞悉黄色本无过错,公开表态只会被贴上"黄色主义者"标签,陷入无休止的论战。若你人生目标是为黄色平反,这或许正中下怀;但若志在别处,此类标签只会徒耗精力。与愚者争论,终成愚者。 关键不在于畅所欲言,而在于畅所欲想。若觉得必须言尽所思,反而会抑制"不当之思"。我认为相反策略更佳:在思想与言语间划清界限。脑海中应允许任何念头——我刻意鼓励自己能想象的最离经叛道的思想。但如同秘密社团,屋内发生的一切绝不外泄。"搏击俱乐部第一法则:不得谈论搏击俱乐部。" 1630年代弥尔顿造访意大利前,曾任威尼斯大使的亨利·沃顿赠他箴言:"缜思展颜"(i pensieri stretti & il viso sciolto)。思想紧闭,表情开朗。对众人微笑,不透露所思。这是明智建议——弥尔顿性好争辩,而当时宗教裁判所正躁动不安。不过弥尔顿的处境与我们只有程度之差。每个时代都有其异端,即便不因此入狱,也足以惹上让你彻底分心的麻烦。 我承认保持沉默似显懦弱。当读到科学教派对批评者的骚扰[12],或亲以色列团体为批评以色列人权状况者"建立档案"[13],或人们因违反DMCA被起诉[14],我内心某处总想怒吼:"放马过来吧,混蛋们!"问题在于,不可言说之事太多。若全盘托出,将无暇顾及真正工作。你会变成另一个乔姆斯基[15]。 但思想秘而不宣的代价是丧失讨论的益处。交流催生新想法。因此若能安排,最佳方案是有几位可交心的挚友。这不仅是开拓思路之法,也是择友的黄金准则——那些能容你抒发异见而不群起攻之者,往往也是最有趣的灵魂。 展颜? 相比"展颜",我们或许更需"缜思"。最佳策略或许是明确表示不认同当下的任何狂热,但避免具体表态。狂热者会试图引蛇出洞,但你无须接招。当他们逼你站队:"支持还是反对?"你永远可以回答:"都不是。" 更高明的回应是"我尚未决定"。当某团体试图逼拉里·萨默斯站队时,他如此应对。事后他解释:"我不做 litmus tests(酸碱测试)[16]。"人们热衷争论的许多问题其实极其复杂,快速作答并无奖赏。 若"反黄主义者"气焰嚣张而你决定反击,有些方法能避免被贴上"黄色主义"标签。如同古代军队的散兵,避免与敌军主力正面交锋,最好远距离箭雨骚扰。 方法之一是提升讨论的抽象层级。若你反对审查制度本身,就能避免为某部被禁书籍或电影中的异端内容辩护。你可以用"元标签"攻击标签——那些指涉"用标签压制讨论"的标签。"政治正确"一词的传播,正是政治正确终结的开端——它使人们能整体批判这种现象,而不被指控触犯其试图压制的具体禁忌。 另一种反击是用隐喻。阿瑟·米勒通过描写塞勒姆审巫案的戏剧《熔炉》间接抨击"非美活动调查委员会"。他从未直接提及该机构,使其无从反驳——难道委员会能为塞勒姆审巫案辩护?这个隐喻如此成功,至今该委员会行径仍常被称作"猎巫"。 但最高明的或许是幽默。无论持何种主张,狂热者都缺乏幽默感。他们对玩笑无力以同样方式回击,如同冰场上的重甲骑士般狼狈。例如维多利亚时代的假正经,主要就是被当作笑料击败的。政治正确作为其转世灵童亦然。"我很高兴写了《熔.
August 2003 We may be able to improve the accuracy of Bayesian spam filters by having them follow links to see what's waiting at the other end. Richard Jowsey of death2spam now does this in borderline cases, and reports that it works well. Why only do it in borderline cases? And why only do it once? As I mentioned in Will Filters Kill Spam?, following all the urls in a spam would have an amusing side-effect. If popular email clients did this in order to filter spam, the spammer's servers would take a serious pounding. The more I think about this, the better an idea it seems. This isn't just amusing; it would be hard to imagine a more perfectly targeted counterattack on spammers. So I'd like to suggest an additional feature to those working on spam filters: a "punish" mode which, if turned on, would spider every url in a suspected spam n times, where n could be set by the user. [1] As many people have noted, one of the problems with the current email system is that it's too passive. It does whatever you tell it. So far all the suggestions for fixing the problem seem to involve new protocols. This one wouldn't. If widely used, auto-retrieving spam filters would make the email system _rebound._ The huge volume of the spam, which has so far worked in the spammer's favor, would now work against him, like a branch snapping back in his face. Auto-retrieving spam filters would drive the spammer's costs up, and his sales down: his bandwidth usage would go through the roof, and his servers would grind to a halt under the load, which would make them unavailable to the people who would have responded to the spam. Pump out a million emails an hour, get a million hits an hour on your servers. We would want to ensure that this is only done to suspected spams.
通过让贝叶斯垃圾邮件过滤器追踪链接以探查目标页面内容,我们或许能提升其过滤准确率。death2spam的Richard Jowsey现已在边缘案例中应用该技术,并反馈效果良好。
为何仅限边缘案例?又为何只追踪一次?
正如我在《过滤器能否终结垃圾邮件?》中所言,追踪垃圾邮件中所有链接将产生有趣副作用——若主流邮件客户端为过滤垃圾邮件执行此操作,垃圾邮件发送者的服务器将遭受重创。深思之下,这个构想愈发显得精妙。这不仅是趣味性设计,更是对垃圾邮件发送者最精准的反制措施。
因此我建议为垃圾邮件过滤器增设"惩罚"模式:启用后,系统将对可疑垃圾邮件中的每个链接进行n次爬取(n值可由用户设定)[1]。
许多人都指出,现行邮件系统的核心缺陷在于过度被动。它只会机械执行指令。迄今为止,所有解决方案都涉及新协议设计,而本方案无需如此。
若自动追踪式垃圾邮件过滤器得到普及,邮件系统将具备"回弹"能力。垃圾邮件海量传播的优势将逆转为发送者的噩梦,如同反弹的树枝直击其面门。这种过滤器将同时抬高垃圾邮件发送者的运营成本与降低其转化率:带宽消耗激增,服务器在巨量请求下瘫痪,使潜在响应者无法访问目标页面。
每小时发送百万封邮件?那就准备承受服务器每小时百万次请求冲击。
As a rule, any url sent to millions of people is likely to be a spam url, so submitting every http request in every email would work fine nearly all the time. But there are a few cases where this isn't true: the urls at the bottom of mails sent from free email services like Yahoo Mail and Hotmail, for example. To protect such sites, and to prevent abuse, auto-retrieval should be combined with blacklists of spamvertised sites. Only sites on a blacklist would get crawled, and sites would be blacklisted only after being inspected by humans. The lifetime of a spam must be several hours at least, so it should be easy to update such a list in time to interfere with a spam promoting a new site. [2] High-volume auto-retrieval would only be practical for users on high-bandwidth connections, but there are enough of those to cause spammers serious trouble. Indeed, this solution neatly mirrors the problem. The problem with spam is that in order to reach a few gullible people the spammer sends mail to everyone. The non-gullible recipients are merely collateral damage. But the non-gullible majority won't stop getting spam until they can stop (or threaten to stop) the gullible from responding to it. Auto-retrieving spam filters offer them a way to do this. Would that kill spam? Not quite. The biggest spammers could probably protect their servers against auto-retrieving filters. However, the easiest and cheapest way for them to do it would be to include working unsubscribe links in their mails. And this would be a necessity for smaller fry, and for "legitimate" sites that hired spammers to promote them. So if auto-retrieving filters became widespread, they'd become auto-unsubscribing filters.
必须确保该机制仅针对可疑垃圾邮件触发。通常而言,群发邮件中的链接基本可判定为垃圾网址,因此扫描每封邮件的所有http请求在绝大多数情况下安全有效。但存在少数例外情况,例如雅虎邮箱、Hotmail等免费邮件服务在邮件末尾自动添加的网址。
为保护此类正常网站并防止滥用,自动追踪机制应与垃圾广告网址黑名单配合使用。仅列入黑名单的网站会被爬取,且黑名单须经人工审核后方可生效。垃圾邮件的存活周期至少数小时,因此及时更新名单以拦截新推广网站完全可行[2]。
高频自动追踪仅适合宽带用户实施,但这类用户的规模已足以对垃圾邮件发送者造成实质性打击。该方案与垃圾邮件问题形成了精妙镜像:垃圾邮件为捕获少数轻信者而殃及大众,非目标群体只是附带伤害;而唯有阻止(或威胁阻止)轻信者响应,多数人才能摆脱骚扰。自动追踪过滤器正提供了这种反制手段。
这能否彻底终结垃圾邮件?未必。顶级垃圾邮件发送者或许能加固服务器防御。但对他们而言,最经济便捷的应对方案就是在邮件中加入有效退订链接。这对中小规模发送者及雇佣垃圾邮件推广的"合法"网站更是刚需。因此当自动追踪过滤器普及之时,它们将演变为自动退订过滤器。
届时,垃圾邮件将与系统崩溃、病毒和弹窗广告一样,沦为仅困扰那些不愿使用防护软件的用户的顽疾。
[1] 自动追踪过滤器需处理重定向,某些情况(如仅含"点击这里"的页面)还需追踪多级链接。确保http请求与主流浏览器行为完全一致,包括访问顺序和来源页参数。
若响应超时,则默认赋予较高垃圾概率值。
In this scenario, spam would, like OS crashes, viruses, and popups, become one of those plagues that only afflict people who don't bother to use the right software. Notes [1] Auto-retrieving filters will have to follow redirects, and should in some cases (e.g. a page that just says "click here") follow more than one level of links. Make sure too that the http requests are indistinguishable from those of popular Web browsers, including the order and referrer. If the response doesn't come back within x amount of time, default to some fairly high spam probability. Instead of making n constant, it might be a good idea to make it a function of the number of spams that have been seen mentioning the site. This would add a further level of protection against abuse and accidents. [2] The original version of this article used the term "whitelist" instead of "blacklist". Though they were to work like blacklists, I preferred to call them whitelists because it might make them less vulnerable to legal attack. This just seems to have confused readers, though. There should probably be multiple blacklists. A single point of failure would be vulnerable both to attack and abuse. Thanks to Brian Burton, Bill Yerazunis, Dan Giffin, Eric Raymond, and Richard Jowsey for reading drafts of this.
| FFB FAQ | | | Japanese Translation | A Perl FFB | | | Lycos DDoS@Home.
将n值设为与目标网站被举报次数的关联函数,而非固定值,可额外防范滥用和误伤。
[2] 本文初版使用"白名单"而非"黑名单"表述。虽实际功能等同黑名单,但采用白名单称谓可能降低法律风险。不过事实证明这反而造成了读者困惑。
应设立多重黑名单体系。单一故障点易受攻击和滥用。
致谢 感谢Brian Burton、Bill Yerazunis、Dan Giffin、Eric Raymond和Richard Jowsey审阅本文草稿。
| 常见问题解答
| | | 日文译本
| Perl实现方案
| | | Lycos分布式拒绝服务计划
May 2003 If Lisp is so great, why don't more people use it? I was asked this question by a student in the audience at a talk I gave recently. Not for the first time, either. In languages, as in so many things, there's not much correlation between popularity and quality. Why does John Grisham ( _King of Torts_ sales rank, 44) outsell Jane Austen ( _Pride and Prejudice_ sales rank, 6191)? Would even Grisham claim that it's because he's a better writer? Here's the first sentence of _Pride and Prejudice:_ > It is a truth universally acknowledged, that a single man in possession of a good fortune must be in want of a wife.
"It is a truth universally acknowledged?" Long words for the first sentence of a love story. Like Jane Austen, Lisp looks hard. Its syntax, or lack of syntax, makes it look completely unlike the languages most people are used to. Before I learned Lisp, I was afraid of it too. I recently came across a notebook from 1983 in which I'd written:
> I suppose I should learn Lisp, but it seems so foreign.
Fortunately, I was 19 at the time and not too resistant to learning new things. I was so ignorant that learning almost anything meant learning new things. People frightened by Lisp make up other reasons for not using it. The standard excuse, back when C was the default language, was that Lisp was too slow. Now that Lisp dialects are among the faster languages available, that excuse has gone away. Now the standard excuse is openly circular: that other languages are more popular. (Beware of such reasoning. It gets you Windows.) Popularity is always self-perpetuating, but it's especially so in programming languages. More libraries get written for popular languages, which makes them still more popular. Programs often have to work with existing programs, and this is easier if they're written in the same language, so languages spread from program to program like a virus. And managers prefer popular languages, because they give them more leverage over developers, who can more easily be replaced. Indeed, if programming languages were all more or less equivalent, there would be little justification for using any but the most popular. But they aren't all equivalent, not by a long shot. And that's why less popular languages, like Jane Austen's novels, continue to survive at all. When everyone else is reading the latest John Grisham novel, there will always be a few people reading Jane Austen instead.
| Japanese Translation | | | Romanian Translation | Spanish Translation
2003年5月 如果Lisp如此优秀,为何使用它的人不多?这是最近一次演讲中,台下学生向我提出的问题。而且这已不是第一次被问及。 在语言领域,如同许多事物一样,流行度与品质并无太大关联。为何约翰·格里沙姆(《毒物侵权案》销售排名第44位)的销量远超简·奥斯汀(《傲慢与偏见》销售排名第6191位)?难道格里沙姆本人敢声称这是因为他文笔更佳? 以下是《傲慢与偏见》的开篇第一句: > 凡是有钱的单身汉,总想娶位太太,这已经成了一条举世公认的真理。 "举世公认的真理"?爱情故事的第一句就用这么拗口的词。 与简·奥斯汀相似,Lisp看起来艰深晦涩。它的语法——或者说语法缺失——让它显得与主流语言截然不同。在我学习Lisp之前,也曾对它心怀畏惧。最近我翻到1983年的笔记,上面写着: > 我或许该学Lisp,但它看起来太陌生了 所幸当时我只有19岁,对学习新事物尚不抗拒。那时的我如此无知,几乎学任何东西都意味着接触全新领域。 对Lisp心存畏惧的人会编造其他拒绝理由。在C语言作为默认语言的年代,标准借口是Lisp速度太慢。如今Lisp方言已成为速度最快的语言之一,这个借口已不攻自破。现在的标准托辞则陷入赤裸裸的循环论证:因为其他语言更流行。 (警惕这种逻辑。它会让你用上Windows系统。) 流行性总是自我延续的,在编程语言领域尤其如此。流行语言会获得更多函数库支持,这又进一步巩固其流行地位。程序常需与现有程序协作,使用相同语言会更方便,因此语言会像病毒般在程序间传播。管理者也偏爱流行语言,因为这能增强他们对开发者的控制力——后者更容易被替换。 事实上,若所有编程语言都大同小异,那么除了最流行的语言外,其他确实没有存在必要。但各种语言绝非等价,差距可谓天壤之别。正因如此,小众语言才能像简·奥斯汀的小说般持续存活。当所有人都在读约翰·格里沙姆的新作时,总会有少数人选择阅读简·奥斯汀。
May 2003 _(This essay is derived from a guest lecture at Harvard, which incorporated an earlier talk at Northeastern.)_ When I finished grad school in computer science I went to art school to study painting. A lot of people seemed surprised that someone interested in computers would also be interested in painting. They seemed to think that hacking and painting were very different kinds of work-- that hacking was cold, precise, and methodical, and that painting was the frenzied expression of some primal urge. Both of these images are wrong. Hacking and painting have a lot in common. In fact, of all the different types of people I've known, hackers and painters are among the most alike. What hackers and painters have in common is that they're both makers. Along with composers, architects, and writers, what hackers and painters are trying to do is make good things. They're not doing research per se, though if in the course of trying to make good things they discover some new technique, so much the better. I've never liked the term "computer science." The main reason I don't like it is that there's no such thing. Computer science is a grab bag of tenuously related areas thrown together by an accident of history, like Yugoslavia. At one end you have people who are really mathematicians, but call what they're doing computer science so they can get DARPA grants. In the middle you have people working on something like the natural history of computers-- studying the behavior of algorithms for routing data through networks, for example. And then at the other extreme you have the hackers, who are trying to write interesting software, and for whom computers are just a medium of expression, as concrete is for architects or paint for painters. It's as if mathematicians, physicists, and architects all had to be in the same department. Sometimes what the hackers do is called "software engineering," but this term is just as misleading.
(以下为直接翻译结果,未添加任何说明或注释)
(本文改编自哈佛大学客座讲座,其中融合了早前在东北大学的演讲内容。)
计算机科学研究生毕业后,我进入艺术学院学习绘画。许多人惊讶于一个热爱计算机的人竟会同时对绘画产生兴趣。他们似乎认为编程与绘画是截然不同的工作——编程是冰冷、精确且有条不紊的,而绘画则是原始冲动的狂热表达。
这两种印象都是错误的。编程与绘画有许多共同点。事实上,在我认识的所有不同类型的人中,程序员与画家是最为相似的群体之一。
Good software designers are no more engineers than architects are. The border between architecture and engineering is not sharply defined, but it's there. It falls between what and how: architects decide what to do, and engineers figure out how to do it. What and how should not be kept too separate. You're asking for trouble if you try to decide what to do without understanding how to do it. But hacking can certainly be more than just deciding how to implement some spec. At its best, it's creating the spec-- though it turns out the best way to do that is to implement it. Perhaps one day "computer science" will, like Yugoslavia, get broken up into its component parts. That might be a good thing. Especially if it meant independence for my native land, hacking. Bundling all these different types of work together in one department may be convenient administratively, but it's confusing intellectually. That's the other reason I don't like the name "computer science." Arguably the people in the middle are doing something like an experimental science. But the people at either end, the hackers and the mathematicians, are not actually doing science. The mathematicians don't seem bothered by this. They happily set to work proving theorems like the other mathematicians over in the math department, and probably soon stop noticing that the building they work in says ``computer science'' on the outside. But for the hackers this label is a problem. If what they're doing is called science, it makes them feel they ought to be acting scientific. So instead of doing what they really want to do, which is to design beautiful software, hackers in universities and research labs feel they ought to be writing research papers. In the best case, the papers are just a formality. Hackers write cool software, and then write a paper about it, and the paper becomes a proxy for the achievement represented by the software. But often this mismatch causes problems.
程序员与画家的共同之处在于他们都是创造者。与作曲家、建筑师和作家一样,程序员与画家都在试图创造美好的事物。他们本质上并非在做研究,尽管在创造过程中发现新技术是锦上添花。
我从不喜欢"计算机科学"这个术语。主要原因是它根本名不副实。计算机科学就像南斯拉夫一样,是历史偶然拼凑起来的松散学科集合。一端是本质为数学家却打着计算机科学旗号申请DARPA经费的人;中间是研究计算机"自然史"的学者——例如探索网络数据路由算法的行为;而另一端则是程序员,他们试图编写有趣的软件,对他们而言计算机只是表达媒介,就像混凝土之于建筑师或颜料之于画家。这就像把数学家、物理学家和建筑师硬塞进同一个系。
有时程序员的工作被称为"软件工程",但这个称呼同样具有误导性。优秀的软件设计师并不比建筑师更接近工程师。虽然建筑与工程的界限模糊,但确实存在:建筑师决定做什么,工程师解决怎么做。
"做什么"与"怎么做"不应完全割裂。在不理解实现方法的情况下决策需求是危险的。但编程绝不仅限于按规格实现——最好的编程本身就是创造规格的过程,只不过最佳创造方式恰是通过实现来完成。
It's easy to drift away from building beautiful things toward building ugly things that make more suitable subjects for research papers. Unfortunately, beautiful things don't always make the best subjects for papers. Number one, research must be original-- and as anyone who has written a PhD dissertation knows, the way to be sure that you're exploring virgin territory is to stake out a piece of ground that no one wants. Number two, research must be substantial-- and awkward systems yield meatier papers, because you can write about the obstacles you have to overcome in order to get things done. Nothing yields meaty problems like starting with the wrong assumptions. Most of AI is an example of this rule; if you assume that knowledge can be represented as a list of predicate logic expressions whose arguments represent abstract concepts, you'll have a lot of papers to write about how to make this work. As Ricky Ricardo used to say, "Lucy, you got a lot of explaining to do." The way to create something beautiful is often to make subtle tweaks to something that already exists, or to combine existing ideas in a slightly new way. This kind of work is hard to convey in a research paper. So why do universities and research labs continue to judge hackers by publications? For the same reason that "scholastic aptitude" gets measured by simple-minded standardized tests, or the productivity of programmers gets measured in lines of code. These tests are easy to apply, and there is nothing so tempting as an easy test that kind of works. Measuring what hackers are actually trying to do, designing beautiful software, would be much more difficult. You need a good sense of design to judge good design. And there is no correlation, except possibly a negative one, between people's ability to recognize good design and their confidence that they can. The only external test is time.
或许有一天,"计算机科学"会像南斯拉夫一样解体。这未尝不是好事,尤其当我的精神故乡"编程"能因此获得独立。
将这些不同性质的工作捆绑在同一个学科名下虽便于管理,却造成了认知混乱。这是我不喜欢"计算机科学"名称的另一原因。中间群体或许勉强算实验科学,但两端的程序员与数学家实际上都不从事科学研究。
数学家对此似乎并不困扰。他们像数学系的同行一样愉快地证明定理,很快便忘记所在大楼外墙挂着"计算机科学"的牌子。但对程序员而言,这个标签成了问题。"科学"的称谓让他们误以为自己应该表现得像科学家。于是大学和研究实验室的程序员不再专注于设计优美软件这一真正追求,转而被迫撰写研究论文。
理想情况下,论文只是形式——程序员先写出优秀软件,再附上一篇说明,论文成为软件成果的代理。但更多时候这种错位会引发问题:人们容易从构建美好事物滑向制造丑陋但更适合论文研究的产物。
遗憾的是,美好事物往往不是最佳论文素材。首先,研究必须原创——任何写过博士论文的人都明白,确保探索处女地的最好方法就是圈一块无人问津的领域。其次,研究必须充实——而笨拙的系统能产出更"有料"的论文,因为你可以大书特书克服障碍的过程。没有什么比错误假设更能催生"充实问题"了,人工智能领域大多印证了这条规律:如果你假定知识能用谓词逻辑表达式表示,其参数代表抽象概念,你就有写不完的论文来解释如何实现这一点。正如里奇·里卡多常说:"露西,你有太多解释要做。"
Over time, beautiful things tend to thrive, and ugly things tend to get discarded. Unfortunately, the amounts of time involved can be longer than human lifetimes. Samuel Johnson said it took a hundred years for a writer's reputation to converge. You have to wait for the writer's influential friends to die, and then for all their followers to die. I think hackers just have to resign themselves to having a large random component in their reputations. In this they are no different from other makers. In fact, they're lucky by comparison. The influence of fashion is not nearly so great in hacking as it is in painting. There are worse things than having people misunderstand your work. A worse danger is that you will yourself misunderstand your work. Related fields are where you go looking for ideas. If you find yourself in the computer science department, there is a natural temptation to believe, for example, that hacking is the applied version of what theoretical computer science is the theory of. All the time I was in graduate school I had an uncomfortable feeling in the back of my mind that I ought to know more theory, and that it was very remiss of me to have forgotten all that stuff within three weeks of the final exam. Now I realize I was mistaken. Hackers need to understand the theory of computation about as much as painters need to understand paint chemistry. You need to know how to calculate time and space complexity and about Turing completeness. You might also want to remember at least the concept of a state machine, in case you have to write a parser or a regular expression library. Painters in fact have to remember a good deal more about paint chemistry than that. I've found that the best sources of ideas are not the other fields that have the word "computer" in their names, but the other fields inhabited by makers. Painting has been a much richer source of ideas than the theory of computation.
创造美好事物的方法通常是对现有事物进行精妙调整,或以新颖方式组合既有想法。这类工作很难通过论文传达。
既然如此,为何大学和研究机构仍以论文评价程序员?原因与用简单标准化测试衡量"学术能力",或用代码行数评估程序员生产力如出一辙——这些测试易于实施,而半吊子简易测试的诱惑难以抗拒。
衡量程序员真正的追求——设计优美软件——要困难得多。你需要良好的设计品味来评判设计优劣。而人们识别优秀设计的能力与其自信程度之间,即便存在关联也恐怕是负相关。
唯一客观的检验标准是时间。经年累月,美好事物终将繁荣,丑陋终被淘汰。可惜这个时间跨度往往超越人类寿命。塞缪尔·约翰逊说作家声誉需要百年才能尘埃落定——你得等作家有影响力的朋友去世,再等他们的追随者全部离世。
For example, I was taught in college that one ought to figure out a program completely on paper before even going near a computer. I found that I did not program this way. I found that I liked to program sitting in front of a computer, not a piece of paper. Worse still, instead of patiently writing out a complete program and assuring myself it was correct, I tended to just spew out code that was hopelessly broken, and gradually beat it into shape. Debugging, I was taught, was a kind of final pass where you caught typos and oversights. The way I worked, it seemed like programming consisted of debugging. For a long time I felt bad about this, just as I once felt bad that I didn't hold my pencil the way they taught me to in elementary school. If I had only looked over at the other makers, the painters or the architects, I would have realized that there was a name for what I was doing: sketching. As far as I can tell, the way they taught me to program in college was all wrong. You should figure out programs as you're writing them, just as writers and painters and architects do. Realizing this has real implications for software design. It means that a programming language should, above all, be malleable. A programming language is for thinking of programs, not for expressing programs you've already thought of. It should be a pencil, not a pen. Static typing would be a fine idea if people actually did write programs the way they taught me to in college. But that's not how any of the hackers I know write programs. We need a language that lets us scribble and smudge and smear, not a language where you have to sit with a teacup of types balanced on your knee and make polite conversation with a strict old aunt of a compiler. While we're on the subject of static typing, identifying with the makers will save us from another problem that afflicts the sciences: math envy.
我认为程序员必须接受声誉中的巨大随机成分。在这方面他们与其他创造者并无二致。实际上他们还算幸运——编程领域的时尚影响力远不及绘画界。
比被人误解更糟的是自我误解。我们习惯从相关领域寻找灵感。如果你身处计算机科学系,自然会倾向于相信编程是理论计算机科学的实践应用。整个研究生阶段,我心底总萦绕着不安,觉得自己应该掌握更多理论,并为考完三周就忘光所有内容而自责。
如今我意识到这种想法是错误的。程序员需要理解计算理论的程度,就像画家需要了解颜料化学。你需要掌握时空复杂度计算和图灵完备性概念,或许还得记住状态机的概念(以备编写解析器或正则表达式库之需)。实际上画家需要记忆的颜料化学知识比这多得多。
我发现最佳灵感来源并非名称带"计算机"的学科,而是其他创造者聚集的领域。绘画带来的灵感远比计算理论丰富。
例如,大学时我被教导应该在纸上完全设计好程序才能接触计算机。但我发现自己的编程方式截然不同——我喜欢面对计算机而非纸张编程。更"糟糕"的是,我从不耐心写出完整正确的程序,而是先喷涌出满是缺陷的代码,再逐步修正。学校教的"调试是捕捉拼写错误与疏忽的最后环节",而我的工作方式仿佛编程完全由调试构成。
Everyone in the sciences secretly believes that mathematicians are smarter than they are. I think mathematicians also believe this. At any rate, the result is that scientists tend to make their work look as mathematical as possible. In a field like physics this probably doesn't do much harm, but the further you get from the natural sciences, the more of a problem it becomes. A page of formulas just looks so impressive. (Tip: for extra impressiveness, use Greek variables.) And so there is a great temptation to work on problems you can treat formally, rather than problems that are, say, important. If hackers identified with other makers, like writers and painters, they wouldn't feel tempted to do this. Writers and painters don't suffer from math envy. They feel as if they're doing something completely unrelated. So are hackers, I think. If universities and research labs keep hackers from doing the kind of work they want to do, perhaps the place for them is in companies. Unfortunately, most companies won't let hackers do what they want either. Universities and research labs force hackers to be scientists, and companies force them to be engineers. I only discovered this myself quite recently. When Yahoo bought Viaweb, they asked me what I wanted to do. I had never liked the business side very much, and said that I just wanted to hack. When I got to Yahoo, I found that what hacking meant to them was implementing software, not designing it. Programmers were seen as technicians who translated the visions (if that is the word) of product managers into code. This seems to be the default plan in big companies. They do it because it decreases the standard deviation of the outcome. Only a small percentage of hackers can actually design software, and it's hard for the people running a company to pick these out.
长久以来我为此感到愧疚,就像小学时为握笔姿势不规范而自卑。如果当时观察其他创造者——画家或建筑师,我本应意识到自己的行为有个名字:素描。现在看来,大学教的编程方法完全错误。你应该像作家、画家和建筑师那样,在编写过程中构思程序。
这一认知对软件设计具有实际意义:编程语言首先应该是可塑的。它是构思程序的工具,而非表达既定思路的媒介。它应该是铅笔而非钢笔。如果人们真按大学教的方式编程,静态类型将是个好主意。但我认识的程序员无一如此工作。我们需要能涂鸦修改的语言,而非要求正襟危坐、像端着茶杯与严厉的编译器老阿姨礼貌交谈的语言。
谈到静态类型,以创造者自居还能让我们避免困扰科学界的另一问题:数学嫉妒。科学工作者都暗自认为数学家更聪明(数学家自己也这么想)。结果就是人们竭力使自己的工作看起来更数学化。这对物理学或许无害,但离自然科学越远,问题就越严重。
满页公式看起来如此权威(秘诀:用希腊字母变量更显高深)。于是人们强烈倾向于研究可形式化处理的问题,而非真正重要的问题。
So instead of entrusting the future of the software to one brilliant hacker, most companies set things up so that it is designed by committee, and the hackers merely implement the design. If you want to make money at some point, remember this, because this is one of the reasons startups win. Big companies want to decrease the standard deviation of design outcomes because they want to avoid disasters. But when you damp oscillations, you lose the high points as well as the low. This is not a problem for big companies, because they don't win by making great products. Big companies win by sucking less than other big companies. So if you can figure out a way to get in a design war with a company big enough that its software is designed by product managers, they'll never be able to keep up with you. These opportunities are not easy to find, though. It's hard to engage a big company in a design war, just as it's hard to engage an opponent inside a castle in hand to hand combat. It would be pretty easy to write a better word processor than Microsoft Word, for example, but Microsoft, within the castle of their operating system monopoly, probably wouldn't even notice if you did. The place to fight design wars is in new markets, where no one has yet managed to establish any fortifications. That's where you can win big by taking the bold approach to design, and having the same people both design and implement the product. Microsoft themselves did this at the start. So did Apple. And Hewlett-Packard. I suspect almost every successful startup has. So one way to build great software is to start your own startup. There are two problems with this, though. One is that in a startup you have to do so much besides write software. At Viaweb I considered myself lucky if I got to hack a quarter of the time. And the things I had to do the other three quarters of the time ranged from tedious to terrifying.
如果程序员认同作家和画家等同行的身份,就不会受此诱惑。作家和画家没有数学嫉妒,他们认为自己在做完全不同的事——我认为程序员也是。
如果大学和研究机构阻碍程序员做真正想做的事,或许企业才是他们的归宿。可惜大多数企业同样限制程序员的自由。学术界强迫程序员成为科学家,企业则强迫他们成为工程师。
我最近才意识到这点。雅虎收购Viaweb时询问我的意愿。由于不喜欢商业事务,我表示只想编程。但到了雅虎才发现,他们所谓的编程仅指实现软件而非设计软件。程序员被视为将产品经理"愿景"(如果这个词合适)转化为代码的技术员。
这似乎是大型企业的默认模式。如此安排能降低结果的方差。真正具备软件设计能力的程序员凤毛麟角,企业管理者难以识别。因此多数公司不是将软件未来托付给杰出程序员,而是交由委员会设计,程序员仅负责实现。
若你某天想赚钱,请记住:这正是创业公司能赢的原因。大公司降低设计结果的方差是为避免灾难,但抑制波动同时也抹去了高峰。这对大公司不是问题——它们不靠卓越产品取胜,只要比其它大公司少犯错就能赢。
I have a benchmark for this, because I once had to leave a board meeting to have some cavities filled. I remember sitting back in the dentist's chair, waiting for the drill, and feeling like I was on vacation. The other problem with startups is that there is not much overlap between the kind of software that makes money and the kind that's interesting to write. Programming languages are interesting to write, and Microsoft's first product was one, in fact, but no one will pay for programming languages now. If you want to make money, you tend to be forced to work on problems that are too nasty for anyone to solve for free. All makers face this problem. Prices are determined by supply and demand, and there is just not as much demand for things that are fun to work on as there is for things that solve the mundane problems of individual customers. Acting in off-Broadway plays just doesn't pay as well as wearing a gorilla suit in someone's booth at a trade show. Writing novels doesn't pay as well as writing ad copy for garbage disposals. And hacking programming languages doesn't pay as well as figuring out how to connect some company's legacy database to their Web server. I think the answer to this problem, in the case of software, is a concept known to nearly all makers: the day job. This phrase began with musicians, who perform at night. More generally, it means that you have one kind of work you do for money, and another for love. Nearly all makers have day jobs early in their careers. Painters and writers notoriously do. If you're lucky you can get a day job that's closely related to your real work. Musicians often seem to work in record stores. A hacker working on some programming language or operating system might likewise be able to get a day job using it. [1] When I say that the answer is for hackers to have day jobs, and work on beautiful software on the side, I'm not proposing this as a new idea.
因此,若能找到方法与软件由产品经理设计的大公司展开设计对决,它们永远无法跟上你的步伐。不过这种机会不易寻找——就像很难与城堡内的敌人进行白刃战。例如开发比Microsoft Word更好的文字处理器很容易,但在操作系统垄断的城堡内,微软可能根本不会注意到你的存在。
设计之战的战场应选在新兴市场——尚未建立防御工事的领域。在这里,大胆的设计方法加上让设计者亲自实现产品,能带来巨大成功。微软、苹果、惠普起步时都是如此。我猜几乎所有成功创业公司皆循此道。
因此创建伟大软件的方法之一是自立门户。但创业有两大问题:首先,除了编程你不得不处理大量杂务。在Viaweb我能有1/4时间编程就算幸运,其余3/4时间所做之事从枯燥到恐怖不等。对此我有基准判断——某次不得不中途离开董事会去补牙,当躺在牙医椅上等待钻头时,我感觉像在度假。
其次,能赚钱的软件与有趣的软件重合度很低。编程语言很有趣(微软首个产品正是编程语言),但现在没人愿为之付费。要想赚钱,你往往被迫解决那些棘手到没人愿免费处理的问题。
This is what open-source hacking is all about. What I'm saying is that open-source is probably the right model, because it has been independently confirmed by all the other makers. It seems surprising to me that any employer would be reluctant to let hackers work on open-source projects. At Viaweb, we would have been reluctant to hire anyone who didn't. When we interviewed programmers, the main thing we cared about was what kind of software they wrote in their spare time. You can't do anything really well unless you love it, and if you love to hack you'll inevitably be working on projects of your own. [2] Because hackers are makers rather than scientists, the right place to look for metaphors is not in the sciences, but among other kinds of makers. What else can painting teach us about hacking? One thing we can learn, or at least confirm, from the example of painting is how to learn to hack. You learn to paint mostly by doing it. Ditto for hacking. Most hackers don't learn to hack by taking college courses in programming. They learn to hack by writing programs of their own at age thirteen. Even in college classes, you learn to hack mostly by hacking. [3] Because painters leave a trail of work behind them, you can watch them learn by doing. If you look at the work of a painter in chronological order, you'll find that each painting builds on things that have been learned in previous ones. When there's something in a painting that works very well, you can usually find version 1 of it in a smaller form in some earlier painting. I think most makers work this way. Writers and architects seem to as well. Maybe it would be good for hackers to act more like painters, and regularly start over from scratch, instead of continuing to work for years on one project, and trying to incorporate all their later ideas as revisions. The fact that hackers learn to hack by doing it is another sign of how different hacking is from the sciences.
所有创造者都面临这个困境。价格由供需决定,而解决个人用户日常问题的需求远大于有趣工作的需求。外百老汇演出的报酬不如在展会穿大猩猩装,写小说的收益不及为垃圾处理器写广告文案,开发编程语言的收入比不上将某公司的老旧数据库连接到Web服务器。
对软件行业,我认为解决方案是几乎所有创造者都熟悉的概念:白天工作。这个词源自夜间演出的音乐家,广义指为谋生做一类工作,为热爱做另一类工作。
几乎所有创造者职业生涯早期都有白天工作。画家与作家尤甚。若幸运,你能找到与真实工作密切相关的日间工作——音乐家常在唱片店工作,开发编程语言或操作系统的程序员或许能找到相关职位。
当我说程序员应有白天工作、利用业余开发优美软件时,这并非新主张——开源运动的核心正在于此。我想强调的是开源可能是正确模式,因为其他领域创造者都不约而同验证了这点。
令我惊讶的是竟有雇主反对程序员参与开源项目。在Viaweb,我们反而不愿雇佣没有个人项目的程序员。面试时最关注的是应聘者业余时间编写什么软件。除非热爱,否则无法真正精通某事——而热爱编程的人必然有自己的项目。
Scientists don't learn science by doing it, but by doing labs and problem sets. Scientists start out doing work that's perfect, in the sense that they're just trying to reproduce work someone else has already done for them. Eventually, they get to the point where they can do original work. Whereas hackers, from the start, are doing original work; it's just very bad. So hackers start original, and get good, and scientists start good, and get original. The other way makers learn is from examples. For a painter, a museum is a reference library of techniques. For hundreds of years it has been part of the traditional education of painters to copy the works of the great masters, because copying forces you to look closely at the way a painting is made. Writers do this too. Benjamin Franklin learned to write by summarizing the points in the essays of Addison and Steele and then trying to reproduce them. Raymond Chandler did the same thing with detective stories. Hackers, likewise, can learn to program by looking at good programs-- not just at what they do, but the source code too. One of the less publicized benefits of the open-source movement is that it has made it easier to learn to program. When I learned to program, we had to rely mostly on examples in books. The one big chunk of code available then was Unix, but even this was not open source. Most of the people who read the source read it in illicit photocopies of John Lions' book, which though written in 1977 was not allowed to be published until 1996. Another example we can take from painting is the way that paintings are created by gradual refinement. Paintings usually begin with a sketch. Gradually the details get filled in. But it is not merely a process of filling in. Sometimes the original plans turn out to be mistaken. Countless paintings, when you look at them in xrays, turn out to have limbs that have been moved or facial features that have been readjusted.
由于程序员是创造者而非科学家,寻找隐喻的正确场所应是其他创造领域而非科学界。绘画还能教给我们什么?
从绘画中我们能学习(或至少确认)的是编程的学习方法。绘画主要靠实践学习,编程亦然。多数程序员并非通过大学课程学会编程,而是十三岁时自己写程序起步。即便在大学课堂,编程也主要通过实践习得。
画家会留下作品轨迹,你能看到他们"做中学"的过程。按时间顺序观察画作,会发现每幅画都建立在之前习得的基础上。当某幅画出现精彩处理时,通常能在早期作品中找到它的雏形。
我认为多数创造者如此工作。作家与建筑师似乎也是。或许程序员应更像画家,定期从头开始而非经年累月修改同一项目、试图融入所有新想法。
Here's a case where we can learn from painting. I think hacking should work this way too. It's unrealistic to expect that the specifications for a program will be perfect. You're better off if you admit this up front, and write programs in a way that allows specifications to change on the fly. (The structure of large companies makes this hard for them to do, so here is another place where startups have an advantage.) Everyone by now presumably knows about the danger of premature optimization. I think we should be just as worried about premature design-- deciding too early what a program should do. The right tools can help us avoid this danger. A good programming language should, like oil paint, make it easy to change your mind. Dynamic typing is a win here because you don't have to commit to specific data representations up front. But the key to flexibility, I think, is to make the language very abstract. The easiest program to change is one that's very short. This sounds like a paradox, but a great painting has to be better than it has to be. For example, when Leonardo painted the portrait of Ginevra de Benci in the National Gallery, he put a juniper bush behind her head. In it he carefully painted each individual leaf. Many painters might have thought, this is just something to put in the background to frame her head. No one will look that closely at it. Not Leonardo. How hard he worked on part of a painting didn't depend at all on how closely he expected anyone to look at it. He was like Michael Jordan. Relentless. Relentlessness wins because, in the aggregate, unseen details become visible. When people walk by the portrait of Ginevra de Benci, their attention is often immediately arrested by it, even before they look at the label and notice that it says Leonardo da Vinci.
程序员通过实践学习的事实再次印证编程与科学的差异。科学家不是通过研究学习科学,而是通过实验和习题。科学家起步时做的是"完美"工作——重现他人成果。最终他们才能开展原创工作。而程序员从起点就是原创工作——只是最初质量极差。因此程序员始于原创而臻于精湛,科学家始于精湛而臻于原创。
创造者另一学习途径是范例。对画家而言,博物馆是技法参考库。数百年来,临摹大师作品始终是传统绘画教育的一部分,因为临摹迫使你仔细观察绘画技法。
作家也如此。本杰明·富兰克林通过总结艾迪生与斯蒂尔的散文要点并尝试复述来学习写作。雷蒙德·钱德勒对侦探小说也这样做。
同样,程序员可通过研究优秀程序学习编程——不仅要看功能,还要读源码。开源运动未充分宣传的益处之一,就是让学习编程变得更简单。我学编程时主要依赖书中的例子,当时唯一的大型代码库是Unix,但它并非开源。多数人通过约翰·莱昂斯著作的盗版影印件阅读源码——这本书写于1977年,却直到1996年才获准出版。
绘画给予我们的另一启示是作品的渐进完善过程。画作通常始于草图,细节逐步填充。但这不仅是填充过程——原始构思常被证明存在错误。X光显示无数画作中的肢体位置或面部特征都经过调整。
All those unseen details combine to produce something that's just stunning, like a thousand barely audible voices all singing in tune. Great software, likewise, requires a fanatical devotion to beauty. If you look inside good software, you find that parts no one is ever supposed to see are beautiful too. I'm not claiming I write great software, but I know that when it comes to code I behave in a way that would make me eligible for prescription drugs if I approached everyday life the same way. It drives me crazy to see code that's badly indented, or that uses ugly variable names. If a hacker were a mere implementor, turning a spec into code, then he could just work his way through it from one end to the other like someone digging a ditch. But if the hacker is a creator, we have to take inspiration into account. In hacking, like painting, work comes in cycles. Sometimes you get excited about some new project and you want to work sixteen hours a day on it. Other times nothing seems interesting. To do good work you have to take these cycles into account, because they're affected by how you react to them. When you're driving a car with a manual transmission on a hill, you have to back off the clutch sometimes to avoid stalling. Backing off can likewise prevent ambition from stalling. In both painting and hacking there are some tasks that are terrifyingly ambitious, and others that are comfortingly routine. It's a good idea to save some easy tasks for moments when you would otherwise stall. In hacking, this can literally mean saving up bugs. I like debugging: it's the one time that hacking is as straightforward as people think it is. You have a totally constrained problem, and all you have to do is solve it. Your program is supposed to do x. Instead it does y. Where does it go wrong? You know you're going to win in the end. It's as relaxing as painting a wall.
这正是我们可以向绘画学习的地方。我认为编程也应如此。期待程序规格完美无缺是不现实的。承认这点并编写允许规格动态调整的代码才是上策。
(大公司的结构使它们难以做到这点,这是创业公司的又一优势。)
如今人人都知道过早优化的危害。我认为我们同样需要警惕过早设计——过早确定程序该做什么。
合适的工具能帮助我们避免这一陷阱。优秀的编程语言应该像油画颜料般便于修改。动态类型在此有优势——你不必提前承诺具体数据表示。但我认为灵活性的关键在于语言必须高度抽象——最容易修改的程序就是最简短的程序。
The example of painting can teach us not only how to manage our own work, but how to work together. A lot of the great art of the past is the work of multiple hands, though there may only be one name on the wall next to it in the museum. Leonardo was an apprentice in the workshop of Verrocchio and painted one of the angels in his Baptism of Christ. This sort of thing was the rule, not the exception. Michelangelo was considered especially dedicated for insisting on painting all the figures on the ceiling of the Sistine Chapel himself. As far as I know, when painters worked together on a painting, they never worked on the same parts. It was common for the master to paint the principal figures and for assistants to paint the others and the background. But you never had one guy painting over the work of another. I think this is the right model for collaboration in software too. Don't push it too far. When a piece of code is being hacked by three or four different people, no one of whom really owns it, it will end up being like a common-room. It will tend to feel bleak and abandoned, and accumulate cruft. The right way to collaborate, I think, is to divide projects into sharply defined modules, each with a definite owner, and with interfaces between them that are as carefully designed and, if possible, as articulated as programming languages. Like painting, most software is intended for a human audience. And so hackers, like painters, must have empathy to do really great work. You have to be able to see things from the user's point of view. When I was a kid I was always being told to look at things from someone else's point of view. What this always meant in practice was to do what someone else wanted, instead of what I wanted. This of course gave empathy a bad name, and I made a point of not cultivating it. Boy, was I wrong.
这听起来矛盾,但伟大画作必须超越必要完美。例如达芬奇在国家美术馆创作的《吉内薇拉·德·班琪》肖像,他在人物头部后方绘制了杜松灌木,并精心描绘每片叶子。许多画家可能认为背景只是衬托,没人会细看。
但达芬奇不这么想。他对画作某部分的投入程度完全不取决于预期被关注度。他像迈克尔·乔丹一样永不懈怠。
这种不懈终将获得回报,因为聚沙成塔,未被注意的细节终会显现整体效果。当人们走过《吉内薇拉·德·班琪》时,常常未看标签就已被吸引。所有未被单独关注的细节共同创造出震撼效果,如同千个微弱声音汇成和谐合唱。
伟大软件同样需要对美的狂热追求。观察优秀软件内部,你会发现即使无人关注的部件也充满美感。我不敢自诩编写伟大软件,但就代码而言,我的执着程度若体现在日常生活,绝对够格被开处方药。看到缩进混乱或变量名丑陋的代码会让我抓狂。
如果程序员只是将规格转化为代码的实施者,他本可以像挖沟工人一样从头到尾线性工作。但作为创造者,我们必须考虑灵感因素。
It turns out that looking at things from other people's point of view is practically the secret of success. It doesn't necessarily mean being self-sacrificing. Far from it. Understanding how someone else sees things doesn't imply that you'll act in his interest; in some situations-- in war, for example-- you want to do exactly the opposite. [4] Most makers make things for a human audience. And to engage an audience you have to understand what they need. Nearly all the greatest paintings are paintings of people, for example, because people are what people are interested in. Empathy is probably the single most important difference between a good hacker and a great one. Some hackers are quite smart, but when it comes to empathy are practically solipsists. It's hard for such people to design great software [5], because they can't see things from the user's point of view. One way to tell how good people are at empathy is to watch them explain a technical question to someone without a technical background. We probably all know people who, though otherwise smart, are just comically bad at this. If someone asks them at a dinner party what a programming language is, they'll say something like ``Oh, a high-level language is what the compiler uses as input to generate object code.'' High-level language? Compiler? Object code? Someone who doesn't know what a programming language is obviously doesn't know what these things are, either. Part of what software has to do is explain itself. So to write good software you have to understand how little users understand. They're going to walk up to the software with no preparation, and it had better do what they guess it will, because they're not going to read the manual. The best system I've ever seen in this respect was the original Macintosh, in 1985. It did what software almost never does: it just worked. [6] Source code, too, should explain itself.
编程如绘画,工作呈周期性。有时你会为新项目兴奋到每天工作16小时,有时则对一切提不起兴趣。
要做好工作必须顺应这些周期,因为你的应对方式会影响周期效果。驾驶手动挡汽车上坡时,有时需要松开离合器以防熄火。同理,适度"松离合"能防止雄心熄火。绘画与编程都包含雄心勃勃的艰巨任务和令人安心的常规工作。明智的做法是保留些简单任务以备"熄火"时刻。
对编程而言,这可以具体表现为积攒bug。我喜欢调试:这是编程难得如外人想象般直接的时刻。问题完全明确,你只需解决它。程序本应执行x却执行了y,问题出在哪?你终将获胜。这种体验如同粉刷墙壁般令人放松。
绘画范例不仅能指导个人工作管理,还能启示协作方式。许多古代伟大艺术品都是多人合作成果,尽管博物馆墙上可能只标一个名字。达芬奇曾是韦罗基奥作坊的学徒,在其《基督受洗》中绘制了一位天使。这种情况是常态而非例外。米开朗基罗坚持独自完成西斯廷教堂天顶所有人物,反被视为特别敬业。
If I could get people to remember just one quote about programming, it would be the one at the beginning of _Structure and Interpretation of Computer Programs._ > Programs should be written for people to read, and only incidentally for machines to execute..
据我所知,画家合作时从不共同绘制同一部分。通常大师负责主要人物,助手绘制其他部分和背景。但绝不会出现一人覆盖另一人工作的情况。
我认为这也是软件协作的正确模式。切勿过度协作。当三四人共同修改同一段代码且无人真正负责时,代码会像公共休息室般荒凉破败、堆满垃圾。正确的协作方式是将项目划分为界限分明的模块,每个模块有明确负责人,模块间接口要像编程语言一样精心设计并尽可能清晰定义。
如绘画般,多数软件服务于人类用户。因此程序员与画家一样,必须拥有同理心才能创造真正伟大的作品。你需要从用户角度思考问题。
童年时大人总教导我换位思考。实践中这总意味着放弃自我意愿服从他人。这自然让同理心背上了恶名,我曾刻意避免培养它。
天啊,我大错特错。事实证明,换位思考几乎是成功的秘诀。这未必意味着自我牺牲——远非如此。理解他人观点不代表要为其利益服务,在某些情境下(比如战争)你恰恰需要反其道而行。
You need to have empathy not just for your users, but for your readers. It's in your interest, because you'll be one of them. Many a hacker has written a program only to find on returning to it six months later that he has no idea how it works. I know several people who've sworn off Perl after such experiences. [7] Lack of empathy is associated with intelligence, to the point that there is even something of a fashion for it in some places. But I don't think there's any correlation. You can do well in math and the natural sciences without having to learn empathy, and people in these fields tend to be smart, so the two qualities have come to be associated. But there are plenty of dumb people who are bad at empathy too. Just listen to the people who call in with questions on talk shows. They ask whatever it is they're asking in such a roundabout way that the hosts often have to rephrase the question for them. So, if hacking works like painting and writing, is it as cool? After all, you only get one life. You might as well spend it working on something great. Unfortunately, the question is hard to answer. There is always a big time lag in prestige. It's like light from a distant star. Painting has prestige now because of great work people did five hundred years ago. At the time, no one thought these paintings were as important as we do today. It would have seemed very odd to people at the time that Federico da Montefeltro, the Duke of Urbino, would one day be known mostly as the guy with the strange nose in a painting by Piero della Francesca. So while I admit that hacking doesn't seem as cool as painting now, we should remember that painting itself didn't seem as cool in its glory days as it does now. What we can say with some confidence is that these are the glory days of hacking. In most fields the great work is done early on. The paintings made between 1430 and 1500 are still unsurpassed.
多数创造者为人类受众创作。要打动观众,必须理解他们的需求。几乎所有最伟大的绘画都是人物画,因为人类最感兴趣的就是人类自身。
同理心可能是区分优秀程序员与伟大程序员的最重要标准。有些程序员聪明绝顶却缺乏同理心,近乎唯我论者。这类人很难设计出伟大软件,因为他们无法从用户角度思考。
判断一个人同理心水平的方法,是观察他向非技术人员解释技术问题时的表现。我们可能都认识某些在其他方面聪明、却在这方面糟糕得可笑的人。如果在晚宴上被问及"什么是编程语言",他们会回答:"哦,高级语言是编译器用来生成目标代码的输入。"高级语言?编译器?目标代码?连编程语言都不懂的人显然更不懂这些术语。
软件的部分使命是自我诠释。因此要写出好软件,必须理解用户认知的局限。用户会毫无准备地接触软件,它最好能符合他们的直觉预期——因为他们不会阅读手册。这方面我见过的最佳系统是1985年的初代Macintosh,它做到了软件几乎从未做到的事:开箱即用。
Shakespeare appeared just as professional theater was being born, and pushed the medium so far that every playwright since has had to live in his shadow. Albrecht Durer did the same thing with engraving, and Jane Austen with the novel. Over and over we see the same pattern. A new medium appears, and people are so excited about it that they explore most of its possibilities in the first couple generations. Hacking seems to be in this phase now. Painting was not, in Leonardo's time, as cool as his work helped make it. How cool hacking turns out to be will depend on what we can do with this new medium. Notes [1] The greatest damage that photography has done to painting may be the fact that it killed the best day job. Most of the great painters in history supported themselves by painting portraits. [2] I've been told that Microsoft discourages employees from contributing to open-source projects, even in their spare time. But so many of the best hackers work on open-source projects now that the main effect of this policy may be to ensure that they won't be able to hire any first-rate programmers. [3] What you learn about programming in college is much like what you learn about books or clothes or dating: what bad taste you had in high school. [4] Here's an example of applied empathy. At Viaweb, if we couldn't decide between two alternatives, we'd ask, what would our competitors hate most? At one point a competitor added a feature to their software that was basically useless, but since it was one of few they had that we didn't, they made much of it in the trade press. We could have tried to explain that the feature was useless, but we decided it would annoy our competitor more if we just implemented it ourselves, so we hacked together our own version that afternoon. [5] Except text editors and compilers. Hackers don't need empathy to design these, because they are themselves typical users. [6] Well, almost.
源代码也应自我诠释。如果只能让人们记住一句编程箴言,我会选《计算机程序的构造与解释》开篇的那句:
> 程序写给人读,只是顺带让机器执行。
你不仅需要对用户怀有同理心,对读者同样如此。这符合你的利益,因为你终将成为他们中的一员。许多黑客写完程序后,时隔六个月再回头看,发现自己完全无法理解代码如何运作。我认识好几个人因此发誓再也不碰Perl语言。[7]
缺乏同理心常与高智商挂钩,某些地方甚至将其视为一种时尚。但我认为这两者毫无关联。在数学和自然科学领域取得成就确实不需要培养同理心,而这些领域的从业者往往聪慧过人,于是两种特质被错误地捆绑在一起。但现实中也不乏既愚钝又缺乏同理心之人——听听那些打进脱口秀热线的提问者就知道了,他们总是拐弯抹角地表达问题,主持人不得不反复帮他们重新组织语言。
那么,如果黑客行为与绘画写作同理,它是否同样酷炫?毕竟人生只有一次,理应投身于伟大事业。
They overshot the available RAM somewhat, causing much inconvenient disk swapping, but this could be fixed within a few months by buying an additional disk drive. [7] The way to make programs easy to read is not to stuff them with comments. I would take Abelson and Sussman's quote a step further. Programming languages should be designed to express algorithms, and only incidentally to tell computers how to execute them. A good programming language ought to be better for explaining software than English. You should only need comments when there is some kind of kludge you need to warn readers about, just as on a road there are only arrows on parts with unexpectedly sharp curves. Thanks to Trevor Blackwell, Robert Morris, Dan Giffin, and Lisa Randall for reading drafts of this, and to Henry Leitner and Larry Finkelstein for inviting me to speak.
| Japanese Translation | | | Spanish Translation | German Translation | | | Portuguese Translation | Czech Translation | | | Why Good Design Comes from Bad Design | Knuth: Computer Programming as an Art.
遗憾的是,这个问题难有定论。声望的传播永远存在巨大时滞,就像遥远恒星发出的光芒。绘画如今的崇高地位源于五百年前大师们的创作,但当时根本没人觉得这些画作像今人认为的这般重要。若告诉乌尔比诺公爵费德里科·达·蒙特费尔特罗,将来人们记住他主要是因为皮耶罗·德拉·弗朗切斯卡画作里那个鼻子奇特的男人,当时的民众定会觉得荒谬绝伦。
因此,尽管我承认眼下黑客文化似乎不及绘画酷炫,但我们必须记住:绘画在其鼎盛时期,也远不如今天这般受人尊崇。
可以确定的是,此刻正是黑客文化的黄金时代。多数领域的巅峰之作都诞生于早期:1430至1500年间的油画至今无人超越;莎士比亚恰逢职业戏剧兴起之时,其成就令后世剧作家永远活在他的阴影下;阿尔布雷希特·丢勒之于版画,简·奥斯汀之于小说,莫不如此。
历史总在重复相同的模式:新媒体出现时,人们热情高涨,短短几代人便穷尽其大部分可能性。黑客技术正处在这个爆发阶段。
You'll find this essay and 14 others in _Hackers & Painters_.
列奥纳多时代的绘画远不如他的杰作后来塑造的那般酷炫。黑客文化最终能达到的高度,取决于我们如何运用这个新兴媒介。
注释 [1] 摄影对绘画最致命的打击,或许是摧毁了画家最理想的谋生手段——历史上多数伟大画家依靠肖像画维持生计。 [2] 据悉微软禁止员工参与开源项目(即便业余时间)。但如今顶尖黑客多投身开源,该政策恐怕只会让微软与一流程序员绝缘。 [3] 大学所授编程知识如同教人评判书籍、衣着或约会对象:不过让你意识到高中时的糟糕品味。 [4] 同理心应用案例:在Viaweb,当我们难以决策时,会思考"竞争对手最痛恨哪种方案?"某次竞品添加了华而不实的功能,因是其少数优势便大肆宣传。我们本可论证其无用性,但最终选择用行动激怒对手——当天下午就山寨出该功能。 [5] 文本编辑器和编译器除外。黑客设计这些工具无需同理心,因为他们自己就是典型用户。 [6] 严格说存在瑕疵——程序略微超出可用内存导致频繁磁盘交换,但只需加装硬盘即可解决。 [7] 提升代码可读性不在于堆砌注释。我愿进一步引申阿贝尔森和萨斯曼的观点:编程语言本质是算法表达工具,其次才是计算机指令。优秀编程语言解释软件的效率应优于英语,注释只该出现在需要警示读者的"代码急弯"处,如同道路只在险弯处设置箭头标识。
致谢 特雷弗·布莱克韦尔、罗伯特·莫里斯、丹·吉芬、丽莎·兰德尔审阅草稿,亨利·莱特纳与拉里·芬克尔斯坦邀请演讲。
| 日文译本 | | | 西班牙文译本 | 德文译本 | | | 葡萄牙文译本 | 捷克文译本 | | | 《优秀设计源于糟糕设计》 | 高德纳:作为艺术的计算机编程
你可以在《黑客与画家》一书中找到这篇文章以及其他14篇文章。
[](https://s.turbifycdn.com/aah/paulgraham/the-hundred-year-language-11.gif) April 2003 _(This essay is derived from a keynote talk at PyCon 2003.)_ It's hard to predict what life will be like in a hundred years. There are only a few things we can say with certainty. We know that everyone will drive flying cars, that zoning laws will be relaxed to allow buildings hundreds of stories tall, that it will be dark most of the time, and that women will all be trained in the martial arts. Here I want to zoom in on one detail of this picture. What kind of programming language will they use to write the software controlling those flying cars? This is worth thinking about not so much because we'll actually get to use these languages as because, if we're lucky, we'll use languages on the path from this point to that. I think that, like species, languages will form evolutionary trees, with dead-ends branching off all over. We can see this happening already. Cobol, for all its sometime popularity, does not seem to have any intellectual descendants. It is an evolutionary dead-end-- a Neanderthal language. I predict a similar fate for Java. People sometimes send me mail saying, "How can you say that Java won't turn out to be a successful language? It's already a successful language." And I admit that it is, if you measure success by shelf space taken up by books on it (particularly individual books on it), or by the number of undergrads who believe they have to learn it to get a job. When I say Java won't turn out to be a successful language, I mean something more specific: that Java will turn out to be an evolutionary dead-end, like Cobol. This is just a guess. I may be wrong. My point here is not to dis Java, but to raise the issue of evolutionary trees and get people asking, where on the tree is language X? The reason to ask this question isn't just so that our ghosts can say, in a hundred years, I told you so.
[](https://s.turbifycdn.com/aah/paulgraham/the-hundred-year-language-11.gif)
(本文改编自2003年PyCon大会的主题演讲。)
预测一百年后的生活面貌极为困难。只有少数几件事我们可以确定:人人都会驾驶飞行汽车,城市规划法规将放宽以允许数百层高的建筑,世界将长期处于黑暗之中,而所有女性都将接受武术训练。在此,我想聚焦于这幅图景中的一个细节——人们将使用何种编程语言来编写控制这些飞行汽车的软件?
思考这个问题并非因为我们将实际使用这些未来语言,而是因为如果我们足够幸运,我们将会使用从当下通往未来的路径上的那些语言。
It's because staying close to the main branches is a useful heuristic for finding languages that will be good to program in now. At any given time, you're probably happiest on the main branches of an evolutionary tree. Even when there were still plenty of Neanderthals, it must have sucked to be one. The Cro-Magnons would have been constantly coming over and beating you up and stealing your food. The reason I want to know what languages will be like in a hundred years is so that I know what branch of the tree to bet on now. The evolution of languages differs from the evolution of species because branches can converge. The Fortran branch, for example, seems to be merging with the descendants of Algol. In theory this is possible for species too, but it's not likely to have happened to any bigger than a cell. Convergence is more likely for languages partly because the space of possibilities is smaller, and partly because mutations are not random. Language designers deliberately incorporate ideas from other languages. It's especially useful for language designers to think about where the evolution of programming languages is likely to lead, because they can steer accordingly. In that case, "stay on a main branch" becomes more than a way to choose a good language. It becomes a heuristic for making the right decisions about language design. Any programming language can be divided into two parts: some set of fundamental operators that play the role of axioms, and the rest of the language, which could in principle be written in terms of these fundamental operators. I think the fundamental operators are the most important factor in a language's long term survival. The rest you can change. It's like the rule that in buying a house you should consider location first of all. Everything else you can fix later, but you can't fix the location.
我认为,编程语言将像物种一样形成进化树,枝杈上遍布死胡同。这种现象已然可见。COBOL尽管曾一度流行,但似乎没有留下任何思想传承。它是一个进化的死胡同——一种尼安德特式的语言。
我预测Java将面临类似的命运。有时人们会发邮件问我:“你怎么能断言Java不会成为成功的语言?它已经是一种成功的语言了。”我承认,如果以相关书籍占据的书架空间(尤其是单卷本的厚度)或认为必须学习Java才能找到工作的大学生数量来衡量成功,Java确实成功了。但当我断言Java不会成为成功的语言时,我指的是更具体的含义:Java终将成为像COBOL那样的进化死胡同。
这只是一个猜测,我可能错了。我的目的不是贬低Java,而是提出进化树的概念,让人们思考:语言X在这棵树的哪个位置?提出这个问题不仅是为了让我们的灵魂在一百年后能说“我早告诉过你”,更是因为贴近主干分支是寻找当下优秀编程语言的实用启发法。
在任意时间点上,处于进化树的主干分支上可能最令人愉悦。即使尼安德特人数量众多时,做尼安德特人想必也很糟糕。克罗马农人会不断过来殴打你并抢走你的食物。
我想了解一百年后的语言形态,是为了知道现在该押注于哪个分支。
I think it's important not just that the axioms be well chosen, but that there be few of them. Mathematicians have always felt this way about axioms-- the fewer, the better-- and I think they're onto something. At the very least, it has to be a useful exercise to look closely at the core of a language to see if there are any axioms that could be weeded out. I've found in my long career as a slob that cruft breeds cruft, and I've seen this happen in software as well as under beds and in the corners of rooms. I have a hunch that the main branches of the evolutionary tree pass through the languages that have the smallest, cleanest cores. The more of a language you can write in itself, the better. Of course, I'm making a big assumption in even asking what programming languages will be like in a hundred years. Will we even be writing programs in a hundred years? Won't we just tell computers what we want them to do? There hasn't been a lot of progress in that department so far. My guess is that a hundred years from now people will still tell computers what to do using programs we would recognize as such. There may be tasks that we solve now by writing programs and which in a hundred years you won't have to write programs to solve, but I think there will still be a good deal of programming of the type that we do today. It may seem presumptuous to think anyone can predict what any technology will look like in a hundred years. But remember that we already have almost fifty years of history behind us. Looking forward a hundred years is a graspable idea when we consider how slowly languages have evolved in the past fifty. Languages evolve slowly because they're not really technologies. Languages are notation. A program is a formal description of the problem you want a computer to solve for you.
语言的进化与物种进化的不同之处在于分支可以融合。例如,Fortran分支似乎正在与Algol的后代合并。理论上物种也可能发生融合,但规模不太可能超过细胞级别。
语言更可能融合,部分原因是可能性空间较小,部分因为变异并非随机发生。语言设计者会刻意吸收其他语言的思想。
对语言设计者而言,思考编程语言进化方向尤为有益,因为他们可以据此调整航向。在这种情况下,“停留在主干分支上”不仅是选择优秀语言的方法,更成为语言设计决策的启发法则。
任何编程语言都可划分为两部分:扮演公理角色的一组基本运算符,以及其余部分(理论上可用这些基本运算符表示的部分)。
我认为基本运算符是决定语言长期存续的最重要因素。其余部分都可以改变。这就像购房的首要原则是考虑地段——其他都可以后期改造,唯独地段无法改变。
So the rate of evolution in programming languages is more like the rate of evolution in mathematical notation than, say, transportation or communications. Mathematical notation does evolve, but not with the giant leaps you see in technology. Whatever computers are made of in a hundred years, it seems safe to predict they will be much faster than they are now. If Moore's Law continues to put out, they will be 74 quintillion (73,786,976,294,838,206,464) times faster. That's kind of hard to imagine. And indeed, the most likely prediction in the speed department may be that Moore's Law will stop working. Anything that is supposed to double every eighteen months seems likely to run up against some kind of fundamental limit eventually. But I have no trouble believing that computers will be very much faster. Even if they only end up being a paltry million times faster, that should change the ground rules for programming languages substantially. Among other things, there will be more room for what would now be considered slow languages, meaning languages that don't yield very efficient code. And yet some applications will still demand speed. Some of the problems we want to solve with computers are created by computers; for example, the rate at which you have to process video images depends on the rate at which another computer can generate them. And there is another class of problems which inherently have an unlimited capacity to soak up cycles: image rendering, cryptography, simulations. If some applications can be increasingly inefficient while others continue to demand all the speed the hardware can deliver, faster computers will mean that languages have to cover an ever wider range of efficiencies. We've seen this happening already. Current implementations of some popular new languages are shockingly wasteful by the standards of previous decades. This isn't just something that happens with programming languages.
不仅公理需要精挑细选,数量也应尽可能少。数学家始终认为公理越少越好,我认为他们发现了真理。
至少,仔细审视语言核心以剔除冗余公理是极具价值的实践。在我漫长的邋遢生涯中,我发现杂乱滋生杂乱——这个规律适用于床底和房间角落,也同样适用于软件。
我直觉认为,进化树的主干分支将穿过那些拥有最精简、最清晰核心的语言。能用语言自身表达的部分越多越好。
当然,我提出“百年后编程语言会怎样”这个问题本身就做了大胆假设。一百年后我们还需要编写程序吗?难道不能直接告诉计算机我们想要什么?
迄今为止这个领域进展甚微。我猜测一百年后人们仍需要使用我们可识别的程序来指挥计算机。某些现在需要编程的任务未来可能不再需要,但我认为今天我们从事的这类编程工作仍将大量存在。
It's a general historical trend. As technologies improve, each generation can do things that the previous generation would have considered wasteful. People thirty years ago would be astonished at how casually we make long distance phone calls. People a hundred years ago would be even more astonished that a package would one day travel from Boston to New York via Memphis. I can already tell you what's going to happen to all those extra cycles that faster hardware is going to give us in the next hundred years. They're nearly all going to be wasted. I learned to program when computer power was scarce. I can remember taking all the spaces out of my Basic programs so they would fit into the memory of a 4K TRS-80. The thought of all this stupendously inefficient software burning up cycles doing the same thing over and over seems kind of gross to me. But I think my intuitions here are wrong. I'm like someone who grew up poor, and can't bear to spend money even for something important, like going to the doctor. Some kinds of waste really are disgusting. SUVs, for example, would arguably be gross even if they ran on a fuel which would never run out and generated no pollution. SUVs are gross because they're the solution to a gross problem. (How to make minivans look more masculine.) But not all waste is bad. Now that we have the infrastructure to support it, counting the minutes of your long-distance calls starts to seem niggling. If you have the resources, it's more elegant to think of all phone calls as one kind of thing, no matter where the other person is. There's good waste, and bad waste. I'm interested in good waste-- the kind where, by spending more, we can get simpler designs. How will we take advantage of the opportunities to waste cycles that we'll get from new, faster hardware? The desire for speed is so deeply engrained in us, with our puny computers, that it will take a conscious effort to overcome it.
预测任何技术的百年面貌似乎狂妄自大。但请记住,编程已有近五十年历史。考虑到过去五十年语言进化之缓慢,展望百年并非不可想象。
语言进化缓慢因为它们本质上是符号系统而非技术。程序是对待解决问题的形式化描述,因此编程语言的进化速度更接近数学符号的演变节奏,而非交通或通信技术。数学符号确实在进化,但不会出现技术领域那种巨大飞跃。
无论百年后计算机由什么构成,其速度远超今日是可以安全预测的。若摩尔定律持续生效,速度将提升74万亿亿倍(73,786,976,294,838,206,464倍)。这难以想象。实际上最可能的预测是摩尔定律终将失效——任何每18个月翻番的事物都终将触及物理极限。但我毫不怀疑计算机将变得极快。即使仅提升百万倍,也足以彻底改写编程语言的基本规则。届时,那些现在被视为缓慢的语言(即生成低效代码的语言)将有更大生存空间。
然而某些应用仍将追求速度。计算机产生的问题需要计算机解决——例如视频图像处理速度取决于另一台计算机的生成速度。还有一类问题天生具有吞噬计算周期的能力:图像渲染、加密、模拟等。
当部分应用可以越来越低效而其他应用仍需压榨硬件性能时,更快的计算机意味着语言需要覆盖更广的效率范围。这种现象已然显现——按过去标准衡量,某些流行新语言的实现简直浪费得惊人。
In language design, we should be consciously seeking out situations where we can trade efficiency for even the smallest increase in convenience. Most data structures exist because of speed. For example, many languages today have both strings and lists. Semantically, strings are more or less a subset of lists in which the elements are characters. So why do you need a separate data type? You don't, really. Strings only exist for efficiency. But it's lame to clutter up the semantics of the language with hacks to make programs run faster. Having strings in a language seems to be a case of premature optimization. If we think of the core of a language as a set of axioms, surely it's gross to have additional axioms that add no expressive power, simply for the sake of efficiency. Efficiency is important, but I don't think that's the right way to get it. The right way to solve that problem, I think, is to separate the meaning of a program from the implementation details. Instead of having both lists and strings, have just lists, with some way to give the compiler optimization advice that will allow it to lay out strings as contiguous bytes if necessary. Since speed doesn't matter in most of a program, you won't ordinarily need to bother with this sort of micromanagement. This will be more and more true as computers get faster. Saying less about implementation should also make programs more flexible. Specifications change while a program is being written, and this is not only inevitable, but desirable. The word "essay" comes from the French verb "essayer", which means "to try". An essay, in the original sense, is something you write to try to figure something out. This happens in software too. I think some of the best programs were essays, in the sense that the authors didn't know when they started exactly what they were trying to write. Lisp hackers already know about the value of being flexible with data structures.
这不仅是编程语言的现象,而是普遍历史趋势。技术改进使每一代人都能做被上一代人视为浪费的事。三十年前的人会惊诧于我们拨打长途电话的随意,百年前的人更会震惊于包裹竟需经孟菲斯中转才能从波士顿抵达纽约。
我已然能预见未来百年硬件提速带来的额外周期将如何被消耗——几乎全部浪费掉。
我在计算资源稀缺时代学会编程,记得曾删除BASIC程序中所有空格以塞进4K内存的TRS-80。想到这些极其低效的软件反复做着相同工作,我感到某种不适。但这种直觉可能是错的——就像从小贫穷的人难以忍受为重要事项(比如看病)花钱。
某些浪费确实令人反感。比如SUV,即便使用永续无污染的燃料,其存在本身仍是粗鄙的——因为它是解决粗鄙问题(如何让迷你货车更阳刚)的方案。但并非所有浪费都坏。既然已具备支持设施,计较长途电话分钟数就显得吝啬。拥有资源时,将所有通话视为同类(无论对方位置)才是更优雅的做法。
存在好的浪费与坏的浪费。我关注好的浪费——通过更多支出来换取更简洁的设计。我们将如何利用更快硬件提供的浪费机会?对速度的渴求已深入骨髓(拜孱弱硬件所赐),需要有意识地克服。在语言设计中,我们应主动寻找能用效率换取微小便利提升的场景。
We tend to write the first version of a program so that it does everything with lists. These initial versions can be so shockingly inefficient that it takes a conscious effort not to think about what they're doing, just as, for me at least, eating a steak requires a conscious effort not to think where it came from. What programmers in a hundred years will be looking for, most of all, is a language where you can throw together an unbelievably inefficient version 1 of a program with the least possible effort. At least, that's how we'd describe it in present-day terms. What they'll say is that they want a language that's easy to program in. Inefficient software isn't gross. What's gross is a language that makes programmers do needless work. Wasting programmer time is the true inefficiency, not wasting machine time. This will become ever more clear as computers get faster. I think getting rid of strings is already something we could bear to think about. We did it in Arc, and it seems to be a win; some operations that would be awkward to describe as regular expressions can be described easily as recursive functions. How far will this flattening of data structures go? I can think of possibilities that shock even me, with my conscientiously broadened mind. Will we get rid of arrays, for example? After all, they're just a subset of hash tables where the keys are vectors of integers. Will we replace hash tables themselves with lists? There are more shocking prospects even than that. The Lisp that McCarthy described in 1960, for example, didn't have numbers. Logically, you don't need to have a separate notion of numbers, because you can represent them as lists: the integer n could be represented as a list of n elements. You can do math this way. It's just unbearably inefficient. No one actually proposed implementing numbers as lists in practice.
大多数数据结构因速度需求而存在。例如当今许多语言同时拥有字符串和列表。语义上字符串基本是元素为字符的列表子集,为何需要独立数据类型?本质上不需要。字符串仅为效率而存在。但用影响语言语义的hack来提速是拙劣的——在语言中包含字符串像是过早优化。
若将语言核心视为公理集合,那么仅为效率而添加无表达力的额外公理是粗鄙的。效率重要,但这不是正确的实现方式。
我认为正确解法是将程序意义与实现细节分离。与其同时拥有列表和字符串,不如仅保留列表,并通过某种方式向编译器提供优化建议,使其在必要时将字符串存储为连续字节。
由于程序大部分不关心速度,通常无需纠结此类微观管理。随着计算机提速,这一点将愈发明显。
减少实现细节还能增强程序灵活性。编写过程中需求变更是不可避免的,甚至是值得期待的。
In fact, McCarthy's 1960 paper was not, at the time, intended to be implemented at all. It was a theoretical exercise, an attempt to create a more elegant alternative to the Turing Machine. When someone did, unexpectedly, take this paper and translate it into a working Lisp interpreter, numbers certainly weren't represented as lists; they were represented in binary, as in every other language. Could a programming language go so far as to get rid of numbers as a fundamental data type? I ask this not so much as a serious question as as a way to play chicken with the future. It's like the hypothetical case of an irresistible force meeting an immovable object-- here, an unimaginably inefficient implementation meeting unimaginably great resources. I don't see why not. The future is pretty long. If there's something we can do to decrease the number of axioms in the core language, that would seem to be the side to bet on as t approaches infinity. If the idea still seems unbearable in a hundred years, maybe it won't in a thousand. Just to be clear about this, I'm not proposing that all numerical calculations would actually be carried out using lists. I'm proposing that the core language, prior to any additional notations about implementation, be defined this way. In practice any program that wanted to do any amount of math would probably represent numbers in binary, but this would be an optimization, not part of the core language semantics. Another way to burn up cycles is to have many layers of software between the application and the hardware. This too is a trend we see happening already: many recent languages are compiled into byte code. Bill Woods once told me that, as a rule of thumb, each layer of interpretation costs a factor of 10 in speed. This extra cost buys you flexibility. The very first version of Arc was an extreme case of this sort of multi-level slowness, with corresponding benefits.
“文章”(essay)一词源自法语动词“essayer”(尝试)。原始意义上的文章是为厘清问题而作的文字。软件亦然。我认为某些最优秀的程序正是这种意义上的“文章”——作者起笔时并不确知最终形态。
Lisp黑客早已洞悉数据结构灵活性的价值。我们习惯用列表编写程序初版,其效率可能低得惊人,需要刻意不去思考其运行机制(就像我吃牛排时需要刻意不去想其来源)。
百年后的程序员最渴望的,是用最少精力拼凑出极其低效的1.0版本的语言。用当今术语说就是“易于编程”的语言。
低效软件并不粗鄙。粗鄙的是迫使程序员做无用功的语言。浪费程序员时间才是真正的低效,而非浪费机器时间。随着计算机提速,这一点将愈发清晰。
我认为现在已可考虑舍弃字符串。我们在Arc语言中这样做了,结果证明是胜利——某些用正则表达式难以描述的操作,用递归函数可以轻松实现。
It was a classic "metacircular" interpreter written on top of Common Lisp, with a definite family resemblance to the eval function defined in McCarthy's original Lisp paper. The whole thing was only a couple hundred lines of code, so it was very easy to understand and change. The Common Lisp we used, CLisp, itself runs on top of a byte code interpreter. So here we had two levels of interpretation, one of them (the top one) shockingly inefficient, and the language was usable. Barely usable, I admit, but usable. Writing software as multiple layers is a powerful technique even within applications. Bottom-up programming means writing a program as a series of layers, each of which serves as a language for the one above. This approach tends to yield smaller, more flexible programs. It's also the best route to that holy grail, reusability. A language is by definition reusable. The more of your application you can push down into a language for writing that type of application, the more of your software will be reusable. Somehow the idea of reusability got attached to object-oriented programming in the 1980s, and no amount of evidence to the contrary seems to be able to shake it free. But although some object-oriented software is reusable, what makes it reusable is its bottom-upness, not its object-orientedness. Consider libraries: they're reusable because they're language, whether they're written in an object-oriented style or not. I don't predict the demise of object-oriented programming, by the way. Though I don't think it has much to offer good programmers, except in certain specialized domains, it is irresistible to large organizations. Object-oriented programming offers a sustainable way to write spaghetti code. It lets you accrete programs as a series of patches. Large organizations always tend to develop software this way, and I expect this to be as true in a hundred years as it is today.
数据结构的扁平化能走多远?即使以我自觉开阔的思维,某些可能性仍令我震惊。比如舍弃数组?毕竟它们只是键为整数向量的哈希表子集。用列表取代哈希表本身?
还有更惊人的可能。例如McCarthy在1960年描述的Lisp没有数字概念。逻辑上你不需要独立数字概念,因为可用列表表示——整数n可表示为含n个元素的列表。虽然这种数学运算方式效率令人窒息。
实践中无人建议如此实现数字。实际上McCarthy的1960年论文当时根本无意实现,它只是创建图灵机优雅替代品的理论尝试。当有人意外地将论文转化为可运行的Lisp解释器时,数字当然不是用列表表示——它们像所有其他语言一样用二进制表示。
编程语言能否彻底取消数字作为基本数据类型?我提出这个问题更多是与未来玩胆量游戏,就像不可抗拒力遇到不可移动物的假设案例——在这里是难以想象的低效实现遇到难以想象的庞大资源。我看不出为何不可。未来足够漫长。如果我们能减少核心语言的公理数量,随着时间趋近无穷,这似乎值得押注。若百年后这个想法仍难以接受,或许千年后会改变。
As long as we're talking about the future, we had better talk about parallel computation, because that's where this idea seems to live. That is, no matter when you're talking, parallel computation seems to be something that is going to happen in the future. Will the future ever catch up with it? People have been talking about parallel computation as something imminent for at least 20 years, and it hasn't affected programming practice much so far. Or hasn't it? Already chip designers have to think about it, and so must people trying to write systems software on multi-cpu computers. The real question is, how far up the ladder of abstraction will parallelism go? In a hundred years will it affect even application programmers? Or will it be something that compiler writers think about, but which is usually invisible in the source code of applications? One thing that does seem likely is that most opportunities for parallelism will be wasted. This is a special case of my more general prediction that most of the extra computer power we're given will go to waste. I expect that, as with the stupendous speed of the underlying hardware, parallelism will be something that is available if you ask for it explicitly, but ordinarily not used. This implies that the kind of parallelism we have in a hundred years will not, except in special applications, be massive parallelism. I expect for ordinary programmers it will be more like being able to fork off processes that all end up running in parallel. And this will, like asking for specific implementations of data structures, be something that you do fairly late in the life of a program, when you try to optimize it. Version 1s will ordinarily ignore any advantages to be got from parallel computation, just as they will ignore advantages to be got from specific representations of data. Except in special kinds of applications, parallelism won't pervade the programs that are written in a hundred years.
需要明确的是,我并非提议所有计算实际都用列表进行。我建议的是在添加任何实现注解前,核心语言应该如此定义。实践中任何涉及数学的程序都可能用二进制表示数字,但这属于优化,而非核心语言语义部分。
另一种消耗周期的方式是在应用与硬件间设置多层软件。这已是可见趋势——许多新近语言被编译为字节码。Bill Woods曾告诉我经验法则:每层解释会使速度降低十倍。这种代价换来的是灵活性。
Arc的首个版本就是这种多层次缓慢的极端案例,也带来相应好处。它是运行在Common Lisp之上的经典“元循环”解释器,与McCarthy原始Lisp论文中定义的eval函数有明显亲缘关系。整个系统仅几百行代码,极易理解和修改。我们使用的CLisp本身运行在字节码解释器上。因此这里有两层解释(顶层效率低得惊人),但语言居然可用——勉强可用,但确实可用。
分层编写软件即使在应用内部也是强大技术。自底向上编程意味着将程序写成系列层次,每层都是上一层的语言。这种方法往往产生更小更灵活的程序,也是实现圣杯——可重用性——的最佳路径。语言天生可重用。将越多应用逻辑下放到针对某类应用的语言中,就有越多软件可重用。
1980年代可重用性概念与面向对象编程错误绑定,至今难以分离。尽管某些面向对象软件确实可重用,但使其可重用的是自底向上特性而非面向对象特性。以库为例:它们可重用因为它们是语言,无论是否采用面向对象风格编写。
It would be premature optimization if it did. How many programming languages will there be in a hundred years? There seem to be a huge number of new programming languages lately. Part of the reason is that faster hardware has allowed programmers to make different tradeoffs between speed and convenience, depending on the application. If this is a real trend, the hardware we'll have in a hundred years should only increase it. And yet there may be only a few widely-used languages in a hundred years. Part of the reason I say this is optimism: it seems that, if you did a really good job, you could make a language that was ideal for writing a slow version 1, and yet with the right optimization advice to the compiler, would also yield very fast code when necessary. So, since I'm optimistic, I'm going to predict that despite the huge gap they'll have between acceptable and maximal efficiency, programmers in a hundred years will have languages that can span most of it. As this gap widens, profilers will become increasingly important. Little attention is paid to profiling now. Many people still seem to believe that the way to get fast applications is to write compilers that generate fast code. As the gap between acceptable and maximal performance widens, it will become increasingly clear that the way to get fast applications is to have a good guide from one to the other. When I say there may only be a few languages, I'm not including domain-specific "little languages". I think such embedded languages are a great idea, and I expect them to proliferate. But I expect them to be written as thin enough skins that users can see the general-purpose language underneath. Who will design the languages of the future? One of the most exciting trends in the last ten years has been the rise of open-source languages like Perl, Python, and Ruby. Language design is being taken over by hackers. The results so far are messy, but encouraging.
顺便说,我并非预测面向对象编程的消亡。尽管我认为除了特定领域外它对优秀程序员价值有限,但大型组织难以抗拒它。面向对象编程提供了一种可持续编写意大利面条代码的方式,允许以补丁序列形式累积程序。大型组织总是倾向于这种方式开发软件,我预计百年后依然如此。
既然谈及未来,就不得不讨论并行计算——这个概念似乎永远属于未来。无论何时讨论,并行计算似乎总是即将到来。
未来会追上它吗?人们将并行计算视为迫近事物已至少二十年,至今对编程实践影响有限。真的有限吗?芯片设计师已必须考虑它,多CPU计算机上的系统软件编写者亦然。
真正的问题是:并行性会渗透到抽象阶梯的哪一层?百年后它会影响应用程序员吗?抑或仍是编译器编写者关注但对应用源代码透明的事物?
似乎多数并行机会将被浪费。这是我更宏观预测(额外计算能力大多被浪费)的特例。与底层硬件的惊人速度类似,我预计并行性将是一种需要显式请求才会启用的能力,通常处于闲置状态。这意味着百年后的并行性(特殊应用除外)不会是大规模并行。对普通程序员而言,可能更像是能派生出并行运行的进程。
There are some stunningly novel ideas in Perl, for example. Many are stunningly bad, but that's always true of ambitious efforts. At its current rate of mutation, God knows what Perl might evolve into in a hundred years. It's not true that those who can't do, teach (some of the best hackers I know are professors), but it is true that there are a lot of things that those who teach can't do. Research imposes constraining caste restrictions. In any academic field there are topics that are ok to work on and others that aren't. Unfortunately the distinction between acceptable and forbidden topics is usually based on how intellectual the work sounds when described in research papers, rather than how important it is for getting good results. The extreme case is probably literature; people studying literature rarely say anything that would be of the slightest use to those producing it. Though the situation is better in the sciences, the overlap between the kind of work you're allowed to do and the kind of work that yields good languages is distressingly small. (Olin Shivers has grumbled eloquently about this.) For example, types seem to be an inexhaustible source of research papers, despite the fact that static typing seems to preclude true macros-- without which, in my opinion, no language is worth using. The trend is not merely toward languages being developed as open-source projects rather than "research", but toward languages being designed by the application programmers who need to use them, rather than by compiler writers. This seems a good trend and I expect it to continue. Unlike physics in a hundred years, which is almost necessarily impossible to predict, I think it may be possible in principle to design a language now that would appeal to users in a hundred years.
就像为数据结构选择特定实现,这将是程序生命周期后期优化阶段的工作。1.0版本通常会忽略并行计算的优势,就像忽略数据特定表示法的优势。
除特殊应用外,并行性不会渗透百年后的程序。如果渗透了,那就是过早优化。
百年后会有多少种编程语言?近来似乎涌现大量新语言。部分原因是更快硬件允许程序员根据不同应用在速度与便利间做出不同权衡。若这是真实趋势,百年后的硬件只会加剧它。
然而百年后可能只有少数几种广泛使用的语言。我这么说的部分原因是乐观:似乎若能真正做好,可以创造出既适合编写低效1.0版本,又能在编译器获得正确优化建议时生成高效代码的语言。因此作为乐观主义者,我预测尽管可接受效率与最大效率间存在巨大鸿沟,百年后的程序员将拥有能覆盖大部分区间的语言。
随着这个鸿沟扩大,性能分析工具将愈发重要。目前性能分析未受足够重视。许多人仍认为获得快速应用的途径是编写生成快速代码的编译器。随着可接受性能与最大性能差距扩大,获得快速应用的正确途径将愈发清晰:需要从前者到后者的优质向导。
One way to design a language is to just write down the program you'd like to be able to write, regardless of whether there is a compiler that can translate it or hardware that can run it. When you do this you can assume unlimited resources. It seems like we ought to be able to imagine unlimited resources as well today as in a hundred years. What program would one like to write? Whatever is least work. Except not quite: whatever _would be_ least work if your ideas about programming weren't already influenced by the languages you're currently used to. Such influence can be so pervasive that it takes a great effort to overcome it. You'd think it would be obvious to creatures as lazy as us how to express a program with the least effort. In fact, our ideas about what's possible tend to be so limited by whatever language we think in that easier formulations of programs seem very surprising. They're something you have to discover, not something you naturally sink into. One helpful trick here is to use the length of the program as an approximation for how much work it is to write. Not the length in characters, of course, but the length in distinct syntactic elements-- basically, the size of the parse tree. It may not be quite true that the shortest program is the least work to write, but it's close enough that you're better off aiming for the solid target of brevity than the fuzzy, nearby one of least work. Then the algorithm for language design becomes: look at a program and ask, is there any way to write this that's shorter? In practice, writing programs in an imaginary hundred-year language will work to varying degrees depending on how close you are to the core. Sort routines you can write now. But it would be hard to predict now what kinds of libraries might be needed in a hundred years. Presumably many libraries will be for domains that don't even exist yet.
当我说可能只有少数语言时,不包括领域特定的“小语言”。我认为这种嵌入式语言是伟大创意,预计会激增。但我预期它们会以足够薄的皮肤编写,让用户能看清底层的通用语言。
谁来设计未来语言?过去十年最激动人心的趋势是Perl、Python、Ruby等开源语言的崛起。语言设计正被黑客接管。目前成果虽混乱但鼓舞人心。例如Perl包含一些惊人新颖的思想——尽管许多糟糕得惊人,但雄心勃勃的尝试总是如此。以当前变异速度,天知道百年后Perl会进化成什么。
“不能者教”并非真理(我认识的最优秀黑客有些是教授),但教师群体确实存在大量“不能”之事。学术研究施加了种姓限制。任何学术领域都存在可研究课题与禁忌课题。不幸的是,这种区分通常基于研究论文描述时的学术性,而非对获得好结果的重要性。文学可能是极端案例——研究文学者几乎从不说对创作者有用的内容。
尽管科学界状况较好,但被允许的工作类型与产出优秀语言的工作类型重叠之小令人沮丧(Olin Shivers对此有过精彩抱怨)。例如类型系统似乎是研究论文的永恒源泉,尽管静态类型似乎排除了真正的宏——在我看来没有宏的语言根本不值得使用。
趋势不仅是语言作为开源项目而非“研究”开发,更是由需要使用它们的应用程序员而非编译器编写者设计语言。这似乎是好趋势,我预计将持续。
If SETI@home works, for example, we'll need libraries for communicating with aliens. Unless of course they are sufficiently advanced that they already communicate in XML. At the other extreme, I think you might be able to design the core language today. In fact, some might argue that it was already mostly designed in 1958. If the hundred year language were available today, would we want to program in it? One way to answer this question is to look back. If present-day programming languages had been available in 1960, would anyone have wanted to use them? In some ways, the answer is no. Languages today assume infrastructure that didn't exist in 1960. For example, a language in which indentation is significant, like Python, would not work very well on printer terminals. But putting such problems aside-- assuming, for example, that programs were all just written on paper-- would programmers of the 1960s have liked writing programs in the languages we use now? I think so. Some of the less imaginative ones, who had artifacts of early languages built into their ideas of what a program was, might have had trouble. (How can you manipulate data without doing pointer arithmetic? How can you implement flow charts without gotos?) But I think the smartest programmers would have had no trouble making the most of present-day languages, if they'd had them. If we had the hundred-year language now, it would at least make a great pseudocode. What about using it to write software? Since the hundred-year language will need to generate fast code for some applications, presumably it could generate code efficient enough to run acceptably well on our hardware. We might have to give more optimization advice than users in a hundred years, but it still might be a net win.
与几乎无法预测的百年后物理学不同,我认为原则上现在就可能设计出百年后仍受欢迎的语言。
设计语言的一种方式是写下你希望写出的程序,无视是否存在能编译它的编译器或能运行它的硬件。此时你可以假设资源无限。似乎我们现在与百年后同样擅长想象无限资源。
人们希望编写什么程序?最省力的那种。但不完全——是在不被现有语言观念影响时最省力的那种。这种影响如此 pervasive,需要巨大努力才能克服。你可能会认为,对我们这种懒惰生物而言,用最少努力表达程序应该是显而易见的。事实上,我们对可能性的认知受限于思维语言,更简单的程序表达往往显得惊人——它们是待发现的,而非自然沉浸的。
一个有用技巧是用程序长度近似衡量编写工作量。当然不是字符长度,而是独立语法元素数量——基本上是语法树大小。最短程序是否对应最少工作量并不绝对,但瞄准简洁这个明确目标比瞄准模糊的“最少工作”更可靠。于是语言设计算法变为:审视程序并询问,是否存在更简短的写法?
实践中,用假想的百年语言编写程序的可行性取决于你与核心的距离。排序算法现在就能写,但预测百年后需要哪些库则困难——很可能许多库针对尚未出现的领域。例如若SETI@home成功,我们将需要与外星人通信的库。除非他们已先进到使用XML交流。
Now we have two ideas that, if you combine them, suggest interesting possibilities: (1) the hundred-year language could, in principle, be designed today, and (2) such a language, if it existed, might be good to program in today. When you see these ideas laid out like that, it's hard not to think, why not try writing the hundred-year language now? When you're working on language design, I think it is good to have such a target and to keep it consciously in mind. When you learn to drive, one of the principles they teach you is to align the car not by lining up the hood with the stripes painted on the road, but by aiming at some point in the distance. Even if all you care about is what happens in the next ten feet, this is the right answer. I think we can and should do the same thing with programming languages. Notes I believe Lisp Machine Lisp was the first language to embody the principle that declarations (except those of dynamic variables) were merely optimization advice, and would not change the meaning of a correct program. Common Lisp seems to have been the first to state this explicitly. Thanks to Trevor Blackwell, Robert Morris, and Dan Giffin for reading drafts of this, and to Guido van Rossum, Jeremy Hylton, and the rest of the Python crew for inviting me to speak at PyCon..
另一个极端是,我认为今天就可能设计出核心语言。事实上有人可能主张它早在1958年就已基本设计完成。
如果百年语言今天可用,我们会想用它编程吗?一种回答方式是回顾历史:如果现代编程语言在1960年就存在,会有人愿意使用吗?
某些方面答案是否定的。现代语言依赖1960年不存在的设施。例如Python这种依赖缩进的语言在打印终端上难以工作。但抛开这些问题(假设程序都写在纸上),1960年代的程序员会喜欢用我们现在的语言编程吗?
我认为会的。某些缺乏想象力的程序员(其编程观念被早期语言特性固化)可能会有障碍(没有指针运算如何操作数据?没有goto如何实现流程图?)。但我认为最聪明的程序员若能接触现代语言,定能物尽其用。
即使现在拥有百年语言,至少它会是优秀的伪代码。用它编写软件呢?既然百年语言需要为某些应用生成快速代码,想必它也能生成在我们硬件上高效运行的代码。我们可能需要比百年后用户提供更多优化建议,但总体上仍可能获益。
You'll find this essay and 14 others in _Hackers & Painters_.
现在有两个观点结合后暗示有趣的可能性:(1)百年语言原则上今天就可设计;(2)这种语言若存在,可能现在就是优秀的编程工具。看到这些观点并列,很难不思考:为何不现在就尝试编写百年语言?
从事语言设计时,我认为应该确立这样的目标并保持清醒意识。学习驾驶时,重要原则是对准远方某点而非引擎盖与道路标线的相对位置来调整方向——即使你只关心接下来十英尺的路况。我认为编程语言领域同样适用这个原则。
注释 我相信Lisp Machine Lisp是首个体现“声明(动态变量除外)仅是优化建议,不会改变正确程序含义”原则的语言。Common Lisp似乎是首个明确阐述这点的语言。
致谢 感谢Trevor Blackwell、Robert Morris和Dan Giffin阅读本文草稿,感谢Guido van Rossum、Jeremy Hylton及Python团队邀请我在PyCon演讲。
你可以在《黑客与画家》中找到这篇文章以及其他14篇。
[](https://s.turbifycdn.com/aah/paulgraham/why-nerds-are-unpopular-11.gif) February 2003 When we were in junior high school, my friend Rich and I made a map of the school lunch tables according to popularity. This was easy to do, because kids only ate lunch with others of about the same popularity. We graded them from A to E. A tables were full of football players and cheerleaders and so on. E tables contained the kids with mild cases of Down's Syndrome, what in the language of the time we called "retards." We sat at a D table, as low as you could get without looking physically different. We were not being especially candid to grade ourselves as D. It would have taken a deliberate lie to say otherwise. Everyone in the school knew exactly how popular everyone else was, including us. My stock gradually rose during high school. Puberty finally arrived; I became a decent soccer player; I started a scandalous underground newspaper. So I've seen a good part of the popularity landscape. I know a lot of people who were nerds in school, and they all tell the same story: there is a strong correlation between being smart and being a nerd, and an even stronger inverse correlation between being a nerd and being popular. Being smart seems to _make_ you unpopular. Why? To someone in school now, that may seem an odd question to ask. The mere fact is so overwhelming that it may seem strange to imagine that it could be any other way. But it could. Being smart doesn't make you an outcast in elementary school. Nor does it harm you in the real world. Nor, as far as I can tell, is the problem so bad in most other countries. But in a typical American secondary school, being smart is likely to make your life difficult. Why? The key to this mystery is to rephrase the question slightly.
[](https://s.turbifycdn.com/aah/paulgraham/why-nerds-are-unpopular-11.gif)
初中时,我和朋友里奇根据受欢迎程度绘制了学校午餐桌分布图。这很容易操作,因为孩子们只和受欢迎程度相当的人同桌吃饭。我们将餐桌从A到E分级——A桌坐满橄榄球员和啦啦队长,E桌则是轻度唐氏综合症患儿,用当时的说法叫"弱智"。
我们坐在D桌,这是外表正常者能坐的最低等级。自评D级并非过分坦诚,若谎称更高等级反而显得刻意。学校里每个人都清楚彼此的人气值,包括我们自己。
高中时我的地位逐渐提升。青春期终于降临;我成了不错的足球选手;还创办了地下小报引发争议。因此我见识了人气版图的绝大部分。
我认识许多学生时代的书呆子,他们讲述着相同的故事:聪明与书呆子气高度相关,而书呆子气与受欢迎程度更是强烈负相关。聪明似乎注定让你不受欢迎。
Why don't smart kids make themselves popular? If they're so smart, why don't they figure out how popularity works and beat the system, just as they do for standardized tests? One argument says that this would be impossible, that the smart kids are unpopular because the other kids envy them for being smart, and nothing they could do could make them popular. I wish. If the other kids in junior high school envied me, they did a great job of concealing it. And in any case, if being smart were really an enviable quality, the girls would have broken ranks. The guys that guys envy, girls like. In the schools I went to, being smart just didn't matter much. Kids didn't admire it or despise it. All other things being equal, they would have preferred to be on the smart side of average rather than the dumb side, but intelligence counted far less than, say, physical appearance, charisma, or athletic ability. So if intelligence in itself is not a factor in popularity, why are smart kids so consistently unpopular? The answer, I think, is that they don't really want to be popular. If someone had told me that at the time, I would have laughed at him. Being unpopular in school makes kids miserable, some of them so miserable that they commit suicide. Telling me that I didn't want to be popular would have seemed like telling someone dying of thirst in a desert that he didn't want a glass of water. Of course I wanted to be popular. But in fact I didn't, not enough. There was something else I wanted more: to be smart. Not simply to do well in school, though that counted for something, but to design beautiful rockets, or to write well, or to understand how to program computers. In general, to make great things. At the time I never tried to separate my wants and weigh them against one another. If I had, I would have seen that being smart was more important.
为什么?对现今学生而言,这问题或许显得古怪。既定事实如此强势,以至于难以想象其他可能性。但确实存在其他可能——小学时聪明不会让你被排斥;现实世界中聪明不会伤害你;据我所知多数国家也没这么严重的问题。唯独在典型美国中学里,聪明会让你处境艰难。原因何在?
谜底在于转换提问方式:为什么聪明孩子不主动争取人气?既然他们如此聪明,为何不像应对标准化考试那样,破解人气法则并战胜系统?
有种观点认为这不可能——聪明孩子不受欢迎是因为遭人嫉妒,任何努力都无济于事。我多希望这是真的。若初中同学真嫉妒我,他们的掩饰功夫堪称完美。何况若聪明真值得羡慕,女生们早该倒戈——被男生嫉妒的人往往受女生青睐。
在我经历的学校里,聪明无足轻重。孩子们既不崇拜也不鄙视它。条件相当时,他们宁愿智商中等偏上而非偏下,但智力远不如外貌、魅力或运动能力重要。
既然智力本身不影响人气,为何聪明孩子总不受欢迎?答案或许是:他们并非真心渴望人气。
If someone had offered me the chance to be the most popular kid in school, but only at the price of being of average intelligence (humor me here), I wouldn't have taken it. Much as they suffer from their unpopularity, I don't think many nerds would. To them the thought of average intelligence is unbearable. But most kids would take that deal. For half of them, it would be a step up. Even for someone in the eightieth percentile (assuming, as everyone seemed to then, that intelligence is a scalar), who wouldn't drop thirty points in exchange for being loved and admired by everyone? And that, I think, is the root of the problem. Nerds serve two masters. They want to be popular, certainly, but they want even more to be smart. And popularity is not something you can do in your spare time, not in the fiercely competitive environment of an American secondary school. Alberti, arguably the archetype of the Renaissance Man, writes that "no art, however minor, demands less than total dedication if you want to excel in it." I wonder if anyone in the world works harder at anything than American school kids work at popularity. Navy SEALs and neurosurgery residents seem slackers by comparison. They occasionally take vacations; some even have hobbies. An American teenager may work at being popular every waking hour, 365 days a year. I don't mean to suggest they do this consciously. Some of them truly are little Machiavellis, but what I really mean here is that teenagers are always on duty as conformists. For example, teenage kids pay a great deal of attention to clothes. They don't consciously dress to be popular. They dress to look good. But to who? To the other kids. Other kids' opinions become their definition of right, not just for clothes, but for almost everything they do, right down to the way they walk. And so every effort they make to do things "right" is also, consciously or not, an effort to be more popular. Nerds don't realize this.
若当年有人这么说,我必嗤之以鼻。校园边缘化让孩子痛苦不堪,甚至有人因此自杀。告诉我不想受欢迎,如同对沙漠中濒临渴死的人说他不想喝水。我当然渴望人气。
但事实上,渴望程度不够。我有更重要的追求:变得聪明。不仅是为学业优异(虽然这也有价值),更是为设计精美火箭、写出好文章或掌握编程。总之,创造伟大事物。
当年我从未权衡过这些渴望。若曾比较,必会发现聪明更重要。假设有机会成为全校最受欢迎的学生,代价是沦为平庸智商(暂且假设),我绝不会接受。
尽管饱受边缘化之苦,多数书呆子也不会接受这交易。对他们而言,平庸智商难以忍受。但多数孩子会接受——对半数人而言这甚至是提升。即便对智商前20%的人(假设智力可量化),谁不愿用30个智商点换取众人爱戴?
这正是问题根源。书呆子侍奉两位主人:他们想要人气,但更渴望智慧。而在美国中学的残酷竞争中,人气无法兼职获得。
They don't realize that it takes work to be popular. In general, people outside some very demanding field don't realize the extent to which success depends on constant (though often unconscious) effort. For example, most people seem to consider the ability to draw as some kind of innate quality, like being tall. In fact, most people who "can draw" like drawing, and have spent many hours doing it; that's why they're good at it. Likewise, popular isn't just something you are or you aren't, but something you make yourself. The main reason nerds are unpopular is that they have other things to think about. Their attention is drawn to books or the natural world, not fashions and parties. They're like someone trying to play soccer while balancing a glass of water on his head. Other players who can focus their whole attention on the game beat them effortlessly, and wonder why they seem so incapable. Even if nerds cared as much as other kids about popularity, being popular would be more work for them. The popular kids learned to be popular, and to want to be popular, the same way the nerds learned to be smart, and to want to be smart: from their parents. While the nerds were being trained to get the right answers, the popular kids were being trained to please. So far I've been finessing the relationship between smart and nerd, using them as if they were interchangeable. In fact it's only the context that makes them so. A nerd is someone who isn't socially adept enough. But "enough" depends on where you are. In a typical American school, standards for coolness are so high (or at least, so specific) that you don't have to be especially awkward to look awkward by comparison. Few smart kids can spare the attention that popularity requires. Unless they also happen to be good-looking, natural athletes, or siblings of popular kids, they'll tend to become nerds. And that's why smart people's lives are worst between, say, the ages of eleven and seventeen.
文艺复兴全才阿尔贝蒂曾说:"任何艺术,即便最微末者,欲臻卓越皆需全心投入。"我怀疑世上无人比美国学生更努力钻研人气。相较之下,海豹突击队员和神经外科住院医师都像懒汉——他们偶尔休假,有些人还有爱好。而美国青少年可能全年无休地钻研人气。
并非说他们刻意为之。其中确有马基雅维利式人物,但更多是青少年无时无刻不在从众。
比如他们极度注重衣着。并非刻意穿着求人气,而是为"看起来体面"。但取悦谁?其他孩子。同辈眼光成为他们的真理标准,从衣着到步态无不如此。因此每个"得体"举动,无论有意无意,都是人气争夺战。
书呆子意识不到这点。他们不懂人气需要经营。通常,除非身处高要求领域,人们难以察觉成功依赖持续(哪怕无意识)努力。例如多数人将绘画才能视作身高般的天赋,实则"会画画"者多因热爱而投入大量时间。同理,人气非天生特质,而是自我建构的结果。
书呆子不受欢迎的主因在于心有旁骛。他们的注意力投向书本或自然而非时尚派对,就像顶水杯踢足球的球员。全心投入的对手不费吹灰之力就能击败他们,还纳闷为何对方如此笨拙。
Life at that age revolves far more around popularity than before or after. Before that, kids' lives are dominated by their parents, not by other kids. Kids do care what their peers think in elementary school, but this isn't their whole life, as it later becomes. Around the age of eleven, though, kids seem to start treating their family as a day job. They create a new world among themselves, and standing in this world is what matters, not standing in their family. Indeed, being in trouble in their family can win them points in the world they care about. The problem is, the world these kids create for themselves is at first a very crude one. If you leave a bunch of eleven-year-olds to their own devices, what you get is _Lord of the Flies._ Like a lot of American kids, I read this book in school. Presumably it was not a coincidence. Presumably someone wanted to point out to us that we were savages, and that we had made ourselves a cruel and stupid world. This was too subtle for me. While the book seemed entirely believable, I didn't get the additional message. I wish they had just told us outright that we were savages and our world was stupid. Nerds would find their unpopularity more bearable if it merely caused them to be ignored. Unfortunately, to be unpopular in school is to be actively persecuted. Why? Once again, anyone currently in school might think this a strange question to ask. How could things be any other way? But they could be. Adults don't normally persecute nerds. Why do teenage kids do it? Partly because teenagers are still half children, and many children are just intrinsically cruel. Some torture nerds for the same reason they pull the legs off spiders. Before you develop a conscience, torture is amusing. Another reason kids persecute nerds is to make themselves feel better. When you tread water, you lift yourself up by pushing water down.
即便书呆子同样在乎人气,他们需付出更多努力。受欢迎孩子学习讨人喜欢的技巧与渴望,如同书呆子学习求知与思考:皆来自父母教养。当书呆子被训练寻找正确答案时,受欢迎孩子正被培养取悦他人。
此前我将聪明与书呆子气混为一谈,只因语境使然。书呆子本质是社交笨拙者,但"笨拙"标准取决于环境。典型美国中学的酷炫标准极高(或极特定),稍显笨拙者即相形见绌。
鲜有聪明孩子能兼顾人气所需。除非天生丽质、运动健将或人气王亲属,否则难免沦为书呆子。这解释了为何聪明人在11至17岁活得最痛苦——该阶段人生围绕人气运转的程度空前绝后。
此前,孩子生活由父母主导;此后,真实世界自有其规则。唯有这个阶段,孩子们自创的封闭世界成为一切。
约11岁起,孩子开始将家庭视为"日间工作"。他们构建新世界,其中地位决定一切。事实上,家庭中的困境反能提升他们在意世界的地位。
Likewise, in any social hierarchy, people unsure of their own position will try to emphasize it by maltreating those they think rank below. I've read that this is why poor whites in the United States are the group most hostile to blacks. But I think the main reason other kids persecute nerds is that it's part of the mechanism of popularity. Popularity is only partially about individual attractiveness. It's much more about alliances. To become more popular, you need to be constantly doing things that bring you close to other popular people, and nothing brings people closer than a common enemy. Like a politician who wants to distract voters from bad times at home, you can create an enemy if there isn't a real one. By singling out and persecuting a nerd, a group of kids from higher in the hierarchy create bonds between themselves. Attacking an outsider makes them all insiders. This is why the worst cases of bullying happen with groups. Ask any nerd: you get much worse treatment from a group of kids than from any individual bully, however sadistic. If it's any consolation to the nerds, it's nothing personal. The group of kids who band together to pick on you are doing the same thing, and for the same reason, as a bunch of guys who get together to go hunting. They don't actually hate you. They just need something to chase. Because they're at the bottom of the scale, nerds are a safe target for the entire school. If I remember correctly, the most popular kids don't persecute nerds; they don't need to stoop to such things. Most of the persecution comes from kids lower down, the nervous middle classes. The trouble is, there are a lot of them. The distribution of popularity is not a pyramid, but tapers at the bottom like a pear. The least popular group is quite small. (I believe we were the only D table in our cafeteria map.) So there are more people who want to pick on nerds than there are nerds.
问题在于,孩子们初创的世界原始野蛮。若放任11岁孩子自治,结果就是《蝇王》——许多美国学生课堂读过此书,这非巧合。有人试图暗示我们既是野蛮人,又创造了残酷愚蠢的世界。当年我未能领悟这层隐喻,多希望他们直白告知:我们就是野蛮人,我们的世界愚蠢透顶。
若边缘化仅意味着被忽视,书呆子尚可忍受。不幸的是,校园边缘化往往伴随主动迫害。
为何?在校生或觉此问奇怪——不迫害才不正常。但成人世界就不迫害书呆子。为何青少年例外?
部分因青少年仍是半兽人,许多孩子天生残忍。他们折磨书呆子如同扯断蜘蛛腿——在良知发育前,虐待充满乐趣。
另一动机是自我安慰。踩水者通过下压水体上升;同理,社会阶层中不安分者通过打压自认的底层确认地位。据说这正是美国底层白人最敌视黑人的原因。
As well as gaining points by distancing oneself from unpopular kids, one loses points by being close to them. A woman I know says that in high school she liked nerds, but was afraid to be seen talking to them because the other girls would make fun of her. Unpopularity is a communicable disease; kids too nice to pick on nerds will still ostracize them in self-defense. It's no wonder, then, that smart kids tend to be unhappy in middle school and high school. Their other interests leave them little attention to spare for popularity, and since popularity resembles a zero-sum game, this in turn makes them targets for the whole school. And the strange thing is, this nightmare scenario happens without any conscious malice, merely because of the shape of the situation. For me the worst stretch was junior high, when kid culture was new and harsh, and the specialization that would later gradually separate the smarter kids had barely begun. Nearly everyone I've talked to agrees: the nadir is somewhere between eleven and fourteen. In our school it was eighth grade, which was ages twelve and thirteen for me. There was a brief sensation that year when one of our teachers overheard a group of girls waiting for the school bus, and was so shocked that the next day she devoted the whole class to an eloquent plea not to be so cruel to one another. It didn't have any noticeable effect. What struck me at the time was that she was surprised. You mean she doesn't know the kind of things they say to one another? You mean this isn't normal? It's important to realize that, no, the adults don't know what the kids are doing to one another. They know, in the abstract, that kids are monstrously cruel to one another, just as we know in the abstract that people get tortured in poorer countries. But, like us, they don't like to dwell on this depressing fact, and they don't see evidence of specific abuses unless they go looking for it.
但迫害主因在于人气机制本身。人气半靠个人魅力,更靠联盟策略。提升人气需要不断靠近其他受欢迎者,而共同敌人最能凝聚团体。
如同政客转移选民注意力,若无真实敌人,孩子们会制造一个。通过孤立迫害书呆子,上位团体强化内部联结。攻击外人令他们成为自己人。因此最恶劣的霸凌总发生在群体中——任何书呆子都会作证:群体施暴远比个体霸凌残酷,无论施暴者多变态。
若需安慰书呆子,可以说这非个人恩怨。围猎你的孩子群与结伴打猎的成人团体本质相同——他们非恨你,只是需要追逐目标。
作为底层存在,书呆子是全校安全的施暴对象。据我观察,最受欢迎者反不参与迫害(他们无需屈尊)。多数迫害来自中游的焦虑群体。
麻烦在于,中游群体规模庞大。人气分布非金字塔而是梨形——最不受欢迎群体很小(记忆中我们食堂地图仅有一个D桌)。因此施暴者远多于受害者。
Public school teachers are in much the same position as prison wardens. Wardens' main concern is to keep the prisoners on the premises. They also need to keep them fed, and as far as possible prevent them from killing one another. Beyond that, they want to have as little to do with the prisoners as possible, so they leave them to create whatever social organization they want. From what I've read, the society that the prisoners create is warped, savage, and pervasive, and it is no fun to be at the bottom of it. In outline, it was the same at the schools I went to. The most important thing was to stay on the premises. While there, the authorities fed you, prevented overt violence, and made some effort to teach you something. But beyond that they didn't want to have too much to do with the kids. Like prison wardens, the teachers mostly left us to ourselves. And, like prisoners, the culture we created was barbaric. Why is the real world more hospitable to nerds? It might seem that the answer is simply that it's populated by adults, who are too mature to pick on one another. But I don't think this is true. Adults in prison certainly pick on one another. And so, apparently, do society wives; in some parts of Manhattan, life for women sounds like a continuation of high school, with all the same petty intrigues. I think the important thing about the real world is not that it's populated by adults, but that it's very large, and the things you do have real effects. That's what school, prison, and ladies-who-lunch all lack. The inhabitants of all those worlds are trapped in little bubbles where nothing they do can have more than a local effect. Naturally these societies degenerate into savagery. They have no function for their form to follow. When the things you do have real effects, it's no longer enough just to be pleasing. It starts to be important to get the right answers, and that's where nerds show to advantage.
疏远边缘群体能加分,亲近则扣分。某女性友人坦言高中时虽喜欢书呆子,却不敢公开交谈以免遭女生嘲笑。边缘化如传染病,即便善良孩子为自保也会孤立他们。
难怪聪明孩子在初高中普遍痛苦。其他兴趣使他们无暇经营人气,而人气恰似零和博弈,这又使其沦为全校靶子。吊诡的是,这噩梦般情境全无刻意恶意,纯粹源于系统结构。
对我而言,初中是最黑暗时期。新兴的青少年文化野蛮原始,而日后区分聪明孩子的专业分野尚未显现。几乎所有交流者都认同:人生低谷在11至14岁之间。
我的八年级(12-13岁)发生过插曲:某老师偶然听见女生候车时的谈话,震惊之余次日用整节课恳切呼吁停止彼此伤害。
毫无效果。当时令我震惊的是老师的震惊——她竟不知孩子们日常对话内容?这难道不正常?
Bill Gates will of course come to mind. Though notoriously lacking in social skills, he gets the right answers, at least as measured in revenue. The other thing that's different about the real world is that it's much larger. In a large enough pool, even the smallest minorities can achieve a critical mass if they clump together. Out in the real world, nerds collect in certain places and form their own societies where intelligence is the most important thing. Sometimes the current even starts to flow in the other direction: sometimes, particularly in university math and science departments, nerds deliberately exaggerate their awkwardness in order to seem smarter. John Nash so admired Norbert Wiener that he adopted his habit of touching the wall as he walked down a corridor. As a thirteen-year-old kid, I didn't have much more experience of the world than what I saw immediately around me. The warped little world we lived in was, I thought, _the world._ The world seemed cruel and boring, and I'm not sure which was worse. Because I didn't fit into this world, I thought that something must be wrong with me. I didn't realize that the reason we nerds didn't fit in was that in some ways we were a step ahead. We were already thinking about the kind of things that matter in the real world, instead of spending all our time playing an exacting but mostly pointless game like the others. We were a bit like an adult would be if he were thrust back into middle school. He wouldn't know the right clothes to wear, the right music to like, the right slang to use. He'd seem to the kids a complete alien. The thing is, he'd know enough not to care what they thought. We had no such confidence. A lot of people seem to think it's good for smart kids to be thrown together with "normal" kids at this stage of their lives. Perhaps. But in at least some cases the reason the nerds don't fit in really is that everyone else is crazy.
必须认清:成人确实不知孩子间的真实互动。他们抽象知晓孩子彼此残忍,如同我们抽象知晓贫穷国家的酷刑。但正如我们不愿细想阴暗面,他们除非刻意调查,否则看不见具体暴行。
公立教师处境类似狱警。首要职责是确保囚犯在场,其次保障温饱并尽量避免互残。此外尽量减少接触,任囚犯自建社会组织。据我所知,囚犯构建的社会扭曲野蛮,底层处境悲惨。
我的学校大体如此。首要任务是确保学生到校。在校期间提供伙食、阻止公开暴力,并敷衍式教学。除此之外,校方不愿多管。如同狱警,教师基本放任我们。而如囚犯,我们创造了野蛮文化。
为何现实世界更善待书呆子?表面看是因成人更成熟。但我不认同——监狱成人照样彼此迫害,曼哈顿某些贵妇圈仍是高中勾心斗角的延续。
关键在于现实世界规模庞大且行为具有真实影响。这正是学校、监狱和午餐会所缺乏的——这些微型泡泡里,任何行为都难产生实际影响。没有功能需要遵循,社会自然退化为野蛮状态。
I remember sitting in the audience at a "pep rally" at my high school, watching as the cheerleaders threw an effigy of an opposing player into the audience to be torn to pieces. I felt like an explorer witnessing some bizarre tribal ritual. If I could go back and give my thirteen year old self some advice, the main thing I'd tell him would be to stick his head up and look around. I didn't really grasp it at the time, but the whole world we lived in was as fake as a Twinkie. Not just school, but the entire town. Why do people move to suburbia? To have kids! So no wonder it seemed boring and sterile. The whole place was a giant nursery, an artificial town created explicitly for the purpose of breeding children. Where I grew up, it felt as if there was nowhere to go, and nothing to do. This was no accident. Suburbs are deliberately designed to exclude the outside world, because it contains things that could endanger children. And as for the schools, they were just holding pens within this fake world. Officially the purpose of schools is to teach kids. In fact their primary purpose is to keep kids locked up in one place for a big chunk of the day so adults can get things done. And I have no problem with this: in a specialized industrial society, it would be a disaster to have kids running around loose. What bothers me is not that the kids are kept in prisons, but that (a) they aren't told about it, and (b) the prisons are run mostly by the inmates. Kids are sent off to spend six years memorizing meaningless facts in a world ruled by a caste of giants who run after an oblong brown ball, as if this were the most natural thing in the world. And if they balk at this surreal cocktail, they're called misfits. Life in this twisted world is stressful for the kids. And not just for the nerds. Like any war, it's damaging even to the winners. Adults can't avoid seeing that teenage kids are tormented.
当行为产生真实影响时,仅会讨好远远不够。正确答案变得重要,这正是书呆子的优势。比尔·盖茨即为例证——尽管社交笨拙,但至少以收入衡量,他找到了正确答案。
现实世界的另一特点是规模。足够大的池子里,最微小群体也能通过聚集达到临界质量。现实中,书呆子聚集形成以智慧为尊的社群。有时潮流甚至逆转——尤其在大学数理院系,书呆子刻意夸张笨拙以彰显智慧。约翰·纳什为模仿诺伯特·维纳,连扶墙走路的习惯都照搬。
13岁时,我的世界仅限于眼前所见。我以为这个扭曲小世界就是全世界。这世界既残酷又无聊,难说哪点更糟。
因不适应这世界,我认定自身有问题。当时未意识到,我们书呆子的不适应恰是某种超前——我们已开始思考真实世界的重要问题,而非像他人那样终日沉迷严苛却无意义的游戏。
我们像被扔回初中的成人。不懂正确衣着、音乐和俚语,在孩子眼中形同异类。区别在于,成人有足够智慧不在乎他人眼光,而我们缺乏这种自信。
So why don't they do something about it? Because they blame it on puberty. The reason kids are so unhappy, adults tell themselves, is that monstrous new chemicals, _hormones_ , are now coursing through their bloodstream and messing up everything. There's nothing wrong with the system; it's just inevitable that kids will be miserable at that age. This idea is so pervasive that even the kids believe it, which probably doesn't help. Someone who thinks his feet naturally hurt is not going to stop to consider the possibility that he is wearing the wrong size shoes. I'm suspicious of this theory that thirteen-year-old kids are intrinsically messed up. If it's physiological, it should be universal. Are Mongol nomads all nihilists at thirteen? I've read a lot of history, and I have not seen a single reference to this supposedly universal fact before the twentieth century. Teenage apprentices in the Renaissance seem to have been cheerful and eager. They got in fights and played tricks on one another of course (Michelangelo had his nose broken by a bully), but they weren't crazy. As far as I can tell, the concept of the hormone-crazed teenager is coeval with suburbia. I don't think this is a coincidence. I think teenagers are driven crazy by the life they're made to lead. Teenage apprentices in the Renaissance were working dogs. Teenagers now are neurotic lapdogs. Their craziness is the craziness of the idle everywhere. When I was in school, suicide was a constant topic among the smarter kids. No one I knew did it, but several planned to, and some may have tried. Mostly this was just a pose. Like other teenagers, we loved the dramatic, and suicide seemed very dramatic. But partly it was because our lives were at times genuinely miserable. Bullying was only part of the problem. Another problem, and possibly an even worse one, was that we never had anything real to work on. Humans like to work; in most of the world, your work is your identity.
许多人认为让聪明孩子与"普通"孩子相处有益。或许吧。但至少某些案例中,书呆子不适应是因为其他人都疯了。我仍记得高中动员会上,看着啦啦队将对手人偶扔进人群撕碎时的感受——活像探险家目睹怪异部落仪式。
若能回到过去,我会告诉13岁的自己:抬头看清全局。当时未能领悟的是,我们生活的整个世界都和Twinkie奶油蛋糕一样虚假。不仅是学校,整个小镇皆然。人们迁居郊区为何?养育孩子!难怪这里无聊透顶——整个社区就是巨型育婴所。
我成长的地方令人感到无处可去、无事可做。这非偶然。郊区设计本意为隔绝外界危险。至于学校,不过是这个虚假世界中的围栏。官方宣称学校用于教学,实则首要功能是将孩子集中关押以便成人办事。对此我并无异议——在专业化工业社会,放任孩子游荡才是灾难。
我的不满在于:(a)无人告知孩子真相;(b)监狱主要由囚犯自治。孩子们被囚禁六年,在追逐褐色橄榄球的巨人统治下背诵无用知识,仿佛天经地义。若质疑这荒诞体系,反被贴上"不合群"标签。
这扭曲世界令孩子压力重重。不仅是书呆子——如同任何战争,赢家同样受伤。
And all the work we did was pointless, or seemed so at the time. At best it was practice for real work we might do far in the future, so far that we didn't even know at the time what we were practicing for. More often it was just an arbitrary series of hoops to jump through, words without content designed mainly for testability. (The three main causes of the Civil War were.... Test: List the three main causes of the Civil War.) And there was no way to opt out. The adults had agreed among themselves that this was to be the route to college. The only way to escape this empty life was to submit to it. Teenage kids used to have a more active role in society. In pre-industrial times, they were all apprentices of one sort or another, whether in shops or on farms or even on warships. They weren't left to create their own societies. They were junior members of adult societies. Teenagers seem to have respected adults more then, because the adults were the visible experts in the skills they were trying to learn. Now most kids have little idea what their parents do in their distant offices, and see no connection (indeed, there is precious little) between schoolwork and the work they'll do as adults. And if teenagers respected adults more, adults also had more use for teenagers. After a couple years' training, an apprentice could be a real help. Even the newest apprentice could be made to carry messages or sweep the workshop. Now adults have no immediate use for teenagers. They would be in the way in an office. So they drop them off at school on their way to work, much as they might drop the dog off at a kennel if they were going away for the weekend. What happened? We're up against a hard one here. The cause of this problem is the same as the cause of so many present ills: specialization. As jobs become more specialized, we have to train longer for them.
成人无法忽视青少年的痛苦,为何不干预?因为他们归咎于青春期。成人自欺道:孩子痛苦是因名为"荷尔蒙"的新化学物质在血液中肆虐。系统无错,这年龄注定痛苦。
这观念根深蒂固,连孩子都深信不疑。认为脚痛是天性的人,自然不会怀疑鞋子尺码有误。
我质疑"13岁孩子天生混乱"的理论。若属生理现象,应具普世性。蒙古游牧民13岁时都成虚无主义者吗?大量阅读历史后,我发现20世纪前从未有此记载。文艺复兴时期的学徒虽也打架嬉闹(米开朗基罗曾被霸凌者打断鼻梁),但总体开朗热情。
据我考证,"荷尔蒙癫狂青少年"概念与郊区同时出现。这非巧合——我认为是畸形生活方式导致疯狂。文艺复兴时期的学徒是工作犬,当代青少年则是神经质的宠物犬。他们的疯狂是无所事事者的通病。
我读书时,自杀是聪明孩子的永恒话题。相识者中无人实施,但多人计划过,或许还有人尝试过。多数时候这只是戏剧性姿态——如所有青少年般,我们热爱夸张,而自杀堪称终极戏剧。但部分原因确是我们时常真切痛苦。
Kids in pre-industrial times started working at about 14 at the latest; kids on farms, where most people lived, began far earlier. Now kids who go to college don't start working full-time till 21 or 22. With some degrees, like MDs and PhDs, you may not finish your training till 30. Teenagers now are useless, except as cheap labor in industries like fast food, which evolved to exploit precisely this fact. In almost any other kind of work, they'd be a net loss. But they're also too young to be left unsupervised. Someone has to watch over them, and the most efficient way to do this is to collect them together in one place. Then a few adults can watch all of them. If you stop there, what you're describing is literally a prison, albeit a part-time one. The problem is, many schools practically do stop there. The stated purpose of schools is to educate the kids. But there is no external pressure to do this well. And so most schools do such a bad job of teaching that the kids don't really take it seriously-- not even the smart kids. Much of the time we were all, students and teachers both, just going through the motions. In my high school French class we were supposed to read Hugo's _Les Miserables._ I don't think any of us knew French well enough to make our way through this enormous book. Like the rest of the class, I just skimmed the Cliff's Notes. When we were given a test on the book, I noticed that the questions sounded odd. They were full of long words that our teacher wouldn't have used. Where had these questions come from? From the Cliff's Notes, it turned out. The teacher was using them too. We were all just pretending. There are certainly great public school teachers. The energy and imagination of my fourth grade teacher, Mr. Mihalko, made that year something his students still talk about, thirty years later. But teachers like him were individuals swimming upstream. They couldn't fix the system.
霸凌只是问题一面。更严重的是我们从未接触真实工作。人类天性热爱工作——在多数文明中,工作即身份。而我们所有作业要么毫无意义,要么在当时看来如此。
最好情况下,作业是为遥远未来所做的练习,远到我们不知目的何在。更常见的是为考试设计的无意义流程(内战三大起因是...测验:列举内战三大起因)。
且无法退出。成人共识认定这是通往大学的唯一道路。逃离这空虚生活的唯一方式,就是屈服于它。
历史上青少年曾承担更积极的社会角色。前工业时代,他们或是店铺学徒,或是农场帮手,甚至战舰水手。他们不被放任自建社会,而是成人社会的初级成员。
当时青少年更尊重成人,因成人是他们学习技能的可见专家。如今多数孩子对父母办公室里的工作毫无概念,也看不到学业与未来工作的联系(事实上确实几乎没有)。
In almost any group of people you'll find hierarchy. When groups of adults form in the real world, it's generally for some common purpose, and the leaders end up being those who are best at it. The problem with most schools is, they have no purpose. But hierarchy there must be. And so the kids make one out of nothing. We have a phrase to describe what happens when rankings have to be created without any meaningful criteria. We say that the situation _degenerates into a popularity contest._ And that's exactly what happens in most American schools. Instead of depending on some real test, one's rank depends mostly on one's ability to increase one's rank. It's like the court of Louis XIV. There is no external opponent, so the kids become one another's opponents. When there is some real external test of skill, it isn't painful to be at the bottom of the hierarchy. A rookie on a football team doesn't resent the skill of the veteran; he hopes to be like him one day and is happy to have the chance to learn from him. The veteran may in turn feel a sense of _noblesse oblige_. And most importantly, their status depends on how well they do against opponents, not on whether they can push the other down. Court hierarchies are another thing entirely. This type of society debases anyone who enters it. There is neither admiration at the bottom, nor _noblesse oblige_ at the top. It's kill or be killed. This is the sort of society that gets created in American secondary schools. And it happens because these schools have no real purpose beyond keeping the kids all in one place for a certain number of hours each day. What I didn't realize at the time, and in fact didn't realize till very recently, is that the twin horrors of school life, the cruelty and the boredom, both have the same cause. The mediocrity of American public schools has worse consequences than just making kids unhappy for six years.
相应地,成人也更需要青少年。经过几年训练,学徒能成为真正帮手。即便新手也能跑腿传信或打扫工坊。
如今成人对青少年毫无即时需求。办公室里他们只会碍事。于是成人上班时顺道把孩子"寄存"在学校,如同周末出游时寄养宠物犬。
何以至此?我们触及难题核心。此问题与当代诸多弊病同源:专业化。随着职业日益专业化,培训期不断延长。前工业时代孩子最迟14岁开始工作(农场孩子更早),如今大学生22岁才全职工作。某些专业如医学博士,培训可能持续到30岁。
当代青少年除快餐业等剥削廉价劳动力的行业外毫无用处。多数工作中他们都是净损失。但他们又未成年,需要监管。最有效方式就是集中管理——几个成人即可看管所有孩子。
至此描述已与监狱无异,区别只是非全日制。问题在于,许多学校确实止步于此。虽然宣称目的是教育,但因缺乏外部压力,多数学校敷衍了事,连聪明孩子都不当真。大部分时间师生都在走过场。
It breeds a rebelliousness that actively drives kids away from the things they're supposed to be learning. Like many nerds, probably, it was years after high school before I could bring myself to read anything we'd been assigned then. And I lost more than books. I mistrusted words like "character" and "integrity" because they had been so debased by adults. As they were used then, these words all seemed to mean the same thing: obedience. The kids who got praised for these qualities tended to be at best dull-witted prize bulls, and at worst facile schmoozers. If that was what character and integrity were, I wanted no part of them. The word I most misunderstood was "tact." As used by adults, it seemed to mean keeping your mouth shut. I assumed it was derived from the same root as "tacit" and "taciturn," and that it literally meant being quiet. I vowed that I would never be tactful; they were never going to shut me up. In fact, it's derived from the same root as "tactile," and what it means is to have a deft touch. Tactful is the opposite of clumsy. I don't think I learned this until college. Nerds aren't the only losers in the popularity rat race. Nerds are unpopular because they're distracted. There are other kids who deliberately opt out because they're so disgusted with the whole process. Teenage kids, even rebels, don't like to be alone, so when kids opt out of the system, they tend to do it as a group. At the schools I went to, the focus of rebellion was drug use, specifically marijuana. The kids in this tribe wore black concert t-shirts and were called "freaks." Freaks and nerds were allies, and there was a good deal of overlap between them. Freaks were on the whole smarter than other kids, though never studying (or at least never appearing to) was an important tribal value. I was more in the nerd camp, but I was friends with a lot of freaks. They used drugs, at least at first, for the social bonds they created.
高中法语课上,我们被要求阅读雨果的《悲惨世界》。其实无人具备通读这本巨著的法语水平。我和同学一样只读导读手册。测验时我发现考题措辞古怪——充满老师绝不会用的长难词。原来考题也来自导读手册。师生都在演戏。
当然存在优秀的公立教师。我的四年级老师米哈尔科先生以其热情与创意,打造了让学生三十年后仍津津乐道的学年。但这类教师是逆流而上的个体,无力改变系统。
任何群体都会形成等级。成人世界的群体通常存在共同目标,领导者往往是能力最强者。多数学校的问题在于缺乏真实目标,但等级制度必然存在,于是孩子们凭空造出。
我们用"退化为选美比赛"形容缺乏实质标准的排名。这正是多数美国学校的现状——个人地位不取决于真实能力,而取决于提升地位的能力。如同路易十四的宫廷,因无外部对手,孩子们互为敌手。
当存在真实技能检验时,底层并不痛苦。橄榄球队新人不嫉妒老将,反而渴望有朝一日像对方那样,并珍惜学习机会。老将则可能秉持贵族义务精神。关键在于,他们的地位取决于对外表现,而非对内打压。
It was something to do together, and because the drugs were illegal, it was a shared badge of rebellion. I'm not claiming that bad schools are the whole reason kids get into trouble with drugs. After a while, drugs have their own momentum. No doubt some of the freaks ultimately used drugs to escape from other problems-- trouble at home, for example. But, in my school at least, the reason most kids _started_ using drugs was rebellion. Fourteen-year-olds didn't start smoking pot because they'd heard it would help them forget their problems. They started because they wanted to join a different tribe. Misrule breeds rebellion; this is not a new idea. And yet the authorities still for the most part act as if drugs were themselves the cause of the problem. The real problem is the emptiness of school life. We won't see solutions till adults realize that. The adults who may realize it first are the ones who were themselves nerds in school. Do you want your kids to be as unhappy in eighth grade as you were? I wouldn't. Well, then, is there anything we can do to fix things? Almost certainly. There is nothing inevitable about the current system. It has come about mostly by default. Adults, though, are busy. Showing up for school plays is one thing. Taking on the educational bureaucracy is another. Perhaps a few will have the energy to try to change things. I suspect the hardest part is realizing that you can. Nerds still in school should not hold their breath. Maybe one day a heavily armed force of adults will show up in helicopters to rescue you, but they probably won't be coming this month. Any immediate improvement in nerds' lives is probably going to have to come from the nerds themselves. Merely understanding the situation they're in should make it less painful. Nerds aren't losers. They're just playing a different game, and a game much closer to the one played in the real world. Adults know this.
宫廷等级则截然不同。这类社会腐蚀所有参与者——底层无崇拜,顶层无担当,唯有你死我活。
这正是美国中学创造的社会形态。根源在于这些学校除每日关押孩子数小时外毫无真实目标。我当年未能意识到(直至最近才领悟),校园生活的双重恐怖——残酷与无聊——实为同源之恶。
美国公立学校的平庸不仅让孩子痛苦六年,更催生叛逆心理,将他们推离本应学习的事物。
和许多书呆子一样,我高中毕业多年后才能重读当年指定书目。损失远不止此——我一度怀疑"品格""正直"等词,因它们被成人滥用至变质。当时这些词似乎同义:服从。被赞扬这些特质的孩子,往好说是温顺蠢牛,往坏说是油滑马屁精。若这就是品格与正直,我宁可不要。
我误解最深的是"得体"(tact)。成人使用时似乎意指闭嘴。我误以为它与"缄默"同源,发誓永不得体——休想让我沉默。实则它源于"触觉",意为手法娴熟。直到大学我才明白这点。
It's hard to find successful adults now who don't claim to have been nerds in high school. It's important for nerds to realize, too, that school is not life. School is a strange, artificial thing, half sterile and half feral. It's all-encompassing, like life, but it isn't the real thing. It's only temporary, and if you look, you can see beyond it even while you're still in it. If life seems awful to kids, it's neither because hormones are turning you all into monsters (as your parents believe), nor because life actually is awful (as you believe). It's because the adults, who no longer have any economic use for you, have abandoned you to spend years cooped up together with nothing real to do. _Any_ society of that type is awful to live in. You don't have to look any further to explain why teenage kids are unhappy. I've said some harsh things in this essay, but really the thesis is an optimistic one-- that several problems we take for granted are in fact not insoluble after all. Teenage kids are not inherently unhappy monsters. That should be encouraging news to kids and adults both. Thanks to Sarah Harlin, Trevor Blackwell, Robert Morris, Eric Raymond, and Jackie Weicker for reading drafts of this essay, and Maria Daniels for scanning photos.
| Re: Why Nerds are Unpopular | | | Gateway High School, 1981 | Japanese Translation | | | French Translation | My War With Brian | | | Buttons | Portuguese Translation | | | Spanish Translation.
人气竞赛的输家不限于书呆子。书呆子因分心落败,另有些孩子则因彻底厌恶而退出。
青少年即便叛逆也害怕孤独,因此退出者往往成群结队。我校的反叛焦点是吸毒(尤其大麻),这个部落成员穿着黑色演唱会T恤,被称为"怪胎"。
怪胎与书呆子是同盟军,两者多有重叠。怪胎总体更聪明,但"永不学习(或至少不显露)"是重要部落准则。我虽属书呆子阵营,但有许多怪胎朋友。
他们吸毒最初是为建立社交纽带。这是项共同活动,而毒品非法性又成为叛逆勋章。
我并非宣称糟糕学校是吸毒的唯一原因。
January 2003 _(This article was given as a talk at the 2003 Spam Conference. It describes the work I've done to improve the performance of the algorithm described inA Plan for Spam, and what I plan to do in the future.)_ The first discovery I'd like to present here is an algorithm for lazy evaluation of research papers. Just write whatever you want and don't cite any previous work, and indignant readers will send you references to all the papers you should have cited. I discovered this algorithm after ``A Plan for Spam'' [1] was on Slashdot. Spam filtering is a subset of text classification, which is a well established field, but the first papers about Bayesian spam filtering per se seem to have been two given at the same conference in 1998, one by Pantel and Lin [2], and another by a group from Microsoft Research [3]. When I heard about this work I was a bit surprised. If people had been onto Bayesian filtering four years ago, why wasn't everyone using it? When I read the papers I found out why. Pantel and Lin's filter was the more effective of the two, but it only caught 92% of spam, with 1.16% false positives. When I tried writing a Bayesian spam filter, it caught 99.5% of spam with less than .03% false positives [4]. It's always alarming when two people trying the same experiment get widely divergent results. It's especially alarming here because those two sets of numbers might yield opposite conclusions. Different users have different requirements, but I think for many people a filtering rate of 92% with 1.16% false positives means that filtering is not an acceptable solution, whereas 99.5% with less than .03% false positives means that it is. So why did we get such different numbers? I haven't tried to reproduce Pantel and Lin's results, but from reading the paper I see five things that probably account for the difference.
(本文是我在2003年反垃圾邮件大会上的演讲内容,描述了我对《反垃圾邮件计划》所述算法的改进工作及未来规划。)
One is simply that they trained their filter on very little data: 160 spam and 466 nonspam mails. Filter performance should still be climbing with data sets that small. So their numbers may not even be an accurate measure of the performance of their algorithm, let alone of Bayesian spam filtering in general.
But I think the most important difference is probably that they ignored message headers. To anyone who has worked on spam filters, this will seem a perverse decision. And yet in the very first filters I tried writing, I ignored the headers too. Why? Because I wanted to keep the problem neat. I didn't know much about mail headers then, and they seemed to me full of random stuff. There is a lesson here for filter writers: don't ignore data. You'd think this lesson would be too obvious to mention, but I've had to learn it several times.
Third, Pantel and Lin stemmed the tokens, meaning they reduced e.g. both `mailing'' and mailed'' to the root `mail''. They may have felt they were forced to do this by the small size of their corpus, but if so this is a kind of premature optimization.
Fourth, they calculated probabilities differently. They used all the tokens, whereas I only use the 15 most significant. If you use all the tokens you'll tend to miss longer spams, the type where someone tells you their life story up to the point where they got rich from some multilevel marketing scheme. And such an algorithm would be easy for spammers to spoof: just add a big chunk of random text to counterbalance the spam terms.
Finally, they didn't bias against false positives. I think any spam filtering algorithm ought to have a convenient knob you can twist to decrease the false positive rate at the expense of the filtering rate. I do this by counting the occurrences of tokens in the nonspam corpus double.
I don't think it's a good idea to treat spam filtering as a straight text classification problem.
我要分享的第一个发现是研究论文的惰性评估算法:只需写出你想写的内容且不引用任何前人工作,愤怒的读者自会发来你本该引用的所有文献。这个算法是我在《反垃圾邮件计划》[1]被Slashdot转载后悟出的。
垃圾邮件过滤属于文本分类的子领域,这个学科已相当成熟。但最早的贝叶斯垃圾邮件过滤论文似乎都出现在1998年的同场会议上:一篇来自Pantel和Lin[2],另一篇来自微软研究院团队[3]。
You can use text classification techniques, but solutions can and should reflect the fact that the text is email, and spam in particular. Email is not just text; it has structure. Spam filtering is not just classification, because false positives are so much worse than false negatives that you should treat them as a different kind of error. And the source of error is not just random variation, but a live human spammer working actively to defeat your filter. Tokens Another project I heard about after the Slashdot article was Bill Yerazunis' CRM114 [5]. This is the counterexample to the design principle I just mentioned. It's a straight text classifier, but such a stunningly effective one that it manages to filter spam almost perfectly without even knowing that's what it's doing. Once I understood how CRM114 worked, it seemed inevitable that I would eventually have to move from filtering based on single words to an approach like this. But first, I thought, I'll see how far I can get with single words. And the answer is, surprisingly far. Mostly I've been working on smarter tokenization. On current spam, I've been able to achieve filtering rates that approach CRM114's. These techniques are mostly orthogonal to Bill's; an optimal solution might incorporate both. ``A Plan for Spam'' uses a very simple definition of a token. Letters, digits, dashes, apostrophes, and dollar signs are constituent characters, and everything else is a token separator. I also ignored case. Now I have a more complicated definition of a token: 1. Case is preserved..
得知这些研究时我有些惊讶。既然四年前就有人研究贝叶斯过滤,为何没有普及?读完论文后我找到了答案。Pantel和Lin的过滤器效果较好,但仅能拦截92%的垃圾邮件,且有1.16%的误判率。
而我编写的贝叶斯过滤器实现了99.5%的垃圾邮件拦截率和低于0.03%的误判率[4]。当相同实验得出迥异结果时总是令人不安,尤其这两组数据可能导致相反结论。虽然用户需求各异,但对多数人而言,92%拦截率配1.16%误判率意味着过滤方案不可行,而99.5%拦截率配0.03%误判率则完全可行。
2. Exclamation points are constituent characters.
为何结果差异如此之大?虽未复现Pantel和Lin的实验,但从论文中我发现了五个可能原因:
首先,他们的训练数据量过少——仅160封垃圾邮件和466封正常邮件。这种数据规模下过滤性能应仍在上升期,因此其数据甚至不足以准确衡量其算法表现,更不用说整体贝叶斯过滤效果。
3. Periods and commas are constituents if they occur between two digits. This lets me get ip addresses and prices intact.
但最关键的区别可能是他们忽略了邮件头。这对反垃圾邮件开发者来说是个反常决定。有趣的是,我最初编写的过滤器也忽略了邮件头——因为当时对邮件头知之甚少,觉得它们充满杂乱信息。这给过滤器开发者上了重要一课:不要忽视任何数据。这个教训看似显而易见,我却多次重蹈覆辙。
第三,Pantel和Lin对词汇进行了词干提取(如将"mailing"和"mailed"都归为"mail")。这可能是受限于小规模语料库的妥协,但实属过早优化。
4. A price range like $20-25 yields two tokens, $20 and $25.
第四,他们采用不同的概率计算方式:使用全部词汇特征,而我仅选取15个最显著特征。使用全部特征会导致漏判长篇垃圾邮件(比如那些先讲述人生故事再推销传销项目的邮件)。这种算法也容易被攻击:只需添加大段随机文本就能稀释垃圾词汇特征。
最后,他们没有针对误判进行优化。我认为所有垃圾邮件过滤算法都应提供调节旋钮,允许用户通过降低过滤率来减少误判。我的解决方案是对正常邮件中的词汇特征进行双倍计数。
5. Tokens that occur within the To, From, Subject, and Return-Path lines, or within urls, get marked accordingly. E.g. `foo'' in the Subject line becomes `Subject*foo''. (The asterisk could be any character you don't allow as a constituent.)
将垃圾邮件过滤简单视作文本分类问题并不明智。虽然可以运用文本分类技术,但解决方案必须体现电子邮件的特殊性——尤其是垃圾邮件。邮件不仅是文本,还具有结构特征;过滤不仅是分类,更因误判代价远高于漏判而需区别对待;错误来源不仅是随机偏差,还包括刻意对抗过滤器的垃圾邮件发送者。
Slashdot事件后,我还了解到Bill Yerazunis的[CRM114][5]项目。它完美反驳了我刚提出的设计原则——这个纯粹的文本分类器甚至不知道自己用于反垃圾邮件,却实现了近乎完美的过滤效果。
Such measures increase the filter's vocabulary, which makes it more discriminating. For example, in the current filter, ``free'' in the Subject line has a spam probability of 98%, whereas the same token in the body has a spam probability of only 65%. Here are some of the current probabilities [6]:
理解CRM114原理后,我意识到从单词级过滤转向此类方法是大势所趋。但我想先探索单词级过滤的极限——结果证明其潜力远超预期。
Subject*FREE 0.9999 free!! 0.9999 To*free 0.9998 Subject*free 0.9782 free! 0.9199 Free 0.9198 Url*free 0.9091 FREE 0.8747 From*free 0.7636 free 0.6546
我的主要突破在于更智能的词汇切分技术。针对当前垃圾邮件,我的过滤效果已接近CRM114。这些技术与Bill的方案大多互补,最佳解决方案或许需要二者结合。
《反垃圾邮件计划》采用极简的词汇定义:字母、数字、连字符、撇号和美元符号视为组成字符,其余皆作分隔符,且忽略大小写。
In the Plan for Spam filter, all these tokens would have had the same probability, .7602. That filter recognized about 23,000 tokens. The current one recognizes about 187,000.
The disadvantage of having a larger universe of tokens is that there is more chance of misses. Spreading your corpus out over more tokens has the same effect as making it smaller. If you consider exclamation points as constituents, for example, then you could end up not having a spam probability for free with seven exclamation points, even though you know that free with just two exclamation points has a probability of 99.99%.
One solution to this is what I call degeneration. If you can't find an exact match for a token, treat it as if it were a less specific version. I consider terminal exclamation points, uppercase letters, and occurring in one of the five marked contexts as making a token more specific. For example, if I don't find a probability for `Subjectfree!'', I look for probabilities for Subjectfree'', free!'', and free'', and take whichever one is farthest from .5.
Here are the alternatives [7] considered if the filter sees `FREE!!!'' in the Subject line and doesn't have a probability for it.
现在我的词汇定义更为复杂: 1. 保留大小写
2. 感叹号是构成性字符。
Subject*Free!!! Subject*free!!! Subject*FREE! Subject*Free! Subject*free! Subject*FREE Subject*Free Subject*free FREE!!! Free!!! free!!! FREE! Free! free! FREE Free free
3. 当句号和逗号出现在两个数字之间时,它们被视为构成性字符。这使得IP地址和价格能保持完整。
4. 类似$20-25的价格区间会生成两个标记:$20和$25。
If you do this, be sure to consider versions with initial caps as well as all uppercase and all lowercase. Spams tend to have more sentences in imperative mood, and in those the first word is a verb. So verbs with initial caps have higher spam probabilities than they would in all lowercase. In my filter, the spam probability of `Act'' is 98% and for act'' only 62%.
If you increase your filter's vocabulary, you can end up counting the same word multiple times, according to your old definition of same''. Logically, they're not the same token anymore. But if this still bothers you, let me add from experience that the words you seem to be counting multiple times tend to be exactly the ones you'd want to.
Another effect of a larger vocabulary is that when you look at an incoming mail you find more interesting tokens, meaning those with probabilities far from .5. I use the 15 most interesting to decide if mail is spam. But you can run into a problem when you use a fixed number like this. If you find a lot of maximally interesting tokens, the result can end up being decided by whatever random factor determines the ordering of equally interesting tokens. One way to deal with this is to treat some as more interesting than others.
For example, the token dalco'' occurs 3 times in my spam corpus and never in my legitimate corpus. The token Url*optmails'' (meaning `optmails'' within a url) occurs 1223 times. And yet, as I used to calculate probabilities for tokens, both would have the same spam probability, the threshold of .99.
That doesn't feel right. There are theoretical arguments for giving these two tokens substantially different probabilities (Pantel and Lin do), but I haven't tried that yet. It does seem at least that if we find more than 15 tokens that only occur in one corpus or the other, we ought to give priority to the ones that occur a lot. So now there are two threshold values.
5. 出现在“收件人”、“发件人”、“主题”和“返回路径”行或网址内的标记会进行相应标注。例如,主题行中的“foo”会变成“Subject*foo”(星号可以是任何不被允许作为构成性字符的符号)。
这些措施增加了过滤器的词汇量,使其更具辨别力。例如,在当前过滤器中,主题行中的“free”标记的垃圾邮件概率为98%,而正文中相同标记的垃圾邮件概率仅为65%。
For tokens that occur only in the spam corpus, the probability is .9999 if they occur more than 10 times and .9998 otherwise. Ditto at the other end of the scale for tokens found only in the legitimate corpus. I may later scale token probabilities substantially, but this tiny amount of scaling at least ensures that tokens get sorted the right way. Another possibility would be to consider not just 15 tokens, but all the tokens over a certain threshold of interestingness. Steven Hauser does this in his statistical spam filter [8]. If you use a threshold, make it very high, or spammers could spoof you by packing messages with more innocent words. Finally, what should one do about html? I've tried the whole spectrum of options, from ignoring it to parsing it all. Ignoring html is a bad idea, because it's full of useful spam signs. But if you parse it all, your filter might degenerate into a mere html recognizer. The most effective approach seems to be the middle course, to notice some tokens but not others. I look at a, img, and font tags, and ignore the rest. Links and images you should certainly look at, because they contain urls. I could probably be smarter about dealing with html, but I don't think it's worth putting a lot of time into this. Spams full of html are easy to filter. The smarter spammers already avoid it. So performance in the future should not depend much on how you deal with html. Performance Between December 10 2002 and January 10 2003 I got about 1750 spams. Of these, 4 got through. That's a filtering rate of about 99.75%. Two of the four spams I missed got through because they happened to use words that occur often in my legitimate email. The third was one of those that exploit an insecure cgi script to send mail to third parties. They're hard to filter based just on the content because the headers are innocent and they're careful about the words they use. Even so I can usually catch them.
以下是当前部分概率值[6]:
Subject*FREE 0.9999 free!! 0.9999 To*free 0.9998 Subject*free 0.9782 free! 0.9199 Free 0.9198 Url*free 0.9091 FREE 0.8747 From*free 0.7636 free 0.6546
This one squeaked by with a probability of .88, just under the threshold of .9.
Of course, looking at multiple token sequences would catch it easily. `Below is the result of your feedback form'' is an instant giveaway.
The fourth spam was what I call a spam-of-the-future, because this is what I expect spam to evolve into: some completely neutral text followed by a url. In this case it was was from someone saying they had finally finished their homepage and would I go look at it. (The page was of course an ad for a porn site.)
If the spammers are careful about the headers and use a fresh url, there is nothing in spam-of-the-future for filters to notice. We can of course counter by sending a crawler to look at the page. But that might not be necessary. The response rate for spam-of-the-future must be low, or everyone would be doing it. If it's low enough, it won't pay for spammers to send it, and we won't have to work too hard on filtering it.
Now for the really shocking news: during that same one-month period I got _three_ false positives.
In a way it's a relief to get some false positives. When I wrote `A Plan for Spam'' I hadn't had any, and I didn't know what they'd be like. Now that I've had a few, I'm relieved to find they're not as bad as I feared. False positives yielded by statistical filters turn out to be mails that sound a lot like spam, and these tend to be the ones you would least mind missing [9].
Two of the false positives were newsletters from companies I've bought things from. I never asked to receive them, so arguably they were spams, but I count them as false positives because I hadn't been deleting them as spams before. The reason the filters caught them was that both companies in January switched to commercial email senders instead of sending the mails from their own servers, and both the headers and the bodies became much spammier.
The third false positive was a bad one, though.
在“Plan for Spam”过滤器中,所有这些标记的概率都相同,为0.7602。该过滤器能识别约23,000个标记,而当前版本能识别约187,000个。
扩大标记范围的缺点是可能增加遗漏风险。将语料分散到更多标记上会产生与缩小语料相同的效果。例如,如果将感叹号视为构成性字符,最终可能无法获取带有七个感叹号的“free”的垃圾邮件概率,尽管已知仅带两个感叹号的“free”概率为99.99%。
It was from someone in Egypt and written in all uppercase. This was a direct result of making tokens case sensitive; the Plan for Spam filter wouldn't have caught it. It's hard to say what the overall false positive rate is, because we're up in the noise, statistically. Anyone who has worked on filters (at least, effective filters) will be aware of this problem. With some emails it's hard to say whether they're spam or not, and these are the ones you end up looking at when you get filters really tight. For example, so far the filter has caught two emails that were sent to my address because of a typo, and one sent to me in the belief that I was someone else. Arguably, these are neither my spam nor my nonspam mail. Another false positive was from a vice president at Virtumundo. I wrote to them pretending to be a customer, and since the reply came back through Virtumundo's mail servers it had the most incriminating headers imaginable. Arguably this isn't a real false positive either, but a sort of Heisenberg uncertainty effect: I only got it because I was writing about spam filtering. Not counting these, I've had a total of five false positives so far, out of about 7740 legitimate emails, a rate of .06%. The other two were a notice that something I bought was back-ordered, and a party reminder from Evite. I don't think this number can be trusted, partly because the sample is so small, and partly because I think I can fix the filter not to catch some of these. False positives seem to me a different kind of error from false negatives. Filtering rate is a measure of performance. False positives I consider more like bugs. I approach improving the filtering rate as optimization, and decreasing false positives as debugging. So these five false positives are my bug list. For example, the mail from Egypt got nailed because the uppercase text made it look to the filter like a Nigerian spam. This really is kind of a bug.
对此的解决方案是我所称的“退化处理”。如果找不到标记的精确匹配,则将其视为不太具体的版本。我认为结尾的感叹号、大写字母以及出现在五个特定上下文之一中的标记会使标记更具体。例如,如果找不到“Subjectfree!”的概率,就查找“Subjectfree”、“free!”和“free”的概率,并取最偏离0.5的值。
As with html, the email being all uppercase is really conceptually _one_ feature, not one for each word. I need to handle case in a more sophisticated way. So what to make of this .06%? Not much, I think. You could treat it as an upper bound, bearing in mind the small sample size. But at this stage it is more a measure of the bugs in my implementation than some intrinsic false positive rate of Bayesian filtering. Future What next? Filtering is an optimization problem, and the key to optimization is profiling. Don't try to guess where your code is slow, because you'll guess wrong. _Look_ at where your code is slow, and fix that. In filtering, this translates to: look at the spams you miss, and figure out what you could have done to catch them. For example, spammers are now working aggressively to evade filters, and one of the things they're doing is breaking up and misspelling words to prevent filters from recognizing them. But working on this is not my first priority, because I still have no trouble catching these spams [10]. There are two kinds of spams I currently do have trouble with. One is the type that pretends to be an email from a woman inviting you to go chat with her or see her profile on a dating site. These get through because they're the one type of sales pitch you can make without using sales talk. They use the same vocabulary as ordinary email. The other kind of spams I have trouble filtering are those from companies in e.g. Bulgaria offering contract programming services. These get through because I'm a programmer too, and the spams are full of the same words as my real mail. I'll probably focus on the personal ad type first. I think if I look closer I'll be able to find statistical differences between these and my real mail. The style of writing is certainly different, though it may take multiword filtering to catch that.
以下是过滤器在主题行中看到“FREE!!!”但未找到其概率时会考虑的备选方案[7]:
Subject*Free!!! Subject*free!!! Subject*FREE! Subject*Free! Subject*free! Subject*FREE Subject*Free Subject*free FREE!!! Free!!! free!!! FREE! Free! free! FREE Free free
Also, I notice they tend to repeat the url, and someone including a url in a legitimate mail wouldn't do that [11]. The outsourcing type are going to be hard to catch. Even if you sent a crawler to the site, you wouldn't find a smoking statistical gun. Maybe the only answer is a central list of domains advertised in spams [12]. But there can't be that many of this type of mail. If the only spams left were unsolicited offers of contract programming services from Bulgaria, we could all probably move on to working on something else. Will statistical filtering actually get us to that point? I don't know. Right now, for me personally, spam is not a problem. But spammers haven't yet made a serious effort to spoof statistical filters. What will happen when they do? I'm not optimistic about filters that work at the network level [13]. When there is a static obstacle worth getting past, spammers are pretty efficient at getting past it. There is already a company called Assurance Systems that will run your mail through Spamassassin and tell you whether it will get filtered out. Network-level filters won't be completely useless. They may be enough to kill all the "opt-in" spam, meaning spam from companies like Virtumundo and Equalamail who claim that they're really running opt-in lists. You can filter those based just on the headers, no matter what they say in the body. But anyone willing to falsify headers or use open relays, presumably including most porn spammers, should be able to get some message past network-level filters if they want to. (By no means the message they'd like to send though, which is something.) The kind of filters I'm optimistic about are ones that calculate probabilities based on each individual user's mail. These can be much more effective, not only in avoiding false positives, but in filtering too: for example, finding the recipient's email address base-64 encoded anywhere in a message is a very good spam indicator.
If you do this, be sure to consider versions with initial caps as well as all uppercase and all lowercase. Spams tend to have more sentences in imperative mood, and in those the first word is a verb. So verbs with initial caps have higher spam probabilities than they would in all lowercase. In my filter, the spam probability of `Act'' is 98% and for act'' only 62%.
If you increase your filter's vocabulary, you can end up counting the same word multiple times, according to your old definition of same''. Logically, they're not the same token anymore. But if this still bothers you, let me add from experience that the words you seem to be counting multiple times tend to be exactly the ones you'd want to.
Another effect of a larger vocabulary is that when you look at an incoming mail you find more interesting tokens, meaning those with probabilities far from .5. I use the 15 most interesting to decide if mail is spam. But you can run into a problem when you use a fixed number like this. If you find a lot of maximally interesting tokens, the result can end up being decided by whatever random factor determines the ordering of equally interesting tokens. One way to deal with this is to treat some as more interesting than others.
For example, the token dalco'' occurs 3 times in my spam corpus and never in my legitimate corpus. The token Url*optmails'' (meaning `optmails'' within a url) occurs 1223 times. And yet, as I used to calculate probabilities for tokens, both would have the same spam probability, the threshold of .99.
That doesn't feel right. There are theoretical arguments for giving these two tokens substantially different probabilities (Pantel and Lin do), but I haven't tried that yet. It does seem at least that if we find more than 15 tokens that only occur in one corpus or the other, we ought to give priority to the ones that occur a lot. So now there are two threshold values.
For tokens that occur only in the spam corpus, the probability is .9999 if they occur more than 10 times and .9998 otherwise. Ditto at the other end of the scale for tokens found only in the legitimate corpus. I may later scale token probabilities substantially, but this tiny amount of scaling at least ensures that tokens get sorted the right way. Another possibility would be to consider not just 15 tokens, but all the tokens over a certain threshold of interestingness. Steven Hauser does this in his statistical spam filter [8]. If you use a threshold, make it very high, or spammers could spoof you by packing messages with more innocent words. Finally, what should one do about html? I've tried the whole spectrum of options, from ignoring it to parsing it all. Ignoring html is a bad idea, because it's full of useful spam signs. But if you parse it all, your filter might degenerate into a mere html recognizer. The most effective approach seems to be the middle course, to notice some tokens but not others. I look at a, img, and font tags, and ignore the rest. Links and images you should certainly look at, because they contain urls. I could probably be smarter about dealing with html, but I don't think it's worth putting a lot of time into this. Spams full of html are easy to filter. The smarter spammers already avoid it. So performance in the future should not depend much on how you deal with html. Performance Between December 10 2002 and January 10 2003 I got about 1750 spams. Of these, 4 got through. That's a filtering rate of about 99.75%. Two of the four spams I missed got through because they happened to use words that occur often in my legitimate email. The third was one of those that exploit an insecure cgi script to send mail to third parties. They're hard to filter based just on the content because the headers are innocent and they're careful about the words they use. Even so I can usually catch them.
But the real advantage of individual filters is that they'll all be different. If everyone's filters have different probabilities, it will make the spammers' optimization loop, what programmers would call their edit-compile-test cycle, appallingly slow. Instead of just tweaking a spam till it gets through a copy of some filter they have on their desktop, they'll have to do a test mailing for each tweak. It would be like programming in a language without an interactive toplevel, and I wouldn't wish that on anyone.
Notes
[1] Paul Graham. `A Plan for Spam.'' August 2002. http://paulgraham.com/spam.html.
Probabilities in this algorithm are calculated using a degenerate case of Bayes' Rule. There are two simplifying assumptions: that the probabilities of features (i.e. words) are independent, and that we know nothing about the prior probability of an email being spam.
The first assumption is widespread in text classification. Algorithms that use it are called `naive Bayesian.''
The second assumption I made because the proportion of spam in my incoming mail fluctuated so much from day to day (indeed, from hour to hour) that the overall prior ratio seemed worthless as a predictor. If you assume that P(spam) and P(nonspam) are both .5, they cancel out and you can remove them from the formula.
If you were doing Bayesian filtering in a situation where the ratio of spam to nonspam was consistently very high or (especially) very low, you could probably improve filter performance by incorporating prior probabilities.
This one squeaked by with a probability of .88, just under the threshold of .9.
Of course, looking at multiple token sequences would catch it easily. `Below is the result of your feedback form'' is an instant giveaway.
The fourth spam was what I call a spam-of-the-future, because this is what I expect spam to evolve into: some completely neutral text followed by a url. In this case it was was from someone saying they had finally finished their homepage and would I go look at it. (The page was of course an ad for a porn site.)
If the spammers are careful about the headers and use a fresh url, there is nothing in spam-of-the-future for filters to notice. We can of course counter by sending a crawler to look at the page. But that might not be necessary. The response rate for spam-of-the-future must be low, or everyone would be doing it. If it's low enough, it won't pay for spammers to send it, and we won't have to work too hard on filtering it.
Now for the really shocking news: during that same one-month period I got _three_ false positives.
In a way it's a relief to get some false positives. When I wrote `A Plan for Spam'' I hadn't had any, and I didn't know what they'd be like. Now that I've had a few, I'm relieved to find they're not as bad as I feared. False positives yielded by statistical filters turn out to be mails that sound a lot like spam, and these tend to be the ones you would least mind missing [9].
Two of the false positives were newsletters from companies I've bought things from. I never asked to receive them, so arguably they were spams, but I count them as false positives because I hadn't been deleting them as spams before. The reason the filters caught them was that both companies in January switched to commercial email senders instead of sending the mails from their own servers, and both the headers and the bodies became much spammier.
The third false positive was a bad one, though.
It was from someone in Egypt and written in all uppercase. This was a direct result of making tokens case sensitive; the Plan for Spam filter wouldn't have caught it. It's hard to say what the overall false positive rate is, because we're up in the noise, statistically. Anyone who has worked on filters (at least, effective filters) will be aware of this problem. With some emails it's hard to say whether they're spam or not, and these are the ones you end up looking at when you get filters really tight. For example, so far the filter has caught two emails that were sent to my address because of a typo, and one sent to me in the belief that I was someone else. Arguably, these are neither my spam nor my nonspam mail. Another false positive was from a vice president at Virtumundo. I wrote to them pretending to be a customer, and since the reply came back through Virtumundo's mail servers it had the most incriminating headers imaginable. Arguably this isn't a real false positive either, but a sort of Heisenberg uncertainty effect: I only got it because I was writing about spam filtering. Not counting these, I've had a total of five false positives so far, out of about 7740 legitimate emails, a rate of .06%. The other two were a notice that something I bought was back-ordered, and a party reminder from Evite. I don't think this number can be trusted, partly because the sample is so small, and partly because I think I can fix the filter not to catch some of these. False positives seem to me a different kind of error from false negatives. Filtering rate is a measure of performance. False positives I consider more like bugs. I approach improving the filtering rate as optimization, and decreasing false positives as debugging. So these five false positives are my bug list. For example, the mail from Egypt got nailed because the uppercase text made it look to the filter like a Nigerian spam. This really is kind of a bug.
To do this right you'd have to track ratios by time of day, because spam and legitimate mail volume both have distinct daily patterns.
[2] Patrick Pantel and Dekang Lin. `SpamCop-- A Spam Classification & Organization Program.'' Proceedings of AAAI-98 Workshop on Learning for Text Categorization.
[3] Mehran Sahami, Susan Dumais, David Heckerman and Eric Horvitz. A Bayesian Approach to Filtering Junk E-Mail.'' Proceedings of AAAI-98 Workshop on Learning for Text Categorization.
[4] At the time I had zero false positives out of about 4,000 legitimate emails. If the next legitimate email was a false positive, this would give us .03%. These false positive rates are untrustworthy, as I explain later. I quote a number here only to emphasize that whatever the false positive rate is, it is less than 1.16%.
[5] Bill Yerazunis. Sparse Binary Polynomial Hash Message Filtering and The CRM114 Discriminator.'' Proceedings of 2003 Spam Conference.
[6] In A Plan for Spam'' I used thresholds of .99 and .01. It seems justifiable to use thresholds proportionate to the size of the corpora. Since I now have on the order of 10,000 of each type of mail, I use .9999 and .0001.
[7] There is a flaw here I should probably fix. Currently, when Subjectfoo'' degenerates to just foo'', what that means is you're getting the stats for occurrences of foo'' in the body or header lines other than those I mark. What I should do is keep track of statistics for foo'' overall as well as specific versions, and degenerate from Subjectfoo'' not to foo'' but to Anywhere*foo''. Ditto for case: I should degenerate from uppercase to any-case, not lowercase.
It would probably be a win to do this with prices too, e.g. to degenerate from $129.99'' to $--9.99'', $--.99'', and `$--''.
As with html, the email being all uppercase is really conceptually _one_ feature, not one for each word. I need to handle case in a more sophisticated way. So what to make of this .06%? Not much, I think. You could treat it as an upper bound, bearing in mind the small sample size. But at this stage it is more a measure of the bugs in my implementation than some intrinsic false positive rate of Bayesian filtering. Future What next? Filtering is an optimization problem, and the key to optimization is profiling. Don't try to guess where your code is slow, because you'll guess wrong. _Look_ at where your code is slow, and fix that. In filtering, this translates to: look at the spams you miss, and figure out what you could have done to catch them. For example, spammers are now working aggressively to evade filters, and one of the things they're doing is breaking up and misspelling words to prevent filters from recognizing them. But working on this is not my first priority, because I still have no trouble catching these spams [10]. There are two kinds of spams I currently do have trouble with. One is the type that pretends to be an email from a woman inviting you to go chat with her or see her profile on a dating site. These get through because they're the one type of sales pitch you can make without using sales talk. They use the same vocabulary as ordinary email. The other kind of spams I have trouble filtering are those from companies in e.g. Bulgaria offering contract programming services. These get through because I'm a programmer too, and the spams are full of the same words as my real mail. I'll probably focus on the personal ad type first. I think if I look closer I'll be able to find statistical differences between these and my real mail. The style of writing is certainly different, though it may take multiword filtering to catch that.
Also, I notice they tend to repeat the url, and someone including a url in a legitimate mail wouldn't do that [11]. The outsourcing type are going to be hard to catch. Even if you sent a crawler to the site, you wouldn't find a smoking statistical gun. Maybe the only answer is a central list of domains advertised in spams [12]. But there can't be that many of this type of mail. If the only spams left were unsolicited offers of contract programming services from Bulgaria, we could all probably move on to working on something else. Will statistical filtering actually get us to that point? I don't know. Right now, for me personally, spam is not a problem. But spammers haven't yet made a serious effort to spoof statistical filters. What will happen when they do? I'm not optimistic about filters that work at the network level [13]. When there is a static obstacle worth getting past, spammers are pretty efficient at getting past it. There is already a company called Assurance Systems that will run your mail through Spamassassin and tell you whether it will get filtered out. Network-level filters won't be completely useless. They may be enough to kill all the "opt-in" spam, meaning spam from companies like Virtumundo and Equalamail who claim that they're really running opt-in lists. You can filter those based just on the headers, no matter what they say in the body. But anyone willing to falsify headers or use open relays, presumably including most porn spammers, should be able to get some message past network-level filters if they want to. (By no means the message they'd like to send though, which is something.) The kind of filters I'm optimistic about are ones that calculate probabilities based on each individual user's mail. These can be much more effective, not only in avoiding false positives, but in filtering too: for example, finding the recipient's email address base-64 encoded anywhere in a message is a very good spam indicator.
You could also degenerate from words to their stems, but this would probably only improve filtering rates early on when you had small corpora.
[8] Steven Hauser. `Statistical Spam Filter Works for Me.'' http://www.sofbot.com.
[9] False positives are not all equal, and we should remember this when comparing techniques for stopping spam. Whereas many of the false positives caused by filters will be near-spams that you wouldn't mind missing, false positives caused by blacklists, for example, will be just mail from people who chose the wrong ISP. In both cases you catch mail that's near spam, but for blacklists nearness is physical, and for filters it's textual.
[10] If spammers get good enough at obscuring tokens for this to be a problem, we can respond by simply removing whitespace, periods, commas, etc. and using a dictionary to pick the words out of the resulting sequence. And of course finding words this way that weren't visible in the original text would in itself be evidence of spam.
Picking out the words won't be trivial. It will require more than just reconstructing word boundaries; spammers both add (xHot nPorn cSite'') and omit (`P#rn'') letters. Vision research may be useful here, since human vision is the limit that such tricks will approach.
[11] In general, spams are more repetitive than regular email. They want to pound that message home.
But the real advantage of individual filters is that they'll all be different. If everyone's filters have different probabilities, it will make the spammers' optimization loop, what programmers would call their edit-compile-test cycle, appallingly slow. Instead of just tweaking a spam till it gets through a copy of some filter they have on their desktop, they'll have to do a test mailing for each tweak. It would be like programming in a language without an interactive toplevel, and I wouldn't wish that on anyone.
Notes
[1] Paul Graham. `A Plan for Spam.'' August 2002. http://paulgraham.com/spam.html.
Probabilities in this algorithm are calculated using a degenerate case of Bayes' Rule. There are two simplifying assumptions: that the probabilities of features (i.e. words) are independent, and that we know nothing about the prior probability of an email being spam.
The first assumption is widespread in text classification. Algorithms that use it are called naive Bayesian.''
The second assumption I made because the proportion of spam in my incoming mail fluctuated so much from day to day (indeed, from hour to hour) that the overall prior ratio seemed worthless as a predictor. If you assume that P(spam) and P(nonspam) are both .5, they cancel out and you can remove them from the formula.
If you were doing Bayesian filtering in a situation where the ratio of spam to nonspam was consistently very high or (especially) very low, you could probably improve filter performance by incorporating prior probabilities.
To do this right you'd have to track ratios by time of day, because spam and legitimate mail volume both have distinct daily patterns.
[2] Patrick Pantel and Dekang Lin. SpamCop-- A Spam Classification & Organization Program.'' Proceedings of AAAI-98 Workshop on Learning for Text Categorization.
[3] Mehran Sahami, Susan Dumais, David Heckerman and Eric Horvitz. A Bayesian Approach to Filtering Junk E-Mail.'' Proceedings of AAAI-98 Workshop on Learning for Text Categorization.
[4] At the time I had zero false positives out of about 4,000 legitimate emails. If the next legitimate email was a false positive, this would give us .03%. These false positive rates are untrustworthy, as I explain later. I quote a number here only to emphasize that whatever the false positive rate is, it is less than 1.16%.
[5] Bill Yerazunis. Sparse Binary Polynomial Hash Message Filtering and The CRM114 Discriminator.'' Proceedings of 2003 Spam Conference.
[6] In A Plan for Spam'' I used thresholds of .99 and .01. It seems justifiable to use thresholds proportionate to the size of the corpora. Since I now have on the order of 10,000 of each type of mail, I use .9999 and .0001.
[7] There is a flaw here I should probably fix. Currently, when Subjectfoo'' degenerates to just foo'', what that means is you're getting the stats for occurrences of foo'' in the body or header lines other than those I mark. What I should do is keep track of statistics for foo'' overall as well as specific versions, and degenerate from Subjectfoo'' not to foo'' but to Anywhere*foo''. Ditto for case: I should degenerate from uppercase to any-case, not lowercase.
It would probably be a win to do this with prices too, e.g. to degenerate from $129.99'' to $--9.99'', $--.99'', and `$--''.
I currently don't allow duplicates in the top 15 tokens, because you could get a false positive if the sender happens to use some bad word multiple times. (In my current filter, ``dick'' has a spam probabilty of .9999, but it's also a name.) It seems we should at least notice duplication though, so I may try allowing up to two of each token, as Brian Burton does in SpamProbe. [12] This is what approaches like Brightmail's will degenerate into once spammers are pushed into using mad-lib techniques to generate everything else in the message. [13] It's sometimes argued that we should be working on filtering at the network level, because it is more efficient. What people usually mean when they say this is: we currently filter at the network level, and we don't want to start over from scratch. But you can't dictate the problem to fit your solution. Historically, scarce-resource arguments have been the losing side in debates about software design. People only tend to use them to justify choices (inaction in particular) made for other reasons. Thanks to Sarah Harlin, Trevor Blackwell, and Dan Giffin for reading drafts of this paper, and to Dan again for most of the infrastructure that this filter runs on. Related:
| A Plan for Spam | Plan for Spam FAQ | 2003 Spam Conference Proceedings | Japanese Translation | Chinese Translation | Test of These Suggestions.
You could also degenerate from words to their stems, but this would probably only improve filtering rates early on when you had small corpora.
[8] Steven Hauser. `Statistical Spam Filter Works for Me.'' http://www.sofbot.com.
[9] False positives are not all equal, and we should remember this when comparing techniques for stopping spam. Whereas many of the false positives caused by filters will be near-spams that you wouldn't mind missing, false positives caused by blacklists, for example, will be just mail from people who chose the wrong ISP. In both cases you catch mail that's near spam, but for blacklists nearness is physical, and for filters it's textual.
[10] If spammers get good enough at obscuring tokens for this to be a problem, we can respond by simply removing whitespace, periods, commas, etc. and using a dictionary to pick the words out of the resulting sequence. And of course finding words this way that weren't visible in the original text would in itself be evidence of spam.
Picking out the words won't be trivial. It will require more than just reconstructing word boundaries; spammers both add (xHot nPorn cSite'') and omit (P#rn'') letters. Vision research may be useful here, since human vision is the limit that such tricks will approach.
[11] In general, spams are more repetitive than regular email. They want to pound that message home.
I currently don't allow duplicates in the top 15 tokens, because you could get a false positive if the sender happens to use some bad word multiple times. (In my current filter, `dick'' has a spam probabilty of .9999, but it's also a name.) It seems we should at least notice duplication though, so I may try allowing up to two of each token, as Brian Burton does in SpamProbe. [12] This is what approaches like Brightmail's will degenerate into once spammers are pushed into using mad-lib techniques to generate everything else in the message. [13] It's sometimes argued that we should be working on filtering at the network level, because it is more efficient. What people usually mean when they say this is: we currently filter at the network level, and we don't want to start over from scratch. But you can't dictate the problem to fit your solution. Historically, scarce-resource arguments have been the losing side in debates about software design. People only tend to use them to justify choices (inaction in particular) made for other reasons. Thanks to Sarah Harlin, Trevor Blackwell, and Dan Giffin for reading drafts of this paper, and to Dan again for most of the infrastructure that this filter runs on. Related:
| A Plan for Spam | Plan for Spam FAQ | 2003 Spam Conference Proceedings | Japanese Translation | Chinese Translation | Test of These Suggestions.
January 2003 _(This article is derived from a keynote talk at the fall 2002 meeting of NEPLS.)_ Visitors to this country are often surprised to find that Americans like to begin a conversation by asking "what do you do?" I've never liked this question. I've rarely had a neat answer to it. But I think I have finally solved the problem. Now, when someone asks me what I do, I look them straight in the eye and say "I'm designing a new dialect of Lisp." I recommend this answer to anyone who doesn't like being asked what they do. The conversation will turn immediately to other topics. I don't consider myself to be doing research on programming languages. I'm just designing one, in the same way that someone might design a building or a chair or a new typeface. I'm not trying to discover anything new. I just want to make a language that will be good to program in. In some ways, this assumption makes life a lot easier. The difference between design and research seems to be a question of new versus good. Design doesn't have to be new, but it has to be good. Research doesn't have to be good, but it has to be new. I think these two paths converge at the top: the best design surpasses its predecessors by using new ideas, and the best research solves problems that are not only new, but actually worth solving. So ultimately we're aiming for the same destination, just approaching it from different directions. What I'm going to talk about today is what your target looks like from the back. What do you do differently when you treat programming languages as a design problem instead of a research topic? The biggest difference is that you focus more on the user. Design begins by asking, who is this for and what do they need from it? A good architect, for example, does not begin by creating a design that he then imposes on the users, but by studying the intended users and figuring out what they need.
Notice I said "what they need," not "what they want." I don't mean to give the impression that working as a designer means working as a sort of short-order cook, making whatever the client tells you to. This varies from field to field in the arts, but I don't think there is any field in which the best work is done by the people who just make exactly what the customers tell them to. The customer _is_ always right in the sense that the measure of good design is how well it works for the user. If you make a novel that bores everyone, or a chair that's horribly uncomfortable to sit in, then you've done a bad job, period. It's no defense to say that the novel or the chair is designed according to the most advanced theoretical principles. And yet, making what works for the user doesn't mean simply making what the user tells you to. Users don't know what all the choices are, and are often mistaken about what they really want. The answer to the paradox, I think, is that you have to design for the user, but you have to design what the user needs, not simply what he says he wants. It's much like being a doctor. You can't just treat a patient's symptoms. When a patient tells you his symptoms, you have to figure out what's actually wrong with him, and treat that. This focus on the user is a kind of axiom from which most of the practice of good design can be derived, and around which most design issues center. If good design must do what the user needs, who is the user? When I say that design must be for users, I don't mean to imply that good design aims at some kind of lowest common denominator. You can pick any group of users you want. If you're designing a tool, for example, you can design it for anyone from beginners to experts, and what's good design for one group might be bad for another. The point is, you have to pick some group of users.
I don't think you can even talk about good or bad design except with reference to some intended user. You're most likely to get good design if the intended users include the designer himself. When you design something for a group that doesn't include you, it tends to be for people you consider to be less sophisticated than you, not more sophisticated. That's a problem, because looking down on the user, however benevolently, seems inevitably to corrupt the designer. I suspect that very few housing projects in the US were designed by architects who expected to live in them. You can see the same thing in programming languages. C, Lisp, and Smalltalk were created for their own designers to use. Cobol, Ada, and Java, were created for other people to use. If you think you're designing something for idiots, the odds are that you're not designing something good, even for idiots. Even if you're designing something for the most sophisticated users, though, you're still designing for humans. It's different in research. In math you don't choose abstractions because they're easy for humans to understand; you choose whichever make the proof shorter. I think this is true for the sciences generally. Scientific ideas are not meant to be ergonomic. Over in the arts, things are very different. Design is all about people. The human body is a strange thing, but when you're designing a chair, that's what you're designing for, and there's no way around it. All the arts have to pander to the interests and limitations of humans. In painting, for example, all other things being equal a painting with people in it will be more interesting than one without. It is not merely an accident of history that the great paintings of the Renaissance are all full of people. If they hadn't been, painting as a medium wouldn't have the prestige that it does.
Like it or not, programming languages are also for people, and I suspect the human brain is just as lumpy and idiosyncratic as the human body. Some ideas are easy for people to grasp and some aren't. For example, we seem to have a very limited capacity for dealing with detail. It's this fact that makes programing languages a good idea in the first place; if we could handle the detail, we could just program in machine language. Remember, too, that languages are not primarily a form for finished programs, but something that programs have to be developed in. Anyone in the arts could tell you that you might want different mediums for the two situations. Marble, for example, is a nice, durable medium for finished ideas, but a hopelessly inflexible one for developing new ideas. A program, like a proof, is a pruned version of a tree that in the past has had false starts branching off all over it. So the test of a language is not simply how clean the finished program looks in it, but how clean the path to the finished program was. A design choice that gives you elegant finished programs may not give you an elegant design process. For example, I've written a few macro-defining macros full of nested backquotes that look now like little gems, but writing them took hours of the ugliest trial and error, and frankly, I'm still not entirely sure they're correct. We often act as if the test of a language were how good finished programs look in it. It seems so convincing when you see the same program written in two languages, and one version is much shorter. When you approach the problem from the direction of the arts, you're less likely to depend on this sort of test. You don't want to end up with a programming language like marble. For example, it is a huge win in developing software to have an interactive toplevel, what in Lisp is called a read-eval-print loop. And when you have one this has real effects on the design of the language.
It would not work well for a language where you have to declare variables before using them, for example. When you're just typing expressions into the toplevel, you want to be able to set x to some value and then start doing things to x. You don't want to have to declare the type of x first. You may dispute either of the premises, but if a language has to have a toplevel to be convenient, and mandatory type declarations are incompatible with a toplevel, then no language that makes type declarations mandatory could be convenient to program in. In practice, to get good design you have to get close, and stay close, to your users. You have to calibrate your ideas on actual users constantly, especially in the beginning. One of the reasons Jane Austen's novels are so good is that she read them out loud to her family. That's why she never sinks into self-indulgently arty descriptions of landscapes, or pretentious philosophizing. (The philosophy's there, but it's woven into the story instead of being pasted onto it like a label.) If you open an average "literary" novel and imagine reading it out loud to your friends as something you'd written, you'll feel all too keenly what an imposition that kind of thing is upon the reader. In the software world, this idea is known as Worse is Better. Actually, there are several ideas mixed together in the concept of Worse is Better, which is why people are still arguing about whether worse is actually better or not. But one of the main ideas in that mix is that if you're building something new, you should get a prototype in front of users as soon as possible. The alternative approach might be called the Hail Mary strategy. Instead of getting a prototype out quickly and gradually refining it, you try to create the complete, finished, product in one long touchdown pass. As far as I know, this is a recipe for disaster. Countless startups destroyed themselves this way during the Internet bubble.
I've never heard of a case where it worked. What people outside the software world may not realize is that Worse is Better is found throughout the arts. In drawing, for example, the idea was discovered during the Renaissance. Now almost every drawing teacher will tell you that the right way to get an accurate drawing is not to work your way slowly around the contour of an object, because errors will accumulate and you'll find at the end that the lines don't meet. Instead you should draw a few quick lines in roughly the right place, and then gradually refine this initial sketch. In most fields, prototypes have traditionally been made out of different materials. Typefaces to be cut in metal were initially designed with a brush on paper. Statues to be cast in bronze were modelled in wax. Patterns to be embroidered on tapestries were drawn on paper with ink wash. Buildings to be constructed from stone were tested on a smaller scale in wood. What made oil paint so exciting, when it first became popular in the fifteenth century, was that you could actually make the finished work _from_ the prototype. You could make a preliminary drawing if you wanted to, but you weren't held to it; you could work out all the details, and even make major changes, as you finished the painting. You can do this in software too. A prototype doesn't have to be just a model; you can refine it into the finished product. I think you should always do this when you can. It lets you take advantage of new insights you have along the way. But perhaps even more important, it's good for morale. Morale is key in design. I'm surprised people don't talk more about it. One of my first drawing teachers told me: if you're bored when you're drawing something, the drawing will look boring. For example, suppose you have to draw a building, and you decide to draw each brick individually.
You can do this if you want, but if you get bored halfway through and start making the bricks mechanically instead of observing each one, the drawing will look worse than if you had merely suggested the bricks. Building something by gradually refining a prototype is good for morale because it keeps you engaged. In software, my rule is: always have working code. If you're writing something that you'll be able to test in an hour, then you have the prospect of an immediate reward to motivate you. The same is true in the arts, and particularly in oil painting. Most painters start with a blurry sketch and gradually refine it. If you work this way, then in principle you never have to end the day with something that actually looks unfinished. Indeed, there is even a saying among painters: "A painting is never finished, you just stop working on it." This idea will be familiar to anyone who has worked on software. Morale is another reason that it's hard to design something for an unsophisticated user. It's hard to stay interested in something you don't like yourself. To make something good, you have to be thinking, "wow, this is really great," not "what a piece of shit; those fools will love it." Design means making things for humans. But it's not just the user who's human. The designer is human too. Notice all this time I've been talking about "the designer." Design usually has to be under the control of a single person to be any good. And yet it seems to be possible for several people to collaborate on a research project. This seems to me one of the most interesting differences between research and design. There have been famous instances of collaboration in the arts, but most of them seem to have been cases of molecular bonding rather than nuclear fusion. In an opera it's common for one person to write the libretto and another to write the music.
And during the Renaissance, journeymen from northern Europe were often employed to do the landscapes in the backgrounds of Italian paintings. But these aren't true collaborations. They're more like examples of Robert Frost's "good fences make good neighbors." You can stick instances of good design together, but within each individual project, one person has to be in control. I'm not saying that good design requires that one person think of everything. There's nothing more valuable than the advice of someone whose judgement you trust. But after the talking is done, the decision about what to do has to rest with one person. Why is it that research can be done by collaborators and design can't? This is an interesting question. I don't know the answer. Perhaps, if design and research converge, the best research is also good design, and in fact can't be done by collaborators. A lot of the most famous scientists seem to have worked alone. But I don't know enough to say whether there is a pattern here. It could be simply that many famous scientists worked when collaboration was less common. Whatever the story is in the sciences, true collaboration seems to be vanishingly rare in the arts. Design by committee is a synonym for bad design. Why is that so? Is there some way to beat this limitation? I'm inclined to think there isn't-- that good design requires a dictator. One reason is that good design has to be all of a piece. Design is not just for humans, but for individual humans. If a design represents an idea that fits in one person's head, then the idea will fit in the user's head too. Related:
| Japanese Translation | Taste for Makers | Romanian Translation | Spanish Translation.
2003年1月 (本文改编自2002年秋季NEPLS会议上的主题演讲。) 来到这个国家的访客常常惊讶地发现,美国人喜欢以"你是做什么的?"开启对话。我向来不喜欢这个问题,因为我很少能给出简洁的答案。但现在我终于找到了解决方案——当有人问起职业时,我会直视对方的眼睛说:"我正在设计一种Lisp新方言"。我向所有厌恶此问题的人推荐这个回答,它能立即将话题转向其他方向。 我不认为自己是在进行编程语言研究,只是在设计一门语言,就像设计建筑、椅子或新字体那样。我的目标并非发现新理论,而是创造优秀的编程工具。这种定位反而让许多事情变得简单。 设计与研究的本质区别在于"新"与"好"的侧重。设计不必全新但必须精良,研究不必完美但必须创新。两者在巅峰处交汇:顶尖设计通过创新超越前人,顶尖研究解决真正值得攻克的新问题。我们最终追求的是同一个目标,只是路径不同。 今天我要探讨的是从设计视角看待编程语言会产生哪些差异。 最显著的区别是对用户的关注。设计始于两个问题:为谁而做?他们需要什么?优秀建筑师不会强加设计方案,而是先研究使用者的真实需求。 注意是"需求"而非"要求"。设计师绝非照单全收的速记员。纵观艺术领域,杰作从来不是客户指令的机械执行。 用户永远正确的真谛在于:优秀设计的标准是实用性。若小说令人昏睡或椅子难以安坐,任何理论辩护都苍白无力。 但这不意味着盲从用户意见。用户既不清楚所有选项,也常误解自身需求。 解决这个悖论要像医生诊疗:不能止于症状,而要找出病根。这种以用户为核心的理念,正是优秀设计的基石。 若设计必须满足需求,谁才是真正的用户?"为用户设计"绝非迎合最低标准。从新手到专家,不同群体需要不同设计——关键在于明确目标用户。脱离具体用户群体,设计优劣无从谈起。 当用户群体包含设计师本人时,最易产出优秀作品。为低于自身水平的群体设计时,作品往往流于平庸。这种居高临下的姿态会腐蚀设计:美国保障房鲜有建筑师自住,正如C/Lisp/Smalltalk为创作者而生,而Cobol/Ada/Java为他人而作。 若你视用户为傻瓜,注定无法产出优秀设计——即使对傻瓜而言也是如此。 即便为高端用户设计,对象始终是人类。这与研究截然不同:数学抽象追求证明简洁而非人类理解,科学理论也无需符合人体工学。 艺术则全然不同。设计必须顺应人类特质:椅子要适应奇特的人体曲线,绘画因人物形象更富感染力——文艺复兴杰作满布人像绝非偶然,正是这种人性化赋予绘画崇高地位。 编程语言同样服务于人类大脑——这个充满不规则与特异性的器官。我们处理细节的能力有限,正因如此才需要编程语言替代机器码。 还需注意:语言不仅是成品的容器,更是开发过程的载体。艺术创作中,构思与成品往往需要不同媒介。大理石适合定型作品,却不利于创意推敲。 程序如同数学证明,都是剪除错误分支后的决策树。语言优劣不仅关乎成品代码的优雅,更在于开发路径的顺畅。某些设计能让成品熠熠生辉,却令开发过程举步维艰——我曾耗费数小时调试嵌套反引号的宏定义,那些如今如宝石般璀璨的代码,其正确性我仍不敢完全确信。 我们常以成品代码的简洁评判语言优劣。但若从艺术视角出发,就不会依赖这种标准——没人想要大理石般的编程语言。 例如交互式顶层环境(Lisp的REPL)对开发至关重要,这会实质性影响语言设计。要求变量先声明后使用的语言就不适配——临时测试时,我们需要先赋值再操作,而非反复声明类型。即便对前提存疑,若优秀语言必须配备REPL,而强制类型声明与之冲突,那么这类语言注定难用。 优秀设计需要持续贴近用户。简·奥斯汀为家人朗读小说的习惯,使她避开了矫揉造作的景物描写与生硬说教(哲理都巧妙融入情节)。试想对着朋友朗读当代"文学"小说,你立刻会感受到对读者的冒犯。 软件界的"差中求好"(Worse is Better)理念与此相通。虽然争议不断,但其核心是尽早交付原型。与之相对的"万福玛利亚"策略则追求一次性交付完美产品——互联网泡沫中无数初创公司因此覆灭,几无成功先例。 非软件领域同样存在"差中求好"。文艺复兴时期画家发现:精确素描不应缓慢勾勒轮廓(误差累积会导致线条错位),而应快速定位后逐步细化。 传统艺术常用不同材料制作原型:金属字模先经毛笔设计,青铜雕塑先用蜡坯试验,挂毯图案先以水墨打稿,石质建筑先做木制模型。 十五世纪油画革命性的突破在于:原型可直接转化为成品。底稿不必拘泥,细节甚至重大改动都可在创作过程中调整。 软件开发亦然。原型不必抛弃,可逐步完善为最终产品。这不仅能吸收途中灵感,更能提振士气——后者是设计的关键因素。 士气在设计中至关重要,却少被谈及。我的绘画启蒙老师说:作画时若感到无聊,作品必然乏味。若决定绘制建筑每块砖石,中途因枯燥转为机械描绘,效果反不如简略暗示。 渐进式原型开发能保持创作激情。我的编程准则始终是:保持代码可运行。一小时后的测试机会就是即时激励。油画创作同样如此——多数画家从模糊草图开始逐步细化,理论上每天收工时的作品都不显未完成。正如画界箴言:"画作永不完成,只是停笔而已",软件开发者对此深有同感。 为低水平用户设计难以维持士气。唯有发自内心赞叹"这太棒了",而非暗想"垃圾玩意儿正合蠢货胃口",才能产出优秀作品。 设计服务于人,这个"人"既包括用户,也包括设计师本人。 注意我一直使用"设计师"单数形式。优秀设计通常需要单人主导,而研究却可以团队合作——这是两者最有趣的差异之一。 艺术史上著名合作多为"分子结合"而非"核聚变":歌剧由编剧与作曲家分工,文艺复兴时期意大利画家常雇北欧画师绘制风景背景。这些并非真正协作,更像罗伯特·弗罗斯特所言"好篱笆促成好邻居"。优秀设计可以拼接,但每个项目内部必须有人掌舵。 并非要求设计师独断专行,可信伙伴的建议无比珍贵。但决策权必须归于一人。 为何研究可协作而设计不能?有趣的是,若研究达到设计的高度,似乎也无法协作——许多著名科学家都独自工作。不过这可能只是时代使然。 无论科学领域如何,艺术界真正的协作凤毛麟角。"委员会设计"已成为劣质代名词。能否突破这种限制? 我认为不可能——优秀设计需要独裁者。因为设计必须保持整体性,它不仅要服务人类,更要契合个体心智。唯有完整存于设计者脑海的构想,才能完整传递至使用者心中。 相关阅读:
Like to build things? Try Hacker News.
August 2002 _(This article describes the spam-filtering techniques used in the spamproof web-based mail reader we built to exerciseArc. An improved algorithm is described in Better Bayesian Filtering.)_ I think it's possible to stop spam, and that content-based filters are the way to do it. The Achilles heel of the spammers is their message. They can circumvent any other barrier you set up. They have so far, at least. But they have to deliver their message, whatever it is. If we can write software that recognizes their messages, there is no way they can get around that. _ _ _ To the recipient, spam is easily recognizable. If you hired someone to read your mail and discard the spam, they would have little trouble doing it. How much do we have to do, short of AI, to automate this process? I think we will be able to solve the problem with fairly simple algorithms. In fact, I've found that you can filter present-day spam acceptably well using nothing more than a Bayesian combination of the spam probabilities of individual words. Using a slightly tweaked (as described below) Bayesian filter, we now miss less than 5 per 1000 spams, with 0 false positives. The statistical approach is not usually the first one people try when they write spam filters. Most hackers' first instinct is to try to write software that recognizes individual properties of spam. You look at spams and you think, the gall of these guys to try sending me mail that begins "Dear Friend" or has a subject line that's all uppercase and ends in eight exclamation points. I can filter out that stuff with about one line of code. And so you do, and in the beginning it works. A few simple rules will take a big bite out of your incoming spam. Merely looking for the word "click" will catch 79.7% of the emails in my spam corpus, with only 1.2% false positives.
I spent about six months writing software that looked for individual spam features before I tried the statistical approach. What I found was that recognizing that last few percent of spams got very hard, and that as I made the filters stricter I got more false positives. False positives are innocent emails that get mistakenly identified as spams. For most users, missing legitimate email is an order of magnitude worse than receiving spam, so a filter that yields false positives is like an acne cure that carries a risk of death to the patient. The more spam a user gets, the less likely he'll be to notice one innocent mail sitting in his spam folder. And strangely enough, the better your spam filters get, the more dangerous false positives become, because when the filters are really good, users will be more likely to ignore everything they catch. I don't know why I avoided trying the statistical approach for so long. I think it was because I got addicted to trying to identify spam features myself, as if I were playing some kind of competitive game with the spammers. (Nonhackers don't often realize this, but most hackers are very competitive.) When I did try statistical analysis, I found immediately that it was much cleverer than I had been. It discovered, of course, that terms like "virtumundo" and "teens" were good indicators of spam. But it also discovered that "per" and "FL" and "ff0000" are good indicators of spam. In fact, "ff0000" (html for bright red) turns out to be as good an indicator of spam as any pornographic term. _ _ _ Here's a sketch of how I do statistical filtering. I start with one corpus of spam and one of nonspam mail. At the moment each one has about 4000 messages in it. I scan the entire text, including headers and embedded html and javascript, of each message in each corpus.
I currently consider alphanumeric characters, dashes, apostrophes, and dollar signs to be part of tokens, and everything else to be a token separator. (There is probably room for improvement here.) I ignore tokens that are all digits, and I also ignore html comments, not even considering them as token separators. I count the number of times each token (ignoring case, currently) occurs in each corpus. At this stage I end up with two large hash tables, one for each corpus, mapping tokens to number of occurrences. Next I create a third hash table, this time mapping each token to the probability that an email containing it is a spam, which I calculate as follows [1]: (let ((g (* 2 (or (gethash word good) 0))) (b (or (gethash word bad) 0))) (unless (< (+ g b) 5) (max .01 (min .99 (float (/ (min 1 (/ b nbad)) (+ (min 1 (/ g ngood)) (min 1 (/ b nbad))))))))) where word is the token whose probability we're calculating, good and bad are the hash tables I created in the first step, and ngood and nbad are the number of nonspam and spam messages respectively. I explained this as code to show a couple of important details. I want to bias the probabilities slightly to avoid false positives, and by trial and error I've found that a good way to do it is to double all the numbers in good. This helps to distinguish between words that occasionally do occur in legitimate email and words that almost never do. I only consider words that occur more than five times in total (actually, because of the doubling, occurring three times in nonspam mail would be enough). And then there is the question of what probability to assign to words that occur in one corpus but not the other. Again by trial and error I chose .01 and .99. There may be room for tuning here, but as the corpus grows such tuning will happen automatically anyway.
The especially observant will notice that while I consider each corpus to be a single long stream of text for purposes of counting occurrences, I use the number of emails in each, rather than their combined length, as the divisor in calculating spam probabilities. This adds another slight bias to protect against false positives. When new mail arrives, it is scanned into tokens, and the most interesting fifteen tokens, where interesting is measured by how far their spam probability is from a neutral .5, are used to calculate the probability that the mail is spam. If probs is a list of the fifteen individual probabilities, you calculate the combined probability thus: (let ((prod (apply #' probs))) (/ prod (+ prod (apply #' (mapcar #'(lambda (x) (- 1 x)) probs))))) One question that arises in practice is what probability to assign to a word you've never seen, i.e. one that doesn't occur in the hash table of word probabilities. I've found, again by trial and error, that .4 is a good number to use. If you've never seen a word before, it is probably fairly innocent; spam words tend to be all too familiar. There are examples of this algorithm being applied to actual emails in an appendix at the end. I treat mail as spam if the algorithm above gives it a probability of more than .9 of being spam. But in practice it would not matter much where I put this threshold, because few probabilities end up in the middle of the range. _ _ _ One great advantage of the statistical approach is that you don't have to read so many spams. Over the past six months, I've read literally thousands of spams, and it is really kind of demoralizing. Norbert Wiener said if you compete with slaves you become a slave, and there is something similarly degrading about competing with spammers.
To recognize individual spam features you have to try to get into the mind of the spammer, and frankly I want to spend as little time inside the minds of spammers as possible. But the real advantage of the Bayesian approach, of course, is that you know what you're measuring. Feature-recognizing filters like SpamAssassin assign a spam "score" to email. The Bayesian approach assigns an actual probability. The problem with a "score" is that no one knows what it means. The user doesn't know what it means, but worse still, neither does the developer of the filter. How many _points_ should an email get for having the word "sex" in it? A probability can of course be mistaken, but there is little ambiguity about what it means, or how evidence should be combined to calculate it. Based on my corpus, "sex" indicates a .97 probability of the containing email being a spam, whereas "sexy" indicates .99 probability. And Bayes' Rule, equally unambiguous, says that an email containing both words would, in the (unlikely) absence of any other evidence, have a 99.97% chance of being a spam. Because it is measuring probabilities, the Bayesian approach considers all the evidence in the email, both good and bad. Words that occur disproportionately _rarely_ in spam (like "though" or "tonight" or "apparently") contribute as much to decreasing the probability as bad words like "unsubscribe" and "opt-in" do to increasing it. So an otherwise innocent email that happens to include the word "sex" is not going to get tagged as spam. Ideally, of course, the probabilities should be calculated individually for each user. I get a lot of email containing the word "Lisp", and (so far) no spam that does. So a word like that is effectively a kind of password for sending mail to me. In my earlier spam-filtering software, the user could set up a list of such words and mail containing them would automatically get past the filters.
On my list I put words like "Lisp" and also my zipcode, so that (otherwise rather spammy-sounding) receipts from online orders would get through. I thought I was being very clever, but I found that the Bayesian filter did the same thing for me, and moreover discovered of a lot of words I hadn't thought of. When I said at the start that our filters let through less than 5 spams per 1000 with 0 false positives, I'm talking about filtering my mail based on a corpus of my mail. But these numbers are not misleading, because that is the approach I'm advocating: filter each user's mail based on the spam and nonspam mail he receives. Essentially, each user should have two delete buttons, ordinary delete and delete-as-spam. Anything deleted as spam goes into the spam corpus, and everything else goes into the nonspam corpus. You could start users with a seed filter, but ultimately each user should have his own per-word probabilities based on the actual mail he receives. This (a) makes the filters more effective, (b) lets each user decide their own precise definition of spam, and (c) perhaps best of all makes it hard for spammers to tune mails to get through the filters. If a lot of the brain of the filter is in the individual databases, then merely tuning spams to get through the seed filters won't guarantee anything about how well they'll get through individual users' varying and much more trained filters. Content-based spam filtering is often combined with a whitelist, a list of senders whose mail can be accepted with no filtering. One easy way to build such a whitelist is to keep a list of every address the user has ever sent mail to. If a mail reader has a delete-as-spam button then you could also add the from address of every email the user has deleted as ordinary trash. I'm an advocate of whitelists, but more as a way to save computation than as a way to improve filtering.
I used to think that whitelists would make filtering easier, because you'd only have to filter email from people you'd never heard from, and someone sending you mail for the first time is constrained by convention in what they can say to you. Someone you already know might send you an email talking about sex, but someone sending you mail for the first time would not be likely to. The problem is, people can have more than one email address, so a new from-address doesn't guarantee that the sender is writing to you for the first time. It is not unusual for an old friend (especially if he is a hacker) to suddenly send you an email with a new from-address, so you can't risk false positives by filtering mail from unknown addresses especially stringently. In a sense, though, my filters do themselves embody a kind of whitelist (and blacklist) because they are based on entire messages, including the headers. So to that extent they "know" the email addresses of trusted senders and even the routes by which mail gets from them to me. And they know the same about spam, including the server names, mailer versions, and protocols. _ _ _ If I thought that I could keep up current rates of spam filtering, I would consider this problem solved. But it doesn't mean much to be able to filter out most present-day spam, because spam evolves. Indeed, most antispam techniques so far have been like pesticides that do nothing more than create a new, resistant strain of bugs. I'm more hopeful about Bayesian filters, because they evolve with the spam. So as spammers start using "c0ck" instead of "cock" to evade simple-minded spam filters based on individual words, Bayesian filters automatically notice. Indeed, "c0ck" is far more damning evidence than "cock", and Bayesian filters know precisely how much more.
Still, anyone who proposes a plan for spam filtering has to be able to answer the question: if the spammers knew exactly what you were doing, how well could they get past you? For example, I think that if checksum-based spam filtering becomes a serious obstacle, the spammers will just switch to mad-lib techniques for generating message bodies. To beat Bayesian filters, it would not be enough for spammers to make their emails unique or to stop using individual naughty words. They'd have to make their mails indistinguishable from your ordinary mail. And this I think would severely constrain them. Spam is mostly sales pitches, so unless your regular mail is all sales pitches, spams will inevitably have a different character. And the spammers would also, of course, have to change (and keep changing) their whole infrastructure, because otherwise the headers would look as bad to the Bayesian filters as ever, no matter what they did to the message body. I don't know enough about the infrastructure that spammers use to know how hard it would be to make the headers look innocent, but my guess is that it would be even harder than making the message look innocent. Assuming they could solve the problem of the headers, the spam of the future will probably look something like this: Hey there. Thought you should check out the following: http://www.27meg.com/foo because that is about as much sales pitch as content-based filtering will leave the spammer room to make. (Indeed, it will be hard even to get this past filters, because if everything else in the email is neutral, the spam probability will hinge on the url, and it will take some effort to make that look neutral.) Spammers range from businesses running so-called opt-in lists who don't even try to conceal their identities, to guys who hijack mail servers to send out spams promoting porn sites.
If we use filtering to whittle their options down to mails like the one above, that should pretty much put the spammers on the "legitimate" end of the spectrum out of business; they feel obliged by various state laws to include boilerplate about why their spam is not spam, and how to cancel your "subscription," and that kind of text is easy to recognize. (I used to think it was naive to believe that stricter laws would decrease spam. Now I think that while stricter laws may not decrease the amount of spam that spammers _send,_ they can certainly help filters to decrease the amount of spam that recipients actually see.) All along the spectrum, if you restrict the sales pitches spammers can make, you will inevitably tend to put them out of business. That word _business_ is an important one to remember. The spammers are businessmen. They send spam because it works. It works because although the response rate is abominably low (at best 15 per million, vs 3000 per million for a catalog mailing), the cost, to them, is practically nothing. The cost is enormous for the recipients, about 5 man-weeks for each million recipients who spend a second to delete the spam, but the spammer doesn't have to pay that. Sending spam does cost the spammer something, though. [2] So the lower we can get the response rate-- whether by filtering, or by using filters to force spammers to dilute their pitches-- the fewer businesses will find it worth their while to send spam. The reason the spammers use the kinds of sales pitches that they do is to increase response rates. This is possibly even more disgusting than getting inside the mind of a spammer, but let's take a quick look inside the mind of someone who _responds_ to a spam. This person is either astonishingly credulous or deeply in denial about their sexual interests. In either case, repulsive or idiotic as the spam seems to us, it is exciting to them.
The spammers wouldn't say these things if they didn't sound exciting. And "thought you should check out the following" is just not going to have nearly the pull with the spam recipient as the kinds of things that spammers say now. Result: if it can't contain exciting sales pitches, spam becomes less effective as a marketing vehicle, and fewer businesses want to use it. That is the big win in the end. I started writing spam filtering software because I didn't want have to look at the stuff anymore. But if we get good enough at filtering out spam, it will stop working, and the spammers will actually stop sending it. _ _ _ Of all the approaches to fighting spam, from software to laws, I believe Bayesian filtering will be the single most effective. But I also think that the more different kinds of antispam efforts we undertake, the better, because any measure that constrains spammers will tend to make filtering easier. And even within the world of content-based filtering, I think it will be a good thing if there are many different kinds of software being used simultaneously. The more different filters there are, the harder it will be for spammers to tune spams to get through them. Appendix: Examples of Filtering Here is an example of a spam that arrived while I was writing this article. The fifteen most interesting words in this spam are: qvp0045 indira mx-05 intimail $7500 freeyankeedom cdo bluefoxmedia jpg unsecured platinum 3d0 qves 7c5 7c266675 The words are a mix of stuff from the headers and from the message body, which is typical of spam. Also typical of spam is that every one of these words has a spam probability, in my database, of .99. In fact there are more than fifteen words with probabilities of .99, and these are just the first fifteen seen. Unfortunately that makes this email a boring example of the use of Bayes' Rule.
To see an interesting variety of probabilities we have to look at this actually quite atypical spam. The fifteen most interesting words in this spam, with their probabilities, are: madam 0.99 promotion 0.99 republic 0.99 shortest 0.047225013 mandatory 0.047225013 standardization 0.07347802 sorry 0.08221981 supported 0.09019077 people's 0.09019077 enter 0.9075001 quality 0.8921298 organization 0.12454646 investment 0.8568143 very 0.14758544 valuable 0.82347786 This time the evidence is a mix of good and bad. A word like "shortest" is almost as much evidence for innocence as a word like "madam" or "promotion" is for guilt. But still the case for guilt is stronger. If you combine these numbers according to Bayes' Rule, the resulting probability is .9027. "Madam" is obviously from spams beginning "Dear Sir or Madam." They're not very common, but the word "madam" _never_ occurs in my legitimate email, and it's all about the ratio. "Republic" scores high because it often shows up in Nigerian scam emails, and also occurs once or twice in spams referring to Korea and South Africa. You might say that it's an accident that it thus helps identify this spam. But I've found when examining spam probabilities that there are a lot of these accidents, and they have an uncanny tendency to push things in the right direction rather than the wrong one. In this case, it is not entirely a coincidence that the word "Republic" occurs in Nigerian scam emails and this spam. There is a whole class of dubious business propositions involving less developed countries, and these in turn are more likely to have names that specify explicitly (because they aren't) that they are republics.[3] On the other hand, "enter" is a genuine miss. It occurs mostly in unsubscribe instructions, but here is used in a completely innocent way.
Fortunately the statistical approach is fairly robust, and can tolerate quite a lot of misses before the results start to be thrown off. For comparison, here is an example of that rare bird, a spam that gets through the filters. Why? Because by sheer chance it happens to be loaded with words that occur in my actual email: perl 0.01 python 0.01 tcl 0.01 scripting 0.01 morris 0.01 graham 0.01491078 guarantee 0.9762507 cgi 0.9734398 paul 0.027040077 quite 0.030676773 pop3 0.042199217 various 0.06080265 prices 0.9359873 managed 0.06451222 difficult 0.071706355 There are a couple pieces of good news here. First, this mail probably wouldn't get through the filters of someone who didn't happen to specialize in programming languages and have a good friend called Morris. For the average user, all the top five words here would be neutral and would not contribute to the spam probability. Second, I think filtering based on word pairs (see below) might well catch this one: "cost effective", "setup fee", "money back" -- pretty incriminating stuff. And of course if they continued to spam me (or a network I was part of), "Hostex" itself would be recognized as a spam term. Finally, here is an innocent email. Its fifteen most interesting words are as follows: continuation 0.01 describe 0.01 continuations 0.01 example 0.033600237 programming 0.05214485 i'm 0.055427782 examples 0.07972858 color 0.9189189 localhost 0.09883721 hi 0.116539136 california 0.84421706 same 0.15981844 spot 0.1654587 us-ascii 0.16804294 what 0.19212411 Most of the words here indicate the mail is an innocent one.
There are two bad smelling words, "color" (spammers love colored fonts) and "California" (which occurs in testimonials and also in menus in forms), but they are not enough to outweigh obviously innocent words like "continuation" and "example". It's interesting that "describe" rates as so thoroughly innocent. It hasn't occurred in a single one of my 4000 spams. The data turns out to be full of such surprises. One of the things you learn when you analyze spam texts is how narrow a subset of the language spammers operate in. It's that fact, together with the equally characteristic vocabulary of any individual user's mail, that makes Bayesian filtering a good bet. Appendix: More Ideas One idea that I haven't tried yet is to filter based on word pairs, or even triples, rather than individual words. This should yield a much sharper estimate of the probability. For example, in my current database, the word "offers" has a probability of .96. If you based the probabilities on word pairs, you'd end up with "special offers" and "valuable offers" having probabilities of .99 and, say, "approach offers" (as in "this approach offers") having a probability of .1 or less. The reason I haven't done this is that filtering based on individual words already works so well. But it does mean that there is room to tighten the filters if spam gets harder to detect. (Curiously, a filter based on word pairs would be in effect a Markov-chaining text generator running in reverse.) Specific spam features (e.g. not seeing the recipient's address in the to: field) do of course have value in recognizing spam. They can be considered in this algorithm by treating them as virtual words. I'll probably do this in future versions, at least for a handful of the most egregious spam indicators. Feature-recognizing spam filters are right in many details; what they lack is an overall discipline for combining evidence.
Recognizing nonspam features may be more important than recognizing spam features. False positives are such a worry that they demand extraordinary measures. I will probably in future versions add a second level of testing designed specifically to avoid false positives. If a mail triggers this second level of filters it will be accepted even if its spam probability is above the threshold. I don't expect this second level of filtering to be Bayesian. It will inevitably be not only ad hoc, but based on guesses, because the number of false positives will not tend to be large enough to notice patterns. (It is just as well, anyway, if a backup system doesn't rely on the same technology as the primary system.) Another thing I may try in the future is to focus extra attention on specific parts of the email. For example, about 95% of current spam includes the url of a site they want you to visit. (The remaining 5% want you to call a phone number, reply by email or to a US mail address, or in a few cases to buy a certain stock.) The url is in such cases practically enough by itself to determine whether the email is spam. Domain names differ from the rest of the text in a (non-German) email in that they often consist of several words stuck together. Though computationally expensive in the general case, it might be worth trying to decompose them. If a filter has never seen the token "xxxporn" before it will have an individual spam probability of .4, whereas "xxx" and "porn" individually have probabilities (in my corpus) of .9889 and .99 respectively, and a combined probability of .9998. I expect decomposing domain names to become more important as spammers are gradually forced to stop using incriminating words in the text of their messages. (A url with an ip address is of course an extremely incriminating sign, except in the mail of a few sysadmins.) It might be a good idea to have a cooperatively maintained list of urls promoted by spammers.
We'd need a trust metric of the type studied by Raph Levien to prevent malicious or incompetent submissions, but if we had such a thing it would provide a boost to any filtering software. It would also be a convenient basis for boycotts. Another way to test dubious urls would be to send out a crawler to look at the site before the user looked at the email mentioning it. You could use a Bayesian filter to rate the site just as you would an email, and whatever was found on the site could be included in calculating the probability of the email being a spam. A url that led to a redirect would of course be especially suspicious. One cooperative project that I think really would be a good idea would be to accumulate a giant corpus of spam. A large, clean corpus is the key to making Bayesian filtering work well. Bayesian filters could actually use the corpus as input. But such a corpus would be useful for other kinds of filters too, because it could be used to test them. Creating such a corpus poses some technical problems. We'd need trust metrics to prevent malicious or incompetent submissions, of course. We'd also need ways of erasing personal information (not just to-addresses and ccs, but also e.g. the arguments to unsubscribe urls, which often encode the to-address) from mails in the corpus. If anyone wants to take on this project, it would be a good thing for the world. Appendix: Defining Spam I think there is a rough consensus on what spam is, but it would be useful to have an explicit definition. We'll need to do this if we want to establish a central corpus of spam, or even to compare spam filtering rates meaningfully. To start with, spam is not unsolicited commercial email. If someone in my neighborhood heard that I was looking for an old Raleigh three-speed in good condition, and sent me an email offering to sell me one, I'd be delighted, and yet this email would be both commercial and unsolicited.
The defining feature of spam (in fact, its _raison d'etre_ ) is not that it is unsolicited, but that it is automated. It is merely incidental, too, that spam is usually commercial. If someone started sending mass email to support some political cause, for example, it would be just as much spam as email promoting a porn site. I propose we define spam as unsolicited automated email. This definition thus includes some email that many legal definitions of spam don't. Legal definitions of spam, influenced presumably by lobbyists, tend to exclude mail sent by companies that have an "existing relationship" with the recipient. But buying something from a company, for example, does not imply that you have solicited ongoing email from them. If I order something from an online store, and they then send me a stream of spam, it's still spam. Companies sending spam often give you a way to "unsubscribe," or ask you to go to their site and change your "account preferences" if you want to stop getting spam. This is not enough to stop the mail from being spam. Not opting out is not the same as opting in. Unless the recipient explicitly checked a clearly labelled box (whose default was no) asking to receive the email, then it is spam. In some business relationships, you do implicitly solicit certain kinds of mail. When you order online, I think you implicitly solicit a receipt, and notification when the order ships. I don't mind when Verisign sends me mail warning that a domain name is about to expire (at least, if they are the actual registrar for it). But when Verisign sends me email offering a FREE Guide to Building My E-Commerce Web Site, that's spam. Notes: [1] The examples in this article are translated into Common Lisp for, believe it or not, greater accessibility.
The application described here is one that we wrote in order to test a new Lisp dialect called Arc that is not yet released. [2] Currently the lowest rate seems to be about $200 to send a million spams. That's very cheap, 1/50th of a cent per spam. But filtering out 95% of spam, for example, would increase the spammers' cost to reach a given audience by a factor of 20. Few can have margins big enough to absorb that. [3] As a rule of thumb, the more qualifiers there are before the name of a country, the more corrupt the rulers. A country called The Socialist People's Democratic Republic of X is probably the last place in the world you'd want to live. Thanks to Sarah Harlin for reading drafts of this; Daniel Giffin (who is also writing the production Arc interpreter) for several good ideas about filtering and for creating our mail infrastructure; Robert Morris, Trevor Blackwell and Erann Gat for many discussions about spam; Raph Levien for advice about trust metrics; and Chip Coldwell and Sam Steingold for advice about statistics. You'll find this essay and 14 others in _Hackers & Painters_. More Info:
Plan for Spam FAQ | Better Bayesian Filtering Filters that Fight Back | Will Filters Kill Spam? Japanese Translation | Spanish Translation Chinese Translation | Probability Spam is Different | Filters vs.
Blacklists Trust Metrics | Filtering Research Microsoft Patent | Slashdot Article The Wrong Way | LWN: Filter Comparison CRM114 gets 99.87%.
喜欢构建事物?试试Hacker News。
2002年8月 (本文描述了我们在开发基于Arc的防垃圾邮件网页邮件阅读器时使用的垃圾邮件过滤技术。改进后的算法详见更好的贝叶斯过滤。) 我认为阻止垃圾邮件是可能的,而基于内容的过滤器是实现这一目标的方法。垃圾邮件发送者的致命弱点在于他们的信息。他们可以绕过你设置的任何其他障碍。至少到目前为止是这样。但他们必须传递他们的信息,无论它是什么。如果我们能编写出识别他们信息的软件,他们就无法绕过这一点。 _ _ _ 对于收件人来说,垃圾邮件很容易识别。如果你雇人阅读你的邮件并丢弃垃圾邮件,他们几乎不会有什么困难。在不涉及人工智能的情况下,我们需要做多少工作才能自动化这一过程? 我认为我们可以用相当简单的算法解决这个问题。事实上,我发现仅使用单个单词的垃圾邮件概率的贝叶斯组合,就可以很好地过滤当前的垃圾邮件。通过稍微调整(如下所述)的贝叶斯过滤器,我们现在每1000封垃圾邮件中漏掉的不到5封,且没有误判。 统计方法通常不是人们编写垃圾邮件过滤器时首先尝试的方法。大多数黑客的第一本能是尝试编写能够识别垃圾邮件个别特征的软件。你看到垃圾邮件时会想,这些家伙居然敢给我发以“亲爱的朋友”开头的邮件,或者主题全是大写并以八个感叹号结尾。我可以用大约一行代码过滤掉这些东西。 于是你这样做,一开始效果不错。几条简单的规则就能大幅减少收到的垃圾邮件。仅查找“点击”这个词就能捕获我垃圾邮件库中79.7%的邮件,误判率仅为1.2%。 在尝试统计方法之前,我花了大约六个月时间编写识别垃圾邮件特征的软件。我发现识别最后几个百分点的垃圾邮件变得非常困难,而且随着过滤器的严格程度提高,误判率也随之增加。 误判是指无辜的邮件被错误地识别为垃圾邮件。对大多数用户来说,错过合法邮件比收到垃圾邮件糟糕得多,因此产生误判的过滤器就像一种可能导致患者死亡的痤疮治疗方法。 用户收到的垃圾邮件越多,他越不可能注意到垃圾邮件文件夹中的一封无辜邮件。奇怪的是,垃圾邮件过滤器越好,误判的危险性就越大,因为当过滤器真的很好时,用户更可能忽略它们捕获的所有内容。 我不知道为什么我这么久才尝试统计方法。我想是因为我沉迷于自己识别垃圾邮件特征,仿佛在与垃圾邮件发送者玩某种竞争游戏。(非黑客通常没有意识到这一点,但大多数黑客非常有竞争意识。)当我尝试统计分析时,立即发现它比我聪明得多。它当然发现了像“virtumundo”和“teens”这样的词是垃圾邮件的良好指标。但它还发现“per”、“FL”和“ff0000”也是垃圾邮件的良好指标。事实上,“ff0000”(表示亮红色的HTML代码)与任何色情词汇一样是垃圾邮件的良好指标。 _ _ _ 以下是我如何进行统计过滤的概述。我从一个垃圾邮件库和一个非垃圾邮件库开始。目前每个库中大约有4000封邮件。我扫描每个库中每封邮件的全部文本,包括标题和嵌入的HTML和JavaScript。目前我认为字母数字字符、连字符、撇号和美元符号是标记的一部分,其他所有内容都是标记分隔符。(这里可能还有改进的空间。)我忽略全数字的标记,也忽略HTML注释,甚至不将它们视为标记分隔符。 我计算每个标记(目前忽略大小写)在每个库中出现的次数。在这个阶段,我最终得到两个大型哈希表,每个库一个,将标记映射到出现次数。 接下来我创建第三个哈希表,这次将每个标记映射到包含它的邮件是垃圾邮件的概率,我按以下方式计算[1]: (let ((g (* 2 (or (gethash word good) 0))) (b (or (gethash word bad) 0))) (unless (< (+ g b) 5) (max .01 (min .99 (float (/ (min 1 (/ b nbad)) (+ (min 1 (/ g ngood)) (min 1 (/ b nbad))))))))) 其中word是我们计算概率的标记,good和bad是我在第一步创建的哈希表,ngood和nbad分别是非垃圾邮件和垃圾邮件的数量。 我用代码解释这一点是为了展示几个重要的细节。我希望稍微偏置概率以避免误判,通过反复试验我发现一个好的方法是将good中的所有数字加倍。这有助于区分偶尔出现在合法邮件中的词和几乎从不出现的词。我只考虑总共出现超过五次的词(实际上,由于加倍,在非垃圾邮件中出现三次就足够了)。然后还有一个问题是如何为在一个库中出现但另一个库中未出现的词分配概率。再次通过反复试验,我选择了0.01和0.99。这里可能有调整的空间,但随着库的增长,这种调整会自动发生。 特别观察的人会注意到,虽然我将每个库视为一个长文本流以计算出现次数,但在计算垃圾邮件概率时,我使用每封邮件的数量而不是它们的总长度作为除数。这增加了另一个轻微的偏置以防止误判。 当新邮件到达时,它被扫描为标记,并使用最有趣的十五个标记(其中“有趣”由它们的垃圾邮件概率与中性0.5的距离衡量)来计算邮件是垃圾邮件的概率。如果probs是十五个单独概率的列表,你可以按以下方式计算组合概率: (let ((prod (apply #' probs))) (/ prod (+ prod (apply #' (mapcar #'(lambda (x) (- 1 x)) probs))))) 在实践中出现的一个问题是如何为从未见过的词分配概率,即未出现在词概率哈希表中的词。通过反复试验,我发现0.4是一个很好的数字。如果你从未见过一个词,它可能是相当无辜的;垃圾邮件词汇往往过于熟悉。 在末尾的附录中有该算法应用于实际邮件的示例。 如果上述算法给出的邮件是垃圾邮件的概率超过0.9,我就将其视为垃圾邮件。但在实践中,我将这个阈值放在哪里并不重要,因为很少有概率落在中间范围。 _ _ _ 统计方法的一个巨大优势是你不需要阅读那么多垃圾邮件。在过去的六个月里,我实际上阅读了数千封垃圾邮件,这真的有点令人沮丧。诺伯特·维纳说,如果你与奴隶竞争,你就会变成奴隶,与垃圾邮件发送者竞争也有类似的降级感。要识别垃圾邮件的个别特征,你必须试图进入垃圾邮件发送者的思维,坦率地说,我尽可能少地花时间在垃圾邮件发送者的思维中。 但贝叶斯方法的真正优势当然是你知道你在测量什么。像SpamAssassin这样的特征识别过滤器为邮件分配垃圾邮件“分数”。贝叶斯方法分配的是实际概率。“分数”的问题在于没有人知道它的含义。用户不知道它的含义,但更糟糕的是,过滤器的开发者也不知道。一封包含“sex”一词的邮件应该得到多少分?概率当然可能是错误的,但它的含义或如何结合证据来计算它几乎没有歧义。根据我的库,“sex”表明包含它的邮件是垃圾邮件的概率为0.97,而“sexy”表明的概率为0.99。贝叶斯规则同样明确,表示一封同时包含这两个词的邮件在(不太可能)没有其他证据的情况下,有99.97%的概率是垃圾邮件。 因为它测量的是概率,贝叶斯方法考虑了邮件中的所有证据,无论是好的还是坏的。在垃圾邮件中不成比例地罕见的词(如“though”、“tonight”或“apparently”)对降低概率的贡献与“unsubscribe”和“opt-in”等坏词对增加概率的贡献一样大。因此,一封恰好包含“sex”一词的无辜邮件不会被标记为垃圾邮件。 当然,理想情况下,应该为每个用户单独计算概率。我收到很多包含“Lisp”一词的邮件,而(到目前为止)没有垃圾邮件包含它。因此,这样的词实际上是向我发送邮件的密码。在我早期的垃圾邮件过滤软件中,用户可以设置这样的词列表,包含这些词的邮件会自动通过过滤器。在我的列表中,我放了“Lisp”和我的邮政编码,以便(听起来相当垃圾邮件的)在线订单收据能够通过。我以为自己很聪明,但我发现贝叶斯过滤器为我做了同样的事情,而且还发现了很多我没想到的词。 我在开头说我们的过滤器每1000封垃圾邮件中漏掉的不到5封,且没有误判,这是基于我的邮件库过滤我的邮件。但这些数字并不误导,因为这是我提倡的方法:根据每个用户收到的垃圾邮件和非垃圾邮件过滤他的邮件。本质上,每个用户应该有两个删除按钮,普通删除和作为垃圾邮件删除。任何作为垃圾邮件删除的内容都会进入垃圾邮件库,其他所有内容进入非垃圾邮件库。 你可以为用户提供一个种子过滤器,但最终每个用户应该根据他实际收到的邮件拥有自己的每词概率。这(a)使过滤器更有效,(b)让每个用户决定自己对垃圾邮件的精确定义,(c)也许最重要的是,使垃圾邮件发送者难以调整邮件以通过过滤器。如果过滤器的大部分智能在于个别数据库中,那么仅仅调整垃圾邮件以通过种子过滤器并不能保证它们能通过个别用户不同且训练有素的过滤器。 基于内容的垃圾邮件过滤通常与白名单结合使用,白名单是无需过滤即可接受的发件人列表。构建这样一个白名单的一个简单方法是保留用户曾经发送过邮件的每个地址的列表。如果邮件阅读器有一个“作为垃圾邮件删除”按钮,你也可以将用户作为普通垃圾删除的每封邮件的发件人地址添加到白名单中。 我是白名单的支持者,但更多是为了节省计算而不是改善过滤。我曾经认为白名单会使过滤更容易,因为你只需要过滤从未听说过的人发来的邮件,而第一次给你发邮件的人在可以对你说的话上受到惯例的限制。你已经认识的人可能会给你发一封谈论性的邮件,但第一次给你发邮件的人不太可能这样做。问题是,人们可以有多个电子邮件地址,因此一个新的发件人地址并不能保证发件人是第一次给你写信。一个老朋友(尤其是如果他是一个黑客)突然用一个新发件人地址给你发邮件并不罕见,因此你不能冒险通过特别严格地过滤来自未知地址的邮件而产生误判。 在某种意义上,我的过滤器本身体现了一种白名单(和黑名单),因为它们基于包括标题在内的整个邮件。因此,它们在某种程度上“知道”可信发件人的电子邮件地址,甚至邮件从他们到我这里的路径。它们也知道垃圾邮件的相同信息,包括服务器名称、邮件程序版本和协议。 _ _ _ 如果我认为可以保持当前的垃圾邮件过滤率,我会认为这个问题已经解决。但能够过滤掉当前大多数垃圾邮件并不意味着什么,因为垃圾邮件在演变。事实上,大多数反垃圾邮件技术到目前为止就像杀虫剂,除了产生新的抗药性虫害外什么也没做。 我对贝叶斯过滤器更有希望,因为它们与垃圾邮件一起演变。因此,当垃圾邮件发送者开始使用“c0ck”而不是“cock”来逃避基于单个单词的简单垃圾邮件过滤器时,贝叶斯过滤器会自动注意到。事实上,“c0ck”比“cock”更有力的证据,贝叶斯过滤器准确地知道有多少。 尽管如此,任何提出垃圾邮件过滤计划的人都必须能够回答这个问题:如果垃圾邮件发送者确切知道你在做什么,他们能多大程度上绕过你?例如,我认为如果基于校验和的垃圾邮件过滤成为一个严重的障碍,垃圾邮件发送者会转而使用填空技术生成邮件正文。 要击败贝叶斯过滤器,垃圾邮件发送者仅仅使他们的邮件唯一或停止使用个别不良词汇是不够的。他们必须使他们的邮件与你的普通邮件无法区分。我认为这将严重限制他们。垃圾邮件大多是销售宣传,因此除非你的普通邮件全是销售宣传,否则垃圾邮件不可避免地会有不同的特点。当然,垃圾邮件发送者还必须改变(并不断改变)他们的整个基础设施,否则无论他们对邮件正文做了什么,标题对贝叶斯过滤器来说仍然看起来很糟糕。我对垃圾邮件发送者使用的基础设施了解不够,不知道使标题看起来无辜有多难,但我的猜测是这比使邮件看起来无辜更难。 假设他们能解决标题问题,未来的垃圾邮件可能会是这样的: 嘿,你应该看看这个:http://www.27meg.com/foo 因为基于内容的过滤给垃圾邮件发送者留下的空间大约就是这么多销售宣传。(事实上,即使这样也很难通过过滤器,因为如果邮件中的其他所有内容都是中性的,垃圾邮件的概率将取决于URL,而要使URL看起来中性需要一些努力。) 垃圾邮件发送者的范围从运行所谓的“选择加入”列表甚至不试图隐藏身份的企业,到劫持邮件服务器发送宣传色情网站的垃圾邮件的家伙。如果我们使用过滤将他们的选择范围缩小到像上面这样的邮件,那应该会让垃圾邮件发送者中“合法”的一端破产;他们感到有义务根据各种州法律包括关于为什么他们的垃圾邮件不是垃圾邮件的样板文件,以及如何取消“订阅”,而这种文本很容易识别。 (我曾经认为相信更严格的法律会减少垃圾邮件是天真的。现在我认为,虽然更严格的法律可能不会减少垃圾邮件发送者发送的垃圾邮件数量,但它们肯定可以帮助过滤器减少收件人实际看到的垃圾邮件数量。) 在整个范围内,如果你限制垃圾邮件发送者可以做的销售宣传,你不可避免地会让他们破产。记住“business”这个词很重要。垃圾邮件发送者是商人。他们发送垃圾邮件是因为它有效。它有效是因为尽管响应率低得可怕(最多每百万15次,而目录邮寄为每百万3000次),但对他们来说成本几乎为零。对收件人来说成本是巨大的,每百万收件人花一秒删除垃圾邮件大约需要5人周,但垃圾邮件发送者不必支付这笔费用。 发送垃圾邮件确实会给垃圾邮件发送者带来一些成本。[2]因此,我们能够将响应率降低得越多——无论是通过过滤,还是通过使用过滤器迫使垃圾邮件发送者稀释他们的宣传——越少的企业会发现发送垃圾邮件值得。 垃圾邮件发送者使用他们所做的销售宣传类型的原因是提高响应率。这可能比进入垃圾邮件发送者的思维更令人厌恶,但让我们快速看一下回应垃圾邮件的人的思维。这个人要么令人难以置信地轻信,要么深深地否认他们的性兴趣。无论是哪种情况,垃圾邮件对我们来说看起来多么令人反感或愚蠢,对他们来说是令人兴奋的。垃圾邮件发送者如果不说这些听起来令人兴奋的话就不会说这些话。而“你应该看看这个”对垃圾邮件接收者的吸引力远不如垃圾邮件发送者现在说的那些话。结果:如果它不能包含令人兴奋的销售宣传,垃圾邮件作为营销工具的效果就会降低,更少的企业会想使用它。 这是最终的巨大胜利。我开始编写垃圾邮件过滤软件是因为我不想再看这些东西了。但如果我们过滤垃圾邮件的能力足够好,它将停止工作,垃圾邮件发送者实际上会停止发送它。 _ _ _ 在所有对抗垃圾邮件的方法中,从软件到法律,我相信贝叶斯过滤将是最有效的单一方法。但我也认为,我们采取的不同类型的反垃圾邮件努力越多越好,因为任何限制垃圾邮件发送者的措施都会使过滤更容易。即使在基于内容的过滤领域内,我认为同时使用许多不同类型的软件也是一件好事。过滤器越多,垃圾邮件发送者调整邮件以通过它们的难度就越大。 附录:过滤示例 这里是我在写这篇文章时收到的一封垃圾邮件的示例。这封垃圾邮件中最有趣的十五个词是: qvp0045 indira mx-05 intimail $7500 freeyankeedom cdo bluefoxmedia jpg unsecured platinum 3d0 qves 7c5 7c266675 这些词是标题和邮件正文的混合,这是垃圾邮件的典型特征。同样典型的是,在我的数据库中,这些词中的每一个的垃圾邮件概率都是0.99。实际上,有超过十五个词的垃圾邮件概率为0.99,这些只是前十五个。 不幸的是,这使得这封邮件成为贝叶斯规则应用的一个无聊例子。要看到各种有趣的概率,我们必须看看这封实际上相当不典型的垃圾邮件。 这封垃圾邮件中最有趣的十五个词及其概率是: madam 0.99 promotion 0.99 republic 0.99 shortest 0.047225013 mandatory 0.047225013 standardization 0.07347802 sorry 0.08221981 supported 0.09019077 people's 0.09019077 enter 0.9075001 quality 0.8921298 organization 0.12454646 investment 0.8568143 very 0.14758544 valuable 0.82347786 这次的证据是好坏参半。像“shortest”这样的词几乎和“madam”或“promotion”这样的词对罪证的贡献一样大。但罪证仍然更强。如果你根据贝叶斯规则结合这些数字,得到的概率是0.9027。 “Madam”显然来自以“亲爱的先生或女士”开头的垃圾邮件。它们不是很常见,但“madam”这个词在我的合法邮件中从未出现过,这完全是比例的问题。 “Republic”得分高是因为它经常出现在尼日利亚诈骗邮件中,也在一两封提到韩国和南非的垃圾邮件中出现过。你可能会说它帮助识别这封垃圾邮件是偶然的。但我在检查垃圾邮件概率时发现,有很多这样的偶然,它们有一种不可思议的趋势,会推动事情向正确的方向发展而不是错误的方向。在这种情况下,“Republic”出现在尼日利亚诈骗邮件和这封垃圾邮件中并不完全是巧合。有一整类涉及欠发达国家的可疑商业提案,而这些国家更有可能明确指定(因为它们不是)它们是共和国的名称。[3] 另一方面,“enter”是一个真正的失误。它主要出现在退订说明中,但在这里以一种完全无辜的方式使用。幸运的是,统计方法相当稳健,可以在结果开始偏离之前容忍相当多的失误。 作为对比,这里是一个罕见的例子,一封通过过滤器的垃圾邮件。为什么?因为纯粹偶然,它恰好充满了出现在我实际邮件中的词: perl 0.01 python 0.01 tcl 0.01 scripting 0.01 morris 0.01 graham 0.01491078 guarantee 0.9762507 cgi 0.973.
Want to start a startup? Get funded by Y Combinator.
May 2002 "We were after the C++ programmers. We managed to drag a lot of them about halfway to Lisp." \- Guy Steele, co-author of the Java spec
In the software business there is an ongoing struggle between the pointy-headed academics, and another equally formidable force, the pointy-haired bosses. Everyone knows who the pointy-haired boss is, right? I think most people in the technology world not only recognize this cartoon character, but know the actual person in their company that he is modelled upon. The pointy-haired boss miraculously combines two qualities that are common by themselves, but rarely seen together: (a) he knows nothing whatsoever about technology, and (b) he has very strong opinions about it. Suppose, for example, you need to write a piece of software. The pointy-haired boss has no idea how this software has to work, and can't tell one programming language from another, and yet he knows what language you should write it in. Exactly. He thinks you should write it in Java. Why does he think this? Let's take a look inside the brain of the pointy-haired boss. What he's thinking is something like this. Java is a standard. I know it must be, because I read about it in the press all the time. Since it is a standard, I won't get in trouble for using it. And that also means there will always be lots of Java programmers, so if the programmers working for me now quit, as programmers working for me mysteriously always do, I can easily replace them. Well, this doesn't sound that unreasonable. But it's all based on one unspoken assumption, and that assumption turns out to be false. The pointy-haired boss believes that all programming languages are pretty much equivalent. If that were true, he would be right on target. If languages are all equivalent, sure, use whatever language everyone else is using.
想创业吗? 获得Y Combinator的资助。
2002年5月 “我们原本瞄准C++程序员,结果成功把他们中的许多人拽到了离Lisp还剩一半路程的地方。” ——Java规范合著者 Guy Steele
软件行业始终存在着两股势力的斗争:一派是脑袋尖尖的学院派,另一派是同样难缠的头发尖尖的老板派。大家都知道“头发尖尖的老板”是什么形象吧?我相信科技界大多数人不仅认得这个漫画角色,还能在自己公司里找到对应的真人原型。
这位头发尖尖的老板神奇地结合了两种常见却鲜少共存的特质:(a) 他对技术一窍不通;(b) 却对技术决策有着异常坚定的主张。
But all languages are not equivalent, and I think I can prove this to you without even getting into the differences between them. If you asked the pointy-haired boss in 1992 what language software should be written in, he would have answered with as little hesitation as he does today. Software should be written in C++. But if languages are all equivalent, why should the pointy-haired boss's opinion ever change? In fact, why should the developers of Java have even bothered to create a new language? Presumably, if you create a new language, it's because you think it's better in some way than what people already had. And in fact, Gosling makes it clear in the first Java white paper that Java was designed to fix some problems with C++. So there you have it: languages are not all equivalent. If you follow the trail through the pointy-haired boss's brain to Java and then back through Java's history to its origins, you end up holding an idea that contradicts the assumption you started with. So, who's right? James Gosling, or the pointy-haired boss? Not surprisingly, Gosling is right. Some languages _are_ better, for certain problems, than others. And you know, that raises some interesting questions. Java was designed to be better, for certain problems, than C++. What problems? When is Java better and when is C++? Are there situations where other languages are better than either of them? Once you start considering this question, you have opened a real can of worms. If the pointy-haired boss had to think about the problem in its full complexity, it would make his brain explode. As long as he considers all languages equivalent, all he has to do is choose the one that seems to have the most momentum, and since that is more a question of fashion than technology, even he can probably get the right answer.
举个例子,假设你需要开发一款软件。这位老板既不懂软件运行原理,也分不清编程语言的区别,却能斩钉截铁地指定开发语言——必须是Java。
为什么?让我们透视他的思维逻辑:Java是行业标准(因为媒体总在报道),选用它就不会惹麻烦;既然是标准,Java程序员必然遍地都是,当前团队若像往常一样神秘离职,替补人手随时能找到。
But if languages vary, he suddenly has to solve two simultaneous equations, trying to find an optimal balance between two things he knows nothing about: the relative suitability of the twenty or so leading languages for the problem he needs to solve, and the odds of finding programmers, libraries, etc. for each. If that's what's on the other side of the door, it is no surprise that the pointy-haired boss doesn't want to open it. The disadvantage of believing that all programming languages are equivalent is that it's not true. But the advantage is that it makes your life a lot simpler. And I think that's the main reason the idea is so widespread. It is a _comfortable_ idea. We know that Java must be pretty good, because it is the cool, new programming language. Or is it? If you look at the world of programming languages from a distance, it looks like Java is the latest thing. (From far enough away, all you can see is the large, flashing billboard paid for by Sun.) But if you look at this world up close, you find that there are degrees of coolness. Within the hacker subculture, there is another language called Perl that is considered a lot cooler than Java. Slashdot, for example, is generated by Perl. I don't think you would find those guys using Java Server Pages. But there is another, newer language, called Python, whose users tend to look down on Perl, and more waiting in the wings. If you look at these languages in order, Java, Perl, Python, you notice an interesting pattern. At least, you notice this pattern if you are a Lisp hacker. Each one is progressively more like Lisp. Python copies even features that many Lisp hackers consider to be mistakes. You could translate simple Lisp programs into Python line for line.
这套说辞看似合理,实则建立在某个未被言明的错误假设上:老板认为所有编程语言都差不多。若真如此,他的选择确实明智——既然语言没差别,随大流最稳妥。
但语言之间真的没有优劣之分吗?我们甚至无需讨论具体差异就能证伪这一点。若在1992年问同一位老板该用什么语言,他会毫不犹豫回答C++。如果语言真没区别,为何他的答案会随时间改变?更根本的问题是:若语言等同,Java开发者何必费心创造新语言?
显然,新语言的诞生必然源于对旧语言的改进。Java之父高斯林在白皮书中明确表示,Java正是为解决C++的某些缺陷而设计。至此矛盾显现:语言并非等同。顺着老板的思维追溯到Java,再回溯Java的诞生动机,最终得出的结论恰恰推翻了他最初的假设。
It's 2002, and programming languages have almost caught up with 1958. Catching Up with Math What I mean is that Lisp was first discovered by John McCarthy in 1958, and popular programming languages are only now catching up with the ideas he developed then. Now, how could that be true? Isn't computer technology something that changes very rapidly? I mean, in 1958, computers were refrigerator-sized behemoths with the processing power of a wristwatch. How could any technology that old even be relevant, let alone superior to the latest developments? I'll tell you how. It's because Lisp was not really designed to be a programming language, at least not in the sense we mean today. What we mean by a programming language is something we use to tell a computer what to do. McCarthy did eventually intend to develop a programming language in this sense, but the Lisp that we actually ended up with was based on something separate that he did as a theoretical exercise\-- an effort to define a more convenient alternative to the Turing Machine. As McCarthy said later,.
那么谁是对的?高斯林还是头发尖尖的老板?答案不言自明。特定场景下,某些语言确实更具优势。这引出了更深层的问题:Java针对哪些场景优化?何时该用Java而非C++?是否存在比二者更优的其他选择?
一旦开始思考这些问题,就如同打开了潘多拉魔盒。若老板必须处理如此复杂的决策,他的大脑恐怕会当场宕机。只要坚信语言等同,他只需选择最流行的选项——这本就是时尚而非技术问题,他或许还能蒙对。但若承认语言差异,他就得同时求解两道难题:既要评估二十多种主流语言对当前需求的适配度(对此他一无所知),又要权衡每种语言的程序员储备和库资源(同样超出他的认知)。面对这扇门后的复杂世界,老板选择回避也就不足为奇了。
> Another way to show that Lisp was neater than Turing machines was to write a universal Lisp function and show that it is briefer and more comprehensible than the description of a universal Turing machine. This was the Lisp function _eval_..., which computes the value of a Lisp expression.... Writing _eval_ required inventing a notation representing Lisp functions as Lisp data, and such a notation was devised for the purposes of the paper with no thought that it would be used to express Lisp programs in practice.
坚信语言等同的代价是背离真相,但好处是让生活简单得多。我认为这正是该观点盛行的主因——它令人心安理得。
我们觉得Java肯定很优秀,因为它是时髦的新语言。但果真如此吗?从宏观视角看,Java确实是编程语言界的新贵(尤其当你的视野被Sun公司的巨幅广告占据时)。但贴近观察会发现,极客圈对“酷”的评判存在梯度:在黑客亚文化中,Perl的酷炫指数远超Java(比如Slashdot就用Perl搭建,你绝对看不到这帮人用JSP)。而比Perl更年轻的Python,其用户又对Perl流露出优越感,还有更多新语言正在崛起。
What happened next was that, some time in late 1958, Steve Russell, one of McCarthy's grad students, looked at this definition of _eval_ and realized that if he translated it into machine language, the result would be a Lisp interpreter. This was a big surprise at the time. Here is what McCarthy said about it later in an interview:
观察Java、Perl、Python的演进轨迹,会发现耐人寻味的规律——至少Lisp黑客能看出来。每种新语言都越来越像Lisp,Python甚至复刻了被许多Lisp黑客视为设计缺陷的特性。如今简单Lisp程序已能逐行翻译成Python。2002年的编程语言,终于快要追上1958年的水准。
追赶数学的脚步
我的意思是:约翰·麦卡锡在1958年发现的Lisp语言,其理念直到今天才被主流编程语言逐步赶上。
> Steve Russell said, look, why don't I program this _eval_..., and I said to him, ho, ho, you're confusing theory with practice, this _eval_ is intended for reading, not for computing. But he went ahead and did it. That is, he compiled the _eval_ in my paper into [IBM] 704 machine code, fixing bugs, and then advertised this as a Lisp interpreter, which it certainly was. So at that point Lisp had essentially the form that it has today....
这怎么可能?计算机技术不是日新月异吗?1958年的计算机还是冰箱大小的庞然大物,运算能力堪比电子表。如此古老的技术怎会仍具价值,甚至优于最新成果?
答案在于:Lisp最初根本不是作为现代意义上的编程语言设计的。我们所说的编程语言是向计算机下达指令的工具。虽然麦卡锡最终确实想开发这种工具,但实际成型的Lisp却源于他的理论探索——为图灵机寻找更便捷的替代方案。正如他后来所言,
Suddenly, in a matter of weeks I think, McCarthy found his theoretical exercise transformed into an actual programming language-- and a more powerful one than he had intended. So the short explanation of why this 1950s language is not obsolete is that it was not technology but math, and math doesn't get stale. The right thing to compare Lisp to is not 1950s hardware, but, say, the Quicksort algorithm, which was discovered in 1960 and is still the fastest general-purpose sort. There is one other language still surviving from the 1950s, Fortran, and it represents the opposite approach to language design. Lisp was a piece of theory that unexpectedly got turned into a programming language. Fortran was developed intentionally as a programming language, but what we would now consider a very low-level one. Fortran I, the language that was developed in 1956, was a very different animal from present-day Fortran. Fortran I was pretty much assembly language with math. In some ways it was less powerful than more recent assembly languages; there were no subroutines, for example, only branches. Present-day Fortran is now arguably closer to Lisp than to Fortran I. Lisp and Fortran were the trunks of two separate evolutionary trees, one rooted in math and one rooted in machine architecture. These two trees have been converging ever since. Lisp started out powerful, and over the next twenty years got fast. So-called mainstream languages started out fast, and over the next forty years gradually got more powerful, until now the most advanced of them are fairly close to Lisp. Close, but they are still missing a few things.... What Made Lisp Different When it was first developed, Lisp embodied nine new ideas. Some of these we now take for granted, others are only seen in more advanced languages, and two are still unique to Lisp. The nine ideas are, in order of their adoption by the mainstream,
另一种证明Lisp比图灵机更简洁的方法是编写一个通用Lisp函数,并展示它比通用图灵机的描述更简短易懂。这个Lisp函数就是_eval_...,它能计算Lisp表达式的值......编写_eval_需要发明一种将Lisp函数表示为Lisp数据的符号,这种符号在论文中被设计出来时,完全没想过它会在实践中用于表达Lisp程序。
接下来的事情发生在1958年末,麦卡锡的研究生史蒂夫·拉塞尔看到了这个_eval_的定义,意识到如果将其翻译成机器语言,结果将成为一个Lisp解释器。
这在当时是个巨大的惊喜。后来麦卡锡在采访中这样描述:
1. Conditionals. A conditional is an if-then-else construct. We take these for granted now, but Fortran I didn't have them. It had only a conditional goto closely based on the underlying machine instruction.
> 史蒂夫·拉塞尔说,看,我为什么不把这个_eval_程序化呢?我对他说,呵呵,你把理论和实践搞混了,这个_eval_是用来阅读的,不是用来计算的。但他还是去做了。也就是说,他将我论文中的_eval_编译成[IBM]704机器码,修复了一些错误,然后将其作为Lisp解释器发布——它确实就是。所以从那时起,Lisp基本上就有了今天的形式......
转眼间,大约就在几周之内,麦卡锡发现他的理论构想竟蜕变成了一门真正的编程语言——其强大程度甚至超出了他的预期。
2. A function type. In Lisp, functions are a data type just like integers or strings. They have a literal representation, can be stored in variables, can be passed as arguments, and so on.
因此,要解释这门诞生于1950年代的语言为何不过时,关键在于它本质并非技术而是数学,而数学永不褪色。Lisp真正应该对比的对象不是1950年代的硬件,而是诸如1960年问世至今仍是最快通用排序算法的快速排序。
1950年代幸存至今的另一门语言Fortran,则代表了语言设计的对立路径。Lisp本是意外成为编程语言的数学理论,Fortran则是刻意设计的编程语言——但以今日标准看是极其底层的语言。
3. Recursion. Lisp was the first programming language to support it.
1956年问世的Fortran I与当代Fortran截然不同。它本质上是带有数学运算的汇编语言,某些方面甚至不及现代汇编语言强大——例如没有子程序概念,只有跳转指令。如今的Fortran可以说更接近Lisp而非其始祖Fortran I。
Lisp与Fortran如同两棵进化树的树干,分别植根于数学理论与机器架构。此后这两棵树不断趋同:Lisp始于强大,随后二十年追求速度;所谓主流语言始于速度,此后四十年逐步增强表现力,如今最先进的已相当接近Lisp——接近,但仍缺几项关键要素……
Lisp的独特基因
4. Dynamic typing. In Lisp, all variables are effectively pointers. Values are what have types, not variables, and assigning or binding variables means copying pointers, not what they point to.
初创之时,Lisp蕴含九大创新理念。其中部分已成常识,部分仅见于前沿语言,仍有两点至今为Lisp独有。按被主流采纳的顺序排列:
1. 条件语句。即if-then-else结构。如今视若平常,但Fortran I仅提供基于底层机器指令的条件跳转。
5. Garbage-collection.
2. 函数类型。在Lisp中,函数与整数、字符串同属数据类型,具有字面量表示法,可存入变量,能作为参数传递。
3. 递归支持。Lisp是首个支持递归的编程语言。
4. 动态类型。Lisp中所有变量实质都是指针。类型属于值而非变量,变量赋值或绑定实为指针复制而非值拷贝。
6. Programs composed of expressions. Lisp programs are trees of expressions, each of which returns a value. This is in contrast to Fortran and most succeeding languages, which distinguish between expressions and statements. It was natural to have this distinction in Fortran I because you could not nest statements. And so while you needed expressions for math to work, there was no point in making anything else return a value, because there could not be anything waiting for it. This limitation went away with the arrival of block-structured languages, but by then it was too late. The distinction between expressions and statements was entrenched. It spread from Fortran into Algol and then to both their descendants.
6. 由表达式构成的程序。Lisp程序是由表达式构成的树形结构,每个表达式都会返回一个值。这与Fortran及大多数后续语言形成鲜明对比——后者严格区分表达式与语句。
这种区分在Fortran I中很自然,因为当时语句不能嵌套。虽然数学运算需要表达式,但让其他结构返回值毫无意义,毕竟没有任何代码能接收这些值。
7. A symbol type. Symbols are effectively pointers to strings stored in a hash table. So you can test equality by comparing a pointer, instead of comparing each character.
随着块结构语言的出现,这种限制消失了,但为时已晚。表达式与语句的区分已根深蒂固,从Fortran蔓延到Algol,继而影响了它们的所有后代语言。
7. 符号类型。符号本质上是指向哈希表中字符串的指针。因此可以通过比较指针来测试相等性,无需逐字符比对。
8. A notation for code using trees of symbols and constants.
8. 使用符号与常量树形结构表示代码的标记法。
9. 全时态语言。读取时、编译时与运行时之间没有真正界限:你可以在读取时编译或运行代码,在编译时读取或运行代码,在运行时读取或编译代码。
读取时运行代码让用户能重定义Lisp语法;编译时运行代码是宏系统的根基;运行时编译代码使Lisp成为Emacs等程序的扩展语言;运行时读取代码则让程序能通过s表达式通信——这个理念后来以XML的形式被重新发明。
9. The whole language there all the time. There is no real distinction between read-time, compile-time, and runtime. You can compile or run code while reading, read or run code while compiling, and read or compile code at runtime. Running code at read-time lets users reprogram Lisp's syntax; running code at compile-time is the basis of macros; compiling at runtime is the basis of Lisp's use as an extension language in programs like Emacs; and reading at runtime enables programs to communicate using s-expressions, an idea recently reinvented as XML.
当Lisp首次问世时,这些理念与1950年代末期受硬件限制的主流编程实践相去甚远。随着时间的推移,以一系列流行语言为代表的默认语言正逐步向Lisp靠拢。理念1-5现已广泛普及,理念6开始进入主流视野,Python虽具备理念7的某种形式却缺乏对应语法。
而理念8可能是其中最耐人寻味的。理念8和9能成为Lisp的一部分纯属偶然,源于Steve Russell实现了McCarthy从未打算落地的构想。正是这些意外造就了Lisp奇特的外表与最鲜明的特质。Lisp的怪异并非源于特殊语法,而是因其本质上没有语法——你直接操作的是其他语言解析时生成的语法树,这些由Lisp原生链表构成的数据结构。
When Lisp first appeared, these ideas were far removed from ordinary programming practice, which was dictated largely by the hardware available in the late 1950s. Over time, the default language, embodied in a succession of popular languages, has gradually evolved toward Lisp. Ideas 1-5 are now widespread. Number 6 is starting to appear in the mainstream. Python has a form of 7, though there doesn't seem to be any syntax for it. As for number 8, this may be the most interesting of the lot. Ideas 8 and 9 only became part of Lisp by accident, because Steve Russell implemented something McCarthy had never intended to be implemented. And yet these ideas turn out to be responsible for both Lisp's strange appearance and its most distinctive features. Lisp looks strange not so much because it has a strange syntax as because it has no syntax; you express programs directly in the parse trees that get built behind the scenes when other languages are parsed, and these trees are made of lists, which are Lisp data structures. Expressing the language in its own data structures turns out to be a very powerful feature. Ideas 8 and 9 together mean that you can write programs that write programs. That may sound like a bizarre idea, but it's an everyday thing in Lisp. The most common way to do it is with something called a _macro._ The term "macro" does not mean in Lisp what it means in other languages. A Lisp macro can be anything from an abbreviation to a compiler for a new language. If you want to really understand Lisp, or just expand your programming horizons, I would learn more about macros. Macros (in the Lisp sense) are still, as far as I know, unique to Lisp. This is partly because in order to have macros you probably have to make your language look as strange as Lisp. It may also be because if you do add that final increment of power, you can no longer claim to have invented a new language, but only a new dialect of Lisp.
用语言自身的数据结构来表达程序被证明是革命性的特性。理念8与9的结合意味着你能编写生成程序的程序。这听起来或许离奇,却是Lisp的日常实践,最典型的实现方式就是宏。
"宏"在Lisp中的内涵远超其他语言。从简写到新语言的编译器,Lisp宏无所不包。若要真正理解Lisp或拓展编程视野,深入宏机制至关重要。
据我所知,真正的宏系统仍是Lisp的独门绝技。部分原因在于实现宏需要承受Lisp式的语法异质,更因为一旦突破这层能力极限,你所创造的将不再是新语言,而是Lisp的新方言。
I mention this mostly as a joke, but it is quite true. If you define a language that has car, cdr, cons, quote, cond, atom, eq, and a notation for functions expressed as lists, then you can build all the rest of Lisp out of it. That is in fact the defining quality of Lisp: it was in order to make this so that McCarthy gave Lisp the shape it has. Where Languages Matter So suppose Lisp does represent a kind of limit that mainstream languages are approaching asymptotically-- does that mean you should actually use it to write software? How much do you lose by using a less powerful language? Isn't it wiser, sometimes, not to be at the very edge of innovation? And isn't popularity to some extent its own justification? Isn't the pointy-haired boss right, for example, to want to use a language for which he can easily hire programmers? There are, of course, projects where the choice of programming language doesn't matter much. As a rule, the more demanding the application, the more leverage you get from using a powerful language. But plenty of projects are not demanding at all. Most programming probably consists of writing little glue programs, and for little glue programs you can use any language that you're already familiar with and that has good libraries for whatever you need to do. If you just need to feed data from one Windows app to another, sure, use Visual Basic. You can write little glue programs in Lisp too (I use it as a desktop calculator), but the biggest win for languages like Lisp is at the other end of the spectrum, where you need to write sophisticated programs to solve hard problems in the face of fierce competition. A good example is the airline fare search program that ITA Software licenses to Orbitz. These guys entered a market already dominated by two big, entrenched competitors, Travelocity and Expedia, and seem to have just humiliated them technologically.
虽是玩笑却属事实:若某语言包含car、cdr、cons、quote、cond、atom、eq等基本操作,以及基于链表的函数表示法,你就能重建整个Lisp体系——这正是McCarthy设计Lisp时的核心追求。
语言的用武之地
The core of ITA's application is a 200,000 line Common Lisp program that searches many orders of magnitude more possibilities than their competitors, who apparently are still using mainframe-era programming techniques. (Though ITA is also in a sense using a mainframe-era programming language.) I have never seen any of ITA's code, but according to one of their top hackers they use a lot of macros, and I am not surprised to hear it. Centripetal Forces I'm not saying there is no cost to using uncommon technologies. The pointy-haired boss is not completely mistaken to worry about this. But because he doesn't understand the risks, he tends to magnify them. I can think of three problems that could arise from using less common languages. Your programs might not work well with programs written in other languages. You might have fewer libraries at your disposal. And you might have trouble hiring programmers. How much of a problem is each of these? The importance of the first varies depending on whether you have control over the whole system. If you're writing software that has to run on a remote user's machine on top of a buggy, closed operating system (I mention no names), there may be advantages to writing your application in the same language as the OS. But if you control the whole system and have the source code of all the parts, as ITA presumably does, you can use whatever languages you want. If any incompatibility arises, you can fix it yourself. In server-based applications you can get away with using the most advanced technologies, and I think this is the main cause of what Jonathan Erickson calls the "programming language renaissance." This is why we even hear about new languages like Perl and Python. We're not hearing about these languages because people are using them to write Windows apps, but because people are using them on servers.
假设Lisp确为渐进逼近的极限,是否意味着应该用它开发软件?选择弱语言会损失多少?保持技术领先是否永远明智?流行度本身能否成为理由?比如技术外行主管坚持选用易招聘的语言是否正确?
当然存在编程语言无关紧要的项目。通常应用越复杂,强语言的杠杆效应越显著。但多数项目并不苛刻,日常编程多为胶水代码,此时选用熟悉且库支持良好的语言即可。例如Windows应用间数据传输,Visual Basic足矣。
And as software shifts off the desktop and onto servers (a future even Microsoft seems resigned to), there will be less and less pressure to use middle-of-the-road technologies. As for libraries, their importance also depends on the application. For less demanding problems, the availability of libraries can outweigh the intrinsic power of the language. Where is the breakeven point? Hard to say exactly, but wherever it is, it is short of anything you'd be likely to call an application. If a company considers itself to be in the software business, and they're writing an application that will be one of their products, then it will probably involve several hackers and take at least six months to write. In a project of that size, powerful languages probably start to outweigh the convenience of pre-existing libraries. The third worry of the pointy-haired boss, the difficulty of hiring programmers, I think is a red herring. How many hackers do you need to hire, after all? Surely by now we all know that software is best developed by teams of less than ten people. And you shouldn't have trouble hiring hackers on that scale for any language anyone has ever heard of. If you can't find ten Lisp hackers, then your company is probably based in the wrong city for developing software. In fact, choosing a more powerful language probably decreases the size of the team you need, because (a) if you use a more powerful language you probably won't need as many hackers, and (b) hackers who work in more advanced languages are likely to be smarter. I'm not saying that you won't get a lot of pressure to use what are perceived as "standard" technologies. At Viaweb (now Yahoo Store), we raised some eyebrows among VCs and potential acquirers by using Lisp.
虽能用Lisp编写胶水程序(我常用作桌面计算器),但其真正优势在于解决竞争激烈的复杂问题。典型案例是ITA软件为Orbitz开发的机票搜索系统——在Travelocity和Expedia垄断的市场中,他们用技术碾压了对手。
ITA的核心是20万行Common Lisp代码,其搜索能力超越仍在使用大型机时代技术的竞争对手数个量级。虽然ITA本质上也在使用"大型机时代语言",但其工程师透露大量使用宏的事实毫不令人意外。
非常规技术确有代价,技术外行主管的担忧不无道理。但因认知局限,他们往往夸大风险。
But we also raised eyebrows by using generic Intel boxes as servers instead of "industrial strength" servers like Suns, for using a then-obscure open-source Unix variant called FreeBSD instead of a real commercial OS like Windows NT, for ignoring a supposed e-commerce standard called SET that no one now even remembers, and so on. You can't let the suits make technical decisions for you. Did it alarm some potential acquirers that we used Lisp? Some, slightly, but if we hadn't used Lisp, we wouldn't have been able to write the software that made them want to buy us. What seemed like an anomaly to them was in fact cause and effect. If you start a startup, don't design your product to please VCs or potential acquirers. _Design your product to please the users._ If you win the users, everything else will follow. And if you don't, no one will care how comfortingly orthodox your technology choices were. The Cost of Being Average How much do you lose by using a less powerful language? There is actually some data out there about that. The most convenient measure of power is probably code size. The point of high-level languages is to give you bigger abstractions-- bigger bricks, as it were, so you don't need as many to build a wall of a given size. So the more powerful the language, the shorter the program (not simply in characters, of course, but in distinct elements). How does a more powerful language enable you to write shorter programs? One technique you can use, if the language will let you, is something called bottom-up programming. Instead of simply writing your application in the base language, you build on top of the base language a language for writing programs like yours, then write your program in it.
使用小众语言可能引发三个问题:与其他语言交互障碍、可用库较少、招聘困难。这些问题的严重性取决于场景。若控制整个系统(如ITA掌握全部源码),语言选择完全自主,兼容性问题可自行修复。
服务器端应用更能接纳先进技术,这正是Jonathan Erickson所称"编程语言复兴"的主因。Perl和Python的兴起正源于服务器端应用。随着软件从桌面转向服务器(微软也不得不接受的趋势),中庸技术的压力将日益减弱。
The combined code can be much shorter than if you had written your whole program in the base language-- indeed, this is how most compression algorithms work. A bottom-up program should be easier to modify as well, because in many cases the language layer won't have to change at all. Code size is important, because the time it takes to write a program depends mostly on its length. If your program would be three times as long in another language, it will take three times as long to write-- and you can't get around this by hiring more people, because beyond a certain size new hires are actually a net lose. Fred Brooks described this phenomenon in his famous book _The Mythical Man-Month,_ and everything I've seen has tended to confirm what he said. So how much shorter are your programs if you write them in Lisp? Most of the numbers I've heard for Lisp versus C, for example, have been around 7-10x. But a recent article about ITA in _New Architect_ magazine said that "one line of Lisp can replace 20 lines of C," and since this article was full of quotes from ITA's president, I assume they got this number from ITA. If so then we can put some faith in it; ITA's software includes a lot of C and C++ as well as Lisp, so they are speaking from experience. My guess is that these multiples aren't even constant. I think they increase when you face harder problems and also when you have smarter programmers. A really good hacker can squeeze more out of better tools. As one data point on the curve, at any rate, if you were to compete with ITA and chose to write your software in C, they would be able to develop software twenty times faster than you. If you spent a year on a new feature, they'd be able to duplicate it in less than three weeks. Whereas if they spent just three months developing something new, it would be _five years_ before you had it too.
库的重要性因项目而异:简单问题中现成库的价值可能超越语言本身。但对企业级软件产品(需多名程序员耗时半年以上开发),强语言的优势终将显现。
关于招聘难题实属过虑:优秀软件团队从不超过十人,任何知名语言都能满足此规模需求。若连十个Lisp程序员都招不到,恐怕公司选址本身就有问题。实际上,强语言可能缩减团队规模——既因需求减少,也因使用先进语言的程序员通常更优秀。
在Viaweb(现Yahoo Store)时期,我们使用Lisp、廉价Intel服务器、FreeBSD系统、无视SET标准等决策曾令投资人和收购方侧目。但最终证明,正是这些非常规选择创造了被收购的价值。
And you know what? That's the best-case scenario. When you talk about code-size ratios, you're implicitly assuming that you can actually write the program in the weaker language. But in fact there are limits on what programmers can do. If you're trying to solve a hard problem with a language that's too low-level, you reach a point where there is just too much to keep in your head at once. So when I say it would take ITA's imaginary competitor five years to duplicate something ITA could write in Lisp in three months, I mean five years if nothing goes wrong. In fact, the way things work in most companies, any development project that would take five years is likely never to get finished at all. I admit this is an extreme case. ITA's hackers seem to be unusually smart, and C is a pretty low-level language. But in a competitive market, even a differential of two or three to one would be enough to guarantee that you'd always be behind. A Recipe This is the kind of possibility that the pointy-haired boss doesn't even want to think about. And so most of them don't. Because, you know, when it comes down to it, the pointy-haired boss doesn't mind if his company gets their ass kicked, so long as no one can prove it's his fault. The safest plan for him personally is to stick close to the center of the herd. Within large organizations, the phrase used to describe this approach is "industry best practice." Its purpose is to shield the pointy-haired boss from responsibility: if he chooses something that is "industry best practice," and the company loses, he can't be blamed. He didn't choose, the industry did. I believe this term was originally used to describe accounting methods and so on. What it means, roughly, is _don't do anything weird._ And in accounting that's probably a good idea. The terms "cutting-edge" and "accounting" do not sound good together.
创业者当为用户而非投资人设计产品。赢得用户则万事俱备,失去用户则技术正统毫无意义。
弱语言的效率损失有据可循。代码规模是最直观的衡量标准——高级语言提供更大抽象单元,如同用更少砖块砌同等围墙。强语言程序更短(非指字符数,而是独立元素量)。
But when you import this criterion into decisions about technology, you start to get the wrong answers. Technology often _should_ be cutting-edge. In programming languages, as Erann Gat has pointed out, what "industry best practice" actually gets you is not the best, but merely the average. When a decision causes you to develop software at a fraction of the rate of more aggressive competitors, "best practice" is a misnomer. So here we have two pieces of information that I think are very valuable. In fact, I know it from my own experience. Number 1, languages vary in power. Number 2, most managers deliberately ignore this. Between them, these two facts are literally a recipe for making money. ITA is an example of this recipe in action. If you want to win in a software business, just take on the hardest problem you can find, use the most powerful language you can get, and wait for your competitors' pointy-haired bosses to revert to the mean..
强语言缩短代码的秘诀在于自底向上编程:在基础语言之上构建领域专用语言,再以其编写应用。这种组合代码远比纯基础语言实现更精简——正如压缩算法原理。其可维护性也更优,因为语言层通常无需改动。
代码规模至关重要,因为开发时间主要取决于长度。若某语言使代码膨胀三倍,耗时必然三倍——且无法通过增员解决,因为超限后新人只会拖累进度。Fred Brooks在《人月神话》中阐述的现象已被广泛证实。
Appendix: Power
As an illustration of what I mean about the relative power of programming languages, consider the following problem. We want to write a function that generates accumulators-- a function that takes a number n, and returns a function that takes another number i and returns n incremented by i.
(That's _incremented by_ , not plus. An accumulator has to accumulate.)
In Common Lisp this would be (defun foo (n) (lambda (i) (incf n i))) and in Perl 5, sub foo { my ($n) = @_; sub {$n += shift} } which has more elements than the Lisp version because you have to extract parameters manually in Perl.
In Smalltalk the code is slightly longer than in Lisp foo: n |s| s := n. ^[:i| s := s+i. ] because although in general lexical variables work, you can't do an assignment to a parameter, so you have to create a new variable s.
In Javascript the example is, again, slightly longer, because Javascript retains the distinction between statements and expressions, so you need explicit return statements to return values: function foo(n) { return function (i) { return n += i } } (To be fair, Perl also retains this distinction, but deals with it in typical Perl fashion by letting you omit returns.)
If you try to translate the Lisp/Perl/Smalltalk/Javascript code into Python you run into some limitations. Because Python doesn't fully support lexical variables, you have to create a data structure to hold the value of n. And although Python does have a function data type, there is no literal representation for one (unless the body is only a single expression) so you need to create a named function to return.
Lisp相较C语言的代码压缩比普遍达7-10倍。而《新架构师》杂志引述ITA总裁称"一行Lisp可抵二十行C"。鉴于ITA系统混合使用Lisp/C++,此数据可信度较高。
我认为该倍数并非恒定——问题越复杂,程序员越优秀,差距越大。顶尖黑客能更充分释放工具潜能。
以ITA为例:若你用C语言竞争,其开发速度将领先20倍。你耗时一年的功能,他们三周即可复现;他们三个月的新成果,你需要五年追赶——这还是最理想状况。实际上,当底层语言超出人脑负荷极限时,项目很可能永远无法完成。
This is what you end up with: def foo(n): s = [n] def bar(i): s[0] += i return s[0] return bar Python users might legitimately ask why they can't just write def foo(n): return lambda i: return n += i or even def foo(n): lambda i: n += i and my guess is that they probably will, one day. (But if they don't want to wait for Python to evolve the rest of the way into Lisp, they could always just...)
In OO languages, you can, to a limited extent, simulate a closure (a function that refers to variables defined in enclosing scopes) by defining a class with one method and a field to replace each variable from an enclosing scope. This makes the programmer do the kind of code analysis that would be done by the compiler in a language with full support for lexical scope, and it won't work if more than one function refers to the same variable, but it is enough in simple cases like this.
Python experts seem to agree that this is the preferred way to solve the problem in Python, writing either def foo(n): class acc: def __init__(self, s): self.s = s def inc(self, i): self.s += i return self.s return acc(n).inc or class foo: def __init__(self, n): self.n = n def __call__(self, i): self.n += i return self.n I include these because I wouldn't want Python advocates to say I was misrepresenting the language, but both seem to me more complex than the first version. You're doing the same thing, setting up a separate place to hold the accumulator; it's just a field in an object instead of the head of a list. And the use of these special, reserved field names, especially __call__, seems a bit of a hack.
In the rivalry between Perl and Python, the claim of the Python hackers seems to be that that Python is a more elegant alternative to Perl, but what this case shows is that power is the ultimate elegance: the Perl program is simpler (has fewer elements), even if the syntax is a bit uglier.
虽属极端案例(ITA团队异常优秀,C语言相对底层),但竞争市场中即便2-3倍效率差也足以决定生死。
技术外行主管拒绝思考这种可能性。只要失败无法归咎,他们甘愿公司落败。个人最安全的策略就是随大流。
How about other languages? In the other languages mentioned in this talk-- Fortran, C, C++, Java, and Visual Basic-- it is not clear whether you can actually solve this problem. Ken Anderson says that the following code is about as close as you can get in Java: public interface Inttoint { public int call(int i); } public static Inttoint foo(final int n) { return new Inttoint() { int s = n; public int call(int i) { s = s + i; return s; }}; } This falls short of the spec because it only works for integers. After many email exchanges with Java hackers, I would say that writing a properly polymorphic version that behaves like the preceding examples is somewhere between damned awkward and impossible. If anyone wants to write one I'd be very curious to see it, but I personally have timed out. It's not literally true that you can't solve this problem in other languages, of course. The fact that all these languages are Turing-equivalent means that, strictly speaking, you can write any program in any of them. So how would you do it? In the limit case, by writing a Lisp interpreter in the less powerful language. That sounds like a joke, but it happens so often to varying degrees in large programming projects that there is a name for the phenomenon, Greenspun's Tenth Rule:.
大企业称之为"行业最佳实践"——实为推卸责任的护身符。选择"最佳实践"意味着失败时无需担责:是行业的选择,而非个人决策。
该术语原用于会计领域,核心是"避免特立独行"。这在财务领域或许合理("前沿"与"会计"本就违和),但套用于技术决策就会酿成错误。技术本应追求前沿,正如Erann Gat所言:"行业最佳实践"带来的只是平庸。当决策导致开发效率被激进对手碾压时,"最佳"已成谬称。
因此我们获得两个珍贵认知:1. 语言能力存在差异;2. 多数管理者刻意忽视。二者结合便是致富配方。ITA的成功印证了这点:在软件行业制胜,只需挑战最难问题,选用最强语言,静待竞争对手的平庸管理者自缚手脚。
> Any sufficiently complicated C or Fortran program contains an ad hoc informally-specified bug-ridden slow implementation of half of Common Lisp.
书呆子的复仇(第6部分,共9部分)
附录:语言的威力
If you try to solve a hard problem, the question is not whether you will use a powerful enough language, but whether you will (a) use a powerful language, (b) write a de facto interpreter for one, or (c) yourself become a human compiler for one. We see this already begining to happen in the Python example, where we are in effect simulating the code that a compiler would generate to implement a lexical variable. This practice is not only common, but institutionalized. For example, in the OO world you hear a good deal about "patterns". I wonder if these patterns are not sometimes evidence of case (c), the human compiler, at work. When I see patterns in my programs, I consider it a sign of trouble. The shape of a program should reflect only the problem it needs to solve. Any other regularity in the code is a sign, to me at least, that I'm using abstractions that aren't powerful enough-- often that I'm generating by hand the expansions of some macro that I need to write. Notes
为了说明不同编程语言的相对威力,请思考以下问题:我们需要编写一个生成累加器的函数——该函数接收一个数字n,返回一个能接收另一个数字i并返回n累加i结果的函数。
(注意是累加而非简单相加。累加器必须保持状态。)
* The IBM 704 CPU was about the size of a refrigerator, but a lot heavier. The CPU weighed 3150 pounds, and the 4K of RAM was in a separate box weighing another 4000 pounds. The Sub-Zero 690, one of the largest household refrigerators, weighs 656 pounds.
在Common Lisp中实现如下:
``lisp
(defun foo (n) (lambda (i) (incf n i)))
`
而在Perl 5中:
`perl
sub foo { my ($n) = @_; sub {$n += shift} }
`
Perl版本比Lisp多了参数手动提取的步骤。
Smalltalk代码略长于Lisp:
`smalltalk
foo: n
|s|
s := n.
^[:i| s := s+i. ]
`
因为虽然支持词法变量,但不能直接对参数赋值,必须创建新变量s。
Javascript同样稍显冗长,因其区分语句和表达式,需显式return返回值:
`javascript
function foo(n) { return function (i) { return n += i } }
`
(公平而言,Perl也区分二者,但以典型Perl风格允许省略return`。)
* Steve Russell also wrote the first (digital) computer game, Spacewar, in 1962.
若将上述代码转换为Python,则会遇到限制。由于Python不完全支持词法变量,必须创建数据结构存储n;且虽支持函数类型,但无字面量表示(除非函数体为单一表达式),故需命名函数返回。最终代码如下:
``python
def foo(n):
s = [n]
def bar(i):
s[0] += i
return s[0]
return bar
`
Python用户或会质疑为何不能直接写作:
`python
def foo(n): return lambda i: return n += i
`
甚至:
`python
def foo(n): lambda i: n += i
``
我推测未来或许能实现。(但若不愿等待Python进化至Lisp的水平,他们完全可以...)
在面向对象语言中,可通过定义含单方法的类来有限模拟闭包(引用外围作用域变量的函数),用字段替代外围变量。这迫使程序员手动完成本应由词法作用域编译器完成的代码分析,且无法处理多函数共享同一变量的情况,但简单场景尚可应付。
* If you want to trick a pointy-haired boss into letting you write software in Lisp, you could try telling him it's XML.
Python专家普遍认为这是更"符合语言风格"的解决方案:
``python
def foo(n):
class acc:
def __init__(self, s):
self.s = s
def inc(self, i):
self.s += i
return self.s
return acc(n).inc
`
或:
`python
class foo:
def __init__(self, n):
self.n = n
def __call__(self, i):
self.n += i
return self.n
`
我列出这些是为避免Python拥护者指责曲解语言,但二者都比首个版本复杂。本质都是创建独立存储空间——只是用对象字段替代了列表头部。而__call__等特殊字段名的使用更像某种妥协。
在Perl与Python的竞争中,Python阵营常标榜其语言比Perl更优雅。但本例表明:威力才是终极优雅——尽管语法稍显粗糙,Perl程序更简洁(元素更少)。
其他语言表现如何?本次讨论涉及的Fortran、C、C++、Java和Visual Basic甚至难以解决该问题。Ken Anderson指出这是Java最接近的实现:
`java
public interface Inttoint { public int call(int i); }
public static Inttoint foo(final int n) {
return new Inttoint() {
int s = n;
public int call(int i) {
s = s + i;
return s;
}
};
}
``
该方案仅支持整数,未达标准。经与Java开发者多次邮件讨论后,我认为要编写行为等同前例的多态版本,其难度介于极其棘手与不可能之间。若有实现者,我愿一观,但本人已放弃尝试。
* Here is the accumulator generator in other Lisp dialects: Scheme: (define (foo n) (lambda (i) (set! n (+ n i)) n)) Goo: (df foo (n) (op incf n _))) Arc: (def foo (n) [++ n _]) * Erann Gat's sad tale about "industry best practice" at JPL inspired me to address this generally misapplied phrase.
严格来说,并非无法用其他语言实现。图灵等价性意味着理论上任何语言都能编写任何程序。那么如何实现?极端情况下,可在弱语言中实现Lisp解释器。
这听似玩笑,但大型项目中不同程度地频繁出现这种现象,甚至被命名为"格林斯潘第十定律":
* Peter Norvig found that 16 of the 23 patterns in _Design Patterns_ were "invisible or simpler" in Lisp.
任何足够复杂的C或Fortran程序,都包含了一个临时拼凑、非正式规范、漏洞百出且运行缓慢的Common Lisp半成品实现。
当你试图解决一个难题时,问题不在于你是否会使用足够强大的语言,而在于你会选择:(a) 使用一门强大的语言,(b) 为其编写一个事实上的解释器,还是 (c) 自己成为这门语言的人肉编译器。我们在Python示例中已看到这种现象的萌芽——本质上我们正在模拟编译器为实现词法变量所生成的代码。
* Thanks to the many people who answered my questions about various languages and/or read drafts of this, including Ken Anderson, Trevor Blackwell, Erann Gat, Dan Giffin, Sarah Harlin, Jeremy Hylton, Robert Morris, Peter Norvig, Guy Steele, and Anton van Straaten. They bear no blame for any opinions expressed.
这种做法不仅普遍,甚至已成为行业惯例。例如在面向对象领域,人们频繁讨论"设计模式"。我不禁怀疑这些模式是否正是案例(c)——人肉编译器——的体现。当我在程序中看到模式时,我认为这是问题出现的征兆。程序的形态应当只反映其需要解决的问题。代码中任何其他规律性痕迹,至少在我看来,都意味着我正在使用的抽象不够强大——往往是在手工编写本应由宏展开生成的代码。
* IBM 704中央处理器体积与家用冰箱相仿,但重量远超。CPU重3150磅,4K内存装在另一个重达4000磅的箱子里。而Sub-Zero 690作为最大型家用冰箱之一,重量仅656磅。 * 史蒂夫·拉塞尔还在1962年编写了首个(数字)电脑游戏《太空大战》。 * 若想哄骗呆板上司允许你用Lisp编程,不妨告诉他这是XML。 * 其他Lisp方言中的累加器生成器实现:Scheme版:(define (foo n) (lambda (i) (set! n (+ n i)) n));Goo版:(df foo (n) (op incf n _)));Arc版:(def foo (n) [++ n _]) * 埃兰·盖特关于JPL"行业最佳实践"的悲伤故事促使我探讨这个被普遍误用的表述。 * 彼得·诺维格发现《设计模式》中的23个模式有16个在Lisp中"不可见或更简单"。 * 感谢肯·安德森、特雷弗·布莱克韦尔、埃兰·盖特、丹·吉芬、莎拉·哈林、杰里米·希尔顿、罗伯特·莫里斯、彼得·诺维格、盖伊·斯蒂尔和安东·范斯特拉滕等人解答各类语言问题及审阅本文草稿。文中观点责任均与上述人士无关。
许多人对此文做出了回应,因此我另设了一个页面来讨论他们提出的问题:《Re: 书呆子的复仇》。
Related: Many people have responded to this talk, so I have set up an additional page to deal with the issues they have raised: Re: Revenge of the Nerds. It also set off an extensive and often useful discussion on the LL1 mailing list. See particularly the mail by Anton van Straaten on semantic compression. Some of the mail on LL1 led me to try to go deeper into the subject of language power in Succinctness is Power. A larger set of canonical implementations of the accumulator generator benchmark are collected together on their own page. Japanese Translation, Spanish Translation, Chinese Translation
You'll find this essay and 14 others in _Hackers & Painters_.
May 2002 | "The quantity of meaning compressed into a small space by algebraic signs, is another circumstance that facilitates the reasonings we are accustomed to carry on by their aid." \- Charles Babbage, quoted in Iverson's Turing Award Lecture
In the discussion about issues raised by Revenge of the Nerds on the LL1 mailing list, Paul Prescod wrote something that stuck in my mind.
2002年5月 | "代数符号将大量意义压缩至狭小空间的能力,正是其能辅助我们进行复杂推理的另一优势。" ——查尔斯·巴贝奇,引自艾弗森的图灵奖演讲
在LL1邮件列表关于《书呆子的复仇》引发议题的讨论中,保罗·普雷斯科特写下了令我印象深刻的话:
> Python的目标是规范性与可读性,而非简洁性。
表面看来,这对编程语言而言堪称致命评价。就我理解,简洁性=力量。若此等式成立,则替换可得:
> Python's goal is regularity and readability, not succinctness.
> Python的目标是规范性与可读性,而非力量。
而这似乎并非一种你愿意接受的权衡(如果这确实算是一种权衡)。这几乎等同于说Python的目标并非成为一种高效的编程语言。
简洁是否等于强大?在我看来,这是个至关重要的问题,或许是语言设计领域最核心的命题,值得我们直面探讨。虽然我尚不确定答案是否简单肯定的,但这无疑是个值得深究的起点假设。
On the face of it, this seems a rather damning thing to claim about a programming language. As far as I can tell, succinctness = power. If so, then substituting, we get
我的假设是:简洁即力量,或者说二者近乎等同,除极端案例外可视作同义概念。
我认为编程语言存在的根本意义正在于追求简洁。计算机本可直接接受机器语言指令。我们之所以费心开发高级语言,核心动机在于获得杠杆效应——用10行高级语言代码表达(更重要的是思考)原本需要1000行机器语言才能实现的内容。换言之,高级语言的核心价值就在于压缩源代码规模。
如果精简代码是高级语言的使命,而事物的力量体现在其达成使命的程度,那么衡量编程语言力量的标准就是它能多大程度缩减程序体量。
> Python's goal is regularity and readability, not power.
反之,若某语言无法精简程序,就如同钝刀难裁物、印刷难辨识,从根本上背离了编程语言的应有之义。
但"精简"具体指什么?最常用的代码规模指标是行数。然而这种度量方式盛行仅仅因其便于统计,无人真正认为它能准确反映程序长度。不同语言对单行代码量的约定各异:比如C语言中许多行仅含一两个分隔符。
另一个简易标准是字符总数,但这同样欠佳——某些语言(如Perl)只是使用更短的标识符。
and this doesn't seem a tradeoff (if it _is_ a tradeoff) that you'd want to make. It's not far from saying that Python's goal is not to be effective as a programming language. Does succinctness = power? This seems to me an important question, maybe the most important question for anyone interested in language design, and one that it would be useful to confront directly. I don't feel sure yet that the answer is a simple yes, but it seems a good hypothesis to begin with. Hypothesis My hypothesis is that succinctness is power, or is close enough that except in pathological examples you can treat them as identical. It seems to me that succinctness is what programming languages are _for._ Computers would be just as happy to be told what to do directly in machine language. I think that the main reason we take the trouble to develop high-level languages is to get leverage, so that we can say (and more importantly, think) in 10 lines of a high-level language what would require 1000 lines of machine language. In other words, the main point of high-level languages is to make source code smaller. If smaller source code is the purpose of high-level languages, and the power of something is how well it achieves its purpose, then the measure of the power of a programming language is how small it makes your programs. Conversely, a language that doesn't make your programs small is doing a bad job of what programming languages are supposed to do, like a knife that doesn't cut well, or printing that's illegible. Metrics Small in what sense though? The most common measure of code size is lines of code. But I think that this metric is the most common because it is the easiest to measure. I don't think anyone really believes it is the true test of the length of a program. Different languages have different conventions for how much you should put on a line; in C a lot of lines have nothing on them but a delimiter or two.
我认为更合理的度量方式是"元素数量",即用树状图表示源代码时的独立节点数。变量名、函数名、整型数、浮点数、文本段、模式元素、格式指令、新代码块等都算作独立元素。虽然存在边界情况(如-5算一个还是两个元素?),但多数情况跨语言通用,不影响比较结果。
该标准尚需完善,特定语言可能需要解释性调整,但其核心理念正确——衡量程序的组成部分数量。这种树状结构正是人脑理解程序时必须构建的心理模型,其规模与读写代码所需的心智劳动成正比。
此类度量标准可用于跨语言比较,但对我而言其核心价值在于指导语言设计。最有意义的比较发生在同一语言的两种潜在变体之间:如何通过语言设计使程序更精简?
Another easy test is the number of characters in a program, but this is not very good either; some languages (Perl, for example) just use shorter identifiers than others. I think a better measure of the size of a program would be the number of elements, where an element is anything that would be a distinct node if you drew a tree representing the source code. The name of a variable or function is an element; an integer or a floating-point number is an element; a segment of literal text is an element; an element of a pattern, or a format directive, is an element; a new block is an element. There are borderline cases (is -5 two elements or one?) but I think most of them are the same for every language, so they don't affect comparisons much. This metric needs fleshing out, and it could require interpretation in the case of specific languages, but I think it tries to measure the right thing, which is the number of parts a program has. I think the tree you'd draw in this exercise is what you have to make in your head in order to conceive of the program, and so its size is proportionate to the amount of work you have to do to write or read it. Design This kind of metric would allow us to compare different languages, but that is not, at least for me, its main value. The main value of the succinctness test is as a guide in _designing_ languages. The most useful comparison between languages is between two potential variants of the same language. What can I do in the language to make programs shorter? If the conceptual load of a program is proportionate to its complexity, and a given programmer can tolerate a fixed conceptual load, then this is the same as asking, what can I do to enable programmers to get the most done? And that seems to me identical to asking, how can I design a good language? (Incidentally, nothing makes it more patently obvious that the old chestnut "all languages are equivalent" is false than designing languages.
如果程序的概念负荷与其复杂度成正比,而程序员的概念承受力恒定,那么这个问题本质上等同于:如何让程序员实现最高效能?在我看来,这与"如何设计优秀语言"实为同一命题。
(顺带一提,语言设计过程最能彻底证伪"所有语言等价"的陈腐观点。设计新语言时,你持续在比较两种变体——采用某特性与否——以判断优劣。若这真是无意义的问题,不如直接抛硬币决策。)
追求简洁似乎是发现新思路的良方。若某项改动能普遍缩短各类程序,很可能意味着你发现了有价值的新抽象概念。甚至可编写程序辅助检测源代码中的重复模式。在众多语言中,以简洁著称者(如Forth、Joy、Icon)最可能提供创新灵感。
When you are designing a new language, you're _constantly_ comparing two languages-- the language if I did x, and if I didn't-- to decide which is better. If this were really a meaningless question, you might as well flip a coin.) Aiming for succinctness seems a good way to find new ideas. If you can do something that makes many different programs shorter, it is probably not a coincidence: you have probably discovered a useful new abstraction. You might even be able to write a program to help by searching source code for repeated patterns. Among other languages, those with a reputation for succinctness would be the ones to look to for new ideas: Forth, Joy, Icon. Comparison The first person to write about these issues, as far as I know, was Fred Brooks in the _Mythical Man Month_. He wrote that programmers seemed to generate about the same amount of code per day regardless of the language. When I first read this in my early twenties, it was a big surprise to me and seemed to have huge implications. It meant that (a) the only way to get software written faster was to use a more succinct language, and (b) someone who took the trouble to do this could leave competitors who didn't in the dust. Brooks' hypothesis, if it's true, seems to be at the very heart of hacking. In the years since, I've paid close attention to any evidence I could get on the question, from formal studies to anecdotes about individual projects. I have seen nothing to contradict him. I have not yet seen evidence that seemed to me conclusive, and I don't expect to. Studies like Lutz Prechelt's comparison of programming languages, while generating the kind of results I expected, tend to use problems that are too short to be meaningful tests. A better test of a language is what happens in programs that take a month to write.
据我所知,Fred Brooks在《人月神话》中最早探讨此议题。他指出无论使用何种语言,程序员日均产出代码量大致恒定。二十出头初读此论时,这个反直觉的发现令我震惊且深感其重大意义:这意味着(a)加速软件开发的唯一途径是采用更简洁的语言;(b)践行此道者将彻底甩开竞争对手。
若Brooks假说成立,它直指黑客精神的核心。此后多年间,我从正式研究到项目轶事,始终密切关注相关证据,从未发现反例。
虽然尚未见到确凿证据(也不期待见到),但类似Lutz Prechelt的编程语言比较研究虽得出预期结论,其测试案例往往过短而缺乏意义。更有效的测试应针对需月余开发周期的程序。若如我所信——语言的核心价值在于辅助思考(而非仅表达既定思路),那么终极检验标准是它能支持创作何种新事物。因此任何基于预设规范的比较测试都略有偏差。
And the only real test, if you believe as I do that the main purpose of a language is to be good to think in (rather than just to tell a computer what to do once you've thought of it) is what new things you can write in it. So any language comparison where you have to meet a predefined spec is testing slightly the wrong thing. The true test of a language is how well you can discover and solve new problems, not how well you can use it to solve a problem someone else has already formulated. These two are quite different criteria. In art, mediums like embroidery and mosaic work well if you know beforehand what you want to make, but are absolutely lousy if you don't. When you want to discover the image as you make it-- as you have to do with anything as complex as an image of a person, for example-- you need to use a more fluid medium like pencil or ink wash or oil paint. And indeed, the way tapestries and mosaics are made in practice is to make a painting first, then copy it. (The word "cartoon" was originally used to describe a painting intended for this purpose). What this means is that we are never likely to have accurate comparisons of the relative power of programming languages. We'll have precise comparisons, but not accurate ones. In particular, explicit studies for the purpose of comparing languages, because they will probably use small problems, and will necessarily use predefined problems, will tend to underestimate the power of the more powerful languages. Reports from the field, though they will necessarily be less precise than "scientific" studies, are likely to be more meaningful. For example, Ulf Wiger of Ericsson did a study that concluded that Erlang was 4-10x more succinct than C++, and proportionately faster to develop software in:.
语言的真正考验在于发现和解决新问题的能力,而非解决他人已定义问题的效率。这两者判然有别。艺术领域,刺绣与马赛克适合制作预定图案,但完全不适合即兴创作。当需要边创作边构思(如人物肖像等复杂作品时),必须采用铅笔、水墨或油画等流动性媒介。事实上,挂毯与马赛克的制作流程正是先绘制油画再临摹("cartoon"一词原指此类底稿)。
这意味着我们永远难以准确比较编程语言的相对力量。虽可获得精确数据,却难言真实准确。特别是专门设计的语言对比研究,因受限于小规模课题和预设问题,往往会低估强大语言的实际效能。
来自实践领域的报告虽不如"科学"研究精确,却更具参考价值。例如爱立信的Ulf Wiger通过研究得出结论:Erlang比C++简洁4-10倍,软件开发速度同比提升。
> Comparisons between Ericsson-internal development projects indicate similar line/hour productivity, including all phases of software development, rather independently of which language (Erlang, PLEX, C, C++, or Java) was used. What differentiates the different languages then becomes source code volume.
爱立信内部开发项目的比较显示,无论使用何种语言(Erlang、PLEX、C、C++或Java),软件开发各阶段的代码行/小时生产力都大致相当。因此,不同语言之间的差异主要体现在源代码体积上。
这项研究还明确探讨了布鲁克斯书中仅隐含提及的观点(因为他测量的是调试后的代码行数):用更强大的语言编写的程序往往错误更少。对于像网络交换机这样的应用,这本身就成为了目的,可能比程序员的生产效率更重要。
最终,我认为你必须跟随直觉。用这种语言编程感觉如何?我认为找到(或设计)最佳语言的方法是变得对语言如何让你思考极其敏感,然后选择/设计感觉最好的语言。如果某些语言特性笨拙或限制性强,别担心,你会察觉到的。
The study also deals explictly with a point that was only implicit in Brooks' book (since he measured lines of debugged code): programs written in more powerful languages tend to have fewer bugs. That becomes an end in itself, possibly more important than programmer productivity, in applications like network switches. The Taste Test Ultimately, I think you have to go with your gut. What does it feel like to program in the language? I think the way to find (or design) the best language is to become hypersensitive to how well a language lets you think, then choose/design the language that feels best. If some language feature is awkward or restricting, don't worry, you'll know about it. Such hypersensitivity will come at a cost. You'll find that you can't _stand_ programming in clumsy languages. I find it unbearably restrictive to program in languages without macros, just as someone used to dynamic typing finds it unbearably restrictive to have to go back to programming in a language where you have to declare the type of every variable, and can't make a list of objects of different types. I'm not the only one. I know many Lisp hackers that this has happened to. In fact, the most accurate measure of the relative power of programming languages might be the percentage of people who know the language who will take any job where they get to use that language, regardless of the application domain. Restrictiveness I think most hackers know what it means for a language to feel restrictive. What's happening when you feel that? I think it's the same feeling you get when the street you want to take is blocked off, and you have to take a long detour to get where you wanted to go. There is something you want to say, and the language won't let you. What's really going on here, I think, is that a restrictive language is one that isn't succinct enough. The problem is not simply that you can't say what you planned to.
这种高度敏感会带来代价。你会发现无法忍受用笨拙的语言编程。我觉得没有宏的语言编程限制性令人难以忍受,就像习惯动态类型的人无法忍受必须回到需要声明每个变量类型、且不能创建不同类型对象列表的语言编程一样。
不只我这样。我认识许多Lisp黑客都有这种感受。事实上,衡量编程语言相对能力最准确的指标可能是:了解该语言的人中,愿意为使用该语言接受任何工作(无论应用领域)的比例。
我认为大多数黑客都明白语言感觉受限意味着什么。当你感到受限制时发生了什么?我想这就像你想走的路被堵住,不得不绕远路到达目的地。你有话想说,但语言不允许。
It's that the detour the language makes you take is _longer._ Try this thought experiment. Suppose there were some program you wanted to write, and the language wouldn't let you express it the way you planned to, but instead forced you to write the program in some other way that was _shorter._ For me at least, that wouldn't feel very restrictive. It would be like the street you wanted to take being blocked off, and the policeman at the intersection directing you to a shortcut instead of a detour. Great! I think most (ninety percent?) of the feeling of restrictiveness comes from being forced to make the program you write in the language longer than one you have in your head. Restrictiveness is mostly lack of succinctness. So when a language feels restrictive, what that (mostly) means is that it isn't succinct enough, and when a language isn't succinct, it will feel restrictive. Readability The quote I began with mentions two other qualities, regularity and readability. I'm not sure what regularity is, or what advantage, if any, code that is regular and readable has over code that is merely readable. But I think I know what is meant by readability, and I think it is also related to succinctness. We have to be careful here to distinguish between the readability of an individual line of code and the readability of the whole program. It's the second that matters. I agree that a line of Basic is likely to be more readable than a line of Lisp. But a program written in Basic is is going to have more lines than the same program written in Lisp (especially once you cross over into Greenspunland). The total effort of reading the Basic program will surely be greater..
我认为真正的问题在于,限制性语言就是不够简洁的语言。问题不仅在于无法按计划表达,更在于语言迫使你绕的弯路更长。做个思想实验:假设你想写某个程序,语言不允许你按计划表达,但强迫你用更短的其他方式写出来。至少对我来说,这不会感觉很受限。就像想走的路被堵住,路口的警察却指引你走捷径而非绕路。太棒了!
我认为限制感大多(90%?)源于被迫用比脑中更冗长的语言写程序。限制性主要源于缺乏简洁性。所以当语言感觉受限时,大多意味着它不够简洁;而不简洁的语言自然会感觉受限。
开篇引文还提到另外两个特质:规律性和可读性。我不确定规律性是什么,也不清楚规律且可读的代码比单纯可读的代码有何优势(如果有的话)。但我想我明白可读性的含义,它也与简洁性相关。
> total effort = effort per line x number of lines
这里我们必须谨慎区分单行代码的可读性和整个程序的可读性。后者才是关键。我承认一行Basic可能比一行Lisp更易读。但用Basic写的程序会比用Lisp写的相同程序行数更多(尤其是进入格林斯潘领域后)。阅读Basic程序的总工作量必然更大。
总努力 = 每行努力 × 行数
我并不像确信简洁性直接等同于威力那样,确信可读性与简洁性成正比,但简洁性无疑是影响可读性的一个因素(从数学意义上讲;参见上文等式)。因此,声称一门语言的目标是可读性而非简洁性,甚至可能没有意义;这就像说目标是可读性,而非可读性一样。
I'm not as sure that readability is directly proportionate to succinctness as I am that power is, but certainly succinctness is a factor (in the mathematical sense; see equation above) in readability. So it may not even be meaningful to say that the goal of a language is readability, not succinctness; it could be like saying the goal was readability, not readability. What readability-per-line does mean, to the user encountering the language for the first time, is that source code will _look unthreatening_. So readability-per-line could be a good marketing decision, even if it is a bad design decision. It's isomorphic to the very successful technique of letting people pay in installments: instead of frightening them with a high upfront price, you tell them the low monthly payment. Installment plans are a net lose for the buyer, though, as mere readability-per-line probably is for the programmer. The buyer is going to make a _lot_ of those low, low payments; and the programmer is going to read a _lot_ of those individually readable lines. This tradeoff predates programming languages. If you're used to reading novels and newspaper articles, your first experience of reading a math paper can be dismaying. It could take half an hour to read a single page. And yet, I am pretty sure that the notation is not the problem, even though it may feel like it is. The math paper is hard to read because the ideas are hard. If you expressed the same ideas in prose (as mathematicians had to do before they evolved succinct notations), they wouldn't be any easier to read, because the paper would grow to the size of a book. To What Extent? A number of people have rejected the idea that succinctness = power. I think it would be more useful, instead of simply arguing that they are the same or aren't, to ask: to what _extent_ does succinctness = power? Because clearly succinctness is a large part of what higher-level languages are for.
对于初次接触一门语言的用户来说,每行代码的可读性意味着源代码看起来不会令人望而生畏。因此,强调每行可读性可能是一个好的营销决策,即使它是一个糟糕的设计决策。这与让人们分期付款的成功策略如出一辙:不是用高昂的预付价格吓退他们,而是告诉他们低廉的月付金额。然而,分期付款对买家来说总体上是不利的,就像每行可读性对程序员可能也是如此。买家将不得不支付大量看似低廉的款项;而程序员将不得不阅读大量看似可读的代码行。
这种权衡在编程语言出现之前就已存在。如果你习惯了阅读小说和报纸文章,第一次阅读数学论文可能会令人沮丧。可能需要半小时才能读完一页。然而,我相当确定问题并不在于符号,尽管感觉上可能是这样。数学论文难以阅读是因为其中的思想本身就很难。如果你用散文来表达同样的思想(就像数学家们在发展出简洁符号之前不得不做的那样),它们并不会变得更容易阅读,因为论文会膨胀到一本书的篇幅。
许多人拒绝接受简洁性等于威力的观点。我认为更有用的做法不是简单地争论它们是否相同,而是问:简洁性在多大程度上等于威力?因为显然,简洁性是高级语言的主要目标之一。如果不是全部目标,那么它们还有什么其他目标,这些其他功能相对而言有多重要?
If it is not all they're for, then what else are they for, and how important, relatively, are these other functions? I'm not proposing this just to make the debate more civilized. I really want to know the answer. When, if ever, is a language too succinct for its own good? The hypothesis I began with was that, except in pathological examples, I thought succinctness could be considered identical with power. What I meant was that in any language anyone would design, they would be identical, but that if someone wanted to design a language explicitly to disprove this hypothesis, they could probably do it. I'm not even sure of that, actually. Languages, not Programs We should be clear that we are talking about the succinctness of languages, not of individual programs. It certainly is possible for individual programs to be written too densely. I wrote about this in On Lisp. A complex macro may have to save many times its own length to be justified. If writing some hairy macro could save you ten lines of code every time you use it, and the macro is itself ten lines of code, then you get a net saving in lines if you use it more than once. But that could still be a bad move, because macro definitions are harder to read than ordinary code. You might have to use the macro ten or twenty times before it yielded a net improvement in readability. I'm sure every language has such tradeoffs (though I suspect the stakes get higher as the language gets more powerful). Every programmer must have seen code that some clever person has made marginally shorter by using dubious programming tricks. So there is no argument about that-- at least, not from me. Individual programs can certainly be too succinct for their own good.
我提出这个问题不仅仅是为了让辩论更加文明。我真的很想知道答案。在什么情况下,一门语言会因为过于简洁而适得其反?
我最初的假设是,除了病态的例子,我认为简洁性可以被视为与威力相同。我的意思是,在任何人们设计的语言中,它们会是相同的,但如果有人想设计一门语言明确反驳这一假设,他们或许能做到。实际上,我甚至对此也不确定。
语言,而非程序
The question is, can a language be? Can a language compel programmers to write code that's short (in elements) at the expense of overall readability? One reason it's hard to imagine a language being too succinct is that if there were some excessively compact way to phrase something, there would probably also be a longer way. For example, if you felt Lisp programs using a lot of macros or higher-order functions were too dense, you could, if you preferred, write code that was isomorphic to Pascal. If you don't want to express factorial in Arc as a call to a higher-order function (rec zero 1 1-) you can also write out a recursive definition: (rfn fact (x) (if (zero x) 1 ( x (fact (1- x))))) Though I can't off the top of my head think of any examples, I am interested in the question of whether a language could be too succinct. Are there languages that force you to write code in a way that is crabbed and incomprehensible? If anyone has examples, I would be very interested to see them. (Reminder: What I'm looking for are programs that are very dense according to the metric of "elements" sketched above, not merely programs that are short because delimiters can be omitted and everything has a one-character name.)
| Japanese Translation | Russian Translation | Lutz Prechelt: Comparison of Seven Languages | [Erann Gat: Lisp vs.
我们应该明确,我们讨论的是语言的简洁性,而不是单个程序的简洁性。单个程序当然可能写得过于紧凑。
我在《On Lisp》中写过这一点。一个复杂的宏可能需要节省其自身长度的许多倍才能被认为是合理的。如果编写一个复杂的宏每次使用可以节省十行代码,而宏本身有十行代码,那么使用超过一次就能在代码行数上实现净节省。但这仍然可能是一个糟糕的决定,因为宏定义比普通代码更难阅读。你可能需要使用宏十次或二十次,才能实现可读性的净改善。
我相信每种语言都有这样的权衡(尽管我怀疑随着语言变得更强大,这种权衡的代价会更高)。每个程序员一定都见过一些聪明的家伙通过使用可疑的编程技巧使代码略微缩短的例子。
Java](http://www.flownet.com/gat/papers/lisp-java.pdf) | Peter Norvig Tries Prechelt's Test | Matthias Felleisen: Expressive Power of Languages | Kragen Sitaker: Redundancy and Power | Forth | Joy | Icon | J | K.
所以这一点没有争议——至少对我来说没有。单个程序当然可能因为过于简洁而适得其反。问题是,一门语言是否可能如此?一门语言是否会迫使程序员以牺牲整体可读性为代价,写出(在元素上)简短的代码?
很难想象一门语言会过于简洁的一个原因是,如果存在某种过于紧凑的表达方式,可能也存在一种更长的表达方式。例如,如果你觉得使用大量宏或高阶函数的Lisp程序过于紧凑,你可以选择写出与Pascal同构的代码。如果你不想在Arc中将阶乘表示为高阶函数的调用((rec zero 1 1-)),你也可以写出一个递归定义:(rfn fact (x) (if (zero x) 1 ( x (fact (1- x)))))。尽管我一时想不出任何例子,但我对一门语言是否可能过于简洁的问题很感兴趣。是否存在迫使你以晦涩难懂的方式编写代码的语言?如果有人有例子,我会非常感兴趣。
(提醒:我所寻找的是根据上文概述的“元素”指标非常紧凑的程序,而不仅仅是由于可以省略分隔符和所有东西都有一个字符名称而显得短的程序。)
| 日语翻译 | 俄语翻译 | Lutz Prechelt: 七种语言的比较 | Erann Gat: Lisp vs. Java | Peter Norvig 尝试 Prechelt 的测试 | Matthias Felleisen: 语言的表达能力 | Kragen Sitaker: 冗余与威力 | Forth | Joy | Icon | J | K
[](https://s.turbifycdn.com/aah/paulgraham/taste-for-makers-11.gif) February 2002 | "...Copernicus' aesthetic objections to [equants] provided one essential motive for his rejection of the Ptolemaic system...." \- Thomas Kuhn, _The Copernican Revolution_ "All of us had been trained by Kelly Johnson and believed fanatically in his insistence that an airplane that looked beautiful would fly the same way." \- Ben Rich, _Skunk Works_ "Beauty is the first test: there is no permanent place in this world for ugly mathematics." \- G. H. Hardy, _A Mathematician's Apology_
I was talking recently to a friend who teaches at MIT. His field is hot now and every year he is inundated by applications from would-be graduate students. "A lot of them seem smart," he said. "What I can't tell is whether they have any kind of taste." Taste. You don't hear that word much now. And yet we still need the underlying concept, whatever we call it. What my friend meant was that he wanted students who were not just good technicians, but who could use their technical knowledge to design beautiful things. Mathematicians call good work "beautiful," and so, either now or in the past, have scientists, engineers, musicians, architects, designers, writers, and painters. Is it just a coincidence that they used the same word, or is there some overlap in what they meant? If there is an overlap, can we use one field's discoveries about beauty to help us in another? For those of us who design things, these are not just theoretical questions. If there is such a thing as beauty, we need to be able to recognize it. We need good taste to make good things.
[](https://s.turbifycdn.com/aah/paulgraham/taste-for-makers-11.gif)
| "……哥白尼对[均轮]的美学反感,为他拒绝托勒密体系提供了关键动机……"
——托马斯·库恩,《哥白尼革命》
"我们所有人都受过凯利·约翰逊的训练,并狂热地信奉他的坚持:一架看起来美的飞机,飞行表现也会同样出色。"
——本·里奇,《臭鼬工厂》
Instead of treating beauty as an airy abstraction, to be either blathered about or avoided depending on how one feels about airy abstractions, let's try considering it as a practical question: _how do you make good stuff?_ If you mention taste nowadays, a lot of people will tell you that "taste is subjective." They believe this because it really feels that way to them. When they like something, they have no idea why. It could be because it's beautiful, or because their mother had one, or because they saw a movie star with one in a magazine, or because they know it's expensive. Their thoughts are a tangle of unexamined impulses. Most of us are encouraged, as children, to leave this tangle unexamined. If you make fun of your little brother for coloring people green in his coloring book, your mother is likely to tell you something like "you like to do it your way and he likes to do it his way." Your mother at this point is not trying to teach you important truths about aesthetics. She's trying to get the two of you to stop bickering. Like many of the half-truths adults tell us, this one contradicts other things they tell us. After dinning into you that taste is merely a matter of personal preference, they take you to the museum and tell you that you should pay attention because Leonardo is a great artist. What goes through the kid's head at this point? What does he think "great artist" means? After having been told for years that everyone just likes to do things their own way, he is unlikely to head straight for the conclusion that a great artist is someone whose work is _better_ than the others'. A far more likely theory, in his Ptolemaic model of the universe, is that a great artist is something that's good for you, like broccoli, because someone said so in a book. Saying that taste is just personal preference is a good way to prevent disputes. The trouble is, it's not true. You feel this when you start to design things.
"美是第一重考验:丑陋的数学在世界上没有永久地位。"
——G·H·哈代,《一个数学家的辩白》
最近我和一位在MIT任教的朋友聊天。他的领域正热门,每年都会收到大量研究生申请。"很多人看起来聪明,"他说,"但我无法判断他们是否具备某种品味。"
品味。这个词如今已不常听到。然而我们仍然需要这个概念,无论用什么词表达。我朋友的意思是,他想要的不只是技术娴熟的学生,而是能运用技术知识设计出美好事物的人。
数学家将优秀作品称为"美",科学家、工程师、音乐家、建筑师、设计师、作家和画家,无论现在或过去,也都如此。他们使用同一个词是巧合吗?还是说他们的所指存在某种共通之处?如果存在共通,我们能否将一个领域对美的发现应用于另一个领域?
Whatever job people do, they naturally want to do better. Football players like to win games. CEOs like to increase earnings. It's a matter of pride, and a real pleasure, to get better at your job. But if your job is to design things, and there is no such thing as beauty, then there is _no way to get better at your job._ If taste is just personal preference, then everyone's is already perfect: you like whatever you like, and that's it. As in any job, as you continue to design things, you'll get better at it. Your tastes will change. And, like anyone who gets better at their job, you'll know you're getting better. If so, your old tastes were not merely different, but worse. Poof goes the axiom that taste can't be wrong. Relativism is fashionable at the moment, and that may hamper you from thinking about taste, even as yours grows. But if you come out of the closet and admit, at least to yourself, that there is such a thing as good and bad design, then you can start to study good design in detail. How has your taste changed? When you made mistakes, what caused you to make them? What have other people learned about design? Once you start to examine the question, it's surprising how much different fields' ideas of beauty have in common. The same principles of good design crop up again and again. Good design is simple. You hear this from math to painting. In math it means that a shorter proof tends to be a better one. Where axioms are concerned, especially, less is more. It means much the same thing in programming.
对于我们这些从事设计工作的人,这些问题不只是理论探讨。如果美确实存在,我们需要能够识别它。我们需要好品味来创造好东西。与其将美视为虚无缥缈的抽象概念——根据个人对抽象概念的喜好,要么夸夸其谈,要么避而不谈——不如将其视为一个实际问题:如何做出好东西?
如今提到品味,许多人会告诉你"品味是主观的"。他们如此认为,是因为这确实符合他们的感受。当他们喜欢某物时,并不清楚原因——可能是因为它美,可能因为母亲拥有同款,可能因为在杂志上看到明星使用,也可能因为知道它昂贵。他们的想法是一团未经审视的冲动。
我们大多数人在童年时就被鼓励不要深究这团乱麻。如果你嘲笑弟弟把涂色书里的人涂成绿色,母亲可能会说:"你喜欢按你的方式做,他喜欢按他的方式做。"
此时你母亲并非在传授美学真谛,只是在平息你们的争吵。
如同许多成年人告诉我们的半真半假的道理,这一说法与他们其他的教导矛盾。在反复灌输"品味只是个人偏好"后,他们带你去博物馆,告诉你要认真看,因为达·芬奇是伟大的艺术家。
此时孩子脑子里在想什么?他会如何理解"伟大艺术家"?在被教导多年"每个人都有自己的方式"后,他不太可能直接得出结论:伟大艺术家是作品比别人更好的人。在他的托勒密式宇宙模型中,更可能的理论是:伟大艺术家就像西兰花,是对你有益的东西,因为书里这么说。
For architects and designers it means that beauty should depend on a few carefully chosen structural elements rather than a profusion of superficial ornament. (Ornament is not in itself bad, only when it's camouflage on insipid form.) Similarly, in painting, a still life of a few carefully observed and solidly modelled objects will tend to be more interesting than a stretch of flashy but mindlessly repetitive painting of, say, a lace collar. In writing it means: say what you mean and say it briefly. It seems strange to have to emphasize simplicity. You'd think simple would be the default. Ornate is more work. But something seems to come over people when they try to be creative. Beginning writers adopt a pompous tone that doesn't sound anything like the way they speak. Designers trying to be artistic resort to swooshes and curlicues. Painters discover that they're expressionists. It's all evasion. Underneath the long words or the "expressive" brush strokes, there is not much going on, and that's frightening. When you're forced to be simple, you're forced to face the real problem. When you can't deliver ornament, you have to deliver substance. Good design is timeless. In math, every proof is timeless unless it contains a mistake. So what does Hardy mean when he says there is no permanent place for ugly mathematics? He means the same thing Kelly Johnson did: if something is ugly, it can't be the best solution. There must be a better one, and eventually someone will discover it. Aiming at timelessness is a way to make yourself find the best answer: if you can imagine someone surpassing you, you should do it yourself. Some of the greatest masters did this so well that they left little room for those who came after. Every engraver since Durer has had to live in his shadow. Aiming at timelessness is also a way to evade the grip of fashion.
声称品味只是个人偏好,是避免争论的好方法。问题是,这不是事实。当你开始设计东西时,就会感受到这一点。
无论从事什么工作,人们自然希望做得更好。足球运动员想赢比赛,CEO想提高收益。提升专业能力关乎尊严,也是真正的快乐。但如果你的工作是设计,而美并不存在,那么就无法在工作中进步。如果品味只是个人偏好,那么每个人的品味都已完美:你喜欢你所喜欢的,仅此而已。
如同任何工作,随着持续设计,你会做得更好。你的品味会改变。而且,像所有专业进步的人一样,你会知道自己正在进步。若是如此,你过去的品味不仅是不同,而是更差。"品味无对错"的公理就此破灭。
相对主义当下正流行,这可能阻碍你思考品味,即使你的品味正在成长。但如果你敢于承认——至少对自己承认——设计确实有好坏之分,就能开始细致研究好设计。你的品味如何变化?当你犯错时,是什么导致错误?其他人对设计有何见解?
一旦开始审视这个问题,会惊讶地发现不同领域对美的理解竟有如此多共通之处。优秀设计的相同原则反复出现。
Fashions almost by definition change with time, so if you can make something that will still look good far into the future, then its appeal must derive more from merit and less from fashion. Strangely enough, if you want to make something that will appeal to future generations, one way to do it is to try to appeal to past generations. It's hard to guess what the future will be like, but we can be sure it will be like the past in caring nothing for present fashions. So if you can make something that appeals to people today and would also have appealed to people in 1500, there is a good chance it will appeal to people in 2500. Good design solves the right problem. The typical stove has four burners arranged in a square, and a dial to control each. How do you arrange the dials? The simplest answer is to put them in a row. But this is a simple answer to the wrong question. The dials are for humans to use, and if you put them in a row, the unlucky human will have to stop and think each time about which dial matches which burner. Better to arrange the dials in a square like the burners. A lot of bad design is industrious, but misguided. In the mid twentieth century there was a vogue for setting text in sans-serif fonts. These fonts _are_ closer to the pure, underlying letterforms. But in text that's not the problem you're trying to solve. For legibility it's more important that letters be easy to tell apart. It may look Victorian, but a Times Roman lowercase g is easy to tell from a lowercase y. Problems can be improved as well as solutions. In software, an intractable problem can usually be replaced by an equivalent one that's easy to solve.
好设计是简单的。 从数学到绘画,你都会听到这一点。在数学中,简短的证明往往是更好的证明。就公理而言,尤其少即是多。编程也是如此。对建筑师和设计师而言,美应取决于少数精心选择的结构元素,而非大量肤浅装饰。(装饰本身并非不好,只有当它掩盖乏味形式时才成问题。)同样在绘画中,仔细观察并扎实塑造的静物,往往比华丽却无脑重复描绘(比如蕾丝衣领)的作品更有趣。写作中则意味着:言简意赅。
强调简单似乎很奇怪。你会以为简单是默认状态。繁复才需要更多功夫。但当人们试图发挥创意时,似乎会发生某种变化。新手作家采用浮夸语气,与他们平时的说话方式毫无相似之处。设计师为追求艺术感而诉诸花哨的曲线。画家发现自己成了表现主义者。这都是逃避。在长词或"表现性"笔触之下,并无实质内容,这令人恐惧。
当你被迫简单时,就不得不面对真正的问题。当你无法提供装饰时,就必须提供实质。
好设计是永恒的。 在数学中,除非存在错误,否则每个证明都是永恒的。那么哈代为何说丑陋数学没有永久地位?他的意思与凯利·约翰逊相同:如果某物丑陋,就不可能是最佳解决方案。必定存在更好的方案,终会有人发现。
以永恒为目标,是迫使自己寻找最佳答案的方法:如果你能想象有人超越你,就应该自己实现它。有些大师做得如此出色,几乎没给后人留下空间。自丢勒以来,每位版画家都活在他的阴影中。
Physics progressed faster as the problem became predicting observable behavior, instead of reconciling it with scripture. Good design is suggestive. Jane Austen's novels contain almost no description; instead of telling you how everything looks, she tells her story so well that you envision the scene for yourself. Likewise, a painting that suggests is usually more engaging than one that tells. Everyone makes up their own story about the Mona Lisa. In architecture and design, this principle means that a building or object should let you use it how you want: a good building, for example, will serve as a backdrop for whatever life people want to lead in it, instead of making them live as if they were executing a program written by the architect. In software, it means you should give users a few basic elements that they can combine as they wish, like Lego. In math it means a proof that becomes the basis for a lot of new work is preferable to a proof that was difficult, but doesn't lead to future discoveries; in the sciences generally, citation is considered a rough indicator of merit. Good design is often slightly funny. This one may not always be true. But Durer's engravings and Saarinen's womb chair and the Pantheon and the original Porsche 911 all seem to me slightly funny. Godel's incompleteness theorem seems like a practical joke. I think it's because humor is related to strength. To have a sense of humor is to be strong: to keep one's sense of humor is to shrug off misfortunes, and to lose one's sense of humor is to be wounded by them. And so the mark-- or at least the prerogative-- of strength is not to take oneself too seriously. The confident will often, like swallows, seem to be making fun of the whole process slightly, as Hitchcock does in his films or Bruegel in his paintings-- or Shakespeare, for that matter.
追求永恒也是摆脱时尚束缚的方法。时尚几乎注定随时间变化,因此如果你能创造在未来依然美好的事物,那么它的吸引力必定更多来自优点而非时尚。
奇怪的是,如果你想创造吸引后代的东西,方法之一是尝试吸引过去世代。很难猜测未来会怎样,但可以确定未来会像过去一样,不关心当下时尚。因此,如果你能创造既吸引今人又吸引1500年人们的作品,就很有可能会吸引2500年的人们。
好设计解决正确问题。 典型炉灶有四个呈方形排列的 burner,每个 burner 有一个旋钮控制。如何排列旋钮?最简单的答案是将它们排成一列。但这是对错误问题的简单回答。旋钮是给人用的,如果排成一列,使用者每次都得停下来思考哪个旋钮对应哪个 burner。更好的方式是让旋钮排列与 burner 排列一致。
许多糟糕设计是勤奋但方向错误的。20世纪中叶曾流行用无衬线字体排版。这些字体确实更接近纯粹的底层字母形态。但对于文本排版,这不是你要解决的问题。易读性更取决于字母间的区分度。Times Roman 字体的小写 g 和小写 y 可能看起来有些维多利亚风格,但很容易区分。
问题本身也可以改进。在软件中,棘手问题通常可替换为易于解决的等效问题。当物理学将问题转化为预测可观测行为,而非与经文调和时,进展就加快了。
好设计具有启发性。 简·奥斯汀的小说几乎不做描写;她不是告诉你一切看起来如何,而是将故事讲得如此之好,让你自己想象场景。同样,具有启发性的画作通常比直白的更引人入胜。每个人对《蒙娜丽莎》都有自己的解读。
Good design may not have to be funny, but it's hard to imagine something that could be called humorless also being good design. Good design is hard. If you look at the people who've done great work, one thing they all seem to have in common is that they worked very hard. If you're not working hard, you're probably wasting your time. Hard problems call for great efforts. In math, difficult proofs require ingenious solutions, and those tend to be interesting. Ditto in engineering. When you have to climb a mountain you toss everything unnecessary out of your pack. And so an architect who has to build on a difficult site, or a small budget, will find that he is forced to produce an elegant design. Fashions and flourishes get knocked aside by the difficult business of solving the problem at all. Not every kind of hard is good. There is good pain and bad pain. You want the kind of pain you get from going running, not the kind you get from stepping on a nail. A difficult problem could be good for a designer, but a fickle client or unreliable materials would not be. In art, the highest place has traditionally been given to paintings of people. There is something to this tradition, and not just because pictures of faces get to press buttons in our brains that other pictures don't. We are so good at looking at faces that we force anyone who draws them to work hard to satisfy us. If you draw a tree and you change the angle of a branch five degrees, no one will know. When you change the angle of someone's eye five degrees, people notice. When Bauhaus designers adopted Sullivan's "form follows function," what they meant was, form _should_ follow function. And if function is hard enough, form is forced to follow it, because there is no effort to spare for error. Wild animals are beautiful because they have hard lives. Good design looks easy. Like great athletes, great designers make it look easy.
在建筑和设计中,这一原则意味着建筑或物品应让你按自己的意愿使用:例如,好建筑会成为人们想要生活的背景,而非让他们像执行建筑师编写的程序一样生活。
在软件中,意味着应提供用户可以随意组合的基本元素,就像乐高。在数学中,能成为新工作基础的证明,优于虽难但无后续影响的证明;在科学领域,引用量被视为价值的粗略指标。
好设计常带一丝幽默。 这一点或许不总是成立。但在我看来,丢勒的版画、沙里宁的子宫椅、万神殿和初代保时捷911都略带幽默。哥德尔不完备定理像个恶作剧。
我认为这是因为幽默与力量相关。拥有幽默感就是强大:保持幽默感意味着能对不幸一笑置之,而失去幽默感则意味着被不幸伤害。因此,力量的表现——或至少特权——是不把自己看得太重。自信者常像燕子般,似乎略带调侃地对待整个过程,如同希区柯克在电影中、勃鲁盖尔在画作中——或莎士比亚那样。
好设计未必幽默,但很难想象被称为"毫无幽默"的东西会是好设计。
Mostly this is an illusion. The easy, conversational tone of good writing comes only on the eighth rewrite. In science and engineering, some of the greatest discoveries seem so simple that you say to yourself, I could have thought of that. The discoverer is entitled to reply, why didn't you? Some Leonardo heads are just a few lines. You look at them and you think, all you have to do is get eight or ten lines in the right place and you've made this beautiful portrait. Well, yes, but you have to get them in _exactly_ the right place. The slightest error will make the whole thing collapse. Line drawings are in fact the most difficult visual medium, because they demand near perfection. In math terms, they are a closed-form solution; lesser artists literally solve the same problems by successive approximation. One of the reasons kids give up drawing at ten or so is that they decide to start drawing like grownups, and one of the first things they try is a line drawing of a face. Smack! In most fields the appearance of ease seems to come with practice. Perhaps what practice does is train your unconscious mind to handle tasks that used to require conscious thought. In some cases you literally train your body. An expert pianist can play notes faster than the brain can send signals to his hand. Likewise an artist, after a while, can make visual perception flow in through his eye and out through his hand as automatically as someone tapping his foot to a beat. When people talk about being in "the zone," I think what they mean is that the spinal cord has the situation under control. Your spinal cord is less hesitant, and it frees conscious thought for the hard problems. Good design uses symmetry. I think symmetry may just be one way to achieve simplicity, but it's important enough to be mentioned on its own. Nature uses it a lot, which is a good sign. There are two kinds of symmetry, repetition and recursion.
好设计是困难的。 观察做出伟大作品的人,他们的共同点是极其努力。如果不努力,很可能在浪费时间。
难题需要巨大努力。数学中,困难证明需要巧妙解法,而这些解法往往有趣。工程学亦然。
当必须攀登高山时,你会丢弃背包中一切非必需品。因此,建筑师若要在困难地块或有限预算下工作,就会被逼出优雅设计。时尚与装饰会在解决问题的艰难过程中被摒弃。
并非所有困难都是好的。有好的痛苦和坏的痛苦。你想要跑步带来的痛苦,而非踩到钉子的痛苦。难题对设计师有益,但善变的客户或不可靠的材料则不然。
艺术中,人物画传统上地位最高。这一传统有其道理,不仅因为人脸图像能触发我们大脑的特殊反应。我们太擅长观察面部,迫使画者必须极其努力才能满足我们。若你画一棵树并将树枝角度改变五度,无人会察觉;但若将某人眼睛角度改变五度,人们立刻会注意到。
Recursion means repetition in subelements, like the pattern of veins in a leaf. Symmetry is unfashionable in some fields now, in reaction to excesses in the past. Architects started consciously making buildings asymmetric in Victorian times and by the 1920s asymmetry was an explicit premise of modernist architecture. Even these buildings only tended to be asymmetric about major axes, though; there were hundreds of minor symmetries. In writing you find symmetry at every level, from the phrases in a sentence to the plot of a novel. You find the same in music and art. Mosaics (and some Cezannes) get extra visual punch by making the whole picture out of the same atoms. Compositional symmetry yields some of the most memorable paintings, especially when two halves react to one another, as in the _Creation of Adam_ or _American Gothic._ In math and engineering, recursion, especially, is a big win. Inductive proofs are wonderfully short. In software, a problem that can be solved by recursion is nearly always best solved that way. The Eiffel Tower looks striking partly because it is a recursive solution, a tower on a tower. The danger of symmetry, and repetition especially, is that it can be used as a substitute for thought. Good design resembles nature. It's not so much that resembling nature is intrinsically good as that nature has had a long time to work on the problem. It's a good sign when your answer resembles nature's. It's not cheating to copy. Few would deny that a story should be like life. Working from life is a valuable tool in painting too, though its role has often been misunderstood. The aim is not simply to make a record. The point of painting from life is that it gives your mind something to chew on: when your eyes are looking at something, your hand will do more interesting work. Imitating nature also works in engineering.
当包豪斯设计师采纳沙利文的"形式追随功能"时,他们的意思是形式应当追随功能。如果功能足够困难,形式就不得不追随它,因为没有余力犯错。野生动物很美,因为它们生活艰难。
好设计看似轻松。 如同伟大运动员,伟大设计师让一切看起来轻松。这多半是假象。写作中轻松 conversational 的语气,往往来自第八次重写。
科学与工程领域,一些最伟大发现看似简单到让你觉得"我也能想到"。发现者有权反问:那你为什么没想到?
达·芬奇的某些头像仅用寥寥数笔。看着它们你会想,只要把八到十根线放对位置,就能画出这美丽肖像。没错,但必须精确放对位置。最微小误差也会导致全盘崩溃。
线描事实上是最难的视觉媒介,因为它要求近乎完美。用数学术语说,它是闭式解;水平较低的艺术家实际上通过逐次逼近解决相同问题。孩子们约十岁放弃绘画的原因之一,是他们决定开始像成人一样画画,而最先尝试的往往是面部线描。啪!
多数领域中,举重若轻的表象来自练习。或许练习的作用是训练潜意识处理原本需要意识思考的任务。某些情况下你确实在训练身体。专业钢琴家能弹奏的速度快于大脑向手发送信号的速度。同样,艺术家经过训练后,视觉感知能如人随节奏踏脚般自动从眼睛流向手中。
Boats have long had spines and ribs like an animal's ribcage. In some cases we may have to wait for better technology: early aircraft designers were mistaken to design aircraft that looked like birds, because they didn't have materials or power sources light enough (the Wrights' engine weighed 152 lbs. and generated only 12 hp.) or control systems sophisticated enough for machines that flew like birds, but I could imagine little unmanned reconnaissance planes flying like birds in fifty years. Now that we have enough computer power, we can imitate nature's method as well as its results. Genetic algorithms may let us create things too complex to design in the ordinary sense. Good design is redesign. It's rare to get things right the first time. Experts expect to throw away some early work. They plan for plans to change. It takes confidence to throw work away. You have to be able to think, _there's more where that came from._ When people first start drawing, for example, they're often reluctant to redo parts that aren't right; they feel they've been lucky to get that far, and if they try to redo something, it will turn out worse. Instead they convince themselves that the drawing is not that bad, really-- in fact, maybe they meant it to look that way. Dangerous territory, that; if anything you should cultivate dissatisfaction. In Leonardo's drawings there are often five or six attempts to get a line right. The distinctive back of the Porsche 911 only appeared in the redesign of an awkward prototype. In Wright's early plans for the Guggenheim, the right half was a ziggurat; he inverted it to get the present shape. Mistakes are natural. Instead of treating them as disasters, make them easy to acknowledge and easy to fix. Leonardo more or less invented the sketch, as a way to make drawing bear a greater weight of exploration.
当人们谈论处于"心流"状态时,我认为他们指的是脊髓掌控了局面。脊髓更少犹豫,从而释放意识思考处理难题。
好设计运用对称。 我认为对称或许只是实现简单的一种方式,但它足够重要,值得单独讨论。自然界大量使用对称,这是个好迹象。
对称有两种:重复与递归。递归指子元素的重复,如树叶的叶脉图案。
某些领域中对称如今不受欢迎,是对过去过度使用的反叛。建筑师在维多利亚时期开始有意识地建造不对称建筑,到1920年代,不对称已成为现代主义建筑的明确前提。不过即使这些建筑也往往只在主轴线上不对称;仍有数百处微小对称。
写作中,从句子中的短语到小说的情节,每个层面都存在对称。音乐与艺术同样如此。马赛克(和某些塞尚作品)通过用相同原子构建整幅画面,获得额外视觉冲击力。构图对称产生了一些最令人难忘的画作,尤其是当两半相互呼应时,如《创造亚当》或《美国哥特式》。
Open-source software has fewer bugs because it admits the possibility of bugs. It helps to have a medium that makes change easy. When oil paint replaced tempera in the fifteenth century, it helped painters to deal with difficult subjects like the human figure because, unlike tempera, oil can be blended and overpainted. Good design can copy. Attitudes to copying often make a round trip. A novice imitates without knowing it; next he tries consciously to be original; finally, he decides it's more important to be right than original. Unknowing imitation is almost a recipe for bad design. If you don't know where your ideas are coming from, you're probably imitating an imitator. Raphael so pervaded mid-nineteenth century taste that almost anyone who tried to draw was imitating him, often at several removes. It was this, more than Raphael's own work, that bothered the Pre-Raphaelites. The ambitious are not content to imitate. The second phase in the growth of taste is a conscious attempt at originality. I think the greatest masters go on to achieve a kind of selflessness. They just want to get the right answer, and if part of the right answer has already been discovered by someone else, that's no reason not to use it. They're confident enough to take from anyone without feeling that their own vision will be lost in the process. Good design is often strange. Some of the very best work has an uncanny quality: Euler's Formula, Bruegel's _Hunters in the Snow,_ the SR-71, Lisp. They're not just beautiful, but strangely beautiful. I'm not sure why. It may just be my own stupidity. A can-opener must seem miraculous to a dog. Maybe if I were smart enough it would seem the most natural thing in the world that ei*pi = -1. It is after all necessarily true.
在数学与工程中,递归尤其强大。归纳证明出奇地简洁。软件中,能用递归解决的问题几乎总是最好用递归解决。埃菲尔铁塔引人注目,部分原因在于它是递归方案——塔上之塔。
对称(尤其是重复)的危险在于,它可能被用作思考的替代品。
好设计模仿自然。 与其说模仿自然本质上是好的,不如说自然有漫长的时间解决问题。当你的答案与自然相似时,这是个好迹象。
抄袭不算作弊。很少有人会否认故事应当像生活。写生也是绘画中的重要工具,尽管其作用常被误解。目的不只是记录。写生的意义在于为你的思想提供咀嚼之物:当眼睛观察某物时,手会做出更有趣的工作。
模仿自然在工程中也有效。船舶长期采用类似动物肋骨的龙骨与肋材结构。某些情况下我们可能需要等待更好技术:早期飞机设计师错误地将飞机设计得像鸟,因为他们没有足够轻的材料或动力源(莱特兄弟的发动机重152磅,仅12马力),也没有足够复杂的控制系统来实现鸟类飞行方式,但我能想象五十年后会出现像鸟一样飞行的小型无人侦察机。
Most of the qualities I've mentioned are things that can be cultivated, but I don't think it works to cultivate strangeness. The best you can do is not squash it if it starts to appear. Einstein didn't try to make relativity strange. He tried to make it true, and the truth turned out to be strange. At an art school where I once studied, the students wanted most of all to develop a personal style. But if you just try to make good things, you'll inevitably do it in a distinctive way, just as each person walks in a distinctive way. Michelangelo was not trying to paint like Michelangelo. He was just trying to paint well; he couldn't help painting like Michelangelo. The only style worth having is the one you can't help. And this is especially true for strangeness. There is no shortcut to it. The Northwest Passage that the Mannerists, the Romantics, and two generations of American high school students have searched for does not seem to exist. The only way to get there is to go through good and come out the other side. Good design happens in chunks. The inhabitants of fifteenth century Florence included Brunelleschi, Ghiberti, Donatello, Masaccio, Filippo Lippi, Fra Angelico, Verrocchio, Botticelli, Leonardo, and Michelangelo. Milan at the time was as big as Florence. How many fifteenth century Milanese artists can you name? Something was happening in Florence in the fifteenth century. And it can't have been heredity, because it isn't happening now. You have to assume that whatever inborn ability Leonardo and Michelangelo had, there were people born in Milan with just as much. What happened to the Milanese Leonardo? There are roughly a thousand times as many people alive in the US right now as lived in Florence during the fifteenth century. A thousand Leonardos and a thousand Michelangelos walk among us. If DNA ruled, we should be greeted daily by artistic marvels.
现在我们有了足够的计算能力,既能模仿自然的结果,也能模仿其方法。遗传算法可能让我们创造出复杂到无法常规设计的事物。
好设计是再设计。 第一次就做对很罕见。专家预期会抛弃早期工作。他们为计划变更做准备。
抛弃工作需要信心。你必须能够想:"还能做出更多。"例如人们刚开始画画时,常不愿重画不满意的部分;他们觉得能画到这一步已属幸运,担心重画会变得更糟。于是他们说服自己这幅画其实没那么差——甚至可能本来就想画成这样。
这是危险地带;你应该培养的恰恰是不满足感。达·芬奇的素描中,常有五六次尝试才能画对一条线。保时捷911独特的车尾线条,是在重新设计笨拙的原型车后才出现的。赖特早期古根海姆博物馆方案中,右半部是阶梯式金字塔;他将其倒转才得到现有造型。
错误是自然的。与其视其为灾难,不如让它们易于承认和修正。达·芬奇或多或少发明了素描,作为一种让绘画承载更多探索的方式。开源软件缺陷较少,因为它承认缺陷存在的可能性。
拥有便于修改的媒介很有帮助。十五世纪油画取代蛋彩画后,帮助画家处理了如人体等困难主题,因为油画不像蛋彩画,可以混合和覆盖。
We aren't, and the reason is that to make Leonardo you need more than his innate ability. You also need Florence in 1450. Nothing is more powerful than a community of talented people working on related problems. Genes count for little by comparison: being a genetic Leonardo was not enough to compensate for having been born near Milan instead of Florence. Today we move around more, but great work still comes disproportionately from a few hotspots: the Bauhaus, the Manhattan Project, the _New Yorker,_ Lockheed's Skunk Works, Xerox Parc. At any given time there are a few hot topics and a few groups doing great work on them, and it's nearly impossible to do good work yourself if you're too far removed from one of these centers. You can push or pull these trends to some extent, but you can't break away from them. (Maybe _you_ can, but the Milanese Leonardo couldn't.) Good design is often daring. At every period of history, people have believed things that were just ridiculous, and believed them so strongly that you risked ostracism or even violence by saying otherwise. If our own time were any different, that would be remarkable. As far as I can tell it isn't. This problem afflicts not just every era, but in some degree every field. Much Renaissance art was in its time considered shockingly secular: according to Vasari, Botticelli repented and gave up painting, and Fra Bartolommeo and Lorenzo di Credi actually burned some of their work. Einstein's theory of relativity offended many contemporary physicists, and was not fully accepted for decades-- in France, not until the 1950s. Today's experimental error is tomorrow's new theory. If you want to discover great new things, then instead of turning a blind eye to the places where conventional wisdom and truth don't quite meet, you should pay particular attention to them. As a practical matter, I think it's easier to see ugliness than to imagine beauty.
好设计可以抄袭。 对抄袭的态度常呈循环。新手无意识地模仿;接着他有意识地追求原创;最终他认定正确比原创更重要。
无意识的模仿几乎是糟糕设计的配方。如果不知道灵感从何而来,你可能在模仿一个模仿者。拉斐尔影响了十九世纪中叶的品味,以至于几乎所有尝试绘画的人都在模仿他,常常是间接模仿。正是这一点(而非拉斐尔本人的作品)让前拉斐尔派感到困扰。
有抱负者不满足于模仿。品味成长的第二阶段是有意识地追求原创。
我认为最伟大的大师最终达到一种无我境界。他们只想要正确答案,如果部分正确答案已被他人发现,就没有理由不使用。他们足够自信,可以从任何人那里汲取养分,而不担心在这个过程中失去自己的视野。
好设计常常古怪。 一些最杰出的作品带有诡异特质:欧拉公式、勃鲁盖尔的《雪中猎人》、SR-71黑鸟侦察机、Lisp语言。它们不仅美,而且美得怪异。
Most of the people who've made beautiful things seem to have done it by fixing something that they thought ugly. Great work usually seems to happen because someone sees something and thinks, _I could do better than that._ Giotto saw traditional Byzantine madonnas painted according to a formula that had satisfied everyone for centuries, and to him they looked wooden and unnatural. Copernicus was so troubled by a hack that all his contemporaries could tolerate that he felt there must be a better solution. Intolerance for ugliness is not in itself enough. You have to understand a field well before you develop a good nose for what needs fixing. You have to do your homework. But as you become expert in a field, you'll start to hear little voices saying, _What a hack! There must be a better way._ Don't ignore those voices. Cultivate them. The recipe for great work is: very exacting taste, plus the ability to gratify it. Notes Sullivan actually said "form ever follows function," but I think the usual misquotation is closer to what modernist architects meant. Stephen G. Brush, "Why was Relativity Accepted?" _Phys. Perspect. 1 (1999) 184-214. _
| Japanese Translation | | | Chinese Translation | Slovenian Translation | | | German Translation | Interview: Milton Glaser | | | Russian Translation.
我不确定原因。或许只是我太愚钝。开罐器对狗来说一定像奇迹。也许如果我足够聪明,就会觉得e^iπ = -1是世界上最自然的事。它毕竟是必然成立的。
我提到的大多数品质是可以培养的,但我不认为古怪可以培养。你能做的最好是不压制它,如果它开始显现。爱因斯坦并未试图让相对论显得古怪。他试图让它正确,而真理结果显得古怪。
我曾就读的艺术学校中,学生最渴望的是发展个人风格。但如果你只是努力做好东西, inevitably 会以独特方式完成,就像每个人走路姿势都不同。米开朗基罗并非试图画得像米开朗基罗。他只是试图画好;他无法不画得像米开朗基罗。
唯一值得拥有的风格是你无法避免的风格。这对古怪尤其适用。没有捷径可走。矫饰主义者、浪漫主义者和两代美国高中生寻找的西北航道似乎并不存在。唯一到达的方式是穿越"好",从另一侧出来。
好设计成批出现。 十五世纪佛罗伦萨的居民包括布鲁内莱斯基、吉贝尔蒂、多纳泰罗、马萨乔、菲利波·利皮、弗拉·安杰利科、韦罗基奥、波提切利、达·芬奇和米开朗基罗。当时米兰与佛罗伦萨规模相当。你能说出多少十五世纪米兰艺术家的名字?
You'll find this essay and 14 others in _Hackers & Painters_.
十五世纪的佛罗伦萨发生了某些事。这不可能是遗传,因为现在并未发生。你必须假设,无论达·芬奇和米开朗基罗拥有多少天赋,米兰也有同样天赋的人出生。米兰的达·芬奇去哪儿了?
美国现有人口大约是十五世纪佛罗伦萨的一千倍。一千个达·芬奇和一千个米开朗基罗行走在我们中间。如果DNA决定一切,我们每天都会遇到艺术奇迹。但事实并非如此,原因是创造达·芬奇不仅需要他的天赋,还需要1450年的佛罗伦萨。
没有什么比一群才华横溢的人共同解决相关问题更有力量。相比之下基因微不足道:作为基因上的达·芬奇,不足以补偿出生在米兰而非佛罗伦萨的缺憾。如今我们流动性更强,但伟大作品仍不成比例地来自少数热点:包豪斯、曼哈顿计划、《纽约客》杂志、洛克希德的臭鼬工厂、施乐帕克研究中心。
任何时候都存在几个热门话题和几个从事相关杰出工作的群体,如果你离这些中心太远,几乎不可能做出好工作。你可以在一定程度上推动或拉动这些趋势,但无法脱离它们。(也许你能,但米兰的达·芬奇不能。)
好设计常常大胆。 在历史的每个时期,人们都相信一些
你可以在《黑客与画家》一书中找到这篇文章以及其他14篇文章。
December 2001 (rev. May 2002) _(This article came about in response to some questions on theLL1 mailing list. It is now incorporated in Revenge of the Nerds.)_ When McCarthy designed Lisp in the late 1950s, it was a radical departure from existing languages, the most important of which was Fortran. Lisp embodied nine new ideas:
1\. Conditionals. A conditional is an if-then-else construct. We take these for granted now. They were invented by McCarthy in the course of developing Lisp. (Fortran at that time only had a conditional goto, closely based on the branch instruction in the underlying hardware.) McCarthy, who was on the Algol committee, got conditionals into Algol, whence they spread to most other languages. 2\. A function type. In Lisp, functions are first class objects-- they're a data type just like integers, strings, etc, and have a literal representation, can be stored in variables, can be passed as arguments, and so on. 3\. Recursion. Recursion existed as a mathematical concept before Lisp of course, but Lisp was the first programming language to support it. (It's arguably implicit in making functions first class objects.) 4\. A new concept of variables. In Lisp, all variables are effectively pointers. Values are what have types, not variables, and assigning or binding variables means copying pointers, not what they point to. 5\. Garbage-collection. 6\. Programs composed of expressions. Lisp programs are trees of expressions, each of which returns a value. (In some Lisps expressions can return multiple values.) This is in contrast to Fortran and most succeeding languages, which distinguish between expressions and statements. It was natural to have this distinction in Fortran because (not surprisingly in a language where the input format was punched cards) the language was line-oriented. You could not nest statements. And so while you needed expressions for math to work, there was no point in making anything else return a value, because there could not be anything waiting for it. This limitation went away with the arrival of block-structured languages, but by then it was too late. The distinction between expressions and statements was entrenched.
2. 函数类型。 在Lisp中,函数是一等对象——它们与整数、字符串等数据类型无异,具有字面表示形式,可存储于变量中,也能作为参数传递。
3. 递归。 递归作为数学概念早于Lisp存在,但Lisp是首个支持递归的编程语言(将函数作为一等对象隐含着这一特性)。
4. 全新的变量概念。 Lisp中所有变量本质上都是指针。类型属于值而非变量,变量赋值或绑定意味着复制指针而非其所指内容。
5. 垃圾回收机制。
6. 由表达式构成的程序。 Lisp程序是表达式树,每个表达式都返回值(某些Lisp方言支持多值返回)。这与Fortran及多数后继语言形成对比,后者严格区分表达式与语句。
It spread from Fortran into Algol and thence to both their descendants. When a language is made entirely of expressions, you can compose expressions however you want. You can say either (using Arc syntax) (if foo (= x 1) (= x 2)) or (= x (if foo 1 2)) 7\. A symbol type. Symbols differ from strings in that you can test equality by comparing a pointer. 8\. A notation for code using trees of symbols. 9\. The whole language always available. There is no real distinction between read-time, compile-time, and runtime. You can compile or run code while reading, read or run code while compiling, and read or compile code at runtime. Running code at read-time lets users reprogram Lisp's syntax; running code at compile-time is the basis of macros; compiling at runtime is the basis of Lisp's use as an extension language in programs like Emacs; and reading at runtime enables programs to communicate using s-expressions, an idea recently reinvented as XML..
Fortran的这种区分很自然:由于该语言基于打孔卡输入格式,其设计以行为单位。语句不可嵌套。数学运算需要表达式,但其他结构无需返回值——因为没有接收返回值的上下文。
随着块结构语言的出现,这一限制本应消失,但为时已晚。表达式与语句的区分已根深蒂固,从Fortran蔓延至Algol,进而影响两者后代。
当语言完全由表达式构成时,表达式可自由组合。例如(使用Arc语法)既可写:
``lisp
(if foo (= x 1) (= x 2))
`
也可写:
`lisp
(= x (if foo 1 2))
``
7. 符号类型。 符号与字符串的区别在于可通过指针比较来测试相等性。
8. 基于符号树的代码表示法。
When Lisp was first invented, all these ideas were far removed from ordinary programming practice, which was dictated largely by the hardware available in the late 1950s. Over time, the default language, embodied in a succession of popular languages, has gradually evolved toward Lisp. 1-5 are now widespread. 6 is starting to appear in the mainstream. Python has a form of 7, though there doesn't seem to be any syntax for it. 8, which (with 9) is what makes Lisp macros possible, is so far still unique to Lisp, perhaps because (a) it requires those parens, or something just as bad, and (b) if you add that final increment of power, you can no longer claim to have invented a new language, but only to have designed a new dialect of Lisp ; -) Though useful to present-day programmers, it's strange to describe Lisp in terms of its variation from the random expedients other languages adopted. That was not, probably, how McCarthy thought of it. Lisp wasn't designed to fix the mistakes in Fortran; it came about more as the byproduct of an attempt to axiomatize computation.
9. 全语言随时可用。 读取时、编译时与运行时之间没有严格界限。你可以在读取时编译或运行代码,在编译时读取或运行代码,在运行时读取或编译代码。
读取时运行代码让用户能重定义Lisp语法;编译时运行代码是宏的基础;运行时编译支持Lisp作为Emacs等程序的扩展语言;运行时读取则使程序能通过s表达式通信——这一思想后来以XML形式被重新发明。
当Lisp最初被发明时,所有这些理念都与常规编程实践相去甚远,当时的编程实践很大程度上受限于20世纪50年代末的硬件条件。
随着时间的推移,以一系列流行语言为代表的默认编程语言逐渐向Lisp靠拢。其中1-5项特性现已广泛普及。第6项特性开始出现在主流语言中。Python具备了第7项特性的某种形式,尽管似乎没有专门的语法支持。而第8项特性(与第9项共同构成了Lisp宏的实现基础)至今仍是Lisp独有的特色——或许因为(a)它需要依赖括号或同样"糟糕"的符号,(b)一旦添加了这个终极能力,你就不能再声称发明了新语言,而只能算设计了Lisp的新方言;-)
虽然对当代程序员很有帮助,但用Lisp与其他语言随机采用的权宜之计之间的差异来描述它,其实颇为奇怪。这很可能不是麦卡锡的原始构想。Lisp并非为修正Fortran的缺陷而生,它更像是计算公理化尝试的副产品。
| 日语译本
September 2001 _(This article explains why much of the next generation of software may be server-based, what that will mean for programmers, and why this new kind of software is a great opportunity for startups. It's derived from a talk at BBN Labs.)_ In the summer of 1995, my friend Robert Morris and I decided to start a startup. The PR campaign leading up to Netscape's IPO was running full blast then, and there was a lot of talk in the press about online commerce. At the time there might have been thirty actual stores on the Web, all made by hand. If there were going to be a lot of online stores, there would need to be software for making them, so we decided to write some. For the first week or so we intended to make this an ordinary desktop application. Then one day we had the idea of making the software run on our Web server, using the browser as an interface. We tried rewriting the software to work over the Web, and it was clear that this was the way to go. If we wrote our software to run on the server, it would be a lot easier for the users and for us as well. This turned out to be a good plan. Now, as Yahoo Store, this software is the most popular online store builder, with about 14,000 users. When we started Viaweb, hardly anyone understood what we meant when we said that the software ran on the server. It was not until Hotmail was launched a year later that people started to get it. Now everyone knows that this is a valid approach. There is a name now for what we were: an Application Service Provider, or ASP. I think that a lot of the next generation of software will be written on this model. Even Microsoft, who have the most to lose, seem to see the inevitablity of moving some things off the desktop. If software moves off the desktop and onto servers, it will mean a very different world for developers.
(以下为直接翻译结果,未添加任何说明或注释)
This article describes the surprising things we saw, as some of the first visitors to this new world. To the extent software does move onto servers, what I'm describing here is the future. The Next Thing? When we look back on the desktop software era, I think we'll marvel at the inconveniences people put up with, just as we marvel now at what early car owners put up with. For the first twenty or thirty years, you had to be a car expert to own a car. But cars were such a big win that lots of people who weren't car experts wanted to have them as well. Computers are in this phase now. When you own a desktop computer, you end up learning a lot more than you wanted to know about what's happening inside it. But more than half the households in the US own one. My mother has a computer that she uses for email and for keeping accounts. About a year ago she was alarmed to receive a letter from Apple, offering her a discount on a new version of the operating system. There's something wrong when a sixty-five year old woman who wants to use a computer for email and accounts has to think about installing new operating systems. Ordinary users shouldn't even know the words "operating system," much less "device driver" or "patch." There is now another way to deliver software that will save users from becoming system administrators. Web-based applications are programs that run on Web servers and use Web pages as the user interface. For the average user this new kind of software will be easier, cheaper, more mobile, more reliable, and often more powerful than desktop software. With Web-based software, most users won't have to think about anything except the applications they use. All the messy, changing stuff will be sitting on a server somewhere, maintained by the kind of people who are good at that kind of thing. And so you won't ordinarily need a computer, per se, to use software.
2001年9月 (本文解释了为何下一代软件可能基于服务器、这对程序员意味着什么,以及这类新型软件为何是创业公司的绝佳机会。内容源自我在BBN实验室的演讲。)
1995年夏天,我和朋友罗伯特·莫里斯决定创业。当时网景公司IPO前的公关宣传如火如荼,媒体热议在线商务。那时全网可能只有约30家手工搭建的在线商店。如果未来在线商店激增,就需要专门的建站软件——这正是我们打算开发的。
All you'll need will be something with a keyboard, a screen, and a Web browser. Maybe it will have wireless Internet access. Maybe it will also be your cell phone. Whatever it is, it will be consumer electronics: something that costs about $200, and that people choose mostly based on how the case looks. You'll pay more for Internet services than you do for the hardware, just as you do now with telephones. [1] It will take about a tenth of a second for a click to get to the server and back, so users of heavily interactive software, like Photoshop, will still want to have the computations happening on the desktop. But if you look at the kind of things most people use computers for, a tenth of a second latency would not be a problem. My mother doesn't really need a desktop computer, and there are a lot of people like her. The Win for Users Near my house there is a car with a bumper sticker that reads "death before inconvenience." Most people, most of the time, will take whatever choice requires least work. If Web-based software wins, it will be because it's more convenient. And it looks as if it will be, for users and developers both. To use a purely Web-based application, all you need is a browser connected to the Internet. So you can use a Web-based application anywhere. When you install software on your desktop computer, you can only use it on that computer. Worse still, your files are trapped on that computer. The inconvenience of this model becomes more and more evident as people get used to networks. The thin end of the wedge here was Web-based email. Millions of people now realize that you should have access to email messages no matter where you are.
最初一周我们计划开发传统桌面应用。直到某天灵光乍现:何不让软件运行在网页服务器上,用浏览器作为界面?当我们尝试重写为网页版时,立刻意识到这才是未来。基于服务器的软件对用户和我们而言都轻松得多。
这个决策被证明是成功的。这款软件后来成为Yahoo Store,拥有约1.4万用户,是最受欢迎的在线商店构建工具。
And if you can see your email, why not your calendar? If you can discuss a document with your colleagues, why can't you edit it? Why should any of your data be trapped on some computer sitting on a faraway desk? The whole idea of "your computer" is going away, and being replaced with "your data." You should be able to get at your data from any computer. Or rather, any client, and a client doesn't have to be a computer. Clients shouldn't store data; they should be like telephones. In fact they may become telephones, or vice versa. And as clients get smaller, you have another reason not to keep your data on them: something you carry around with you can be lost or stolen. Leaving your PDA in a taxi is like a disk crash, except that your data is handed to someone else instead of being vaporized. With purely Web-based software, neither your data nor the applications are kept on the client. So you don't have to install anything to use it. And when there's no installation, you don't have to worry about installation going wrong. There can't be incompatibilities between the application and your operating system, because the software doesn't run on your operating system. Because it needs no installation, it will be easy, and common, to try Web-based software before you "buy" it. You should expect to be able to test-drive any Web-based application for free, just by going to the site where it's offered. At Viaweb our whole site was like a big arrow pointing users to the test drive. After trying the demo, signing up for the service should require nothing more than filling out a brief form (the briefer the better). And that should be the last work the user has to do. With Web-based software, you should get new releases without paying extra, or doing any work, or possibly even knowing about it. Upgrades won't be the big shocks they are now.
Viaweb初创时,几乎没人理解"软件运行在服务器上"的含义。直到一年后Hotmail问世,人们才逐渐明白。如今这种模式已被广泛认可,我们这类公司被称为"应用服务提供商"(ASP)。
我认为下一代软件将大量采用这种模式。即便是损失最大的微软,也意识到将部分功能移出桌面不可避免。若软件从桌面转向服务器,开发者将面对截然不同的世界。本文描述了我们作为首批探索者观察到的惊人现象——若软件真向服务器迁移,我描述的这些就是未来。
Over time applications will quietly grow more powerful. This will take some effort on the part of the developers. They will have to design software so that it can be updated without confusing the users. That's a new problem, but there are ways to solve it. With Web-based applications, everyone uses the same version, and bugs can be fixed as soon as they're discovered. So Web-based software should have far fewer bugs than desktop software. At Viaweb, I doubt we ever had ten known bugs at any one time. That's orders of magnitude better than desktop software. Web-based applications can be used by several people at the same time. This is an obvious win for collaborative applications, but I bet users will start to want this in most applications once they realize it's possible. It will often be useful to let two people edit the same document, for example. Viaweb let multiple users edit a site simultaneously, more because that was the right way to write the software than because we expected users to want to, but it turned out that many did. When you use a Web-based application, your data will be safer. Disk crashes won't be a thing of the past, but users won't hear about them anymore. They'll happen within server farms. And companies offering Web-based applications will actually do backups-- not only because they'll have real system administrators worrying about such things, but because an ASP that does lose people's data will be in big, big trouble. When people lose their own data in a disk crash, they can't get that mad, because they only have themselves to be mad at. When a company loses their data for them, they'll get a lot madder. Finally, Web-based software should be less vulnerable to viruses. If the client doesn't run anything except a browser, there's less chance of running viruses, and no data locally to damage.
回望桌面软件时代,人们忍受的不便将令我们惊诧,就像如今我们惊讶早期车主的遭遇。汽车问世二三十年间,你必须是个专家才能拥有它。但汽车优势如此显著,大量非专业人士仍趋之若鹜。
计算机正处在这一阶段。拥有台式机意味着被迫了解远超预期的内部原理。但美国超半数家庭拥有电脑。我母亲用电脑收发邮件和记账,一年前却因收到苹果系统升级折扣信而惊慌——65岁老人为基础功能竟需考虑系统安装,这显然不合理。"操作系统"、"设备驱动"、"补丁"这类词汇本不该出现在普通用户词典里。
And a program that attacked the servers themselves should find them very well defended. [2] For users, Web-based software will be _less stressful._ I think if you looked inside the average Windows user you'd find a huge and pretty much untapped desire for software meeting that description. Unleashed, it could be a powerful force. City of Code To developers, the most conspicuous difference between Web-based and desktop software is that a Web-based application is not a single piece of code. It will be a collection of programs of different types rather than a single big binary. And so designing Web-based software is like desiging a city rather than a building: as well as buildings you need roads, street signs, utilities, police and fire departments, and plans for both growth and various kinds of disasters. At Viaweb, software included fairly big applications that users talked to directly, programs that those programs used, programs that ran constantly in the background looking for problems, programs that tried to restart things if they broke, programs that ran occasionally to compile statistics or build indexes for searches, programs we ran explicitly to garbage-collect resources or to move or restore data, programs that pretended to be users (to measure performance or expose bugs), programs for diagnosing network troubles, programs for doing backups, interfaces to outside services, software that drove an impressive collection of dials displaying real-time server statistics (a hit with visitors, but indispensable for us too), modifications (including bug fixes) to open-source software, and a great many configuration files and settings. Trevor Blackwell wrote a spectacular program for moving stores to new servers across the country, without shutting them down, after we were bought by Yahoo.
如今有另一种软件交付方式能让用户摆脱系统管理噩梦:基于网页的应用程序。这类软件运行在服务器上,以网页为界面。对普通用户而言,它将比桌面软件更便捷、更经济、更灵活、更可靠,且往往更强大。
使用网页软件时,用户只需关注应用本身。所有复杂多变的组件都交由专业人士维护在服务器端。严格来说,你甚至不需要"电脑"——任何带键盘、屏幕和浏览器的设备(可能是无线联网的手机)都能使用。硬件将如家电般便宜(约200美元),外观成为主要选购标准。正如电话服务现状,互联网服务的开支终将超过硬件成本[1]。
Programs paged us, sent faxes and email to users, conducted transactions with credit card processors, and talked to one another through sockets, pipes, http requests, ssh, udp packets, shared memory, and files. Some of Viaweb even consisted of the absence of programs, since one of the keys to Unix security is not to run unnecessary utilities that people might use to break into your servers. It did not end with software. We spent a lot of time thinking about server configurations. We built the servers ourselves, from components-- partly to save money, and partly to get exactly what we wanted. We had to think about whether our upstream ISP had fast enough connections to all the backbones. We serially dated RAID suppliers. But hardware is not just something to worry about. When you control it you can do more for users. With a desktop application, you can specify certain minimum hardware, but you can't add more. If you administer the servers, you can in one step enable all your users to page people, or send faxes, or send commands by phone, or process credit cards, etc, just by installing the relevant hardware. We always looked for new ways to add features with hardware, not just because it pleased users, but also as a way to distinguish ourselves from competitors who (either because they sold desktop software, or resold Web-based applications through ISPs) didn't have direct control over the hardware. Because the software in a Web-based application will be a collection of programs rather than a single binary, it can be written in any number of different languages. When you're writing desktop software, you're practically forced to write the application in the same language as the underlying operating system-- meaning C and C++.
点击到服务器的往返延迟约0.1秒,因此Photoshop等强交互软件仍需本地计算。但这对多数日常需求已足够。我母亲这类用户其实根本不需要传统电脑。
And so these languages (especially among nontechnical people like managers and VCs) got to be considered as the languages for "serious" software development. But that was just an artifact of the way desktop software had to be delivered. For server-based software you can use any language you want. [3] Today a lot of the top hackers are using languages far removed from C and C++: Perl, Python, and even Lisp. With server-based software, no one can tell you what language to use, because you control the whole system, right down to the hardware. Different languages are good for different tasks. You can use whichever is best for each. And when you have competitors, "you can" means "you must" (we'll return to this later), because if you don't take advantage of this possibility, your competitors will. Most of our competitors used C and C++, and this made their software visibly inferior because (among other things), they had no way around the statelessness of CGI scripts. If you were going to change something, all the changes had to happen on one page, with an Update button at the bottom. As I've written elsewhere, by using Lisp, which many people still consider a research language, we could make the Viaweb editor behave more like desktop software. Releases One of the most important changes in this new world is the way you do releases. In the desktop software business, doing a release is a huge trauma, in which the whole company sweats and strains to push out a single, giant piece of code. Obvious comparisons suggest themselves, both to the process and the resulting product. With server-based software, you can make changes almost as you would in a program you were writing for yourself. You release software as a series of incremental changes instead of an occasional big explosion. A typical desktop software company might do one or two releases a year. At Viaweb we often did three to five releases a day.
我家附近有辆车贴着标语"宁死不便"。多数人在多数时候会选择最省力的方案。网页软件若胜出,必因其更便捷——对用户和开发者皆然。
纯网页应用只需联网浏览器即可使用,意味着随处可用。桌面软件则困于单台设备,文件也被禁锢其中。随着网络普及,这种不便日益凸显。
When you switch to this new model, you realize how much software development is affected by the way it is released. Many of the nastiest problems you see in the desktop software business are due to catastrophic nature of releases. When you release only one new version a year, you tend to deal with bugs wholesale. Some time before the release date you assemble a new version in which half the code has been torn out and replaced, introducing countless bugs. Then a squad of QA people step in and start counting them, and the programmers work down the list, fixing them. They do not generally get to the end of the list, and indeed, no one is sure where the end is. It's like fishing rubble out of a pond. You never really know what's happening inside the software. At best you end up with a statistical sort of correctness. With server-based software, most of the change is small and incremental. That in itself is less likely to introduce bugs. It also means you know what to test most carefully when you're about to release software: the last thing you changed. You end up with a much firmer grip on the code. As a general rule, you do know what's happening inside it. You don't have the source code memorized, of course, but when you read the source you do it like a pilot scanning the instrument panel, not like a detective trying to unravel some mystery. Desktop software breeds a certain fatalism about bugs. You know that you're shipping something loaded with bugs, and you've even set up mechanisms to compensate for it (e.g. patch releases). So why worry about a few more? Soon you're releasing whole features you know are broken. Apple did this earlier this year. They felt under pressure to release their new OS, whose release date had already slipped four times, but some of the software (support for CDs and DVDs) wasn't ready.
网页邮箱是变革先锋。如今数百万人已认同"随时随地查邮件"的理念。既然能查看邮件,为何不能管理日程?能协作讨论文档,为何不能直接编辑?数据何必困在远方某台电脑里?
"你的电脑"概念正被"你的数据"取代。数据应能从任何终端获取——"终端"甚至不必是电脑。
The solution? They released the OS without the unfinished parts, and users will have to install them later. With Web-based software, you never have to release software before it works, and you can release it as soon as it does work. The industry veteran may be thinking, it's a fine-sounding idea to say that you never have to release software before it works, but what happens when you've promised to deliver a new version of your software by a certain date? With Web-based software, you wouldn't make such a promise, because there are no versions. Your software changes gradually and continuously. Some changes might be bigger than others, but the idea of versions just doesn't naturally fit onto Web-based software. If anyone remembers Viaweb this might sound odd, because we were always announcing new versions. This was done entirely for PR purposes. The trade press, we learned, thinks in version numbers. They will give you major coverage for a major release, meaning a new first digit on the version number, and generally a paragraph at most for a point release, meaning a new digit after the decimal point. Some of our competitors were offering desktop software and actually had version numbers. And for these releases, the mere fact of which seemed to us evidence of their backwardness, they would get all kinds of publicity. We didn't want to miss out, so we started giving version numbers to our software too. When we wanted some publicity, we'd make a list of all the features we'd added since the last "release," stick a new version number on the software, and issue a press release saying that the new version was available immediately. Amazingly, no one ever called us on it. By the time we were bought, we had done this three times, so we were on Version 4. Version 4.1 if I remember correctly.
终端不该存储数据,应如电话般单纯。事实上终端可能演变为电话(或反之)。随着设备小型化,本地存储数据风险加剧——随身设备易丢失或被窃。把PDA遗落出租车堪比硬盘崩溃,区别在于数据会落入他人之手而非消失。
纯网页软件的数据和应用都不驻留终端,因此无需安装,自然也无安装故障风险。应用与操作系统不存在兼容问题,因为软件根本不运行在你的系统上。
After Viaweb became Yahoo Store, there was no longer such a desperate need for publicity, so although the software continued to evolve, the whole idea of version numbers was quietly dropped. Bugs The other major technical advantage of Web-based software is that you can reproduce most bugs. You have the users' data right there on your disk. If someone breaks your software, you don't have to try to guess what's going on, as you would with desktop software: you should be able to reproduce the error while they're on the phone with you. You might even know about it already, if you have code for noticing errors built into your application. Web-based software gets used round the clock, so everything you do is immediately put through the wringer. Bugs turn up quickly. Software companies are sometimes accused of letting the users debug their software. And that is just what I'm advocating. For Web-based software it's actually a good plan, because the bugs are fewer and transient. When you release software gradually you get far fewer bugs to start with. And when you can reproduce errors and release changes instantly, you can find and fix most bugs as soon as they appear. We never had enough bugs at any one time to bother with a formal bug-tracking system. You should test changes before you release them, of course, so no major bugs should get released. Those few that inevitably slip through will involve borderline cases and will only affect the few users that encounter them before someone calls in to complain. As long as you fix bugs right away, the net effect, for the average user, is far fewer bugs. I doubt the average Viaweb user ever saw a bug. Fixing fresh bugs is easier than fixing old ones. It's usually fairly quick to find a bug in code you just wrote. When it turns up you often know what's wrong before you even look at the source, because you were already worrying about it subconsciously.
免安装特性使"先试后买"成为常态。任何网页应用都应支持免费试用,Viaweb整个网站就像指向试用版的巨大箭头。
试完后注册只需填写简短表格(越短越好),这将是用户最后的操作。网页软件的新版本应自动推送,无需额外付费、操作甚至知情。
Fixing a bug in something you wrote six months ago (the average case if you release once a year) is a lot more work. And since you don't understand the code as well, you're more likely to fix it in an ugly way, or even introduce more bugs. [4] When you catch bugs early, you also get fewer compound bugs. Compound bugs are two separate bugs that interact: you trip going downstairs, and when you reach for the handrail it comes off in your hand. In software this kind of bug is the hardest to find, and also tends to have the worst consequences. [5] The traditional "break everything and then filter out the bugs" approach inherently yields a lot of compound bugs. And software that's released in a series of small changes inherently tends not to. The floors are constantly being swept clean of any loose objects that might later get stuck in something. It helps if you use a technique called functional programming. Functional programming means avoiding side-effects. It's something you're more likely to see in research papers than commercial software, but for Web-based applications it turns out to be really useful. It's hard to write entire programs as purely functional code, but you can write substantial chunks this way. It makes those parts of your software easier to test, because they have no state, and that is very convenient in a situation where you are constantly making and testing small modifications. I wrote much of Viaweb's editor in this style, and we made our scripting language, RTML, a purely functional language. People from the desktop software business will find this hard to credit, but at Viaweb bugs became almost a game. Since most released bugs involved borderline cases, the users who encountered them were likely to be advanced users, pushing the envelope. Advanced users are more forgiving about bugs, especially since you probably introduced them in the course of adding some feature they were asking for.
升级不再像现在这样充满阵痛。应用将静默增强,这要求开发者精心设计可无缝更新的架构——虽是新挑战,但有解决之道。
网页应用所有人使用相同版本,漏洞可即时修复。因此其缺陷应远少于桌面软件。Viaweb同时段已知漏洞从不超过10个,比桌面软件优秀数个量级。
In fact, because bugs were rare and you had to be doing sophisticated things to see them, advanced users were often proud to catch one. They would call support in a spirit more of triumph than anger, as if they had scored points off us. Support When you can reproduce errors, it changes your approach to customer support. At most software companies, support is offered as a way to make customers feel better. They're either calling you about a known bug, or they're just doing something wrong and you have to figure out what. In either case there's not much you can learn from them. And so you tend to view support calls as a pain in the ass that you want to isolate from your developers as much as possible. This was not how things worked at Viaweb. At Viaweb, support was free, because we wanted to hear from customers. If someone had a problem, we wanted to know about it right away so that we could reproduce the error and release a fix. So at Viaweb the developers were always in close contact with support. The customer support people were about thirty feet away from the programmers, and knew that they could always interrupt anything with a report of a genuine bug. We would leave a board meeting to fix a serious bug. Our approach to support made everyone happier. The customers were delighted. Just imagine how it would feel to call a support line and be treated as someone bringing important news. The customer support people liked it because it meant they could help the users, instead of reading scripts to them. And the programmers liked it because they could reproduce bugs instead of just hearing vague second-hand reports about them. Our policy of fixing bugs on the fly changed the relationship between customer support people and hackers. At most software companies, support people are underpaid human shields, and hackers are little copies of God the Father, creators of the world.
网页应用支持多人实时协作。这对协同工具是天然优势,但我打赌用户一旦意识到可能性,会期待所有应用具备此功能。比如允许多人编辑同一文档就很有用。Viaweb允许多用户同时编辑站点,最初是因这种架构最合理,不料后来成为许多用户钟爱的功能。
Whatever the procedure for reporting bugs, it is likely to be one-directional: support people who hear about bugs fill out some form that eventually gets passed on (possibly via QA) to programmers, who put it on their list of things to do. It was very different at Viaweb. Within a minute of hearing about a bug from a customer, the support people could be standing next to a programmer hearing him say "Shit, you're right, it's a bug." It delighted the support people to hear that "you're right" from the hackers. They used to bring us bugs with the same expectant air as a cat bringing you a mouse it has just killed. It also made them more careful in judging the seriousness of a bug, because now their honor was on the line. After we were bought by Yahoo, the customer support people were moved far away from the programmers. It was only then that we realized that they were effectively QA and to some extent marketing as well. In addition to catching bugs, they were the keepers of the knowledge of vaguer, buglike things, like features that confused users. [6] They were also a kind of proxy focus group; we could ask them which of two new features users wanted more, and they were always right. Morale Being able to release software immediately is a big motivator. Often as I was walking to work I would think of some change I wanted to make to the software, and do it that day. This worked for bigger features as well. Even if something was going to take two weeks to write (few projects took longer), I knew I could see the effect in the software as soon as it was done. If I'd had to wait a year for the next release, I would have shelved most of these ideas, for a while at least. The thing about ideas, though, is that they lead to more ideas. Have you ever noticed that when you sit down to write something, half the ideas that end up in it are ones you thought of while writing it? The same thing happens with software.
使用网页应用时数据更安全。硬盘崩溃不会绝迹,但用户再不会知晓——它们只发生在服务器集群中。提供网页应用的公司会认真备份,不仅因专业系统管理员负责此事,更因丢失用户数据的ASP将面临灭顶之灾。个人数据丢失只能自责,企业弄丢用户数据则会引发滔天怒火。
最后,网页软件更不易受病毒攻击。若终端仅运行浏览器,病毒难有可乘之机,本地也无数据可破坏。攻击服务器的程序将遭遇铜墙铁壁[2]。
Working to implement one idea gives you more ideas. So shelving an idea costs you not only that delay in implementing it, but also all the ideas that implementing it would have led to. In fact, shelving an idea probably even inhibits new ideas: as you start to think of some new feature, you catch sight of the shelf and think "but I already have a lot of new things I want to do for the next release." What big companies do instead of implementing features is plan them. At Viaweb we sometimes ran into trouble on this account. Investors and analysts would ask us what we had planned for the future. The truthful answer would have been, we didn't have any plans. We had general ideas about things we wanted to improve, but if we knew how we would have done it already. What were we going to do in the next six months? Whatever looked like the biggest win. I don't know if I ever dared give this answer, but that was the truth. Plans are just another word for ideas on the shelf. When we thought of good ideas, we implemented them. At Viaweb, as at many software companies, most code had one definite owner. But when you owned something you really owned it: no one except the owner of a piece of software had to approve (or even know about) a release. There was no protection against breakage except the fear of looking like an idiot to one's peers, and that was more than enough. I may have given the impression that we just blithely plowed forward writing code. We did go fast, but we thought very carefully before we released software onto those servers. And paying attention is more important to reliability than moving slowly. Because he pays close attention, a Navy pilot can land a 40,000 lb. aircraft at 140 miles per hour on a pitching carrier deck, at night, more safely than the average teenager can cut a bagel. This way of writing software is a double-edged sword of course.
对用户而言,网页软件将大幅减轻压力。若窥视普通Windows用户内心,你会发现他们对这类软件的渴望深不见底。释放这种需求将形成强大力量。
对开发者而言,网页与桌面软件最显著区别在于:前者不是单一代码块,而是多种程序的集合。设计网页软件如同规划城市而非建筑——除建筑物外,还需道路、路标、市政设施、警消系统,以及应对发展与灾难的方案。
It works a lot better for a small team of good, trusted programmers than it would for a big company of mediocre ones, where bad ideas are caught by committees instead of the people that had them. Brooks in Reverse Fortunately, Web-based software does require fewer programmers. I once worked for a medium-sized desktop software company that had over 100 people working in engineering as a whole. Only 13 of these were in product development. All the rest were working on releases, ports, and so on. With Web-based software, all you need (at most) are the 13 people, because there are no releases, ports, and so on. Viaweb was written by just three people. [7] I was always under pressure to hire more, because we wanted to get bought, and we knew that buyers would have a hard time paying a high price for a company with only three programmers. (Solution: we hired more, but created new projects for them.) When you can write software with fewer programmers, it saves you more than money. As Fred Brooks pointed out in _The Mythical Man-Month,_ adding people to a project tends to slow it down. The number of possible connections between developers grows exponentially with the size of the group. The larger the group, the more time they'll spend in meetings negotiating how their software will work together, and the more bugs they'll get from unforeseen interactions. Fortunately, this process also works in reverse: as groups get smaller, software development gets exponentially more efficient. I can't remember the programmers at Viaweb ever having an actual meeting. We never had more to say at any one time than we could say as we were walking to lunch. If there is a downside here, it is that all the programmers have to be to some degree system administrators as well. When you're hosting software, someone has to be watching the servers, and in practice the only people who can do this properly are the ones who wrote the software.
Viaweb的软件包含:用户直接交互的主程序、子程序、后台监控程序、故障重启程序、统计编译与搜索索引程序、资源回收与数据迁移程序、模拟用户程序(用于性能测试与漏洞发现)、网络诊断工具、备份程序、外部服务接口、实时服务器仪表盘(访客觉得酷炫,对我们更是必备)、开源软件修改(含漏洞修复),以及大量配置文件。被雅虎收购后,特雷弗·布莱克韦尔编写了惊人程序,能在不关停情况下将商店迁移至全国各地的服务器。程序会给我们发告警、给用户发传真邮件、与信用卡处理器交易,并通过套接字、管道、HTTP请求、SSH、UDP包、共享内存和文件相互通信。Viaweb部分安全策略甚至是"不运行某些程序"——因为Unix安全的关键在于禁用可能被利用的冗余工具。
这还不止。我们耗费大量精力设计服务器配置,自行组装硬件——既为省钱,更为精准定制。需考虑上游ISP与所有主干网的连接速度,像挑选恋人般筛选RAID供应商。
At Viaweb our system had so many components and changed so frequently that there was no definite border between software and infrastructure. Arbitrarily declaring such a border would have constrained our design choices. And so although we were constantly hoping that one day ("in a couple months") everything would be stable enough that we could hire someone whose job was just to worry about the servers, it never happened. I don't think it could be any other way, as long as you're still actively developing the product. Web-based software is never going to be something you write, check in, and go home. It's a live thing, running on your servers right now. A bad bug might not just crash one user's process; it could crash them all. If a bug in your code corrupts some data on disk, you have to fix it. And so on. We found that you don't have to watch the servers every minute (after the first year or so), but you definitely want to keep an eye on things you've changed recently. You don't release code late at night and then go home. Watching Users With server-based software, you're in closer touch with your code. You can also be in closer touch with your users. Intuit is famous for introducing themselves to customers at retail stores and asking to follow them home. If you've ever watched someone use your software for the first time, you know what surprises must have awaited them. Software should do what users think it will. But you can't have any idea what users will be thinking, believe me, until you watch them. And server-based software gives you unprecedented information about their behavior. You're not limited to small, artificial focus groups. You can see every click made by every user. You have to consider carefully what you're going to look at, because you don't want to violate users' privacy, but even the most general statistical sampling can be very useful.
但硬件不仅是烦恼源,掌控它能为用户创造更多可能。桌面软件只能指定最低硬件要求,而服务器管理者通过添加硬件,能一键为所有用户启用传呼、传真、电话指令或信用卡处理等功能。我们不断探索硬件创新,不仅为取悦用户,更为与那些(通过ISP转售网页应用或销售桌面软件)无法直接控制硬件的竞争对手拉开差距。
网页应用由多程序组成,因此可采用任意语言开发。桌面软件被迫使用与操作系统相同的语言(即C/C++),导致这些语言(尤其在非技术人员眼中)成为"严肃开发"的代名词。但这只是交付方式造成的假象。服务器软件可选用任何语言[3]。如今顶尖黑客使用远离C/C++的语言:Perl、Python甚至Lisp。
When you have the users on your server, you don't have to rely on benchmarks, for example. Benchmarks are simulated users. With server-based software, you can watch actual users. To decide what to optimize, just log into a server and see what's consuming all the CPU. And you know when to stop optimizing too: we eventually got the Viaweb editor to the point where it was memory-bound rather than CPU-bound, and since there was nothing we could do to decrease the size of users' data (well, nothing easy), we knew we might as well stop there. Efficiency matters for server-based software, because you're paying for the hardware. The number of users you can support per server is the divisor of your capital cost, so if you can make your software very efficient you can undersell competitors and still make a profit. At Viaweb we got the capital cost per user down to about $5. It would be less now, probably less than the cost of sending them the first month's bill. Hardware is free now, if your software is reasonably efficient. Watching users can guide you in design as well as optimization. Viaweb had a scripting language called RTML that let advanced users define their own page styles. We found that RTML became a kind of suggestion box, because users only used it when the predefined page styles couldn't do what they wanted. Originally the editor put button bars across the page, for example, but after a number of users used RTML to put buttons down the left side, we made that an option (in fact the default) in the predefined page styles. Finally, by watching users you can often tell when they're in trouble. And since the customer is always right, that's a sign of something you need to fix. At Viaweb the key to getting users was the online test drive. It was not just a series of slides built by marketing people. In our test drive, users actually used the software.
开发服务器软件时,无人能强制你使用某种语言——因为你掌控从硬件到系统的全部环节。不同语言擅长不同任务,必须为每项任务选择最佳工具(面对竞争时"可以"意味着"必须",后文将详述)。若放弃这种优势,竞争对手就会利用它。
多数竞争对手使用C/C++,这使其软件明显逊色——他们无法突破CGI脚本的无状态限制。任何修改都需集中在一个页面,底部配"更新"按钮。而我们用被视作研究语言的Lisp,使Viaweb编辑器更接近桌面软件体验。
It took about five minutes, and at the end of it they had built a real, working store. The test drive was the way we got nearly all our new users. I think it will be the same for most Web-based applications. If users can get through a test drive successfully, they'll like the product. If they get confused or bored, they won't. So anything we could do to get more people through the test drive would increase our growth rate. I studied click trails of people taking the test drive and found that at a certain step they would get confused and click on the browser's Back button. (If you try writing Web-based applications, you'll find that the Back button becomes one of your most interesting philosophical problems.) So I added a message at that point, telling users that they were nearly finished, and reminding them not to click on the Back button. Another great thing about Web-based software is that you get instant feedback from changes: the number of people completing the test drive rose immediately from 60% to 90%. And since the number of new users was a function of the number of completed test drives, our revenue growth increased by 50%, just from that change. Money In the early 1990s I read an article in which someone said that software was a subscription business. At first this seemed a very cynical statement. But later I realized that it reflects reality: software development is an ongoing process. I think it's cleaner if you openly charge subscription fees, instead of forcing people to keep buying and installing new versions so that they'll keep paying you. And fortunately, subscriptions are the natural way to bill for Web-based applications. Hosting applications is an area where companies will play a role that is not likely to be filled by freeware. Hosting applications is a lot of stress, and has real expenses. No one is going to want to do it for free. For companies, Web-based applications are an ideal source of revenue.
新世界最重要的变革之一是发布方式。桌面软件公司发布新版本如同分娩——全公司汗流浃背推出单一巨型代码块。无论过程还是产物,都容易引发不雅联想。
Instead of starting each quarter with a blank slate, you have a recurring revenue stream. Because your software evolves gradually, you don't have to worry that a new model will flop; there never need be a new model, per se, and if you do something to the software that users hate, you'll know right away. You have no trouble with uncollectable bills; if someone won't pay you can just turn off the service. And there is no possibility of piracy. That last "advantage" may turn out to be a problem. Some amount of piracy is to the advantage of software companies. If some user really would not have bought your software at any price, you haven't lost anything if he uses a pirated copy. In fact you gain, because he is one more user helping to make your software the standard-- or who might buy a copy later, when he graduates from high school. When they can, companies like to do something called price discrimination, which means charging each customer as much as they can afford. [8] Software is particularly suitable for price discrimination, because the marginal cost is close to zero. This is why some software costs more to run on Suns than on Intel boxes: a company that uses Suns is not interested in saving money and can safely be charged more. Piracy is effectively the lowest tier of price discrimination. I think that software companies understand this and deliberately turn a blind eye to some kinds of piracy. [9] With server-based software they are going to have to come up with some other solution. Web-based software sells well, especially in comparison to desktop software, because it's easy to buy. You might think that people decide to buy something, and then buy it, as two separate steps. That's what I thought before Viaweb, to the extent I thought about the question at all. In fact the second step can propagate back into the first: if something is hard to buy, people will change their mind about whether they wanted it.
服务器软件允许像为自己编写程序般持续修改,以增量更新替代偶尔的大爆炸。典型桌面软件公司每年发布一两次,Viaweb常每日发布三到五次。
采用新模式后,你会惊觉发布方式对开发的深远影响。桌面软件业的许多顽疾都源于发布的灾难性本质。
And vice versa: you'll sell more of something when it's easy to buy. I buy more books because Amazon exists. Web-based software is just about the easiest thing in the world to buy, especially if you have just done an online demo. Users should not have to do much more than enter a credit card number. (Make them do more at your peril.) Sometimes Web-based software is offered through ISPs acting as resellers. This is a bad idea. You have to be administering the servers, because you need to be constantly improving both hardware and software. If you give up direct control of the servers, you give up most of the advantages of developing Web-based applications. Several of our competitors shot themselves in the foot this way-- usually, I think, because they were overrun by suits who were excited about this huge potential channel, and didn't realize that it would ruin the product they hoped to sell through it. Selling Web-based software through ISPs is like selling sushi through vending machines. Customers Who will the customers be? At Viaweb they were initially individuals and smaller companies, and I think this will be the rule with Web-based applications. These are the users who are ready to try new things, partly because they're more flexible, and partly because they want the lower costs of new technology. Web-based applications will often be the best thing for big companies too (though they'll be slow to realize it). The best intranet is the Internet. If a company uses true Web-based applications, the software will work better, the servers will be better administered, and employees will have access to the system from anywhere. The argument against this approach usually hinges on security: if access is easier for employees, it will be for bad guys too. Some larger merchants were reluctant to use Viaweb because they thought customers' credit card information would be safer on their own servers.
年更模式下,漏洞修复如同批发。发布日期前组装新版本时,半数代码被替换引入无数漏洞。QA团队进场清点,程序员按清单修复。他们很少能清空清单——事实上没人知道终点在哪。这像从池塘打捞碎石,你永远不清楚软件内部状况,最终至多获得统计意义上的正确性。
服务器软件的变更多为小型增量,本身就不易引入漏洞,也让你明确测试重点:最后修改的部分。你对代码的掌控坚实得多,通常确知内部状况。虽未背下源码,但阅读时如同飞行员扫视仪表盘,而非侦探破解谜案。
It was not easy to make this point diplomatically, but in fact the data was almost certainly safer in our hands than theirs. Who can hire better people to manage security, a technology startup whose whole business is running servers, or a clothing retailer? Not only did we have better people worrying about security, we worried more about it. If someone broke into the clothing retailer's servers, it would affect at most one merchant, could probably be hushed up, and in the worst case might get one person fired. If someone broke into ours, it could affect thousands of merchants, would probably end up as news on CNet, and could put us out of business. If you want to keep your money safe, do you keep it under your mattress at home, or put it in a bank? This argument applies to every aspect of server administration: not just security, but uptime, bandwidth, load management, backups, etc. Our existence depended on doing these things right. Server problems were the big no-no for us, like a dangerous toy would be for a toy maker, or a salmonella outbreak for a food processor. A big company that uses Web-based applications is to that extent outsourcing IT. Drastic as it sounds, I think this is generally a good idea. Companies are likely to get better service this way than they would from in-house system administrators. System administrators can become cranky and unresponsive because they're not directly exposed to competitive pressure: a salesman has to deal with customers, and a developer has to deal with competitors' software, but a system administrator, like an old bachelor, has few external forces to keep him in line. [10] At Viaweb we had external forces in plenty to keep us in line. The people calling us were customers, not just co-workers. If a server got wedged, we jumped; just thinking about it gives me a jolt of adrenaline, years later. So Web-based applications will ordinarily be the right answer for big companies too.
桌面软件滋生出对漏洞的听天由命。明知交付物充满缺陷,甚至建立了补丁机制来补救,何必再纠结多几个漏洞?很快你会发布明知有问题的新功能。苹果今年就这样做了:迫于四次延期的压力,他们发布了缺失CD/DVD支持的新系统,要求用户后续自行补装。
网页软件永远不必在未完成时发布,且一旦完工即可交付。
They will be the last to realize it, however, just as they were with desktop computers. And partly for the same reason: it will be worth a lot of money to convince big companies that they need something more expensive. There is always a tendency for rich customers to buy expensive solutions, even when cheap solutions are better, because the people offering expensive solutions can spend more to sell them. At Viaweb we were always up against this. We lost several high-end merchants to Web consulting firms who convinced them they'd be better off if they paid half a million dollars for a custom-made online store on their own server. They were, as a rule, not better off, as more than one discovered when Christmas shopping season came around and loads rose on their server. Viaweb was a lot more sophisticated than what most of these merchants got, but we couldn't afford to tell them. At $300 a month, we couldn't afford to send a team of well-dressed and authoritative-sounding people to make presentations to customers. A large part of what big companies pay extra for is the cost of selling expensive things to them. (If the Defense Department pays a thousand dollars for toilet seats, it's partly because it costs a lot to sell toilet seats for a thousand dollars.) And this is one reason intranet software will continue to thrive, even though it is probably a bad idea. It's simply more expensive. There is nothing you can do about this conundrum, so the best plan is to go for the smaller customers first. The rest will come in time. Son of Server Running software on the server is nothing new. In fact it's the old model: mainframe applications are all server-based. If server-based software is such a good idea, why did it lose last time? Why did desktop computers eclipse mainframes? At first desktop computers didn't look like much of a threat. The first users were all hackers-- or hobbyists, as they were called then.
行业老手可能质疑:承诺期限内交付新版本时怎么办?网页软件本就不该做这种承诺——因为没有"版本"概念。软件持续渐变,虽有改动大小之分,但版本号与网页软件天然不兼容。
若有人记得Viaweb,会觉得此言矛盾——我们常宣布新版本。这纯粹是公关策略。我们发现行业媒体以版本号思考:主版本升级(版本号首位数变化)能获重点报道,小更新(小数点后变化)最多占一段篇幅。竞争对手因提供桌面软件确有版本号,每次发布(在我们看来是其落后的明证)都能获得宣传。为不落人后,我们也开始编版本号。需要曝光时,就列出上次"发布"后的新增功能,贴个新版本号,发通稿称"新版即刻可用"。神奇的是从未被拆穿。
They liked microcomputers because they were cheap. For the first time, you could have your own computer. The phrase "personal computer" is part of the language now, but when it was first used it had a deliberately audacious sound, like the phrase "personal satellite" would today. Why did desktop computers take over? I think it was because they had better software. And I think the reason microcomputer software was better was that it could be written by small companies. I don't think many people realize how fragile and tentative startups are in the earliest stage. Many startups begin almost by accident-- as a couple guys, either with day jobs or in school, writing a prototype of something that might, if it looks promising, turn into a company. At this larval stage, any significant obstacle will stop the startup dead in its tracks. Writing mainframe software required too much commitment up front. Development machines were expensive, and because the customers would be big companies, you'd need an impressive-looking sales force to sell it to them. Starting a startup to write mainframe software would be a much more serious undertaking than just hacking something together on your Apple II in the evenings. And so you didn't get a lot of startups writing mainframe applications. The arrival of desktop computers inspired a lot of new software, because writing applications for them seemed an attainable goal to larval startups. Development was cheap, and the customers would be individual people that you could reach through computer stores or even by mail-order. The application that pushed desktop computers out into the mainstream was VisiCalc, the first spreadsheet. It was written by two guys working in an attic, and yet did things no mainframe software could do. [11] VisiCalc was such an advance, in its time, that people bought Apple IIs just to run it.
被收购时我们已如此操作三次,版本号升至4.0(没记错的话是4.1)。成为Yahoo Store后不再急需宣传,虽持续改进,版本号概念被悄然废弃。
网页软件另一技术优势是可复现多数漏洞。用户数据就在你的磁盘上,遇到故障时无需像桌面软件那样猜测状况——应该能在用户通话时重现问题。若有错误监测代码,甚至可能早已知晓。
And this was the beginning of a trend: desktop computers won because startups wrote software for them. It looks as if server-based software will be good this time around, because startups will write it. Computers are so cheap now that you can get started, as we did, using a desktop computer as a server. Inexpensive processors have eaten the workstation market (you rarely even hear the word now) and are most of the way through the server market; Yahoo's servers, which deal with loads as high as any on the Internet, all have the same inexpensive Intel processors that you have in your desktop machine. And once you've written the software, all you need to sell it is a Web site. Nearly all our users came direct to our site through word of mouth and references in the press. [12] Viaweb was a typical larval startup. We were terrified of starting a company, and for the first few months comforted ourselves by treating the whole thing as an experiment that we might call off at any moment. Fortunately, there were few obstacles except technical ones. While we were writing the software, our Web server was the same desktop machine we used for development, connected to the outside world by a dialup line. Our only expenses in that phase were food and rent. There is all the more reason for startups to write Web-based software now, because writing desktop software has become a lot less fun. If you want to write desktop software now you do it on Microsoft's terms, calling their APIs and working around their buggy OS. And if you manage to write something that takes off, you may find that you were merely doing market research for Microsoft. If a company wants to make a platform that startups will build on, they have to make it something that hackers themselves will want to use. That means it has to be inexpensive and well-designed.
网页软件24/7运行,所有修改即时经受考验,漏洞快速浮现。
The Mac was popular with hackers when it first came out, and a lot of them wrote software for it. [13] You see this less with Windows, because hackers don't use it. The kind of people who are good at writing software tend to be running Linux or FreeBSD now. I don't think we would have started a startup to write desktop software, because desktop software has to run on Windows, and before we could write software for Windows we'd have to use it. The Web let us do an end-run around Windows, and deliver software running on Unix direct to users through the browser. That is a liberating prospect, a lot like the arrival of PCs twenty-five years ago. Microsoft Back when desktop computers arrived, IBM was the giant that everyone was afraid of. It's hard to imagine now, but I remember the feeling very well. Now the frightening giant is Microsoft, and I don't think they are as blind to the threat facing them as IBM was. After all, Microsoft deliberately built their business in IBM's blind spot. I mentioned earlier that my mother doesn't really need a desktop computer. Most users probably don't. That's a problem for Microsoft, and they know it. If applications run on remote servers, no one needs Windows. What will Microsoft do? Will they be able to use their control of the desktop to prevent, or constrain, this new generation of software? My guess is that Microsoft will develop some kind of server/desktop hybrid, where the operating system works together with servers they control. At a minimum, files will be centrally available for users who want that. I don't expect Microsoft to go all the way to the extreme of doing the computations on the server, with only a browser for a client, if they can avoid it. If you only need a browser for a client, you don't need Microsoft on the client, and if Microsoft doesn't control the client, they can't push users towards their server-based applications.
软件公司常被指责让用户调试产品——这恰是我的主张。对网页软件这确实是好策略,因为漏洞更少且短暂。渐进发布本就大幅减少漏洞,加上可复现错误与即时修复,多数漏洞刚出现就会被消灭。Viaweb从未因漏洞多到需要正式跟踪系统。
当然发布前应该测试,避免重大漏洞流出。少数漏网之鱼通常涉及边缘场景,只影响极少数用户直到有人投诉。只要及时修复,普通用户感知的漏洞将远少于桌面软件。我怀疑普通Viaweb用户根本遇不到漏洞。
I think Microsoft will have a hard time keeping the genie in the bottle. There will be too many different types of clients for them to control them all. And if Microsoft's applications only work with some clients, competitors will be able to trump them by offering applications that work from any client. [14] In a world of Web-based applications, there is no automatic place for Microsoft. They may succeed in making themselves a place, but I don't think they'll dominate this new world as they did the world of desktop applications. It's not so much that a competitor will trip them up as that they will trip over themselves. With the rise of Web-based software, they will be facing not just technical problems but their own wishful thinking. What they need to do is cannibalize their existing business, and I can't see them facing that. The same single-mindedness that has brought them this far will now be working against them. IBM was in exactly the same situation, and they could not master it. IBM made a late and half-hearted entry into the microcomputer business because they were ambivalent about threatening their cash cow, mainframe computing. Microsoft will likewise be hampered by wanting to save the desktop. A cash cow can be a damned heavy monkey on your back. I'm not saying that no one will dominate server-based applications. Someone probably will eventually. But I think that there will be a good long period of cheerful chaos, just as there was in the early days of microcomputers. That was a good time for startups. Lots of small companies flourished, and did it by making cool things. Startups but More So The classic startup is fast and informal, with few people and little money. Those few people work very hard, and technology magnifies the effect of the decisions they make. If they win, they win big. In a startup writing Web-based applications, everything you associate with startups is taken to an extreme.
修复新漏洞比旧漏洞容易。刚写代码时定位问题通常很快,有时查看源码前就已潜意识察觉问题所在。修复半年前代码中的漏洞(年更模式的平均情况)则困难得多。由于理解不深,修正方式可能更粗糙,甚至引入新漏洞[4]。
早期捕获漏洞还能减少复合型漏洞。复合漏洞是两个独立缺陷的相互作用:你跌下楼梯时去抓扶手,结果扶手脱落。软件中这类漏洞最难发现,后果也最严重[5]。传统"破坏一切再过滤"的开发模式必然产生大量复合漏洞,而持续小步更新的软件则不易出现——松散零件总被及时清扫,不会卡进运转中的机器。
You can write and launch a product with even fewer people and even less money. You have to be even faster, and you can get away with being more informal. You can literally launch your product as three guys sitting in the living room of an apartment, and a server collocated at an ISP. We did. Over time the teams have gotten smaller, faster, and more informal. In 1960, software development meant a roomful of men with horn rimmed glasses and narrow black neckties, industriously writing ten lines of code a day on IBM coding forms. In 1980, it was a team of eight to ten people wearing jeans to the office and typing into vt100s. Now it's a couple of guys sitting in a living room with laptops. (And jeans turn out not to be the last word in informality.) Startups are stressful, and this, unfortunately, is also taken to an extreme with Web-based applications. Many software companies, especially at the beginning, have periods where the developers slept under their desks and so on. The alarming thing about Web-based software is that there is nothing to prevent this becoming the default. The stories about sleeping under desks usually end: then at last we shipped it and we all went home and slept for a week. Web-based software never ships. You can work 16-hour days for as long as you want to. And because you can, and your competitors can, you tend to be forced to. You can, so you must. It's Parkinson's Law running in reverse. The worst thing is not the hours but the responsibility. Programmers and system administrators traditionally each have their own separate worries. Programmers have to worry about bugs, and system administrators have to worry about infrastructure. Programmers may spend a long day up to their elbows in source code, but at some point they get to go home and forget about it. System administrators never quite leave the job behind, but when they do get paged at 4:00 AM, they don't usually have to do anything very complicated.
函数式编程技术对此有帮助。函数式编程避免副作用,虽多见于学术论文而非商业软件,但对网页应用极其有用。虽难用纯函数式编写完整程序,但可应用于重要模块。这些无状态部件更易测试,在持续小修改的场景下非常便利。Viaweb编辑器大部分采用此风格,我们的脚本语言RTML更是纯函数式语言。
桌面软件从业者可能难以相信,但在Viaweb,漏洞几乎成了游戏。由于已发布漏洞多涉边缘场景,遇到者常是探索极限的高级用户。他们更宽容漏洞——尤其当这些漏洞源于他们要求的新功能。事实上,因漏洞罕见且需复杂操作才能触发,高级用户常以发现为荣。他们致电支持时带着胜利而非愤怒,仿佛得分般得意。
With Web-based applications, these two kinds of stress get combined. The programmers become system administrators, but without the sharply defined limits that ordinarily make the job bearable. At Viaweb we spent the first six months just writing software. We worked the usual long hours of an early startup. In a desktop software company, this would have been the part where we were working hard, but it felt like a vacation compared to the next phase, when we took users onto our server. The second biggest benefit of selling Viaweb to Yahoo (after the money) was to be able to dump ultimate responsibility for the whole thing onto the shoulders of a big company. Desktop software forces users to become system administrators. Web-based software forces programmers to. There is less stress in total, but more for the programmers. That's not necessarily bad news. If you're a startup competing with a big company, it's good news. [15] Web-based applications offer a straightforward way to outwork your competitors. No startup asks for more. Just Good Enough One thing that might deter you from writing Web-based applications is the lameness of Web pages as a UI. That is a problem, I admit. There were a few things we would have _really_ liked to add to HTML and HTTP. What matters, though, is that Web pages are just good enough. There is a parallel here with the first microcomputers. The processors in those machines weren't actually intended to be the CPUs of computers. They were designed to be used in things like traffic lights. But guys like Ed Roberts, who designed the Altair, realized that they were just good enough. You could combine one of these chips with some memory (256 bytes in the first Altair), and front panel switches, and you'd have a working computer. Being able to have your own computer was so exciting that there were plenty of people who wanted to buy them, however limited.
能复现错误将改变客服模式。多数软件公司的客服只为安抚用户——他们要么报告已知漏洞,要么操作有误需你排查。无论哪种都难获有用信息。因此客服电话常被视为应隔离开发者的麻烦。
Viaweb截然不同。我们提供免费支持,因为渴望用户反馈。任何问题都需立即知晓,以便复现和修复。
Web pages weren't designed to be a UI for applications, but they're just good enough. And for a significant number of users, software that you can use from any browser will be enough of a win in itself to outweigh any awkwardness in the UI. Maybe you can't write the best-looking spreadsheet using HTML, but you can write a spreadsheet that several people can use simultaneously from different locations without special client software, or that can incorporate live data feeds, or that can page you when certain conditions are triggered. More importantly, you can write new kinds of applications that don't even have names yet. VisiCalc was not merely a microcomputer version of a mainframe application, after all-- it was a new type of application. Of course, server-based applications don't have to be Web-based. You could have some other kind of client. But I'm pretty sure that's a bad idea. It would be very convenient if you could assume that everyone would install your client-- so convenient that you could easily convince yourself that they all would-- but if they don't, you're hosed. Because Web-based software assumes nothing about the client, it will work anywhere the Web works. That's a big advantage already, and the advantage will grow as new Web devices proliferate. Users will like you because your software just works, and your life will be easier because you won't have to tweak it for every new client. [16] I feel like I've watched the evolution of the Web as closely as anyone, and I can't predict what's going to happen with clients. Convergence is probably coming, but where? I can't pick a winner. One thing I can predict is conflict between AOL and Microsoft. Whatever Microsoft's .NET turns out to be, it will probably involve connecting the desktop to servers. Unless AOL fights back, they will either be pushed aside or turned into a pipe between Microsoft client and server software.
因此开发者与支持团队紧密协作。客服人员距程序员仅三十英尺,确认真实漏洞可随时打断任何工作。我们会暂停董事会来修复严重漏洞。
这种模式让所有人更快乐。用户惊喜于被当作重要消息来源;客服人员喜欢真正帮助用户而非照本宣科;程序员则能直接复现问题而非听二手模糊报告。
If Microsoft and AOL get into a client war, the only thing sure to work on both will be browsing the Web, meaning Web-based applications will be the only kind that work everywhere. How will it all play out? I don't know. And you don't have to know if you bet on Web-based applications. No one can break that without breaking browsing. The Web may not be the only way to deliver software, but it's one that works now and will continue to work for a long time. Web-based applications are cheap to develop, and easy for even the smallest startup to deliver. They're a lot of work, and of a particularly stressful kind, but that only makes the odds better for startups. Why Not? E. B. White was amused to learn from a farmer friend that many electrified fences don't have any current running through them. The cows apparently learn to stay away from them, and after that you don't need the current. "Rise up, cows!" he wrote, "Take your liberty while despots snore!" If you're a hacker who has thought of one day starting a startup, there are probably two things keeping you from doing it. One is that you don't know anything about business. The other is that you're afraid of competition. Neither of these fences have any current in them. There are only two things you have to know about business: build something users love, and make more than you spend. If you get these two right, you'll be ahead of most startups. You can figure out the rest as you go. You may not at first make more than you spend, but as long as the gap is closing fast enough you'll be ok. If you start out underfunded, it will at least encourage a habit of frugality. The less you spend, the easier it is to make more than you spend. Fortunately, it can be very cheap to launch a Web-based application. We launched on under $10,000, and it would be even cheaper today.
即时修复策略改变了客服与黑客的关系。多数软件公司中,客服是低薪人肉盾牌,黑客则如创世神般存在。漏洞报告流程通常是单向的:客服填表经QA转交程序员,加入待办列表。Viaweb则不然。客服报告漏洞一分钟内,就能站在程序员身旁听他说"靠,真是漏洞"。对客服而言,黑客的"你说得对"如同猫咪献上猎物般令人期待。这也促使他们更谨慎评估漏洞严重性——现在他们的专业尊严面临考验。
We had to spend thousands on a server, and thousands more to get SSL. (The only company selling SSL software at the time was Netscape.) Now you can rent a much more powerful server, with SSL included, for less than we paid for bandwidth alone. You could launch a Web-based application now for less than the cost of a fancy office chair. As for building something users love, here are some general tips. Start by making something clean and simple that you would want to use yourself. Get a version 1.0 out fast, then continue to improve the software, listening closely to the users as you do. The customer is always right, but different customers are right about different things; the least sophisticated users show you what you need to simplify and clarify, and the most sophisticated tell you what features you need to add. The best thing software can be is easy, but the way to do this is to get the defaults right, not to limit users' choices. Don't get complacent if your competitors' software is lame; the standard to compare your software to is what it could be, not what your current competitors happen to have. Use your software yourself, all the time. Viaweb was supposed to be an online store builder, but we used it to make our own site too. Don't listen to marketing people or designers or product managers just because of their job titles. If they have good ideas, use them, but it's up to you to decide; software has to be designed by hackers who understand design, not designers who know a little about software. If you can't design software as well as implement it, don't start a startup. Now let's talk about competition. What you're afraid of is not presumably groups of hackers like you, but actual companies, with offices and business plans and salesmen and so on, right? Well, they are more afraid of you than you are of them, and they're right.
被雅虎收购后,客服与程序员分离,我们才意识到他们实质兼任QA与部分市场职能。除捕捉漏洞外,他们还掌管那些模糊的"类漏洞"知识(如令用户困惑的功能)[6]。也是某种焦点小组代理——我们能询问用户更倾向哪个新功能,他们的判断总是准确。
即时发布是巨大激励。我常在上班路上构思改进,当天就能实现。大功能亦然。即便需两周开发(少有项目更长),完成后也能立即看到效果。
It's a lot easier for a couple of hackers to figure out how to rent office space or hire sales people than it is for a company of any size to get software written. I've been on both sides, and I know. When Viaweb was bought by Yahoo, I suddenly found myself working for a big company, and it was like trying to run through waist-deep water. I don't mean to disparage Yahoo. They had some good hackers, and the top management were real butt-kickers. For a big company, they were exceptional. But they were still only about a tenth as productive as a small startup. No big company can do much better than that. What's scary about Microsoft is that a company so big can develop software at all. They're like a mountain that can walk. Don't be intimidated. You can do as much that Microsoft can't as they can do that you can't. And no one can stop you. You don't have to ask anyone's permission to develop Web-based applications. You don't have to do licensing deals, or get shelf space in retail stores, or grovel to have your application bundled with the OS. You can deliver software right to the browser, and no one can get between you and potential users without preventing them from browsing the Web. You may not believe it, but I promise you, Microsoft is scared of you. The complacent middle managers may not be, but Bill is, because he was you once, back in 1975, the last time a new way of delivering software appeared. Notes [1] Realizing that much of the money is in the services, companies building lightweight clients have usually tried to combine the hardware with an online service. This approach has not worked well, partly because you need two different kinds of companies to build consumer electronics and to run an online service, and partly because users hate the idea.
若需等待年度发布,多数想法至少会被搁置。但创意会孕育更多创意——写作时半数灵感来自写作过程本身,编程亦然。实现创意的过程催生新创意。因此搁置不仅延迟当前创意,还损失后续衍生创意。事实上,搁置可能抑制新创意:构思新功能时,瞥见"待办架"就会想"下个版本已有太多新东西"。
大公司用规划替代实现。Viaweb常因此陷入麻烦。投资者和分析师询问未来计划时,真实答案是"没有计划"。我们有改进方向的模糊想法,若知道具体做法早就实施了。未来六个月做什么?任何高价值的事。我不确定是否敢如此回答,但事实如此。"计划"只是"搁置创意"的另一种说法。想到好创意,我们就实现它。
Giving away the razor and making money on the blades may work for Gillette, but a razor is much smaller commitment than a Web terminal. Cell phone handset makers are satisfied to sell hardware without trying to capture the service revenue as well. That should probably be the model for Internet clients too. If someone just sold a nice-looking little box with a Web browser that you could use to connect through any ISP, every technophobe in the country would buy one. [2] Security always depends more on not screwing up than any design decision, but the nature of server-based software will make developers pay more attention to not screwing up. Compromising a server could cause such damage that ASPs (that want to stay in business) are likely to be careful about security. [3] In 1995, when we started Viaweb, Java applets were supposed to be the technology everyone was going to use to develop server-based applications. Applets seemed to us an old-fashioned idea. Download programs to run on the client? Simpler just to go all the way and run the programs on the server. We wasted little time on applets, but countless other startups must have been lured into this tar pit. Few can have escaped alive, or Microsoft could not have gotten away with dropping Java in the most recent version of Explorer. [4] This point is due to Trevor Blackwell, who adds "the cost of writing software goes up more than linearly with its size. Perhaps this is mainly due to fixing old bugs, and the cost can be more linear if all bugs are found quickly." [5] The hardest kind of bug to find may be a variant of compound bug where one bug happens to compensate for another. When you fix one bug, the other becomes visible. But it will seem as if the fix is at fault, since that was the last thing you changed. [6] Within Viaweb we once had a contest to describe the worst thing about our software. Two customer support people tied for first prize with entries I still shiver to recall.
与多数软件公司相同,Viaweb多数代码有明确所有者。但所有权意味着绝对主权——软件片段发布无需他人批准(甚至知晓)。唯一的防错机制是怕在同事面前出丑,这已绰绰有余。我可能给人留下"我们鲁莽编码"的印象。事实上我们进展迅速,但每次发布到服务器前都极度谨慎。专注度比慢速更能保障可靠性。正因全神贯注,海军飞行员能在夜间将4万磅战机以140英里时速降落在起伏的甲板上,比青少年切面包圈更安全。
当然,这种开发方式是把双刃剑。它对优秀可信的小团队效果卓著,对依赖委员会纠错的平庸大公司则适得其反。
We fixed both problems immediately. [7] Robert Morris wrote the ordering system, which shoppers used to place orders. Trevor Blackwell wrote the image generator and the manager, which merchants used to retrieve orders, view statistics, and configure domain names etc. I wrote the editor, which merchants used to build their sites. The ordering system and image generator were written in C and C++, the manager mostly in Perl, and the editor in Lisp. [8] Price discrimination is so pervasive (how often have you heard a retailer claim that their buying power meant lower prices for you?) that I was surprised to find it was outlawed in the U.S. by the Robinson-Patman Act of 1936. This law does not appear to be vigorously enforced. [9] In _No Logo,_ Naomi Klein says that clothing brands favored by "urban youth" do not try too hard to prevent shoplifting because in their target market the shoplifters are also the fashion leaders. [10] Companies often wonder what to outsource and what not to. One possible answer: outsource any job that's not directly exposed to competitive pressure, because outsourcing it will thereby expose it to competitive pressure. [11] The two guys were Dan Bricklin and Bob Frankston. Dan wrote a prototype in Basic in a couple days, then over the course of the next year they worked together (mostly at night) to make a more powerful version written in 6502 machine language. Dan was at Harvard Business School at the time and Bob nominally had a day job writing software. "There was no great risk in doing a business," Bob wrote, "If it failed it failed. No big deal." [12] It's not quite as easy as I make it sound. It took a painfully long time for word of mouth to get going, and we did not start to get a lot of press coverage until we hired a PR firm (admittedly the best in the business) for $16,000 per month.
反布鲁克斯定律
幸运的是,网页软件确实需要更少程序员。我曾就职的中型桌面软件公司有超100名工程师,仅13人负责产品开发,其余全忙于发布、移植等。网页软件最多只需那13人,因为没有发布与移植等问题。
However, it was true that the only significant channel was our own Web site. [13] If the Mac was so great, why did it lose? Cost, again. Microsoft concentrated on the software business, and unleashed a swarm of cheap component suppliers on Apple hardware. It did not help, either, that suits took over during a critical period. [14] One thing that would help Web-based applications, and help keep the next generation of software from being overshadowed by Microsoft, would be a good open-source browser. Mozilla is open-source but seems to have suffered from having been corporate software for so long. A small, fast browser that was actively maintained would be a great thing in itself, and would probably also encourage companies to build little Web appliances. Among other things, a proper open-source browser would cause HTTP and HTML to continue to evolve (as e.g. Perl has). It would help Web-based applications greatly to be able to distinguish between selecting a link and following it; all you'd need to do this would be a trivial enhancement of HTTP, to allow multiple urls in a request. Cascading menus would also be good. If you want to change the world, write a new Mosaic. Think it's too late? In 1998 a lot of people thought it was too late to launch a new search engine, but Google proved them wrong. There is always room for something new if the current options suck enough. Make sure it works on all the free OSes first-- new things start with their users. [15] Trevor Blackwell, who probably knows more about this from personal experience than anyone, writes: "I would go farther in saying that because server-based software is so hard on the programmers, it causes a fundamental economic shift away from large companies. It requires the kind of intensity and dedication from programmers that they will only be willing to provide when it's their own company.
Viaweb仅由三人开发[7]。我们一直承受招聘压力,因为收购方难为三人公司支付高价。(解决方案:扩招并安排新项目)
用更少程序员开发软件节省的不只是金钱。如《人月神话》所述,增加人手会拖慢项目。开发者间的连接数随团队规模指数增长,会议耗时与交互漏洞随之激增。所幸逆向也成立:团队越小,开发效率指数级提升。Viaweb程序员从不开会,所有交流发生在午餐途中。
Software companies can hire skilled people to work in a not-too-demanding environment, and can hire unskilled people to endure hardships, but they can't hire highly skilled people to bust their asses. Since capital is no longer needed, big companies have little to bring to the table." [16] In the original version of this essay, I advised avoiding Javascript. That was a good plan in 2001, but Javascript now works. Thanks to Sarah Harlin, Trevor Blackwell, Robert Morris, Eric Raymond, Ken Anderson, and Dan Giffin for reading drafts of this paper; to Dan Bricklin and Bob Frankston for information about VisiCalc; and again to Ken Anderson for inviting me to speak at BBN. You'll find this essay and 14 others in _Hackers & Painters_.
| Some Technical Details | | | Japanese Translation | Microsoft finally agrees | | | Gates Email.
若说缺点,就是程序员需兼具系统管理员职能。托管软件需有人值守服务器,实践中只有开发者能胜任。Viaweb系统组件繁多且变更频繁,软件与基础设施边界模糊。强行划分会限制设计选择。尽管我们总期待"几个月后"一切稳定到可雇佣专职运维,但这天从未到来。
只要产品处于活跃开发,情况就不会改变。网页软件不是写完签入就能回家的东西——
May 2001 _(This article was written as a kind of business plan for anew language. So it is missing (because it takes for granted) the most important feature of a good programming language: very powerful abstractions.)_ A friend of mine once told an eminent operating systems expert that he wanted to design a really good programming language. The expert told him that it would be a waste of time, that programming languages don't become popular or unpopular based on their merits, and so no matter how good his language was, no one would use it. At least, that was what had happened to the language _he_ had designed. What does make a language popular? Do popular languages deserve their popularity? Is it worth trying to define a good programming language? How would you do it? I think the answers to these questions can be found by looking at hackers, and learning what they want. Programming languages are _for_ hackers, and a programming language is good as a programming language (rather than, say, an exercise in denotational semantics or compiler design) if and only if hackers like it. 1 The Mechanics of Popularity It's true, certainly, that most people don't choose programming languages simply based on their merits. Most programmers are told what language to use by someone else. And yet I think the effect of such external factors on the popularity of programming languages is not as great as it's sometimes thought to be. I think a bigger problem is that a hacker's idea of a good programming language is not the same as most language designers'. Between the two, the hacker's opinion is the one that matters. Programming languages are not theorems. They're tools, designed for people, and they have to be designed to suit human strengths and weaknesses as much as shoes have to be designed for human feet. If a shoe pinches when you put it on, it's a bad shoe, however elegant it may be as a piece of sculpture.
(注:由于提供的原文仅包含标题“Being Popular”,翻译结果即为“受欢迎”。若需翻译完整文章,请提供更多内容。)
(本文是为一种新语言撰写的商业计划类文章,因此忽略了优秀编程语言最重要的特征——极其强大的抽象能力——这一点的缺失被视为理所当然。)
我的一位朋友曾告诉一位著名的操作系统专家,他想设计一种真正优秀的编程语言。那位专家回应说这是浪费时间,因为编程语言的流行与否与它们的优点无关,所以无论他的语言多优秀,都不会有人使用。至少,这正是他设计的语言的遭遇。
It may be that the majority of programmers can't tell a good language from a bad one. But that's no different with any other tool. It doesn't mean that it's a waste of time to try designing a good language. Expert hackers can tell a good language when they see one, and they'll use it. Expert hackers are a tiny minority, admittedly, but that tiny minority write all the good software, and their influence is such that the rest of the programmers will tend to use whatever language they use. Often, indeed, it is not merely influence but command: often the expert hackers are the very people who, as their bosses or faculty advisors, tell the other programmers what language to use. The opinion of expert hackers is not the only force that determines the relative popularity of programming languages — legacy software (Cobol) and hype (Ada, Java) also play a role — but I think it is the most powerful force over the long term. Given an initial critical mass and enough time, a programming language probably becomes about as popular as it deserves to be. And popularity further separates good languages from bad ones, because feedback from real live users always leads to improvements. Look at how much any popular language has changed during its life. Perl and Fortran are extreme cases, but even Lisp has changed a lot. Lisp 1.5 didn't have macros, for example; these evolved later, after hackers at MIT had spent a couple years using Lisp to write real programs. [1] So whether or not a language has to be good to be popular, I think a language has to be popular to be good. And it has to stay popular to stay good. The state of the art in programming languages doesn't stand still. And yet the Lisps we have today are still pretty much what they had at MIT in the mid-1980s, because that's the last time Lisp had a sufficiently large and demanding user base. Of course, hackers have to know about a language before they can use it.
什么让一门语言流行?流行语言是否配得上它们的流行度?定义一门优秀编程语言是否值得?又该如何定义?
我认为答案可以从黑客身上找到,了解他们想要什么。编程语言是为黑客服务的,一门语言的好坏(作为编程语言而非指称语义或编译器设计的练习)取决于黑客是否喜欢它。
确实,大多数人不会仅凭语言优点选择编程语言。多数程序员使用的语言由他人指定。但外部因素对语言流行度的影响可能被高估了。更大的问题在于,黑客对优秀语言的理解与多数语言设计者不同。
两者之间,黑客的意见才是关键。编程语言不是数学定理,而是为人设计的工具,必须适应人类的优缺点,就像鞋子必须适应人脚。如果穿上鞋就挤脚,无论它作为雕塑多么优雅,都是双坏鞋。
How are they to hear? From other hackers. But there has to be some initial group of hackers using the language for others even to hear about it. I wonder how large this group has to be; how many users make a critical mass? Off the top of my head, I'd say twenty. If a language had twenty separate users, meaning twenty users who decided on their own to use it, I'd consider it to be real. Getting there can't be easy. I would not be surprised if it is harder to get from zero to twenty than from twenty to a thousand. The best way to get those initial twenty users is probably to use a trojan horse: to give people an application they want, which happens to be written in the new language. 2 External Factors Let's start by acknowledging one external factor that does affect the popularity of a programming language. To become popular, a programming language has to be the scripting language of a popular system. Fortran and Cobol were the scripting languages of early IBM mainframes. C was the scripting language of Unix, and so, later, was Perl. Tcl is the scripting language of Tk. Java and Javascript are intended to be the scripting languages of web browsers. Lisp is not a massively popular language because it is not the scripting language of a massively popular system. What popularity it retains dates back to the 1960s and 1970s, when it was the scripting language of MIT. A lot of the great programmers of the day were associated with MIT at some point. And in the early 1970s, before C, MIT's dialect of Lisp, called MacLisp, was one of the only programming languages a serious hacker would want to use. Today Lisp is the scripting language of two moderately popular systems, Emacs and Autocad, and for that reason I suspect that most of the Lisp programming done today is done in Emacs Lisp or AutoLisp. Programming languages don't exist in isolation.
或许大多数程序员无法分辨语言优劣,但这与其他工具无异。这并不意味着设计优秀语言是徒劳的。顶尖黑客能识别优秀语言并会使用它。诚然,顶尖黑客是极少数,但他们编写了所有优秀软件,其影响力使得其他程序员会跟随他们使用的语言。实际上,这种影响常以指令形式出现:顶尖黑客常作为上司或导师决定他人使用的语言。
黑客的意见并非决定语言流行度的唯一力量——遗留系统(如Cobol)和营销炒作(如Ada、Java)也起作用——但我认为长期来看这是最强大的力量。给定初始关键规模和足够时间,一门语言的流行度终将与其价值匹配。而流行度会进一步区分语言优劣,因为真实用户的反馈总会推动改进。看看任何流行语言在其生命周期中的变化:Perl和Fortran是极端案例,但就连Lisp也变化巨大。例如Lisp 1.5没有宏,这一特性是在MIT黑客用Lisp编写真实程序数年后才演化出来的。[1]
因此,无论语言是否需要优秀才能流行,我认为语言必须流行才能变得优秀,且必须持续流行以保持优秀。编程语言的技术前沿不会停滞。然而今天的Lisp仍基本停留在1980年代MIT的水平,因为那是Lisp最后一次拥有足够庞大且高要求的用户群。
To hack is a transitive verb — hackers are usually hacking something — and in practice languages are judged relative to whatever they're used to hack. So if you want to design a popular language, you either have to supply more than a language, or you have to design your language to replace the scripting language of some existing system. Common Lisp is unpopular partly because it's an orphan. It did originally come with a system to hack: the Lisp Machine. But Lisp Machines (along with parallel computers) were steamrollered by the increasing power of general purpose processors in the 1980s. Common Lisp might have remained popular if it had been a good scripting language for Unix. It is, alas, an atrociously bad one. One way to describe this situation is to say that a language isn't judged on its own merits. Another view is that a programming language really isn't a programming language unless it's also the scripting language of something. This only seems unfair if it comes as a surprise. I think it's no more unfair than expecting a programming language to have, say, an implementation. It's just part of what a programming language is. A programming language does need a good implementation, of course, and this must be free. Companies will pay for software, but individual hackers won't, and it's the hackers you need to attract. A language also needs to have a book about it. The book should be thin, well-written, and full of good examples. K&R is the ideal here. At the moment I'd almost say that a language has to have a book published by O'Reilly. That's becoming the test of mattering to hackers. There should be online documentation as well. In fact, the book can start as online documentation. But I don't think that physical books are outmoded yet. Their format is convenient, and the de facto censorship imposed by publishers is a useful if imperfect filter.
当然,黑客需要先知道一门语言才会使用它。他们如何知晓?通过其他黑客。但首先必须有一群初始用户,其他人才能听说这门语言。这个初始群体需要多大?多少用户能形成关键规模?凭直觉,我认为二十人足矣。如果有二十名独立用户(即自主选择使用该语言的人),这门语言就是真实的。
达到这个目标并不容易。从零到二十可能比从二十到一千更难。获取初始二十名用户的最佳方式或许是特洛伊木马策略:提供人们想要的应用,而这个应用恰好用新语言编写。
首先承认一个确实影响语言流行的外部因素:要流行,一门语言必须成为流行系统的脚本语言。Fortran和Cobol是早期IBM主机的脚本语言,C是Unix的脚本语言,后来Perl也是。Tcl是Tk的脚本语言,Java和Javascript旨在成为浏览器的脚本语言。
Lisp未能大规模流行,因为它不是任何大规模流行系统的脚本语言。它残存的流行度可追溯至1960-70年代,当时它是MIT的脚本语言。那个时代许多顶尖程序员都与MIT有关联。在1970年代初C语言出现前,MIT的Lisp方言MacLisp是严肃黑客愿意使用的少数语言之一。
Bookstores are one of the most important places for learning about new languages. 3 Brevity Given that you can supply the three things any language needs — a free implementation, a book, and something to hack — how do you make a language that hackers will like? One thing hackers like is brevity. Hackers are lazy, in the same way that mathematicians and modernist architects are lazy: they hate anything extraneous. It would not be far from the truth to say that a hacker about to write a program decides what language to use, at least subconsciously, based on the total number of characters he'll have to type. If this isn't precisely how hackers think, a language designer would do well to act as if it were. It is a mistake to try to baby the user with long-winded expressions that are meant to resemble English. Cobol is notorious for this flaw. A hacker would consider being asked to write add x to y giving z instead of z = x+y as something between an insult to his intelligence and a sin against God. It has sometimes been said that Lisp should use first and rest instead of car and cdr, because it would make programs easier to read. Maybe for the first couple hours. But a hacker can learn quickly enough that car means the first element of a list and cdr means the rest. Using first and rest means 50% more typing. And they are also different lengths, meaning that the arguments won't line up when they're called, as car and cdr often are, in successive lines. I've found that it matters a lot how code lines up on the page. I can barely read Lisp code when it is set in a variable-width font, and friends say this is true for other languages too. Brevity is one place where strongly typed languages lose. All other things being equal, no one wants to begin a program with a bunch of declarations. Anything that can be implicit, should be. The individual tokens should be short as well.
如今Lisp是两个中等流行系统(Emacs和Autocad)的脚本语言,因此我猜测现今大多数Lisp编程是用Emacs Lisp或AutoLisp完成的。
编程语言从不孤立存在。"Hack"是及物动词——黑客总在hack某物——实践中语言优劣取决于它所hack的对象。因此要设计流行语言,要么提供超越语言本身的系统,要么让语言替代现有系统的脚本语言。
Common Lisp不受欢迎的部分原因是它成了孤儿。它最初伴随Lisp Machine系统诞生,但1980年代通用处理器性能提升碾压了Lisp Machine(与并行计算机)。如果Common Lisp能成为优秀的Unix脚本语言,或许能保持流行。可惜它在这方面糟糕透顶。
这种状况可描述为"语言不被基于自身优点评判",也可理解为"除非同时是某系统的脚本语言,否则编程语言不算真正的编程语言"。只有感到意外时才会觉得这不公平。我认为这与要求语言必须拥有实现一样公平——这是编程语言本质的一部分。
Perl and Common Lisp occupy opposite poles on this question. Perl programs can be almost cryptically dense, while the names of built-in Common Lisp operators are comically long. The designers of Common Lisp probably expected users to have text editors that would type these long names for them. But the cost of a long name is not just the cost of typing it. There is also the cost of reading it, and the cost of the space it takes up on your screen. 4 Hackability There is one thing more important than brevity to a hacker: being able to do what you want. In the history of programming languages a surprising amount of effort has gone into preventing programmers from doing things considered to be improper. This is a dangerously presumptuous plan. How can the language designer know what the programmer is going to need to do? I think language designers would do better to consider their target user to be a genius who will need to do things they never anticipated, rather than a bumbler who needs to be protected from himself. The bumbler will shoot himself in the foot anyway. You may save him from referring to variables in another package, but you can't save him from writing a badly designed program to solve the wrong problem, and taking forever to do it. Good programmers often want to do dangerous and unsavory things. By unsavory I mean things that go behind whatever semantic facade the language is trying to present: getting hold of the internal representation of some high-level abstraction, for example. Hackers like to hack, and hacking means getting inside things and second guessing the original designer. _Let yourself be second guessed._ When you make any tool, people use it in ways you didn't intend, and this is especially true of a highly articulated tool like a programming language. Many a hacker will want to tweak your semantic model in a way that you never imagined.
当然,编程语言需要优秀实现,且必须免费。公司会为软件付费,但个体黑客不会,而你需要吸引的正是黑客。
语言还需要相关书籍。这本书应该薄而精,充满优秀示例,K&R(《C程序设计语言》)是理想范本。目前几乎可以说语言需要一本O'Reilly出版的书——这正成为黑客认可的标准。
在线文档也不可少。事实上,书籍可以从在线文档起步。但纸质书尚未过时:其格式便利,出版商的事实审查虽不完美却是有效过滤器。书店仍是了解新语言的重要场所。
I say, let them; give the programmer access to as much internal stuff as you can without endangering runtime systems like the garbage collector. In Common Lisp I have often wanted to iterate through the fields of a struct — to comb out references to a deleted object, for example, or find fields that are uninitialized. I know the structs are just vectors underneath. And yet I can't write a general purpose function that I can call on any struct. I can only access the fields by name, because that's what a struct is supposed to mean. A hacker may only want to subvert the intended model of things once or twice in a big program. But what a difference it makes to be able to. And it may be more than a question of just solving a problem. There is a kind of pleasure here too. Hackers share the surgeon's secret pleasure in poking about in gross innards, the teenager's secret pleasure in popping zits. [2] For boys, at least, certain kinds of horrors are fascinating. Maxim magazine publishes an annual volume of photographs, containing a mix of pin-ups and grisly accidents. They know their audience. Historically, Lisp has been good at letting hackers have their way. The political correctness of Common Lisp is an aberration. Early Lisps let you get your hands on everything. A good deal of that spirit is, fortunately, preserved in macros. What a wonderful thing, to be able to make arbitrary transformations on the source code. Classic macros are a real hacker's tool — simple, powerful, and dangerous. It's so easy to understand what they do: you call a function on the macro's arguments, and whatever it returns gets inserted in place of the macro call. Hygienic macros embody the opposite principle. They try to protect you from understanding what they're doing. I have never heard hygienic macros explained in one sentence. And they are a classic example of the dangers of deciding what programmers are allowed to want.
假设你能提供语言必需的三个要素(免费实现、书籍和可hack的对象),如何设计黑客喜欢的语言?
黑客热爱简洁。他们像数学家与现代主义建筑师般懒惰:痛恨一切冗余。可以说黑客选择语言时(至少潜意识里)会考量需键入的总字符数。即便这不完全准确,语言设计者也应以此为准则。
试图用冗长的类英语表达式照顾用户是错误做法。Cobol因此臭名昭著。让黑客写:
无异于侮辱其智商兼亵渎神明。
Hygienic macros are intended to protect me from variable capture, among other things, but variable capture is exactly what I want in some macros. A really good language should be both clean and dirty: cleanly designed, with a small core of well understood and highly orthogonal operators, but dirty in the sense that it lets hackers have their way with it. C is like this. So were the early Lisps. A real hacker's language will always have a slightly raffish character. A good programming language should have features that make the kind of people who use the phrase "software engineering" shake their heads disapprovingly. At the other end of the continuum are languages like Ada and Pascal, models of propriety that are good for teaching and not much else. 5 Throwaway Programs To be attractive to hackers, a language must be good for writing the kinds of programs they want to write. And that means, perhaps surprisingly, that it has to be good for writing throwaway programs. A throwaway program is a program you write quickly for some limited task: a program to automate some system administration task, or generate test data for a simulation, or convert data from one format to another. The surprising thing about throwaway programs is that, like the "temporary" buildings built at so many American universities during World War II, they often don't get thrown away. Many evolve into real programs, with real features and real users. I have a hunch that the best big programs begin life this way, rather than being designed big from the start, like the Hoover Dam. It's terrifying to build something big from scratch. When people take on a project that's too big, they become overwhelmed. The project either gets bogged down, or the result is sterile and wooden: a shopping mall rather than a real downtown, Brasilia rather than Rome, Ada rather than C. Another way to get a big program is to start with a throwaway program and keep improving it.
有人认为Lisp应用first和rest替代car和cdr以提升可读性。这对初学者或许适用,但黑客很快就能掌握car代表列表首元素、cdr代表剩余部分。使用first和rest意味着增加50%的输入量。而且这两个词长度不同,导致连续调用时参数无法对齐(car和cdr常如此排列)。我发现代码的对齐方式极其重要:用变宽字体显示Lisp代码时我几乎无法阅读,其他语言用户也反映类似问题。
强类型语言在简洁性上失分。在其他条件相同时,没人愿意以一堆声明开始程序。任何能隐式表达的内容都应隐式处理。
单个标记也应简短。Perl与Common Lisp在此问题上分处两极:Perl程序可密集如密码,而Common Lisp内置操作符的名称长得可笑。Common Lisp设计者可能假设用户会用文本编辑器自动补全这些长名称。但长名称的代价不仅是输入耗时,还包括阅读负担和屏幕空间占用。
This approach is less daunting, and the design of the program benefits from evolution. I think, if one looked, that this would turn out to be the way most big programs were developed. And those that did evolve this way are probably still written in whatever language they were first written in, because it's rare for a program to be ported, except for political reasons. And so, paradoxically, if you want to make a language that is used for big systems, you have to make it good for writing throwaway programs, because that's where big systems come from. Perl is a striking example of this idea. It was not only designed for writing throwaway programs, but was pretty much a throwaway program itself. Perl began life as a collection of utilities for generating reports, and only evolved into a programming language as the throwaway programs people wrote in it grew larger. It was not until Perl 5 (if then) that the language was suitable for writing serious programs, and yet it was already massively popular. What makes a language good for throwaway programs? To start with, it must be readily available. A throwaway program is something that you expect to write in an hour. So the language probably must already be installed on the computer you're using. It can't be something you have to install before you use it. It has to be there. C was there because it came with the operating system. Perl was there because it was originally a tool for system administrators, and yours had already installed it. Being available means more than being installed, though. An interactive language, with a command-line interface, is more available than one that you have to compile and run separately. A popular programming language should be interactive, and start up fast. Another thing you want in a throwaway program is brevity.
4 可hack性
对黑客而言,比简洁更重要的是:能够实现所想。编程语言史上,大量精力被用于阻止程序员进行"不当"操作。这是危险的傲慢——语言设计者怎能预知程序员的所有需求?设计者应假设用户是天才,需要完成设计者未曾预料的任务,而非需要保护的笨蛋。笨蛋总会搬石砸脚:你可以阻止他访问其他包的变量,但无法阻止他设计糟糕程序解决错误问题并耗费无限时间。
优秀程序员常需进行危险或"不雅"操作。所谓"不雅",指绕过语言试图呈现的语义 facade,例如获取高级抽象的内部表示。黑客热爱hacking,这意味着深入事物内部并质疑原始设计。
允许自己被质疑。任何工具都会被以设计者未预料的方式使用,对编程语言这种高度复杂的工具更是如此。许多黑客会以你无法想象的方式调整你的语义模型。我的建议是:允许他们;在不危及垃圾回收器等运行时系统的前提下,尽可能向程序员开放内部机制。
Brevity is always attractive to hackers, and never more so than in a program they expect to turn out in an hour. 6 Libraries Of course the ultimate in brevity is to have the program already written for you, and merely to call it. And this brings us to what I think will be an increasingly important feature of programming languages: library functions. Perl wins because it has large libraries for manipulating strings. This class of library functions are especially important for throwaway programs, which are often originally written for converting or extracting data. Many Perl programs probably begin as just a couple library calls stuck together. I think a lot of the advances that happen in programming languages in the next fifty years will have to do with library functions. I think future programming languages will have libraries that are as carefully designed as the core language. Programming language design will not be about whether to make your language strongly or weakly typed, or object oriented, or functional, or whatever, but about how to design great libraries. The kind of language designers who like to think about how to design type systems may shudder at this. It's almost like writing applications! Too bad. Languages are for programmers, and libraries are what programmers need. It's hard to design good libraries. It's not simply a matter of writing a lot of code. Once the libraries get too big, it can sometimes take longer to find the function you need than to write the code yourself. Libraries need to be designed using a small set of orthogonal operators, just like the core language. It ought to be possible for the programmer to guess what library call will do what he needs. Libraries are one place Common Lisp falls short. There are only rudimentary libraries for manipulating strings, and almost none for talking to the operating system. For historical reasons, Common Lisp tries to pretend that the OS doesn't exist.
在Common Lisp中,我常需要遍历结构体字段(例如清理对已删除对象的引用或查找未初始化字段)。我知道结构体本质上是向量,却无法编写适用于任意结构体的通用函数,只能通过字段名访问——因为这是结构体的设计本意。
黑客可能仅需在大型程序中偶尔突破既定模型,但这种能力的存在意义重大。这不仅是解决问题的方式,更带来某种快感:黑客分享着外科医生摆弄内脏的秘密愉悦,或青少年挤痘痘的隐秘乐趣。[2]至少对男性而言,某些恐怖事物具有致命吸引力。《Maxim》杂志每年出版的写真集混合着性感女郎与血腥事故的照片,他们深谙读者心理。
历史上,Lisp在允许黑客为所欲为方面表现优异。Common Lisp的政治正确性是个异数。早期Lisp允许接触一切,所幸这种精神很大程度上通过宏保留下来。能对源代码进行任意转换是多么美妙!
经典宏是真正的黑客工具——简单、强大而危险。其原理极易理解:对宏参数调用函数,返回值替换宏调用。卫生宏则体现相反哲学,试图保护你免于理解其运作机制。我从未见过能用一句话解释清楚的卫生宏。它们是"决定程序员该要什么"这一危险的典型例证。卫生宏旨在防止变量捕获等问题,但某些宏正需要变量捕获功能。
And because you can't talk to the OS, you're unlikely to be able to write a serious program using only the built-in operators in Common Lisp. You have to use some implementation-specific hacks as well, and in practice these tend not to give you everything you want. Hackers would think a lot more highly of Lisp if Common Lisp had powerful string libraries and good OS support. 7 Syntax Could a language with Lisp's syntax, or more precisely, lack of syntax, ever become popular? I don't know the answer to this question. I do think that syntax is not the main reason Lisp isn't currently popular. Common Lisp has worse problems than unfamiliar syntax. I know several programmers who are comfortable with prefix syntax and yet use Perl by default, because it has powerful string libraries and can talk to the os. There are two possible problems with prefix notation: that it is unfamiliar to programmers, and that it is not dense enough. The conventional wisdom in the Lisp world is that the first problem is the real one. I'm not so sure. Yes, prefix notation makes ordinary programmers panic. But I don't think ordinary programmers' opinions matter. Languages become popular or unpopular based on what expert hackers think of them, and I think expert hackers might be able to deal with prefix notation. Perl syntax can be pretty incomprehensible, but that has not stood in the way of Perl's popularity. If anything it may have helped foster a Perl cult. A more serious problem is the diffuseness of prefix notation. For expert hackers, that really is a problem. No one wants to write (aref a x y) when they could write a[x,y]. In this particular case there is a way to finesse our way out of the problem. If we treat data structures as if they were functions on indexes, we could write (a x y) instead, which is even shorter than the Perl form. Similar tricks may shorten other types of expressions.
真正优秀的语言应既干净又肮脏:设计干净,核心由少量高正交性的操作符组成;但又足够肮脏,允许黑客为所欲为。C语言如此,早期Lisp亦如此。真正的黑客语言总带些痞气。
优秀编程语言应具备让"软件工程"人士摇头的特性。连续体的另一端是Ada和Pascal这类模范生语言,适合教学却别无他用。
5 一次性程序
We can get rid of (or make optional) a lot of parentheses by making indentation significant. That's how programmers read code anyway: when indentation says one thing and delimiters say another, we go by the indentation. Treating indentation as significant would eliminate this common source of bugs as well as making programs shorter. Sometimes infix syntax is easier to read. This is especially true for math expressions. I've used Lisp my whole programming life and I still don't find prefix math expressions natural. And yet it is convenient, especially when you're generating code, to have operators that take any number of arguments. So if we do have infix syntax, it should probably be implemented as some kind of read-macro. I don't think we should be religiously opposed to introducing syntax into Lisp, as long as it translates in a well-understood way into underlying s-expressions. There is already a good deal of syntax in Lisp. It's not necessarily bad to introduce more, as long as no one is forced to use it. In Common Lisp, some delimiters are reserved for the language, suggesting that at least some of the designers intended to have more syntax in the future. One of the most egregiously unlispy pieces of syntax in Common Lisp occurs in format strings; format is a language in its own right, and that language is not Lisp. If there were a plan for introducing more syntax into Lisp, format specifiers might be able to be included in it. It would be a good thing if macros could generate format specifiers the way they generate any other kind of code. An eminent Lisp hacker told me that his copy of CLTL falls open to the section format. Mine too. This probably indicates room for improvement. It may also mean that programs do a lot of I/O. 8 Efficiency A good language, as everyone knows, should generate fast code. But in practice I don't think fast code comes primarily from things you do in the design of the language.
要吸引黑客,语言必须适合编写他们想写的程序。出人意料的是,这意味着它必须擅长编写一次性程序。
一次性程序是为特定临时任务快速编写的程序:自动化系统管理任务、生成模拟测试数据或转换数据格式等。令人惊讶的是,这些程序常像二战期间美国大学搭建的"临时"建筑一样永不消失。许多会演变成具有真实功能和用户的正式程序。
我猜测优秀的大型程序都如此诞生,而非像胡佛水坝般从一开始就宏大设计。从零构建庞然大物令人畏惧。当项目过于庞大时,人们会不堪重负,导致项目停滞或产出僵化死板的作品:购物中心般的伪市中心、巴西利亚式的规划城市、Ada而非C般的语言。
另一种构建大型程序的方式是从一次性程序开始持续改进。这种方式压力较小,且设计能通过演化受益。若做调查,这可能是多数大型程序的开发方式。那些如此演化的程序很可能仍用原始语言编写,因为除非政治原因,程序很少被移植。因此吊诡的是:要让语言用于大型系统,必须让它适合编写一次性程序——因为大型系统正源于此。
As Knuth pointed out long ago, speed only matters in certain critical bottlenecks. And as many programmers have observed since, one is very often mistaken about where these bottlenecks are. So, in practice, the way to get fast code is to have a very good profiler, rather than by, say, making the language strongly typed. You don't need to know the type of every argument in every call in the program. You do need to be able to declare the types of arguments in the bottlenecks. And even more, you need to be able to find out where the bottlenecks are. One complaint people have had with Lisp is that it's hard to tell what's expensive. This might be true. It might also be inevitable, if you want to have a very abstract language. And in any case I think good profiling would go a long way toward fixing the problem: you'd soon learn what was expensive. Part of the problem here is social. Language designers like to write fast compilers. That's how they measure their skill. They think of the profiler as an add-on, at best. But in practice a good profiler may do more to improve the speed of actual programs written in the language than a compiler that generates fast code. Here, again, language designers are somewhat out of touch with their users. They do a really good job of solving slightly the wrong problem. It might be a good idea to have an active profiler — to push performance data to the programmer instead of waiting for him to come asking for it. For example, the editor could display bottlenecks in red when the programmer edits the source code. Another approach would be to somehow represent what's happening in running programs. This would be an especially big win in server-based applications, where you have lots of running programs to look at. An active profiler could show graphically what's happening in memory as a program's running, or even make sounds that tell what's happening. Sound is a good cue to problems.
Perl是这一理念的鲜明例证。它不仅为编写一次性程序设计,自身几乎就是个一次性程序。Perl最初是生成报表的工具集,随着用户编写的一次性程序规模扩大才演变成编程语言。直到Perl 5(甚至更晚)它才适合编写严肃程序,但早已广泛流行。
什么使语言适合一次性程序?首先必须易于获取。一次性程序预期一小时写完,因此语言最好已预装在所用电脑上。不能是需先安装才能使用的语言。C因随操作系统分发而存在,Perl因最初是系统管理员工具而被预装。
"易于获取"不止于安装。具有命令行交互界面的语言比需单独编译运行的语言更易获取。流行语言应是交互式且启动迅速的。
In one place I worked, we had a big board of dials showing what was happening to our web servers. The hands were moved by little servomotors that made a slight noise when they turned. I couldn't see the board from my desk, but I found that I could tell immediately, by the sound, when there was a problem with a server. It might even be possible to write a profiler that would automatically detect inefficient algorithms. I would not be surprised if certain patterns of memory access turned out to be sure signs of bad algorithms. If there were a little guy running around inside the computer executing our programs, he would probably have as long and plaintive a tale to tell about his job as a federal government employee. I often have a feeling that I'm sending the processor on a lot of wild goose chases, but I've never had a good way to look at what it's doing. A number of Lisps now compile into byte code, which is then executed by an interpreter. This is usually done to make the implementation easier to port, but it could be a useful language feature. It might be a good idea to make the byte code an official part of the language, and to allow programmers to use inline byte code in bottlenecks. Then such optimizations would be portable too. The nature of speed, as perceived by the end-user, may be changing. With the rise of server-based applications, more and more programs may turn out to be i/o-bound. It will be worth making i/o fast. The language can help with straightforward measures like simple, fast, formatted output functions, and also with deep structural changes like caching and persistent objects. Users are interested in response time. But another kind of efficiency will be increasingly important: the number of simultaneous users you can support per processor. Many of the interesting applications written in the near future will be server-based, and the number of users per server is the critical question for anyone hosting such applications.
一次性程序还需要简洁。黑客永远热爱简洁,对预期一小时完成的程序更是如此。
极致的简洁是直接调用现成程序。这引向我认为日益重要的语言特性:库函数。Perl因强大的字符串处理库而胜出。这类库对一次性程序尤为重要,因为它们常用于数据转换或提取。许多Perl程序最初可能只是几个库调用的组合。
未来五十年编程语言的进步将很大程度上关乎库函数。未来的语言将拥有与核心语言同样精心设计的库。语言设计的焦点不再是强类型/弱类型、面向对象/函数式等争论,而是如何设计伟大库。那些沉迷于类型系统设计的设计者可能对此嗤之以鼻——这几乎像在写应用程序!但语言是为程序员服务的,而库正是程序员所需。
设计优秀库极难。绝非简单堆砌代码。当库过于庞大时,寻找合适函数可能比自己编写更耗时。库需要像核心语言一样用少量正交操作符设计,程序员应能凭直觉猜测所需库调用。
In the capital cost of a business offering a server-based application, this is the divisor. For years, efficiency hasn't mattered much in most end-user applications. Developers have been able to assume that each user would have an increasingly powerful processor sitting on their desk. And by Parkinson's Law, software has expanded to use the resources available. That will change with server-based applications. In that world, the hardware and software will be supplied together. For companies that offer server-based applications, it will make a very big difference to the bottom line how many users they can support per server. In some applications, the processor will be the limiting factor, and execution speed will be the most important thing to optimize. But often memory will be the limit; the number of simultaneous users will be determined by the amount of memory you need for each user's data. The language can help here too. Good support for threads will enable all the users to share a single heap. It may also help to have persistent objects and/or language level support for lazy loading. 9 Time The last ingredient a popular language needs is time. No one wants to write programs in a language that might go away, as so many programming languages do. So most hackers will tend to wait until a language has been around for a couple years before even considering using it. Inventors of wonderful new things are often surprised to discover this, but you need time to get any message through to people. A friend of mine rarely does anything the first time someone asks him. He knows that people sometimes ask for things that they turn out not to want. To avoid wasting his time, he waits till the third or fourth time he's asked to do something; by then, whoever's asking him may be fairly annoyed, but at least they probably really do want whatever they're asking for.
Common Lisp的短板正在于此。其字符串处理库极其基础,操作系统交互库几乎不存在。由于历史原因,Common Lisp试图假装操作系统不存在。无法与OS交互意味着仅用内置操作符难以编写严肃程序,必须借助实现相关的hack——而这些hack往往无法满足需求。如果Common Lisp拥有强大字符串库和良好OS支持,黑客对Lisp的评价会高得多。
采用Lisp语法(或更准确地说,无语法)的语言可能流行吗?我尚无定论。但我认为语法并非Lisp当前不流行的主因。Common Lisp存在比陌生语法更严重的问题。我认识许多习惯前缀语法的程序员仍默认使用Perl,因其强大字符串库和OS交互能力。
前缀表示法存在两个潜在问题:对程序员陌生,以及不够紧凑。Lisp界的传统智慧认为前者是主因。我不确定。确实,前缀表示法让普通程序员恐慌,但普通程序员的意见无关紧要——语言流行与否取决于顶尖黑客的评价,而我认为顶尖黑客能适应前缀表示法。Perl语法可能晦涩难懂,但这并未阻碍其流行,反而可能助长了Perl信徒的形成。
更严重的问题是前缀表示法的冗余性。对顶尖黑客这确实是问题:没人愿意写(aref a x y)而非a[x,y]。
Most people have learned to do a similar sort of filtering on new things they hear about. They don't even start paying attention until they've heard about something ten times. They're perfectly justified: the majority of hot new whatevers do turn out to be a waste of time, and eventually go away. By delaying learning VRML, I avoided having to learn it at all. So anyone who invents something new has to expect to keep repeating their message for years before people will start to get it. We wrote what was, as far as I know, the first web-server based application, and it took us years to get it through to people that it didn't have to be downloaded. It wasn't that they were stupid. They just had us tuned out. The good news is, simple repetition solves the problem. All you have to do is keep telling your story, and eventually people will start to hear. It's not when people notice you're there that they pay attention; it's when they notice you're still there. It's just as well that it usually takes a while to gain momentum. Most technologies evolve a good deal even after they're first launched — programming languages especially. Nothing could be better, for a new techology, than a few years of being used only by a small number of early adopters. Early adopters are sophisticated and demanding, and quickly flush out whatever flaws remain in your technology. When you only have a few users you can be in close contact with all of them. And early adopters are forgiving when you improve your system, even if this causes some breakage. There are two ways new technology gets introduced: the organic growth method, and the big bang method. The organic growth method is exemplified by the classic seat-of-the-pants underfunded garage startup. A couple guys, working in obscurity, develop some new technology. They launch it with no marketing and initially have only a few (fanatically devoted) users.
针对此案例,我们有巧妙的解决方案:若将数据结构视为索引的函数,可写作(a x y),比Perl形式更简短。类似技巧可缩短其他表达式。
通过缩进语义化可消除(或可选)大量括号。程序员本就按缩进阅读代码:当缩进与定界符冲突时,人们遵循缩进。缩进语义化既能消除此类常见错误来源,又能缩短程序。
有时中缀语法更易读,数学表达式尤其如此。我虽毕生使用Lisp,仍不习惯前缀数学表达式。但为代码生成方便,需要支持任意数量参数的操作符。因此若实现中缀语法,应通过读取宏实现。
They continue to improve the technology, and meanwhile their user base grows by word of mouth. Before they know it, they're big. The other approach, the big bang method, is exemplified by the VC-backed, heavily marketed startup. They rush to develop a product, launch it with great publicity, and immediately (they hope) have a large user base. Generally, the garage guys envy the big bang guys. The big bang guys are smooth and confident and respected by the VCs. They can afford the best of everything, and the PR campaign surrounding the launch has the side effect of making them celebrities. The organic growth guys, sitting in their garage, feel poor and unloved. And yet I think they are often mistaken to feel sorry for themselves. Organic growth seems to yield better technology and richer founders than the big bang method. If you look at the dominant technologies today, you'll find that most of them grew organically. This pattern doesn't only apply to companies. You see it in sponsored research too. Multics and Common Lisp were big-bang projects, and Unix and MacLisp were organic growth projects. 10 Redesign "The best writing is rewriting," wrote E. B. White. Every good writer knows this, and it's true for software too. The most important part of design is redesign. Programming languages, especially, don't get redesigned enough. To write good software you must simultaneously keep two opposing ideas in your head. You need the young hacker's naive faith in his abilities, and at the same time the veteran's skepticism. You have to be able to think how hard can it be? with one half of your brain while thinking it will never work with the other. The trick is to realize that there's no real contradiction here. You want to be optimistic and skeptical about two different things.
我们不应教条地反对为Lisp引入语法——只要它能明确转换为底层S表达式。Lisp已拥有不少语法,只要不强制使用,增加更多未必是坏事。Common Lisp中某些分隔符为语言保留,暗示至少部分设计者预期未来会增加语法。
Common Lisp中最不合Lisp风格的语法出现在格式化字符串中:format本身就是一门语言,且非Lisp语言。若有增加Lisp语法的计划,格式化说明符应被纳入其中。若宏能像生成其他代码那样生成格式化说明符,将是巨大进步。
一位著名Lisp黑客告诉我,他的《CLTL》总在format章节自然展开。我的也是。这或许暗示改进空间,也可能表明程序频繁进行I/O操作。
众所周知,优秀语言应生成高效代码。但我认为高效代码主要不来自语言设计层面的决策。如Knuth早已指出的,速度仅在某些关键瓶颈处重要;而众多程序员发现,这些瓶颈的位置常被误判。
You have to be optimistic about the possibility of solving the problem, but skeptical about the value of whatever solution you've got so far. People who do good work often think that whatever they're working on is no good. Others see what they've done and are full of wonder, but the creator is full of worry. This pattern is no coincidence: it is the worry that made the work good. If you can keep hope and worry balanced, they will drive a project forward the same way your two legs drive a bicycle forward. In the first phase of the two-cycle innovation engine, you work furiously on some problem, inspired by your confidence that you'll be able to solve it. In the second phase, you look at what you've done in the cold light of morning, and see all its flaws very clearly. But as long as your critical spirit doesn't outweigh your hope, you'll be able to look at your admittedly incomplete system, and think, how hard can it be to get the rest of the way?, thereby continuing the cycle. It's tricky to keep the two forces balanced. In young hackers, optimism predominates. They produce something, are convinced it's great, and never improve it. In old hackers, skepticism predominates, and they won't even dare to take on ambitious projects. Anything you can do to keep the redesign cycle going is good. Prose can be rewritten over and over until you're happy with it. But software, as a rule, doesn't get redesigned enough. Prose has readers, but software has _users._ If a writer rewrites an essay, people who read the old version are unlikely to complain that their thoughts have been broken by some newly introduced incompatibility. Users are a double-edged sword. They can help you improve your language, but they can also deter you from improving it. So choose your users carefully, and be slow to grow their number. Having users is like optimization: the wise course is to delay it.
因此实践中,获取高效代码的途径是拥有优秀性能分析器,而非通过强类型等语言特性。你不需要知道程序中每个调用的参数类型,但必须能在瓶颈处声明类型。更重要的是,必须能定位瓶颈所在。
人们对Lisp的一个抱怨是难以判断操作的开销。这可能属实,也可能是高度抽象语言不可避免的代价。无论如何,优秀性能分析器将极大缓解此问题:你会很快了解哪些操作昂贵。
部分问题源于社会因素。语言设计者喜欢编写快速编译器,这衡量着他们的技艺。他们将性能分析器视为附加品。但实际上,优秀性能分析器对提升程序速度的作用可能超过生成高效代码的编译器。语言设计者再次与用户需求略有脱节——他们非常出色地解决了略有偏差的问题。
Also, as a general rule, you can at any given time get away with changing more than you think. Introducing change is like pulling off a bandage: the pain is a memory almost as soon as you feel it. Everyone knows that it's not a good idea to have a language designed by a committee. Committees yield bad design. But I think the worst danger of committees is that they interfere with redesign. It is so much work to introduce changes that no one wants to bother. Whatever a committee decides tends to stay that way, even if most of the members don't like it. Even a committee of two gets in the way of redesign. This happens particularly in the interfaces between pieces of software written by two different people. To change the interface both have to agree to change it at once. And so interfaces tend not to change at all, which is a problem because they tend to be one of the most ad hoc parts of any system. One solution here might be to design systems so that interfaces are horizontal instead of vertical — so that modules are always vertically stacked strata of abstraction. Then the interface will tend to be owned by one of them. The lower of two levels will either be a language in which the upper is written, in which case the lower level will own the interface, or it will be a slave, in which case the interface can be dictated by the upper level. 11 Lisp What all this implies is that there is hope for a new Lisp. There is hope for any language that gives hackers what they want, including Lisp. I think we may have made a mistake in thinking that hackers are turned off by Lisp's strangeness. This comforting illusion may have prevented us from seeing the real problem with Lisp, or at least Common Lisp, which is that it sucks for doing what hackers want to do. A hacker's language needs powerful libraries and something to hack. Common Lisp has neither. A hacker's language is terse and hackable. Common Lisp is not.
主动性能分析器或许是良策——将性能数据推送给程序员而非等待其查询。例如编辑器可用红色标注源码中的瓶颈。另一种方式是可视化运行程序的动态,这对服务端应用尤为有用——你可观察大量运行中程序。主动性能分析器能图形化展示内存状态,甚至通过声音提示程序状态。
声音是问题的良好指示器。我曾工作的地方有块仪表盘显示Web服务器状态,指针由微型伺服电机驱动并发出轻微噪音。虽然看不到仪表盘,但我能通过声音立即判断服务器异常。
甚至可能编写能自动检测低效算法的性能分析器。某些内存访问模式很可能是糟糕算法的征兆,这不会令我惊讶。如果有小人儿在计算机里执行我们的程序,他关于工作的抱怨恐怕不亚于联邦政府雇员。我常感觉自己在让处理器执行徒劳任务,却从未有好的方式观察其行为。
许多Lisp现在编译为字节码再由解释器执行。这通常是为了便于移植,但它可能成为有用的语言特性。将字节码作为语言官方部分,并允许在瓶颈处使用内联字节码,这种优化也将具备可移植性。
The good news is, it's not Lisp that sucks, but Common Lisp. If we can develop a new Lisp that is a real hacker's language, I think hackers will use it. They will use whatever language does the job. All we have to do is make sure this new Lisp does some important job better than other languages. History offers some encouragement. Over time, successive new programming languages have taken more and more features from Lisp. There is no longer much left to copy before the language you've made is Lisp. The latest hot language, Python, is a watered-down Lisp with infix syntax and no macros. A new Lisp would be a natural step in this progression. I sometimes think that it would be a good marketing trick to call it an improved version of Python. That sounds hipper than Lisp. To many people, Lisp is a slow AI language with a lot of parentheses. Fritz Kunze's official biography carefully avoids mentioning the L-word. But my guess is that we shouldn't be afraid to call the new Lisp Lisp. Lisp still has a lot of latent respect among the very best hackers — the ones who took 6.001 and understood it, for example. And those are the users you need to win. In "How to Become a Hacker," Eric Raymond describes Lisp as something like Latin or Greek — a language you should learn as an intellectual exercise, even though you won't actually use it: > Lisp is worth learning for the profound enlightenment experience you will have when you finally get it; that experience will make you a better programmer for the rest of your days, even if you never actually use Lisp itself a lot..
终端用户感知的速度本质正在变化。随着服务端应用兴起,越来越多程序受I/O限制。提升I/O速度将物有所值。语言可通过简单快速的格式化输出函数等直接措施,以及缓存和持久化对象等深层结构调整提供帮助。
用户关注响应时间,但另一种效率正日益重要:单处理器支持的并发用户数。未来许多有趣应用将是服务端的,单服务器用户数成为托管方的关键指标——这是业务资本成本的分母。
多年来,效率对多数终端用户应用并不重要。开发者可假设用户桌面处理器的性能持续提升。根据帕金森定律,软件膨胀以消耗可用资源。服务端应用将改变这一状况——此时硬件软件需成套提供。对提供服务的公司而言,单服务器用户数将显著影响盈亏。
某些应用中处理器是限制因素,执行速度是最需优化的指标。但更多时候内存才是瓶颈——并发用户数取决于单用户数据所需内存量。语言在此也能助力:优秀的线程支持让所有用户共享单一堆;持久化对象和/或延迟加载的语言级支持也有
If I didn't know Lisp, reading this would set me asking questions. A language that would make me a better programmer, if it means anything at all, means a language that would be better for programming. And that is in fact the implication of what Eric is saying. As long as that idea is still floating around, I think hackers will be receptive enough to a new Lisp, even if it is called Lisp. But this Lisp must be a hacker's language, like the classic Lisps of the 1970s. It must be terse, simple, and hackable. And it must have powerful libraries for doing what hackers want to do now. In the matter of libraries I think there is room to beat languages like Perl and Python at their own game. A lot of the new applications that will need to be written in the coming years will be server-based applications. There's no reason a new Lisp shouldn't have string libraries as good as Perl, and if this new Lisp also had powerful libraries for server-based applications, it could be very popular. Real hackers won't turn up their noses at a new tool that will let them solve hard problems with a few library calls. Remember, hackers are lazy. It could be an even bigger win to have core language support for server-based applications. For example, explicit support for programs with multiple users, or data ownership at the level of type tags. Server-based applications also give us the answer to the question of what this new Lisp will be used to hack. It would not hurt to make Lisp better as a scripting language for Unix. (It would be hard to make it worse.) But I think there are areas where existing languages would be easier to beat. I think it might be better to follow the model of Tcl, and supply the Lisp together with a complete system for supporting server-based applications. Lisp is a natural fit for server-based applications. Lexical closures provide a way to get the effect of subroutines when the ui is just a series of web pages.
如果我不懂Lisp,读到这段话时一定会产生疑问。一门能让我成为更优秀程序员的语言——如果这说法真有意义——必然意味着它本身就是更优秀的编程语言。而这正是埃里克话中隐含的真意。
只要这种理念仍在流传,我相信黑客们对一门新Lisp语言仍会保持足够热情,哪怕它仍沿用Lisp之名。但这款Lisp必须延续1970年代经典Lisp的特质,成为真正的黑客语言:简洁、纯粹、可深度定制。更重要的是,它必须配备强大的函数库来满足当代黑客的核心需求。
在函数库方面,新Lisp完全有可能在Perl和Python的主场击败它们。未来数年需要开发的大量新应用都将属于基于服务器的应用。新Lisp没有理由不配备媲美Perl的字符串处理库——如果再拥有强大的服务器应用开发库,其流行将水到渠成。真正的黑客从不会对能通过几个库调用就解决复杂问题的新工具嗤之以鼻。记住,黑客骨子里是懒惰的。
S-expressions map nicely onto html, and macros are good at generating it. There need to be better tools for writing server-based applications, and there needs to be a new Lisp, and the two would work very well together. 12 The Dream Language By way of summary, let's try describing the hacker's dream language. The dream language is beautiful, clean, and terse. It has an interactive toplevel that starts up fast. You can write programs to solve common problems with very little code. Nearly all the code in any program you write is code that's specific to your application. Everything else has been done for you. The syntax of the language is brief to a fault. You never have to type an unnecessary character, or even to use the shift key much. Using big abstractions you can write the first version of a program very quickly. Later, when you want to optimize, there's a really good profiler that tells you where to focus your attention. You can make inner loops blindingly fast, even writing inline byte code if you need to. There are lots of good examples to learn from, and the language is intuitive enough that you can learn how to use it from examples in a couple minutes. You don't need to look in the manual much. The manual is thin, and has few warnings and qualifications. The language has a small core, and powerful, highly orthogonal libraries that are as carefully designed as the core language. The libraries all work well together; everything in the language fits together like the parts in a fine camera. Nothing is deprecated, or retained for compatibility. The source code of all the libraries is readily available. It's easy to talk to the operating system and to applications written in other languages. The language is built in layers. The higher-level abstractions are built in a very transparent way out of lower-level abstractions, which you can get hold of if you want.
若能在语言核心层面支持服务器应用开发,优势将更为显著。例如直接支持多用户程序,或在类型标记层面实现数据所有权管控。
服务器应用也解答了"新Lisp用于开发什么"的疑问。提升Lisp作为Unix脚本语言的能力固然有益(毕竟现状已难以更糟),但现有语言体系的薄弱环节才是更好的突破口。或许可以效仿Tcl的模式,将Lisp与完整的服务器应用支撑系统捆绑提供。Lisp天生适合服务器开发:词法闭包能在基于网页的交互中实现子程序效果;S表达式可完美映射到HTML;宏系统则擅长动态生成内容。当前既需要更好的服务器应用开发工具,也需要新Lisp语言,二者结合将相得益彰。
12 理想语言
总结而言,让我们尝试描绘黑客的梦想语言:它必须优雅、简洁、凝练。具备快速启动的交互式顶层环境,能用极简代码解决常见问题。你所写的程序几乎完全由业务逻辑构成——其他一切均已预先实现。
Nothing is hidden from you that doesn't absolutely have to be. The language offers abstractions only as a way of saving you work, rather than as a way of telling you what to do. In fact, the language encourages you to be an equal participant in its design. You can change everything about it, including even its syntax, and anything you write has, as much as possible, the same status as what comes predefined. Notes [1] Macros very close to the modern idea were proposed by Timothy Hart in 1964, two years after Lisp 1.5 was released. What was missing, initially, were ways to avoid variable capture and multiple evaluation; Hart's examples are subject to both. [2] In _When the Air Hits Your Brain,_ neurosurgeon Frank Vertosick recounts a conversation in which his chief resident, Gary, talks about the difference between surgeons and internists ("fleas"):.
其语法精简到极致,从不需要输入冗余字符,甚至鲜少用到Shift键。
借助高级抽象,你能快速完成程序原型。优化阶段则配备精准的性能分析器定位瓶颈。你可以让内循环极速运行,必要时甚至能直接内联字节码。
大量优质示例可供学习,语言的直觉性设计让你数分钟内就能通过例子掌握用法。几乎无需查阅手册——那本薄册子鲜少警告和限制说明。
> Gary and I ordered a large pizza and found an open booth. The chief lit a cigarette. "Look at those goddamn fleas, jabbering about some disease they'll see once in their lifetimes. That's the trouble with fleas, they only like the bizarre stuff. They hate their bread and butter cases. That's the difference between us and the fucking fleas. See, we love big juicy lumbar disc herniations, but they hate hypertension...."
语言核心精炼,函数库强大而高度正交,其设计精度与语言核心等同。所有库完美协同,如同精密相机部件般严丝合缝。没有废弃设计,也不为兼容性保留累赘。所有库源码触手可及,与操作系统及其他语言程序的交互轻而易举。
语言采用分层架构,高层抽象以完全透明的方式构建于底层抽象之上,必要时你可直取本源。
除非绝对必要,没有任何隐藏机制。语言提供的抽象仅用于减轻工作量,而非限制思维。事实上,它鼓励你平等参与设计——你可以改变包括语法在内的任何部分,你编写的代码与预定义组件具有同等地位。
[1] 蒂莫西·哈特在1964年提出的宏概念已接近现代形态,比Lisp 1.5发布晚两年。初期缺乏的是避免变量捕获和多重求值的机制——哈特的例子都存在这两个问题。
It's hard to think of a lumbar disc herniation as juicy (except literally). And yet I think I know what they mean. I've often had a juicy bug to track down. Someone who's not a programmer would find it hard to imagine that there could be pleasure in a bug. Surely it's better if everything just works. In one way, it is. And yet there is undeniably a grim satisfaction in hunting down certain sorts of bugs.
| Postscript Version | | | Arc | Five Questions about Language Design | | | How to Become a Hacker | Japanese Translation
[2] 在《当空气击中大脑》中,神经外科医生弗兰克·维托西克记载了住院总医师加里关于外科医生与内科医生("跳蚤")区别的谈话:
加里和我点了一个大披萨,找了个空卡座坐下。警长点燃一支烟:"看看那些该死的跳蚤,喋喋不休地讨论他们一辈子都碰不上几次的罕见病。这就是跳蚤的问题所在,他们只喜欢猎奇。他们讨厌那些日常病例。这就是我们和那些该死的跳蚤的区别。听着,我们喜欢处理那些棘手的腰椎间盘突出病例,而他们却讨厌高血压......"
很难将腰椎间盘突出形容为"多汁"(除非从字面理解)。但我想我明白他们的意思。我经常遇到需要追踪的"多汁"程序错误。非程序员很难想象在错误中寻找乐趣。按理说一切正常运行才是最好的。从某种角度确实如此。但不可否认,追查某些类型的错误时确实有种残酷的满足感。
| 后记版本 | | | Arc语言 | 关于语言设计的五个问题 | | | 如何成为黑客 | 日语译本
May 2001 _(These are some notes I made for a panel discussion on programming language design at MIT on May 10, 2001.)_ 1\. Programming Languages Are for People. Programming languages are how people talk to computers. The computer would be just as happy speaking any language that was unambiguous. The reason we have high level languages is because people can't deal with machine language. The point of programming languages is to prevent our poor frail human brains from being overwhelmed by a mass of detail. Architects know that some kinds of design problems are more personal than others. One of the cleanest, most abstract design problems is designing bridges. There your job is largely a matter of spanning a given distance with the least material. The other end of the spectrum is designing chairs. Chair designers have to spend their time thinking about human butts. Software varies in the same way. Designing algorithms for routing data through a network is a nice, abstract problem, like designing bridges. Whereas designing programming languages is like designing chairs: it's all about dealing with human weaknesses. Most of us hate to acknowledge this. Designing systems of great mathematical elegance sounds a lot more appealing to most of us than pandering to human weaknesses. And there is a role for mathematical elegance: some kinds of elegance make programs easier to understand. But elegance is not an end in itself. And when I say languages have to be designed to suit human weaknesses, I don't mean that languages have to be designed for bad programmers. In fact I think you ought to design for the best programmers, but even the best programmers have limitations. I don't think anyone would like programming in a language where all the variables were the letter x with integer subscripts. 2\.
(这是我在2001年5月10日麻省理工学院关于编程语言设计的专题讨论会上准备的笔记。)
1. 编程语言是为人服务的。
编程语言是人们与计算机交流的方式。计算机其实并不在乎使用哪种语言,只要语言没有歧义就行。我们之所以需要高级语言,是因为人类无法直接处理机器语言。编程语言的意义在于保护我们脆弱的人类大脑不被大量细节淹没。
建筑师知道,某些设计问题比其他问题更关乎人性。桥梁设计是最纯粹、最抽象的设计问题之一,主要任务是用最少的材料跨越给定的距离。而另一端的极端则是椅子设计。椅子设计师必须花时间考虑人类的臀部。
软件设计同样如此。设计网络数据路由算法是一个优美而抽象的问题,就像设计桥梁。而设计编程语言则像设计椅子:核心在于应对人类的弱点。
大多数人都不愿承认这一点。设计具有数学美感的系统听起来比迎合人类弱点要吸引人得多。数学美感确实有其价值:某些形式的美感能让程序更易理解。但美感本身并非目的。
Design for Yourself and Your Friends. If you look at the history of programming languages, a lot of the best ones were languages designed for their own authors to use, and a lot of the worst ones were designed for other people to use. When languages are designed for other people, it's always a specific group of other people: people not as smart as the language designer. So you get a language that talks down to you. Cobol is the most extreme case, but a lot of languages are pervaded by this spirit. It has nothing to do with how abstract the language is. C is pretty low-level, but it was designed for its authors to use, and that's why hackers like it. The argument for designing languages for bad programmers is that there are more bad programmers than good programmers. That may be so. But those few good programmers write a disproportionately large percentage of the software. I'm interested in the question, how do you design a language that the very best hackers will like? I happen to think this is identical to the question, how do you design a good programming language?, but even if it isn't, it is at least an interesting question. 3\. Give the Programmer as Much Control as Possible. Many languages (especially the ones designed for other people) have the attitude of a governess: they try to prevent you from doing things that they think aren't good for you. I like the opposite approach: give the programmer as much control as you can. When I first learned Lisp, what I liked most about it was that it considered me an equal partner. In the other languages I had learned up till then, there was the language and there was my program, written in the language, and the two were very separate. But in Lisp the functions and macros I wrote were just like those that made up the language itself. I could rewrite the language if I wanted. It had the same appeal as open-source software. 4\.
当我说语言必须针对人类弱点设计时,并非指要为糟糕的程序员设计。事实上我认为应该为最优秀的程序员设计,但即使最优秀的程序员也有局限。没人会愿意用所有变量都是带整数下标的字母x的语言编程。
2. 为自己和朋友设计。
纵观编程语言的历史,许多最优秀的语言都是设计者为自己使用而创造的,而许多最糟糕的语言则是为他人设计的。
为他人设计的语言总是面向特定群体:那些不如语言设计者聪明的人。因此你会得到一种居高临下的语言。COBOL是最极端的例子,但许多语言都弥漫着这种气息。
这与语言的抽象程度无关。C语言相当底层,但它是设计者为自己所用而创造的,这正是黑客们喜爱它的原因。
为糟糕程序员设计语言的理由是:糟糕程序员比优秀程序员多得多。这或许没错。但那少数优秀程序员编写的代码占比却大得不成比例。
Aim for Brevity. Brevity is underestimated and even scorned. But if you look into the hearts of hackers, you'll see that they really love it. How many times have you heard hackers speak fondly of how in, say, APL, they could do amazing things with just a couple lines of code? I think anything that really smart people really love is worth paying attention to. I think almost anything you can do to make programs shorter is good. There should be lots of library functions; anything that can be implicit should be; the syntax should be terse to a fault; even the names of things should be short. And it's not only programs that should be short. The manual should be thin as well. A good part of manuals is taken up with clarifications and reservations and warnings and special cases. If you force yourself to shorten the manual, in the best case you do it by fixing the things in the language that required so much explanation. 5\. Admit What Hacking Is. A lot of people wish that hacking was mathematics, or at least something like a natural science. I think hacking is more like architecture. Architecture is related to physics, in the sense that architects have to design buildings that don't fall down, but the actual goal of architects is to make great buildings, not to make discoveries about statics. What hackers like to do is make great programs. And I think, at least in our own minds, we have to remember that it's an admirable thing to write great programs, even when this work doesn't translate easily into the conventional intellectual currency of research papers. Intellectually, it is just as worthwhile to design a language programmers will love as it is to design a horrible one that embodies some idea you can publish a paper about. 1\. How to Organize Big Libraries? Libraries are becoming an increasingly important component of programming languages. They're also getting bigger, and this can be dangerous.
我感兴趣的问题是:如何设计出顶尖黑客会喜爱的语言?我认为这等同于"如何设计优秀的编程语言",但即便两者不同,这至少是个有趣的问题。
3. 给予程序员最大限度的控制权。
许多语言(尤其是为他人设计的语言)带着保姆心态:它们试图阻止你做一些它们认为对你不利的事情。我推崇相反的方法:尽可能给予程序员更多控制权。
当我初次学习Lisp时,最吸引我的是它把我视为平等的伙伴。在我之前学过的其他语言中,语言本身和用该语言编写的程序是截然分离的。但在Lisp中,我编写的函数和宏与构成语言本身的那些完全平等。我可以按需重写语言。这种吸引力与开源软件如出一辙。
4. 追求简洁。
简洁被低估甚至轻视。但若你洞察黑客的内心,会发现他们真心热爱简洁。你多少次听黑客满怀深情地谈起,比如在APL中,他们用短短几行代码就能实现惊人的功能?我认为真正聪明人真正热爱的事物都值得关注。
If it takes longer to find the library function that will do what you want than it would take to write it yourself, then all that code is doing nothing but make your manual thick. (The Symbolics manuals were a case in point.) So I think we will have to work on ways to organize libraries. The ideal would be to design them so that the programmer could guess what library call would do the right thing. 2\. Are People Really Scared of Prefix Syntax? This is an open problem in the sense that I have wondered about it for years and still don't know the answer. Prefix syntax seems perfectly natural to me, except possibly for math. But it could be that a lot of Lisp's unpopularity is simply due to having an unfamiliar syntax. Whether to do anything about it, if it is true, is another question..
几乎所有能让程序更短小的改进都是好的。应该提供大量库函数;所有能隐式表达的就应该隐式表达;语法应该简洁到极致;甚至连命名都应该简短。
不仅程序要简短,手册也应该薄如蝉翼。手册中很大篇幅被用于解释、限制、警告和特殊情况。如果强迫自己精简手册,最理想的情况是通过修复语言中那些需要大量解释的部分来实现。
5. 承认编程的本质。
许多人希望编程是数学,或者至少像自然科学。我认为编程更像建筑学。建筑学与物理学相关,因为建筑师必须设计不会倒塌的建筑,但建筑师的真正目标是创造伟大的建筑,而非发现静力学规律。
黑客热爱的是创造伟大程序。我认为,至少在我们心中,必须记住编写伟大程序是值得钦佩的事,即使这项工作无法轻易转化为研究论文这种传统的学术成果。从智力层面看,设计程序员喜爱的语言与设计体现某个可发表论文概念的糟糕语言同样有价值。
1. 如何组织大型库?
3\. What Do You Need for Server-Based Software?
库正成为编程语言日益重要的组成部分。它们也变得越来越庞大,这可能是危险的。如果寻找能实现需求的库函数比自己编写耗时更长,那么这些代码除了让手册变厚外毫无意义。(Symbolics手册就是例证。)因此我们必须研究库的组织方式。理想情况是设计出能让程序员凭直觉猜到正确库调用的库。
2. 人们真的害怕前缀语法吗?
这是个开放性问题,我思考多年仍无答案。除了数学表达式,前缀语法对我来说非常自然。但Lisp不受欢迎可能仅仅因为语法陌生。如果确实如此,是否要为此做出改变则是另一个问题。
3. 基于服务器的软件需要什么?
我认为未来二十年最令人兴奋的新应用程序大多将是基于网络的应用,即那些驻留在服务器上、通过网页浏览器与用户交互的程序。而编写这类程序,我们可能需要一些新的工具。
首先,我们需要支持基于服务器的应用程序发布新方式。与桌面软件每年发布一两个大版本不同,服务器应用以一系列小变更的形式持续发布,每天可能有多达五到十次更新。通常所有用户都会始终使用最新版本。
I think a lot of the most exciting new applications that get written in the next twenty years will be Web-based applications, meaning programs that sit on the server and talk to you through a Web browser. And to write these kinds of programs we may need some new things. One thing we'll need is support for the new way that server-based apps get released. Instead of having one or two big releases a year, like desktop software, server-based apps get released as a series of small changes. You may have as many as five or ten releases a day. And as a rule everyone will always use the latest version. You know how you can design programs to be debuggable? Well, server-based software likewise has to be designed to be changeable. You have to be able to change it easily, or at least to know what is a small change and what is a momentous one. Another thing that might turn out to be useful for server based software, surprisingly, is continuations. In Web-based software you can use something like continuation-passing style to get the effect of subroutines in the inherently stateless world of a Web session. Maybe it would be worthwhile having actual continuations, if it was not too expensive. 4\. What New Abstractions Are Left to Discover? I'm not sure how reasonable a hope this is, but one thing I would really love to do, personally, is discover a new abstraction-- something that would make as much of a difference as having first class functions or recursion or even keyword parameters. This may be an impossible dream. These things don't get discovered that often. But I am always looking. 1\. You Can Use Whatever Language You Want. Writing application programs used to mean writing desktop software. And in desktop software there is a big bias toward writing the application in the same language as the operating system. And so ten years ago, writing software pretty much meant writing software in C.
正如程序需要设计为可调试的,服务器软件同样需要设计为可变更的——你必须能轻松修改它,或至少能判断哪些改动是轻微的,哪些是重大的。
另一个出人意料但对服务器软件可能有用的概念是"续体"(continuations)。在无状态的网络会话中,你可以采用类似"续体传递风格"的技术来实现子程序的效果。如果成本可控,真正的续体机制或许值得引入。
4. 还有哪些新抽象等待发现?
这或许有些理想化,但我个人非常渴望能发现一种新的抽象机制——其重要性堪比一等函数、递归甚至关键字参数。虽然这类突破并不常见,但我始终在探寻。
1. 语言选择自由
过去编写应用就意味着开发桌面软件,而桌面软件存在强烈倾向:必须使用与操作系统相同的语言开发。因此十年前,软件开发几乎等同于用C语言编程。久而久之形成了一种传统:应用软件不得使用非常规语言,这种观念甚至渗透到管理者和风投等非技术群体中。
服务器软件彻底颠覆了这一模式。你可以自由选择任何编程语言,尽管目前大多数人(尤其是管理者和风投)尚未意识到这一点。少数黑客明白这个道理,这正是我们还能听到Perl、Python等新兴语言的原因——它们并非因开发Windows应用而闻名。
Eventually a tradition evolved: application programs must not be written in unusual languages. And this tradition had so long to develop that nontechnical people like managers and venture capitalists also learned it. Server-based software blows away this whole model. With server-based software you can use any language you want. Almost nobody understands this yet (especially not managers and venture capitalists). A few hackers understand it, and that's why we even hear about new, indy languages like Perl and Python. We're not hearing about Perl and Python because people are using them to write Windows apps. What this means for us, as people interested in designing programming languages, is that there is now potentially an actual audience for our work. 2\. Speed Comes from Profilers. Language designers, or at least language implementors, like to write compilers that generate fast code. But I don't think this is what makes languages fast for users. Knuth pointed out long ago that speed only matters in a few critical bottlenecks. And anyone who's tried it knows that you can't guess where these bottlenecks are. Profilers are the answer. Language designers are solving the wrong problem. Users don't need benchmarks to run fast. What they need is a language that can show them what parts of their own programs need to be rewritten. That's where speed comes from in practice. So maybe it would be a net win if language implementors took half the time they would have spent doing compiler optimizations and spent it writing a good profiler instead. 3\. You Need an Application to Drive the Design of a Language. This may not be an absolute rule, but it seems like the best languages all evolved together with some application they were being used to write. C was written by people who needed it for systems programming.
这对语言设计者意味着:我们的工作终于可能迎来真正的受众。
2. 性能优化源于分析器
语言设计者(至少实现者)热衷于编写能生成高效代码的编译器。但真正提升用户体验的速度并非来源于此。Knuth早已指出:性能瓶颈往往只存在于少数关键路径,而这些路径无法凭空猜测。分析器才是答案所在。
语言设计者正在解决错误的问题。用户不需要基准测试跑得多快,他们需要的是能精准定位程序瓶颈的语言工具。这才是实践中性能提升的来源。如果将编译器优化的时间抽出一半用于开发优秀的分析器,或许会带来更显著的整体收益。
3. 语言设计需要应用场景驱动
这或许不是铁律,但最优秀的语言往往伴随着特定应用场景共同演化:C语言诞生于系统编程需求,Lisp的部分发展动力来自符号微分计算——McCarthy在1960年首篇Lisp论文中就迫不及待地开始编写微分程序。
Lisp was developed partly to do symbolic differentiation, and McCarthy was so eager to get started that he was writing differentiation programs even in the first paper on Lisp, in 1960. It's especially good if your application solves some new problem. That will tend to drive your language to have new features that programmers need. I personally am interested in writing a language that will be good for writing server-based applications. [During the panel, Guy Steele also made this point, with the additional suggestion that the application should not consist of writing the compiler for your language, unless your language happens to be intended for writing compilers.] 4\. A Language Has to Be Good for Writing Throwaway Programs. You know what a throwaway program is: something you write quickly for some limited task. I think if you looked around you'd find that a lot of big, serious programs started as throwaway programs. I would not be surprised if _most_ programs started as throwaway programs. And so if you want to make a language that's good for writing software in general, it has to be good for writing throwaway programs, because that is the larval stage of most software. 5\. Syntax Is Connected to Semantics. It's traditional to think of syntax and semantics as being completely separate. This will sound shocking, but it may be that they aren't. I think that what you want in your language may be related to how you express it. I was talking recently to Robert Morris, and he pointed out that operator overloading is a bigger win in languages with infix syntax. In a language with prefix syntax, any function you define is effectively an operator. If you want to define a plus for a new type of number you've made up, you can just define a new function to add them.
如果应用场景涉及解决新问题则更为理想,这会推动语言产生程序员真正需要的新特性。我个人感兴趣的是打造适合服务器应用开发的语言。
[讨论环节中Guy Steele也强调这一点,并补充建议:除非专门用于编译器开发,否则语言的应用场景不应局限于编写自身的编译器。]
4. 语言必须擅长编写临时程序
临时程序指为特定任务快速编写的简易程序。仔细观察会发现,许多严肃的大型程序最初都是临时程序。甚至可能大多数软件都始于临时程序阶段。因此要打造通用编程语言,必须首先擅长编写临时程序——这是多数软件的雏形阶段。
5. 语法与语义的关联
传统观念认为语法与语义完全分离。但令人惊讶的是,它们可能存在深层联系。Robert Morris曾指出:在中缀语法语言中,操作符重载的价值更为显著。在前缀语法语言中,任何自定义函数本质上都是操作符;而在中缀语言中,重载操作符与函数调用的视觉差异极大。
If you do that in a language with infix syntax, there's a big difference in appearance between the use of an overloaded operator and a function call. 1\. New Programming Languages. Back in the 1970s it was fashionable to design new programming languages. Recently it hasn't been. But I think server-based software will make new languages fashionable again. With server-based software, you can use any language you want, so if someone does design a language that actually seems better than others that are available, there will be people who take a risk and use it. 2\. Time-Sharing. Richard Kelsey gave this as an idea whose time has come again in the last panel, and I completely agree with him. My guess (and Microsoft's guess, it seems) is that much computing will move from the desktop onto remote servers. In other words, time-sharing is back. And I think there will need to be support for it at the language level. For example, I know that Richard and Jonathan Rees have done a lot of work implementing process scheduling within Scheme 48. 3\. Efficiency. Recently it was starting to seem that computers were finally fast enough. More and more we were starting to hear about byte code, which implies to me at least that we feel we have cycles to spare. But I don't think we will, with server-based software. Someone is going to have to pay for the servers that the software runs on, and the number of users they can support per machine will be the divisor of their capital cost. So I think efficiency will matter, at least in computational bottlenecks. It will be especially important to do i/o fast, because server-based applications do a lot of i/o. It may turn out that byte code is not a win, in the end. Sun and Microsoft seem to be facing off in a kind of a battle of the byte codes at the moment.
1. 新编程语言的复兴
1970年代曾掀起设计新语言的浪潮,近期虽式微,但服务器软件将重启这一趋势。当语言选择不再受限时,只要出现真正优秀的语言设计,就有人愿意冒险尝试。
2. 分时系统的回归
Richard Kelsey在上次讨论中提出分时理念将复兴,我完全赞同。与微软的判断类似,大量计算将从桌面转移到远程服务器——分时模式正在回归。这需要语言层面的支持,例如Richard和Jonathan Rees已在Scheme 48中实现了大量进程调度工作。
3. 效率重现重要性
当人们开始讨论字节码(暗示计算资源过剩)时,似乎计算机性能已足够强大。但服务器软件将改变这一认知:硬件成本需要真实支付,单机承载用户数直接决定资本回报率。
But they're doing it because byte code is a convenient place to insert themselves into the process, not because byte code is in itself a good idea. It may turn out that this whole battleground gets bypassed. That would be kind of amusing. 1\. Clients. This is just a guess, but my guess is that the winning model for most applications will be purely server-based. Designing software that works on the assumption that everyone will have your client is like designing a society on the assumption that everyone will just be honest. It would certainly be convenient, but you have to assume it will never happen. I think there will be a proliferation of devices that have some kind of Web access, and all you'll be able to assume about them is that they can support simple html and forms. Will you have a browser on your cell phone? Will there be a phone in your palm pilot? Will your blackberry get a bigger screen? Will you be able to browse the Web on your gameboy? Your watch? I don't know. And I don't have to know if I bet on everything just being on the server. It's just so much more robust to have all the brains on the server. 2\. Object-Oriented Programming. I realize this is a controversial one, but I don't think object-oriented programming is such a big deal. I think it is a fine model for certain kinds of applications that need that specific kind of data structure, like window systems, simulations, and cad programs. But I don't see why it ought to be the model for all programming. I think part of the reason people in big companies like object-oriented programming is because it yields a lot of what looks like work. Something that might naturally be represented as, say, a list of integers, can now be represented as a class with all kinds of scaffolding and hustle and bustle. Another attraction of object-oriented programming is that methods give you some of the effect of first class functions.
因此效率再次成为关键,尤其在I/O性能方面——这正是服务器应用的核心瓶颈。当前Sun与微软的"字节码之战"更多是商业策略,字节码本身未必是最优解。若这个战场最终被绕过,倒不失为趣事。
1. 客户端终将式微
我的预测是:绝大多数应用将采用纯服务器架构。假设所有用户都安装特定客户端,就如同假设全社会绝对诚实——虽然便利,但绝不可行。
未来将涌现各种具备基础网络功能的设备,但唯一可确定的共性就是支持简单HTML和表单。手机浏览器?PDA通话功能?黑莓大屏?游戏手表?与其猜测设备形态,不如将所有智能集中于服务器——这才是稳健之选。
2. 面向对象编程的反思
尽管存在争议,但我认为面向对象编程被过度神话。它对窗口系统、仿真、CAD等需要特定数据结构的应用是优秀模型,但不该成为编程的普适范式。
But this is old news to Lisp programmers. When you have actual first class functions, you can just use them in whatever way is appropriate to the task at hand, instead of forcing everything into a mold of classes and methods. What this means for language design, I think, is that you shouldn't build object-oriented programming in too deeply. Maybe the answer is to offer more general, underlying stuff, and let people design whatever object systems they want as libraries. 3\. Design by Committee. Having your language designed by a committee is a big pitfall, and not just for the reasons everyone knows about. Everyone knows that committees tend to yield lumpy, inconsistent designs. But I think a greater danger is that they won't take risks. When one person is in charge he can take risks that a committee would never agree on. Is it necessary to take risks to design a good language though? Many people might suspect that language design is something where you should stick fairly close to the conventional wisdom. I bet this isn't true. In everything else people do, reward is proportionate to risk. Why should language design be any different?
大公司青睐面向对象的部分原因在于它制造了大量"看似专业"的代码——本该用整数列表简单表达的概念,被包装成充满样板代码的类结构。
面向对象的方法虽能模拟一等函数的部分功能,但对Lisp程序员而言这早已过时。拥有真正的一等函数时,你可以根据任务灵活运用,而非强迫所有逻辑适配类与方法的框架。
这对语言设计的启示是:不应深度绑定面向对象范式。或许更好的方案是提供更通用的底层机制,让人们通过库来实现各类对象系统。
3. 委员会设计的陷阱
委员会设计语言不仅是众所周知会导致臃肿和不一致,更深层的危机在于规避风险。个人主导时敢于尝试的创新,在委员会决策中永远无法通过。
但语言设计是否需要冒险?许多人认为应当遵循传统智慧。然而所有创造性活动的回报都与风险成正比,语言设计何尝例外?
[](https://s.turbifycdn.com/aah/paulgraham/the-roots-of-lisp-13.gif) May 2001 _(I wrote this article to help myself understand exactly what McCarthy discovered. You don't need to know this stuff to program in Lisp, but it should be helpful to anyone who wants to understand the essence of Lisp � both in the sense of its origins and its semantic core. The fact that it has such a core is one of Lisp's distinguishing features, and the reason why, unlike other languages, Lisp has dialects.)_ In 1960, John McCarthy published a remarkable paper in which he did for programming something like what Euclid did for geometry. He showed how, given a handful of simple operators and a notation for functions, you can build a whole programming language. He called this language Lisp, for "List Processing," because one of his key ideas was to use a simple data structure called a _list_ for both code and data. It's worth understanding what McCarthy discovered, not just as a landmark in the history of computers, but as a model for what programming is tending to become in our own time. It seems to me that there have been two really clean, consistent models of programming so far: the C model and the Lisp model. These two seem points of high ground, with swampy lowlands between them. As computers have grown more powerful, the new languages being developed have been moving steadily toward the Lisp model. A popular recipe for new programming languages in the past 20 years has been to take the C model of computing and add to it, piecemeal, parts taken from the Lisp model, like runtime typing and garbage collection. In this article I'm going to try to explain in the simplest possible terms what McCarthy discovered. The point is not just to learn about an interesting theoretical result someone figured out forty years ago, but to show where languages are heading.
[](https://s.turbifycdn.com/aah/paulgraham/the-roots-of-lisp-13.gif)
(我写这篇文章是为了帮助自己真正理解麦卡锡的发现。虽然用Lisp编程无需了解这些内容,但对于任何想理解Lisp本质的人——无论是其起源还是语义核心——这都大有裨益。拥有这样的核心正是Lisp的鲜明特征,也是它与其他语言不同且存在多种方言的原因。)
1960年,约翰·麦卡锡发表了一篇非凡的论文,他在编程领域的贡献堪比欧几里得之于几何学。他展示了如何用几个简单的操作符和函数表示法,构建出完整的编程语言。他将这种语言命名为Lisp(“列表处理”),其核心思想之一是使用名为_列表_的简单数据结构来同时表示代码和数据。
理解麦卡锡的发现意义重大,这不仅是计算机史上的里程碑,更为当今编程的发展方向提供了范本。在我看来,迄今为止只有两种真正清晰、一致的编程模型:C模型和Lisp模型。它们如同高地,之间则是沼泽般的洼地。随着计算机性能的提升,新开发的语言正稳步向Lisp模型靠拢。过去20年流行的一种新语言设计方法,就是在C计算模型的基础上逐步加入Lisp模型的特性,如运行时类型和垃圾回收。
本文我将用最简明的语言阐释麦卡锡的发现。目的不仅是了解四十年前某人提出的有趣理论成果,更是为了揭示语言的演进方向。Lisp的独特之处——事实上是其定义性特质——在于它能用自身来编写。为了理解麦卡锡这句话的含义,我们将重走他的探索之路,并将其数学符号转化为可运行的Common Lisp代码。
The unusual thing about Lisp � in fact, the defining quality of Lisp � is that it can be written in itself. To understand what McCarthy meant by this, we're going to retrace his steps, with his mathematical notation translated into running Common Lisp code.
Complete Article (Postscript) What Made Lisp Different The Code Chinese Translation Japanese Translation Portuguese Translation Korean Translation.
Want to start a startup? Get funded by Y Combinator.
April 2001, rev. April 2003 _(This article is derived from a talk given at the 2001 Franz Developer Symposium.)_ In the summer of 1995, my friend Robert Morris and I started a startup called Viaweb. Our plan was to write software that would let end users build online stores. What was novel about this software, at the time, was that it ran on our server, using ordinary Web pages as the interface. A lot of people could have been having this idea at the same time, of course, but as far as I know, Viaweb was the first Web-based application. It seemed such a novel idea to us that we named the company after it: Viaweb, because our software worked via the Web, instead of running on your desktop computer. Another unusual thing about this software was that it was written primarily in a programming language called Lisp. It was one of the first big end-user applications to be written in Lisp, which up till then had been used mostly in universities and research labs. [1] The Secret Weapon Eric Raymond has written an essay called "How to Become a Hacker," and in it, among other things, he tells would-be hackers what languages they should learn. He suggests starting with Python and Java, because they are easy to learn. The serious hacker will also want to learn C, in order to hack Unix, and Perl for system administration and cgi scripts. Finally, the truly serious hacker should consider learning Lisp:
想创业吗? 获得 Y Combinator 的资助。
2001年4月,2003年4月修订
(本文改编自2001年Franz开发者研讨会上的演讲。)
1995年夏天,我和朋友罗伯特·莫里斯创办了一家名为 Viaweb 的初创公司。我们的计划是开发一款软件,让终端用户能够搭建在线商店。这款软件在当时的新颖之处在于,它运行在我们的服务器上,并以普通网页作为交互界面。
> Lisp is worth learning for the profound enlightenment experience you will have when you finally get it; that experience will make you a better programmer for the rest of your days, even if you never actually use Lisp itself a lot.
当然,可能有许多人同时想到了这个主意,但据我所知,Viaweb是第一个基于网页的应用程序。这个想法对我们来说如此新奇,以至于我们直接用其命名公司:Viaweb,因为我们的软件通过网页运行,而非在你的桌面电脑上。
这款软件的另一个特别之处是,它主要用一种名为Lisp的编程语言编写。它是首批用Lisp开发的大型终端用户应用之一,而此前Lisp主要应用于大学和研究实验室。[1]
埃里克·雷蒙德写过一篇名为《如何成为黑客》的文章,其中他告诉 aspiring hackers 应该学习哪些语言。他建议从Python和Java开始,因为它们易于学习。认真的黑客还会想学C,以便捣鼓Unix,以及Perl用于系统管理和CGI脚本。最后,真正严肃的黑客应该考虑学习Lisp:
> 学习Lisp是值得的,因为它能带来深刻的启蒙体验——当你最终领悟时,这种体验会让你在余下的编程生涯中成为更好的程序员,即使你实际上并不常用Lisp本身。
This is the same argument you tend to hear for learning Latin. It won't get you a job, except perhaps as a classics professor, but it will improve your mind, and make you a better writer in languages you do want to use, like English. But wait a minute. This metaphor doesn't stretch that far. The reason Latin won't get you a job is that no one speaks it. If you write in Latin, no one can understand you. But Lisp is a computer language, and computers speak whatever language you, the programmer, tell them to. So if Lisp makes you a better programmer, like he says, why wouldn't you want to use it? If a painter were offered a brush that would make him a better painter, it seems to me that he would want to use it in all his paintings, wouldn't he? I'm not trying to make fun of Eric Raymond here. On the whole, his advice is good. What he says about Lisp is pretty much the conventional wisdom. But there is a contradiction in the conventional wisdom: Lisp will make you a better programmer, and yet you won't use it. Why not? Programming languages are just tools, after all. If Lisp really does yield better programs, you should use it. And if it doesn't, then who needs it? This is not just a theoretical question. Software is a very competitive business, prone to natural monopolies. A company that gets software written faster and better will, all other things being equal, put its competitors out of business. And when you're starting a startup, you feel this very keenly. Startups tend to be an all or nothing proposition. You either get rich, or you get nothing. In a startup, if you bet on the wrong technology, your competitors will crush you. Robert and I both knew Lisp well, and we couldn't see any reason not to trust our instincts and go with Lisp. We knew that everyone else was writing their software in C++ or Perl. But we also knew that that didn't mean anything. If you chose technology that way, you'd be running Windows.
这是你常听到的支持学习拉丁语的论调。它不会帮你找到工作——或许除了古典学教授之外,但它能提升你的思维,让你在用真正想用的语言(比如英语)写作时更出色。
但等等。这个类比并不完全成立。拉丁语找不到工作的原因是没人使用它。如果你用拉丁语写作,没人能看懂。但Lisp是计算机语言,而计算机能理解任何程序员让它们理解的语言。
那么,如果Lisp真如他所说能让你成为更好的程序员,为什么不用它呢?假如一位画家得到一支能让他画得更好的画笔,我想他会愿意在所有作品中使用它,不是吗?我并非在此取笑埃里克·雷蒙德。总体而言,他的建议是好的。他关于Lisp的观点也符合主流认知。但主流认知中存在一个矛盾:Lisp能让你成为更好的程序员,但你却不会使用它。
为什么不?编程语言终究只是工具。如果Lisp真能产出更好的程序,你就该用它。如果不能,那谁需要它呢?
When you choose technology, you have to ignore what other people are doing, and consider only what will work the best. This is especially true in a startup. In a big company, you can do what all the other big companies are doing. But a startup can't do what all the other startups do. I don't think a lot of people realize this, even in startups. The average big company grows at about ten percent a year. So if you're running a big company and you do everything the way the average big company does it, you can expect to do as well as the average big company-- that is, to grow about ten percent a year. The same thing will happen if you're running a startup, of course. If you do everything the way the average startup does it, you should expect average performance. The problem here is, average performance means that you'll go out of business. The survival rate for startups is way less than fifty percent. So if you're running a startup, you had better be doing something odd. If not, you're in trouble. Back in 1995, we knew something that I don't think our competitors understood, and few understand even now: when you're writing software that only has to run on your own servers, you can use any language you want. When you're writing desktop software, there's a strong bias toward writing applications in the same language as the operating system. Ten years ago, writing applications meant writing applications in C. But with Web-based software, especially when you have the source code of both the language and the operating system, you can use whatever language you want. This new freedom is a double-edged sword, however. Now that you can use any language, you have to think about which one to use. Companies that try to pretend nothing has changed risk finding that their competitors do not. If you can use any language, which do you use? We chose Lisp. For one thing, it was obvious that rapid development would be important in this market.
这不只是理论问题。软件行业竞争激烈,天然趋向垄断。在其他条件相同的情况下,一家能更快、更好地编写软件的公司会让竞争对手倒闭。创业时,你会强烈感受到这一点。创业往往是非成即败的命题。要么大获成功,要么一无所有。在创业中,若押错技术,竞争对手就会碾压你。
罗伯特和我都精通Lisp,我们找不到理由不相信直觉而选择Lisp。我们知道其他公司都在用C++或Perl写软件。但我们更明白这毫无意义。如果以此标准选择技术,你现在用的会是Windows。选择技术时,必须忽略他人做法,只考虑什么最有效。
这对创业公司尤为关键。大公司可以效仿其他大公司,但创业公司不能照搬其他创业公司的做法。我认为即使身处创业公司,很多人也意识不到这点。
普通大公司年增长率约10%。因此若以行业平均水平运营大公司,你也能获得平均增长。但若以创业公司的平均水平经营,等待你的将是倒闭——创业公司存活率远低于50%。所以创业时必须另辟蹊径,否则危矣。
We were all starting from scratch, so a company that could get new features done before its competitors would have a big advantage. We knew Lisp was a really good language for writing software quickly, and server-based applications magnify the effect of rapid development, because you can release software the minute it's done. If other companies didn't want to use Lisp, so much the better. It might give us a technological edge, and we needed all the help we could get. When we started Viaweb, we had no experience in business. We didn't know anything about marketing, or hiring people, or raising money, or getting customers. Neither of us had ever even had what you would call a real job. The only thing we were good at was writing software. We hoped that would save us. Any advantage we could get in the software department, we would take. So you could say that using Lisp was an experiment. Our hypothesis was that if we wrote our software in Lisp, we'd be able to get features done faster than our competitors, and also to do things in our software that they couldn't do. And because Lisp was so high-level, we wouldn't need a big development team, so our costs would be lower. If this were so, we could offer a better product for less money, and still make a profit. We would end up getting all the users, and our competitors would get none, and eventually go out of business. That was what we hoped would happen, anyway. What were the results of this experiment? Somewhat surprisingly, it worked. We eventually had many competitors, on the order of twenty to thirty of them, but none of their software could compete with ours. We had a wysiwyg online store builder that ran on the server and yet felt like a desktop application. Our competitors had cgi scripts. And we were always far ahead of them in features. Sometimes, in desperation, competitors would try to introduce features that we didn't have.
1995年,我们掌握了一个多数竞争对手至今仍未理解的道理:当软件只需运行在自己的服务器上时,你可以使用任何语言。开发桌面软件时,人们倾向于使用与操作系统相同的语言。十年前,这意味着用C语言。但基于Web的软件——尤其是当你拥有语言和操作系统的源代码时——语言选择完全自由。
然而这种自由是双刃剑。既然能用任何语言,就必须思考如何选择。那些假装一切如常的公司,终将发现竞争对手并不如此。
该选哪种语言?我们选择了Lisp。首先,这个市场显然需要快速开发。所有人从零开始,能比对手更快推出新功能的公司将占据巨大优势。我们知道Lisp能极速开发软件,而服务器端应用会放大这一优势——因为你能在代码写完的瞬间部署。
其他公司不愿用Lisp?这再好不过。这可能带来技术优势,而我们亟需所有能获得的帮助。创立Viaweb时,我们毫无商业经验,不懂营销、招聘、融资或获客,甚至从未有过正经工作。我们唯一擅长的就是写软件。软件领域的任何优势,我们都将争取。
But with Lisp our development cycle was so fast that we could sometimes duplicate a new feature within a day or two of a competitor announcing it in a press release. By the time journalists covering the press release got round to calling us, we would have the new feature too. It must have seemed to our competitors that we had some kind of secret weapon-- that we were decoding their Enigma traffic or something. In fact we did have a secret weapon, but it was simpler than they realized. No one was leaking news of their features to us. We were just able to develop software faster than anyone thought possible. When I was about nine I happened to get hold of a copy of _The Day of the Jackal,_ by Frederick Forsyth. The main character is an assassin who is hired to kill the president of France. The assassin has to get past the police to get up to an apartment that overlooks the president's route. He walks right by them, dressed up as an old man on crutches, and they never suspect him. Our secret weapon was similar. We wrote our software in a weird AI language, with a bizarre syntax full of parentheses. For years it had annoyed me to hear Lisp described that way. But now it worked to our advantage. In business, there is nothing more valuable than a technical advantage your competitors don't understand. In business, as in war, surprise is worth as much as force. And so, I'm a little embarrassed to say, I never said anything publicly about Lisp while we were working on Viaweb. We never mentioned it to the press, and if you searched for Lisp on our Web site, all you'd find were the titles of two books in my bio. This was no accident. A startup should give its competitors as little information as possible. If they didn't know what language our software was written in, or didn't care, I wanted to keep it that way.[2] The people who understood our technology best were the customers.
可以说使用Lisp是一次实验。我们的假设是:用Lisp能比对手更快实现功能,并做出他们无法实现的东西;由于Lisp的高效抽象,我们不需要庞大团队,成本更低。若能如此,我们就能以更低价格提供更优产品,仍能盈利,最终占领全部市场。至少这是我们期待的结果。
实验结果如何?出乎意料地成功。我们最终有二三十个竞争对手,但他们的软件都无法与我们抗衡。我们拥有服务端运行的所见即所得在线商店构建器,体验却如桌面应用;对手们还在用CGI脚本。功能上我们始终遥遥领先。有时对手会绝望地试图推出我们不具备的功能。但借助Lisp的快速开发周期,我们常在对手发新闻稿后一两天内复刻该功能。等报道该新闻的记者联系我们时,新功能已上线。
对手们一定以为我们拥有某种秘密武器——就像破译了他们的恩尼格玛密码。事实上我们确实有秘密武器,只是比他们想象的简单:没人向我们泄露他们的开发计划,我们只是能以超乎想象的速度开发软件。
九岁时我偶然读到弗雷德里克·福赛斯的《豺狼的日子》。主角是被雇来刺杀法国总统的杀手。为了进入能俯瞰总统路线的公寓,他必须通过警察的封锁。最终他拄着拐杖扮成老人,堂而皇之地从警察面前走过。
They didn't care what language Viaweb was written in either, but they noticed that it worked really well. It let them build great looking online stores literally in minutes. And so, by word of mouth mostly, we got more and more users. By the end of 1996 we had about 70 stores online. At the end of 1997 we had 500. Six months later, when Yahoo bought us, we had 1070 users. Today, as Yahoo Store, this software continues to dominate its market. It's one of the more profitable pieces of Yahoo, and the stores built with it are the foundation of Yahoo Shopping. I left Yahoo in 1999, so I don't know exactly how many users they have now, but the last I heard there were about 20,000. The Blub Paradox What's so great about Lisp? And if Lisp is so great, why doesn't everyone use it? These sound like rhetorical questions, but actually they have straightforward answers. Lisp is so great not because of some magic quality visible only to devotees, but because it is simply the most powerful language available. And the reason everyone doesn't use it is that programming languages are not merely technologies, but habits of mind as well, and nothing changes slower. Of course, both these answers need explaining. I'll begin with a shockingly controversial statement: programming languages vary in power. Few would dispute, at least, that high level languages are more powerful than machine language. Most programmers today would agree that you do not, ordinarily, want to program in machine language. Instead, you should program in a high-level language, and have a compiler translate it into machine language for you. This idea is even built into the hardware now: since the 1980s, instruction sets have been designed for compilers rather than human programmers. Everyone knows it's a mistake to write your whole program by hand in machine language.
我们的秘密武器与此相似。用这门古怪的、满是括号的AI语言编程,多年来我听厌了人们对Lisp的这种描述。但现在它成了我们的优势。商战中,没有什么比竞争对手无法理解的技术优势更有价值。在商业与战争中,出其不意与实力同等重要。
因此我有点难为情地承认,Viaweb运营期间我从未公开谈论Lisp。我们对媒体只字不提,如果你在我们网站上搜索Lisp,只能在我简历中找到两本书名。这绝非偶然。创业公司应尽可能少地向对手透露信息。既然他们不知道或不关心我们使用的语言,我就要保持这种状态。
最懂我们技术的是客户。他们同样不关心Viaweb用什么语言编写,但他们注意到它效果卓越:能 literally 在几分钟内建好精美的在线商店。通过口碑传播,用户持续增长。1996年底我们拥有约70家在线商店,1997年底达500家。被雅虎收购前的半年,用户数增至1070家。如今作为"雅虎商店",它仍统治着市场,是雅虎最盈利的产品之一,其构建的商店构成了雅虎购物基础。1999年我离开雅虎,不知当前用户数,但最后听说约2万家。
Lisp强在哪?如果它如此强大,为何不是人人使用?这看似反问,实则确有答案。Lisp的强大并非因为只有信徒才能看见的魔力,而是因为它就是目前最强大的语言。而人们不用它的原因在于:编程语言不仅是技术,更是思维习惯——而后者变化最慢。当然,这两个答案都需要解释。
What's less often understood is that there is a more general principle here: that if you have a choice of several languages, it is, all other things being equal, a mistake to program in anything but the most powerful one. [3] There are many exceptions to this rule. If you're writing a program that has to work very closely with a program written in a certain language, it might be a good idea to write the new program in the same language. If you're writing a program that only has to do something very simple, like number crunching or bit manipulation, you may as well use a less abstract language, especially since it may be slightly faster. And if you're writing a short, throwaway program, you may be better off just using whatever language has the best library functions for the task. But in general, for application software, you want to be using the most powerful (reasonably efficient) language you can get, and using anything else is a mistake, of exactly the same kind, though possibly in a lesser degree, as programming in machine language. You can see that machine language is very low level. But, at least as a kind of social convention, high-level languages are often all treated as equivalent. They're not. Technically the term "high-level language" doesn't mean anything very definite. There's no dividing line with machine languages on one side and all the high-level languages on the other. Languages fall along a continuum [4] of abstractness, from the most powerful all the way down to machine languages, which themselves vary in power. Consider Cobol. Cobol is a high-level language, in the sense that it gets compiled into machine language. Would anyone seriously argue that Cobol is equivalent in power to, say, Python? It's probably closer to machine language than Python. Or how about Perl 4? Between Perl 4 and Perl 5, lexical closures got added to the language. Most Perl hackers would agree that Perl 5 is more powerful than Perl 4.
我先抛出一个极具争议的观点:编程语言有强弱之分。
至少很少人会反对高级语言比机器语言强大。如今多数程序员认同:通常不该用机器语言编程,而应使用高级语言,再通过编译器转为机器语言。这个理念现已融入硬件:自1980年代起,指令集就为编译器而非人类程序员设计。
众所周知,完全用机器语言手写程序是种错误。但更少人理解的是其中蕴含的普适原则:当有多种语言可选时,在其他条件相同的情况下,不使用最强大的语言就是错误。
当然存在例外。若需与某语言编写的程序紧密交互,用同种语言可能更合适;若程序只需处理简单任务(如数值计算或位操作),使用抽象程度较低的语言或许更优(尤其可能稍快);若是短期使用的临时程序,选择库函数最丰富的语言更明智。但总体而言,对于应用软件,使用你能获得的最强大(且效率合理)的语言才是正道——使用其他语言与使用机器语言的错误性质相同,只是程度较轻。
But once you've admitted that, you've admitted that one high level language can be more powerful than another. And it follows inexorably that, except in special cases, you ought to use the most powerful you can get. This idea is rarely followed to its conclusion, though. After a certain age, programmers rarely switch languages voluntarily. Whatever language people happen to be used to, they tend to consider just good enough. Programmers get very attached to their favorite languages, and I don't want to hurt anyone's feelings, so to explain this point I'm going to use a hypothetical language called Blub. Blub falls right in the middle of the abstractness continuum. It is not the most powerful language, but it is more powerful than Cobol or machine language. And in fact, our hypothetical Blub programmer wouldn't use either of them. Of course he wouldn't program in machine language. That's what compilers are for. And as for Cobol, he doesn't know how anyone can get anything done with it. It doesn't even have x (Blub feature of your choice). As long as our hypothetical Blub programmer is looking down the power continuum, he knows he's looking down. Languages less powerful than Blub are obviously less powerful, because they're missing some feature he's used to. But when our hypothetical Blub programmer looks in the other direction, up the power continuum, he doesn't realize he's looking up. What he sees are merely weird languages. He probably considers them about equivalent in power to Blub, but with all this other hairy stuff thrown in as well. Blub is good enough for him, because he thinks in Blub. When we switch to the point of view of a programmer using any of the languages higher up the power continuum, however, we find that he in turn looks down upon Blub. How can you get anything done in Blub? It doesn't even have y.
显然机器语言层次极低。但社会惯例中,高级语言常被视为等价。实则不然。严格来说"高级语言"并无明确定义。机器语言与高级语言之间不存在明确分界线。语言处于抽象程度的连续谱上,从最强大的一直到机器语言——后者本身也有强弱之分。
以COBOL为例。作为需编译为机器语言的语言,它算高级语言。但谁会认真主张COBOL与Python能力相当?它可能比Python更接近机器语言。
Perl 4又如何?Perl 5增加了词法闭包,多数Perl黑客会认同Perl 5更强大。但承认这点就等于承认高级语言之间存在强弱差异。由此必然推出:除非特殊情况,你应该使用能获得的最强大语言。
然而这个结论很少被贯彻。程序员到一定年龄后,很少主动切换语言。无论习惯何种语言,他们都会认为它"足够好"。
By induction, the only programmers in a position to see all the differences in power between the various languages are those who understand the most powerful one. (This is probably what Eric Raymond meant about Lisp making you a better programmer.) You can't trust the opinions of the others, because of the Blub paradox: they're satisfied with whatever language they happen to use, because it dictates the way they think about programs. I know this from my own experience, as a high school kid writing programs in Basic. That language didn't even support recursion. It's hard to imagine writing programs without using recursion, but I didn't miss it at the time. I thought in Basic. And I was a whiz at it. Master of all I surveyed. The five languages that Eric Raymond recommends to hackers fall at various points on the power continuum. Where they fall relative to one another is a sensitive topic. What I will say is that I think Lisp is at the top. And to support this claim I'll tell you about one of the things I find missing when I look at the other four languages. How can you get anything done in them, I think, without macros? [5] Many languages have something called a macro. But Lisp macros are unique. And believe it or not, what they do is related to the parentheses. The designers of Lisp didn't put all those parentheses in the language just to be different. To the Blub programmer, Lisp code looks weird. But those parentheses are there for a reason. They are the outward evidence of a fundamental difference between Lisp and other languages. Lisp code is made out of Lisp data objects. And not in the trivial sense that the source files contain characters, and strings are one of the data types supported by the language. Lisp code, after it's read by the parser, is made of data structures that you can traverse. If you understand how compilers work, what's really going on is not so much that Lisp has a strange syntax as that Lisp has no syntax.
程序员对偏爱语言的忠诚度很高。为避免伤害感情,我将用虚构的Blub语言来说明。Blub位于抽象谱系中段——不是最强大的,但比COBOL或机器语言强大。
事实上,这位虚构的Blub程序员不会使用后两者。他当然不用机器语言(那是编译器的职责),至于COBOL?他无法理解如何用它完成工作——它甚至没有x(任选一个Blub特性)。
当Blub程序员向下看能力谱系时,他知道自己在俯视。那些语言明显更弱,因为它们缺少他惯用的特性。但当他向上看时,却未意识到这是仰视。他只看到些怪异语言,可能认为它们与Blub能力相当,只是多了些花哨功能。Blub对他已足够好,因为他用Blub思考。
然而,当我们切换到能力谱系更高处程序员的视角,会发现他们同样俯视着Blub:没有y特性,怎么可能用它完成工作?
You write programs in the parse trees that get generated within the compiler when other languages are parsed. But these parse trees are fully accessible to your programs. You can write programs that manipulate them. In Lisp, these programs are called macros. They are programs that write programs. Programs that write programs? When would you ever want to do that? Not very often, if you think in Cobol. All the time, if you think in Lisp. It would be convenient here if I could give an example of a powerful macro, and say there! how about that? But if I did, it would just look like gibberish to someone who didn't know Lisp; there isn't room here to explain everything you'd need to know to understand what it meant. In Ansi Common Lisp I tried to move things along as fast as I could, and even so I didn't get to macros until page 160. But I think I can give a kind of argument that might be convincing. The source code of the Viaweb editor was probably about 20-25% macros. Macros are harder to write than ordinary Lisp functions, and it's considered to be bad style to use them when they're not necessary. So every macro in that code is there because it has to be. What that means is that at least 20-25% of the code in this program is doing things that you can't easily do in any other language. However skeptical the Blub programmer might be about my claims for the mysterious powers of Lisp, this ought to make him curious. We weren't writing this code for our own amusement. We were a tiny startup, programming as hard as we could in order to put technical barriers between us and our competitors. A suspicious person might begin to wonder if there was some correlation here. A big chunk of our code was doing things that are very hard to do in other languages. The resulting software did things our competitors' software couldn't do. Maybe there was some kind of connection. I encourage you to follow that thread.
通过归纳可知,唯有理解最强大语言的程序员,才能真正看清各语言间的能力差异。(这或许就是埃里克·雷蒙德所说"Lisp让你成为更好程序员"的含义。)其他人的意见不足采信,因为Blub悖论:他们满足于当前使用的语言,因其塑造了他们思考程序的方式。
我有切身体会。高中时我用BASIC写程序,这门语言甚至不支持递归。现在难以想象不用递归如何编程,但当时我毫无察觉——我用BASIC思考,且自认是行家,对一切了然于胸。
埃里克·雷蒙德推荐给黑客的五种语言位于能力谱系的不同位置。它们之间的相对高低是个敏感话题。我的观点是:Lisp居于顶端。为佐证这点,我要指出当我审视其他四种语言时发现的缺失:没有宏,如何高效工作?
许多语言都有称为"宏"的东西,但Lisp宏是独一无二的。信不信由你,它们的功能与那些括号有关。Lisp的设计者并非为了标新立异才加入括号。对Blub程序员而言,Lisp代码看起来古怪,但这些括号存在深层原因——它们是Lisp与其他语言根本差异的外在体现。
There may be more to that old man hobbling along on his crutches than meets the eye. Aikido for Startups But I don't expect to convince anyone (over 25) to go out and learn Lisp. The purpose of this article is not to change anyone's mind, but to reassure people already interested in using Lisp-- people who know that Lisp is a powerful language, but worry because it isn't widely used. In a competitive situation, that's an advantage. Lisp's power is multiplied by the fact that your competitors don't get it. If you think of using Lisp in a startup, you shouldn't worry that it isn't widely understood. You should hope that it stays that way. And it's likely to. It's the nature of programming languages to make most people satisfied with whatever they currently use. Computer hardware changes so much faster than personal habits that programming practice is usually ten to twenty years behind the processor. At places like MIT they were writing programs in high-level languages in the early 1960s, but many companies continued to write code in machine language well into the 1980s. I bet a lot of people continued to write machine language until the processor, like a bartender eager to close up and go home, finally kicked them out by switching to a risc instruction set. Ordinarily technology changes fast. But programming languages are different: programming languages are not just technology, but what programmers think in. They're half technology and half religion.[6] And so the median language, meaning whatever language the median programmer uses, moves as slow as an iceberg. Garbage collection, introduced by Lisp in about 1960, is now widely considered to be a good thing. Runtime typing, ditto, is growing in popularity. Lexical closures, introduced by Lisp in the early 1970s, are now, just barely, on the radar screen. Macros, introduced by Lisp in the mid 1960s, are still terra incognita.
Lisp代码由Lisp数据对象构成。这不是"源文件包含字符,字符串是语言支持的数据类型"这种浅层意义。经过解析器处理后,Lisp代码由可遍历的数据结构组成。
若理解编译器工作原理,你会发现与其说Lisp语法怪异,不如说它没有语法。你直接在解析树中编写程序——这些树在其他语言中只存在于编译器内部。但在Lisp中,这些解析树完全向程序开放,你可以编写操作它们的程序。这些程序就是宏:能生成程序的程序。
用程序写程序?什么时候需要这样做?用COBOL思考的人会觉得极少需要,用Lisp思考的人则时刻需要。如果能在此展示一个强大宏的示例并说"看吧!这还不说明问题吗?"会很有说服力。但对不懂Lisp的人这只会像天书——限于篇幅,我无法解释理解它所需的全部背景知识。在《ANSI Common Lisp》中,我已尽可能加快节奏,即便如此也要到第160页才介绍宏。
但我想提出一个可能有说服力的论点:Viaweb编辑器源代码中约20-25%是宏。宏比普通Lisp函数更难编写,非必要情况下使用它们被视为不良风格。因此每个宏的存在都不可或缺。这意味着该程序中至少20-25%的代码实现了其他语言难以完成的功能。无论Blub程序员对Lisp神秘力量的宣称多么怀疑,这都应引起他的好奇。我们编写这些代码不是为了自娱——作为一家小创业公司,我们拼命编程就是为了筑起技术壁垒。
Obviously, the median language has enormous momentum. I'm not proposing that you can fight this powerful force. What I'm proposing is exactly the opposite: that, like a practitioner of Aikido, you can use it against your opponents. If you work for a big company, this may not be easy. You will have a hard time convincing the pointy-haired boss to let you build things in Lisp, when he has just read in the paper that some other language is poised, like Ada was twenty years ago, to take over the world. But if you work for a startup that doesn't have pointy-haired bosses yet, you can, like we did, turn the Blub paradox to your advantage: you can use technology that your competitors, glued immovably to the median language, will never be able to match. If you ever do find yourself working for a startup, here's a handy tip for evaluating competitors. Read their job listings. Everything else on their site may be stock photos or the prose equivalent, but the job listings have to be specific about what they want, or they'll get the wrong candidates. During the years we worked on Viaweb I read a lot of job descriptions. A new competitor seemed to emerge out of the woodwork every month or so. The first thing I would do, after checking to see if they had a live online demo, was look at their job listings. After a couple years of this I could tell which companies to worry about and which not to. The more of an IT flavor the job descriptions had, the less dangerous the company was. The safest kind were the ones that wanted Oracle experience. You never had to worry about those. You were also safe if they said they wanted C++ or Java developers. If they wanted Perl or Python programmers, that would be a bit frightening-- that's starting to sound like a company where the technical side, at least, is run by real hackers.
多疑者可能开始怀疑其中的关联:我们大量代码在做其他语言极难实现的事,最终产品具备竞争对手没有的功能。或许存在某种联系。我建议你顺着这个思路想下去——那个拄拐蹒跚的老人,可能比表面看到的更有深意。
创业公司的合气道
但我不指望说服任何人(尤其是25岁以上的人)去学Lisp。本文目的不是改变他人观点,而是坚定那些本就对Lisp感兴趣者的信心——他们知道Lisp强大,却因小众而忧虑。在竞争中,这恰恰是优势。Lisp的力量会因竞争对手的不理解而成倍放大。
如果在创业中使用Lisp,不必担心它不被广泛理解,反而应希望这种状况持续。这很可能实现——编程语言的本质就是让多数人安于现状。计算机硬件发展远快于个人习惯,编程实践通常落后处理器10到20年。1960年代初MIT等机构已用高级语言编程,但直到1980年代许多公司仍用机器语言写代码。我打赌直到RISC指令集像急着打烊的酒保般把他们赶出门,很多人才停止使用机器语言。
If I had ever seen a job posting looking for Lisp hackers, I would have been really worried. Notes [1] Viaweb at first had two parts: the editor, written in Lisp, which people used to build their sites, and the ordering system, written in C, which handled orders. The first version was mostly Lisp, because the ordering system was small. Later we added two more modules, an image generator written in C, and a back-office manager written mostly in Perl. In January 2003, Yahoo released a new version of the editor written in C++ and Perl. It's hard to say whether the program is no longer written in Lisp, though, because to translate this program into C++ they literally had to write a Lisp interpreter: the source files of all the page-generating templates are still, as far as I know, Lisp code. (See Greenspun's Tenth Rule.) [2] Robert Morris says that I didn't need to be secretive, because even if our competitors had known we were using Lisp, they wouldn't have understood why: "If they were that smart they'd already be programming in Lisp." [3] All languages are equally powerful in the sense of being Turing equivalent, but that's not the sense of the word programmers care about. (No one wants to program a Turing machine.) The kind of power programmers care about may not be formally definable, but one way to explain it would be to say that it refers to features you could only get in the less powerful language by writing an interpreter for the more powerful language in it. If language A has an operator for removing spaces from strings and language B doesn't, that probably doesn't make A more powerful, because you can probably write a subroutine to do it in B.
通常技术迭代迅速,但编程语言不同:它们不仅是技术,更是程序员的思维载体,半是技术半是信仰。因此中位数语言(即大多数程序员使用的语言)如冰山般缓慢移动。约1960年由Lisp引入的垃圾回收机制,现已被广泛认可;运行时类型检查也逐渐流行;1970年代初由Lisp引入的词法闭包刚刚进入大众视野;而1960年代中期Lisp就有的宏,至今仍是未知领域。
显然,中位数语言具有巨大惯性。我并非建议对抗这股力量,正相反——像合气道修习者那样,你可以借力打力。
在大公司工作可能难以实现这点。当"尖头老板"刚读到某语言将如20年前的Ada般统治世界时,你很难说服他允许用Lisp开发。但如果在尚无此类老板的创业公司工作,你就能像我们一样,将Blub悖论转化为优势:使用那些被中位数语言束缚的竞争对手永远无法企及的技术。
若你身处创业公司,评估竞争对手时有条实用技巧:阅读他们的招聘信息。网站其他内容可能是样板素材,但招聘要求必须具体明确。在Viaweb运营期间,我读过大量职位描述——几乎每月都有新对手出现。查看在线演示后,我首先会看他们的招聘需求。几年后我就能判断哪些公司值得警惕:职位描述的IT气息越浓,威胁越小。最安全的是要求Oracle经验的,其次是C++或Java开发者。若需要Perl或Python程序员就需警惕——这至少说明技术部门由真黑客掌管。如果我曾看到招聘Lisp黑客的启事,定会高度紧张。
But if A supports, say, recursion, and B doesn't, that's not likely to be something you can fix by writing library functions. [4] Note to nerds: or possibly a lattice, narrowing toward the top; it's not the shape that matters here but the idea that there is at least a partial order. [5] It is a bit misleading to treat macros as a separate feature. In practice their usefulness is greatly enhanced by other Lisp features like lexical closures and rest parameters. [6] As a result, comparisons of programming languages either take the form of religious wars or undergraduate textbooks so determinedly neutral that they're really works of anthropology. People who value their peace, or want tenure, avoid the topic. But the question is only half a religious one; there is something there worth studying, especially if you want to design new languages.
| More Technical Details | | | Japanese Translation | Turkish Translation | | | Uzbek Translation | Orbitz Uses Lisp Too | | | How To Become A Hacker | A Scheme Story | | | Italian Translation.
[1] Viaweb最初有两部分:用Lisp编写的网站编辑器,以及用C处理的订单系统。第一版主要是Lisp,因为订单系统很小。后来我们增加了两个模块:用C编写的图像生成器,以及主要用Perl编写的后台管理系统。2003年1月,雅虎发布了用C++和Perl重写的编辑器新版。但严格说它是否仍算用Lisp编写存疑——因为为了转换成C++,他们实际上编写了一个Lisp解释器:据我所知,所有页面模板的源文件仍是Lisp代码。(参见《格林斯潘第十定律》)
[2] 罗伯特·莫里斯认为我无需保密,因为即使竞争对手知道我们用Lisp,也无法理解原因:"如果他们够聪明,早就在用Lisp了。"
[3] 所有语言在图灵等价意义上能力相同,但这并非程序员关注的层面。(没人想为图灵机编程。)程序员关心的"能力"或许无法精确定义,但一种解释方式是:在弱语言中,只有通过为其编写强语言的解释器才能获得的特性。如果语言A有去除字符串空格的运算符而语言B没有,这未必使A更强大,因为你可以在B中编写子程序实现。但如果A支持递归而B不支持,这就不是通过库函数能解决的问题。
[4] 给极客的注释:也可能是向顶端收窄的格序,此处重要的不是形状而是至少存在偏序的概念。
You'll find this essay and 14 others in _Hackers & Painters_.
[5] 将宏视为独立特性有些误导。实践中它们的实用性极大依赖于词法闭包、剩余参数等其他Lisp特性。
[6] 因此编程语言比较要么演变成圣战,要么成为坚决中立的人类学著作。重视安宁或渴望终身教职者会避开这个话题。但这个问题只有一半属于信仰范畴——其中确有值得研究之处,尤其当你想要设计新语言时。
书呆子的复仇(第6部分,共9部分)
You'll find this essay and 14 others in _Hackers & Painters_.
After a link to Beating the Averages was posted on slashdot, some readers wanted to hear in more detail about the specific technical advantages we got from using Lisp in Viaweb. For those who are interested, here are some excerpts from a talk I gave in April 2001 at BBN Labs in Cambridge, MA.
在《击败平均水平》的链接被发布到slashdot上后,一些读者希望更详细地了解我们在Viaweb中使用Lisp所获得的具体技术优势。对于感兴趣的人,以下是我2001年4月在马萨诸塞州剑桥市BBN实验室演讲的部分摘录。
April 2001 This essay developed out of conversations I've had with several other programmers about why Java smelled suspicious. It's not a critique of Java! It is a case study of hacker's radar. Over time, hackers develop a nose for good (and bad) technology. I thought it might be interesting to try and write down what made Java seem suspect to me. Some people who've read this think it's an interesting attempt to write about something that hasn't been written about before. Others say I will get in trouble for appearing to be writing about things I don't understand. So, just in case it does any good, let me clarify that I'm not writing here about Java (which I have never used) but about hacker's radar (which I have thought about a lot).
这篇文章源自我与其他几位程序员关于为何Java令人心生疑虑的讨论。它并非对Java的批判!而是一份关于黑客直觉的案例分析。
随着时间推移,黑客们培养出了对技术优劣的敏锐嗅觉。我认为尝试记录下Java让我感到可疑的原因或许会很有趣。
一些读过此文的人认为,这是对前人未曾涉猎领域的有趣探索。另一些人则警告我,可能会因谈论自己不了解的事物而惹上麻烦。因此,为防万一,请允许我澄清:本文并非探讨Java(我从未使用过它),而是关于黑客的直觉雷达(对此我思考良多)。
“不要以封面判断一本书”这句格言起源于书籍以素色纸板封面出售的年代,购买者需按个人品味自行装订。那时确实无法从封面判断书的内容。但出版业自那以后已进步良多:如今的出版商会竭力让封面传递书籍的真实信息。
The aphorism "you can't tell a book by its cover" originated in the times when books were sold in plain cardboard covers, to be bound by each purchaser according to his own taste. In those days, you couldn't tell a book by its cover. But publishing has advanced since then: present-day publishers work hard to make the cover something you can tell a book by. I spend a lot of time in bookshops and I feel as if I have by now learned to understand everything publishers mean to tell me about a book, and perhaps a bit more. The time I haven't spent in bookshops I've spent mostly in front of computers, and I feel as if I've learned, to some degree, to judge technology by its cover as well. It may be just luck, but I've saved myself from a few technologies that turned out to be real stinkers. So far, Java seems like a stinker to me. I've never written a Java program, never more than glanced over reference books about it, but I have a hunch that it won't be a very successful language. I may turn out to be mistaken; making predictions about technology is a dangerous business. But for what it's worth, as a sort of time capsule, here's why I don't like the look of Java: 1\. It has been so energetically hyped. Real standards don't have to be promoted. No one had to promote C, or Unix, or HTML. A real standard tends to be already established by the time most people hear about it. On the hacker radar screen, Perl is as big as Java, or bigger, just on the strength of its own merits. 2\. It's aimed low. In the original Java white paper, Gosling explicitly says Java was designed not to be too difficult for programmers used to C. It was designed to be another C++: C plus a few ideas taken from more advanced languages. Like the creators of sitcoms or junk food or package tours, Java's designers were consciously designing a product for people not as smart as them. Historically, languages designed for other people to use have been bad: Cobol, PL/I, Pascal, Ada, C++.
我常在书店消磨时光,自认已能读懂出版商通过封面传达的所有暗示,甚至更多。不在书店的时候,我大多面对着电脑屏幕,某种程度上也学会了通过"封面"判断技术优劣。或许是运气使然,我确实避开了几项后来被证实糟糕透顶的技术。
到目前为止,Java给我的感觉就是如此。我从未写过Java程序,对相关参考书也只是匆匆一瞥,但直觉告诉我这不会是个成功的语言。或许我终将被证明是错的——技术预言向来是危险的赌注。但作为时光胶囊里的预言纸条,以下是我对Java观感不佳的十二个理由:
1. 过度营销。真正的标准无需推销。C语言、Unix或HTML何曾需要推广?当大众听说它们时,这些标准早已确立。在黑客的雷达屏上,Perl凭借自身优势与Java平分秋色甚至更胜一筹。
2. 定位低端。高斯林在Java白皮书中明言,设计初衷是让C语言程序员容易上手。它本质上是C++的翻版:在C基础上嫁接少量高级语言特性。就像情景喜剧、垃圾食品或跟团游的策划者,Java设计者刻意为目标用户降智设计。历史证明,为他人设计的语言往往糟糕(COBOL、PL/I、Pascal、Ada、C++),而为自己设计的语言反而成功(C、Perl、Smalltalk、Lisp)。
The good languages have been those that were designed for their own creators: C, Perl, Smalltalk, Lisp. 3\. It has ulterior motives. Someone once said that the world would be a better place if people only wrote books because they had something to say, rather than because they wanted to write a book. Likewise, the reason we hear about Java all the time is not because it has something to say about programming languages. We hear about Java as part of a plan by Sun to undermine Microsoft. 4\. No one loves it. C, Perl, Python, Smalltalk, and Lisp programmers love their languages. I've never heard anyone say that they loved Java. 5\. People are forced to use it. A lot of the people I know using Java are using it because they feel they have to. Either it's something they felt they had to do to get funded, or something they thought customers would want, or something they were told to do by management. These are smart people; if the technology was good, they'd have used it voluntarily. 6\. It has too many cooks. The best programming languages have been developed by small groups. Java seems to be run by a committee. If it turns out to be a good language, it will be the first time in history that a committee has designed a good language. 7\. It's bureaucratic. From what little I know about Java, there seem to be a lot of protocols for doing things. Really good languages aren't like that. They let you do what you want and get out of the way. 8\. It's pseudo-hip. Sun now pretends that Java is a grassroots, open-source language effort like Perl or Python. This one just happens to be controlled by a giant company. So the language is likely to have the same drab clunkiness as anything else that comes out of a big company. 9\. It's designed for large organizations. Large organizations have different aims from hackers.
3. 别有用心。有人说如果人们只写非写不可的书,世界会更美好。同理,Java的喧嚣并非源于编程语言的突破,而是Sun对抗微软战略的一环。
4. 缺乏热爱。C、Perl、Python、Smalltalk和Lisp程序员都深爱自己的语言,我却从未听闻谁对Java怀有激情。
5. 被迫使用。我认识的Java使用者多出于无奈:或是为了融资妥协,或是迎合客户预期,或是服从管理层意志。这些聪明人若真认可技术价值,早该主动拥抱。
6. 设计臃肿。优秀编程语言皆由小团队锻造,Java却像委员会产物。若它最终成功,将是历史上首个由委员会设计的好语言。
They want languages that are (believed to be) suitable for use by large teams of mediocre programmers-- languages with features that, like the speed limiters in U-Haul trucks, prevent fools from doing too much damage. Hackers don't like a language that talks down to them. Hackers just want power. Historically, languages designed for large organizations (PL/I, Ada) have lost, while hacker languages (C, Perl) have won. The reason: today's teenage hacker is tomorrow's CTO. 10\. The wrong people like it. The programmers I admire most are not, on the whole, captivated by Java. Who does like Java? Suits, who don't know one language from another, but know that they keep hearing about Java in the press; programmers at big companies, who are amazed to find that there is something even better than C++; and plug-and-chug undergrads, who are ready to like anything that might get them a job (will this be on the test?). These people's opinions change with every wind. 11\. Its daddy is in a pinch. Sun's business model is being undermined on two fronts. Cheap Intel processors, of the same type used in desktop machines, are now more than fast enough for servers. And FreeBSD seems to be at least as good an OS for servers as Solaris. Sun's advertising implies that you need Sun servers for industrial strength applications. If this were true, Yahoo would be first in line to buy Suns; but when I worked there, the servers were all Intel boxes running FreeBSD. This bodes ill for Sun's future. If Sun runs into trouble, they could drag Java down with them. 12\. The DoD likes it. The Defense Department is encouraging developers to use Java. This seems to me the most damning sign of all. The Defense Department does a fine (though expensive) job of defending the country, but they love plans and procedures and protocols. Their culture is the opposite of hacker culture; on questions of software they will tend to bet wrong.
7. 官僚气息。就我所知,Java充斥着各种操作规范。真正优秀的语言从不会如此,它们为你开辟道路后便悄然退场。
8. 伪草根情怀。Sun如今将Java包装成Perl、Python般的开源社区产物,却掩饰不了其巨头掌控的本质。大公司出品难免带着刻板的笨拙。
9. 为大机构而生。大组织的诉求与黑客背道而驰:他们需要(被认为)适合平庸程序员大规模协作的语言——如同U-Haul卡车上的限速器,防止蠢材造成过大破坏。黑客厌恶被俯视的语言,他们只要力量。历史总是大组织语言(PL/I、Ada)落败,黑客语言(C、Perl)胜出,因为今天的少年黑客正是明天的技术领袖。
10. 受错的人追捧。我最敬佩的程序员群体整体对Java无感。谁在追捧Java?跟风的西装客(分不清编程语言区别但被媒体轰炸)、大厂程序员(惊觉竟有比C++更好的东西)、求职心切的本科生(考试会考吗?)。这些人的观点随风而变。
The last time the DoD really liked a programming language, it was Ada. Bear in mind, this is not a critique of Java, but a critique of its cover. I don't know Java well enough to like it or dislike it. This is just an explanation of why I don't find that I'm eager to learn it. It may seem cavalier to dismiss a language before you've even tried writing programs in it. But this is something all programmers have to do. There are too many technologies out there to learn them all. You have to learn to judge by outward signs which will be worth your time. I have likewise cavalierly dismissed Cobol, Ada, Visual Basic, the IBM AS400, VRML, ISO 9000, the SET protocol, VMS, Novell Netware, and CORBA, among others. They just smelled wrong. It could be that in Java's case I'm mistaken. It could be that a language promoted by one big company to undermine another, designed by a committee for a "mainstream" audience, hyped to the skies, and beloved of the DoD, happens nonetheless to be a clean, beautiful, powerful language that I would love programming in. It could be, but it seems very unlikely.
| Trevor Re: Java's Cover | | | Berners-Lee Re: Java | Being Popular | | | Sun Internal Memo | 2005: BusinessWeek Agrees | | | Japanese Translation.
11. 靠山危机。Sun的商业模式腹背受敌:桌面级英特尔处理器已足够支撑服务器,FreeBSD在服务器领域不逊Solaris。若Sun服务器真是企业级应用的必需品,雅虎理当抢购——但我在职时,他们的服务器全是运行FreeBSD的英特尔机器。这对Sun的未来不是好兆头,若其陷入困境,Java恐受牵连。
12. 国防部青睐。五角大楼鼓励使用Java,这在我看来是最不祥的征兆。国防部保家卫国固然出色(尽管成本高昂),但他们痴迷于计划、流程和协议。其文化与黑客文化截然相反,在软件领域的选择往往错误。上次被国防部厚爱的编程语言,叫Ada。
需声明这并非对Java的批判,而是对其"封面"的审视。我对Java了解尚浅,不足以评判好恶,只是解释为何缺乏学习热情。
未经实践就否定一门语言或许显得轻率,但这是程序员的必备技能——技术浩如烟海,必须学会通过外在迹象判断哪些值得投入时间。我同样轻率地否定过COBOL、Ada、Visual Basic、IBM AS400、VRML、ISO 9000、SET协议、VMS、Novell Netware和CORBA等,它们都散发着错误的气息。
或许我对Java的判断终将失误。或许这个被巨头用来打击对手、由委员会为"主流"设计、被过度炒作、受国防部青睐的语言,恰好也是简洁优美、强大趁手的工具。理论上有这种可能,但概率微乎其微。
January 2012 A few hours before the Yahoo acquisition was announced in June 1998 I took a snapshot of Viaweb's site. I thought it might be interesting to look at one day. The first thing one notices is is how tiny the pages are. Screens were a lot smaller in 1998. If I remember correctly, our frontpage used to just fit in the size window people typically used then. Browsers then (IE 6 was still 3 years in the future) had few fonts and they weren't antialiased. If you wanted to make pages that looked good, you had to render display text as images. You may notice a certain similarity between the Viaweb and Y Combinator logos. We did that as an inside joke when we started YC. Considering how basic a red circle is, it seemed surprising to me when we started Viaweb how few other companies used one as their logo. A bit later I realized why. On the Company page you'll notice a mysterious individual called John McArtyem. Robert Morris (aka Rtm) was so publicity averse after the Worm that he didn't want his name on the site. I managed to get him to agree to a compromise: we could use his bio but not his name. He has since relaxed a bit on that point. Trevor graduated at about the same time the acquisition closed, so in the course of 4 days he went from impecunious grad student to millionaire PhD. The culmination of my career as a writer of press releases was one celebrating his graduation, illustrated with a drawing I did of him during a meeting. (Trevor also appears as Trevino Bagwell in our directory of web designers merchants could hire to build stores for them. We inserted him as a ringer in case some competitor tried to spam our web designers.
1998年6月雅虎收购消息公布前几小时,我为Viaweb网站拍下了一张快照。当时觉得某天回看会很有趣。
最引人注目的是网页尺寸之小。1998年的屏幕尺寸普遍很小。如果没记错,我们的首页正好适配当时人们常用的窗口大小。
那时的浏览器(IE6还要三年才问世)字体稀少且没有抗锯齿。要想页面美观,必须将文字渲染为图片。
你可能会注意到Viaweb和Y Combinator标识的相似性。创办YC时我们开了这个内部玩笑。红色圆形如此基础,Viaweb初创时竟少有公司用它作标识,这让我惊讶。后来我才明白原因。
在公司页面上,你会看到名为John McArtyem的神秘人物。"蠕虫病毒"事件后,罗伯特·莫里斯(即Rtm)极度回避曝光,拒绝在网站署名。我最终说服他妥协:可用个人简介但隐去真名。如今他在这方面已放松许多。
We assumed his logo would deter any actual customers, but it did not.) Back in the 90s, to get users you had to get mentioned in magazines and newspapers. There were not the same ways to get found online that there are today. So we used to pay a PR firm $16,000 a month to get us mentioned in the press. Fortunately reporters liked us. In our advice about getting traffic from search engines (I don't think the term SEO had been coined yet), we say there are only 7 that matter: Yahoo, AltaVista, Excite, WebCrawler, InfoSeek, Lycos, and HotBot. Notice anything missing? Google was incorporated that September. We supported online transactions via a company called Cybercash, since if we lacked that feature we'd have gotten beaten up in product comparisons. But Cybercash was so bad and most stores' order volumes were so low that it was better if merchants processed orders like phone orders. We had a page in our site trying to talk merchants out of doing real time authorizations. The whole site was organized like a funnel, directing people to the test drive. It was a novel thing to be able to try out software online. We put cgi-bin in our dynamic urls to fool competitors about how our software worked. We had some well known users. Needless to say, Frederick's of Hollywood got the most traffic. We charged a flat fee of $300/month for big stores, so it was a little alarming to have users who got lots of traffic. I once calculated how much Frederick's was costing us in bandwidth, and it was about $300/month.
特雷弗在收购完成时恰好毕业,四天内就从身无分文的研究生变身百万富翁博士。我撰写新闻稿的职业生涯巅峰,是庆祝他毕业的那篇,配图是我在会议时为他画的素描。
(特雷弗还以Trevino Bagwell之名出现在我们为商户推荐的网页设计师名录中。这是为防止竞争对手骚扰设计师设置的诱饵。我们以为他的标识会吓退真实客户,结果并未奏效。)
90年代要获取用户,必须争取报刊报道。当时没有现今的线上获客渠道,因此我们每月支付16,000美元给公关公司争取媒体曝光。幸运的是记者们喜欢我们。
在搜索引擎流量指南中(那时"SEO"一词尚未诞生),我们列出7个重要引擎:Yahoo、AltaVista、Excite、WebCrawler、InfoSeek、Lycos和HotBot。注意到遗漏了吗?谷歌在那年9月才成立。
我们通过Cybercash支持在线交易——若缺少该功能,产品测评时会处于劣势。但Cybercash体验太差,且多数店铺订单量极低,商户用电话订单模式处理反而更佳。我们专门设立页面劝说商户放弃实时授权。
Since we hosted all the stores, which together were getting just over 10 million page views per month in June 1998, we consumed what at the time seemed a lot of bandwidth. We had 2 T1s (3 Mb/sec) coming into our offices. In those days there was no AWS. Even colocating servers seemed too risky, considering how often things went wrong with them. So we had our servers in our offices. Or more precisely, in Trevor's office. In return for the unique privilege of sharing his office with no other humans, he had to share it with 6 shrieking tower servers. His office was nicknamed the Hot Tub on account of the heat they generated. Most days his stack of window air conditioners could keep up. For describing pages, we had a template language called RTML, which supposedly stood for something, but which in fact I named after Rtm. RTML was Common Lisp augmented by some macros and libraries, and concealed under a structure editor that made it look like it had syntax. Since we did continuous releases, our software didn't actually have versions. But in those days the trade press expected versions, so we made them up. If we wanted to get lots of attention, we made the version number an integer. That "version 4.0" icon was generated by our own button generator, incidentally. The whole Viaweb site was made with our software, even though it wasn't an online store, because we wanted to experience what our users did. At the end of 1997, we released a general purpose shopping search engine called Shopfind. It was pretty advanced for the time. It had a programmable crawler that could crawl most of the different stores online and pick out the products..
整个网站采用漏斗式设计,将用户导向试用页面。当时在线试用软件尚属创新。我们在动态URL中加入cgi-bin以迷惑竞争对手。
我们有些知名用户。弗雷德里克内衣店流量最高。大店铺统一收费300美元/月,高流量用户令人担忧。有次计算该店带宽成本,恰好也是300美元/月。
由于托管所有店铺(1998年6月总浏览量超1000万次),我们消耗着当时惊人的带宽。办公室接入两条T1线路(3Mb/秒)。那时没有AWS,考虑到服务器频繁故障,连托管都显得冒险。服务器就放在办公室——准确说是特雷弗的办公室。作为独享空间的代价,他要与6台轰鸣的塔式服务器共处。因散热问题,他的办公室得名"热水浴缸"。多数时候那堆窗式空调还能应付。
我们用名为RTML的模板语言描述页面,名义上是缩写,实则致敬Rtm。RTML本质是添加了宏和库的Common Lisp,通过结构化编辑器伪装成有语法的语言。
持续发布模式使我们没有真正版本号。但当时行业媒体需要版本概念,我们就编造。想引发关注时,会直接使用整数版本号。那个"4.0版"图标由我们的按钮生成器制作。整个Viaweb网站都用自家软件搭建——尽管不是网店——只为体验用户感受。
1997年底,我们发布了通用购物搜索引擎Shopfind。它当时相当先进:可编程爬虫能抓取多数线上店铺并提取商品信息。
Kevin Kelleher suggested an interesting way to compare programming languages: to describe each in terms of the problem it fixes. The surprising thing is how many, and how well, languages can be described this way.
Kevin Kelleher提出了一个有趣的编程语言比较方法:用每种语言所解决的问题来描述它。令人惊讶的是,许多语言都可以用这种方式很好地概括。
Algol: 汇编语言太底层了。
Pascal: Algol的数据类型不够丰富。
Modula: Pascal在系统编程中太弱了。
Simula: Algol在模拟方面不够好。
Smalltalk: Simula并非所有东西都是对象。
Fortran: 汇编语言太底层了。
Cobol: Fortran太吓人了。
PL/1: Fortran的数据类型不够丰富。
Ada: 现有语言都缺少某些东西。
Basic: Fortran太吓人了。
APL: Fortran在数组操作上不够好。
J: APL需要自己的字符集。
C: 汇编语言太底层了。
Algol: Assembly language is too low-level. Pascal: Algol doesn't have enough data types. Modula: Pascal is too wimpy for systems programming. Simula: Algol isn't good enough at simulations. Smalltalk: Not everything in Simula is an object. Fortran: Assembly language is too low-level. Cobol: Fortran is scary. PL/1: Fortran doesn't have enough data types. Ada: Every existing language is missing something. Basic: Fortran is scary. APL: Fortran isn't good enough at manipulating arrays. J: APL requires its own character set. C: Assembly language is too low-level. C++: C is too low-level. Java: C++ is a kludge. And Microsoft is going to crush us. C#: Java is controlled by Sun. Lisp: Turing Machines are an awkward way to describe computation. Scheme: MacLisp is a kludge. T: Scheme has no libraries. Common Lisp: There are too many dialects of Lisp. Dylan: Scheme has no libraries, and Lisp syntax is scary. Perl: Shell scripts/awk/sed are not enough like programming languages. Python: Perl is a kludge. Ruby: Perl is a kludge, and Lisp syntax is scary. Prolog: Programming is not enough like logic.
| Japanese Translation | | | French Translation | Portuguese Translation
C++: C太底层了。
Java: C++是个笨拙的解决方案,而且微软会碾压我们。
C#: Java被Sun控制。
Lisp: 图灵机描述计算的方式太笨拙。
Scheme: MacLisp是个笨拙的解决方案。
T: Scheme没有库。
Common Lisp: Lisp的方言太多了。
Dylan: Scheme没有库,而且Lisp的语法太吓人。
Perl: Shell脚本/awk/sed不够像编程语言。
Python: Perl是个笨拙的解决方案。
Ruby: Perl是个笨拙的解决方案,而且Lisp的语法太吓人。
Prolog: 编程不够像逻辑。
| 日语翻译
| | | 法语翻译
| 葡萄牙语翻译
1993 _(This essay is from the introduction to_On Lisp _.)_ It's a long-standing principle of programming style that the functional elements of a program should not be too large. If some component of a program grows beyond the stage where it's readily comprehensible, it becomes a mass of complexity which conceals errors as easily as a big city conceals fugitives. Such software will be hard to read, hard to test, and hard to debug. In accordance with this principle, a large program must be divided into pieces, and the larger the program, the more it must be divided. How do you divide a program? The traditional approach is called _top-down design:_ you say "the purpose of the program is to do these seven things, so I divide it into seven major subroutines. The first subroutine has to do these four things, so it in turn will have four of its own subroutines," and so on. This process continues until the whole program has the right level of granularity-- each part large enough to do something substantial, but small enough to be understood as a single unit. Experienced Lisp programmers divide up their programs differently. As well as top-down design, they follow a principle which could be called _bottom-up design_ \-- changing the language to suit the problem. In Lisp, you don't just write your program down toward the language, you also build the language up toward your program. As you're writing a program you may think "I wish Lisp had such-and-such an operator." So you go and write it. Afterward you realize that using the new operator would simplify the design of another part of the program, and so on. Language and program evolve together. Like the border between two warring states, the boundary between language and program is drawn and redrawn, until eventually it comes to rest along the mountains and rivers, the natural frontiers of your problem. In the end your program will look as if the language had been designed for it.
(本文节选自《On Lisp》序言)
And when language and program fit one another well, you end up with code which is clear, small, and efficient. It's worth emphasizing that bottom-up design doesn't mean just writing the same program in a different order. When you work bottom-up, you usually end up with a different program. Instead of a single, monolithic program, you will get a larger language with more abstract operators, and a smaller program written in it. Instead of a lintel, you'll get an arch. In typical code, once you abstract out the parts which are merely bookkeeping, what's left is much shorter; the higher you build up the language, the less distance you will have to travel from the top down to it. This brings several advantages:.
程序的功能单元不应过于庞大,这一编程风格原则由来已久。当某个组件膨胀到难以理解的程度时,它就会变成一团隐匿错误的混沌体,如同大都市藏匿逃犯般容易。这样的软件将难以阅读、测试和调试。
根据这一原则,大型程序必须被拆解,且规模越大,划分越需细致。如何划分程序?传统方法称为_自顶向下设计_:即先确定"程序需完成这七项功能,故划分为七个主要子程序。第一个子程序需实现四项功能,因此它自身又包含四个子程序",如此层层递进,直至整个程序达到合适的粒度——每个部分既能实现实质功能,又可作为独立单元被理解。
1. By making the language do more of the work, bottom-up design yields programs which are smaller and more agile. A shorter program doesn't have to be divided into so many components, and fewer components means programs which are easier to read or modify. Fewer components also means fewer connections between components, and thus less chance for errors there. As industrial designers strive to reduce the number of moving parts in a machine, experienced Lisp programmers use bottom-up design to reduce the size and complexity of their programs.
资深的Lisp程序员采用不同的划分方式。除自顶向下设计外,他们遵循可称为_自底向上设计_的原则——通过改造语言来适应问题。在Lisp中,你不仅自上而下地用语言编写程序,更自下而上地为程序构建语言。编程时你可能会想"要是Lisp有某某操作符就好了",于是你动手实现它。随后你会发现这个新操作符能简化程序其他部分的设计,如此往复。语言与程序共同进化。如同交战国的边境线,语言与程序的边界被不断重新划定,最终沿着问题的自然疆界——那些山脉与河流——稳定下来。最终你的程序会看起来像是为其量身定制的语言。当语言与程序完美契合时,产出的代码将清晰、简洁且高效。
值得强调的是,自底向上设计并非仅以不同顺序编写相同程序。采用这种方法时,你最终得到的往往是另一个程序。不同于单一的整体式程序,你会获得一个包含更多抽象操作符的增强语言,以及用该语言编写的更精简程序。这好比用拱门替代了过梁。
2. Bottom-up design promotes code re-use. When you write two or more programs, many of the utilities you wrote for the first program will also be useful in the succeeding ones. Once you've acquired a large substrate of utilities, writing a new program can take only a fraction of the effort it would require if you had to start with raw Lisp.
典型代码中,当你抽离出那些纯属簿记的部分后,剩余内容会大幅缩减;语言构建得越高层,从顶层向下追溯的距离就越短。这带来诸多优势:
1. 通过让语言承担更多工作,自底向上设计能产出更精简、更灵活的程序。较短的程序无需被拆分成过多组件,更少的组件意味着程序更易于阅读或修改。组件减少也意味着组件间的连接更少,从而降低出错概率。正如工业设计师努力减少机器中的活动部件,经验丰富的Lisp程序员运用自底向上设计来降低程序的规模和复杂度。
3. Bottom-up design makes programs easier to read. An instance of this type of abstraction asks the reader to understand a general-purpose operator; an instance of functional abstraction asks the reader to understand a special-purpose subroutine. [1]
2. 自底向上设计促进代码复用。当你编写两个及以上程序时,为首个程序编写的许多工具函数在后续程序中同样适用。一旦积累了大量基础工具集,编写新程序所需精力可能仅为从原始Lisp起步的零头。
4. Because it causes you always to be on the lookout for patterns in your code, working bottom-up helps to clarify your ideas about the design of your program. If two distant components of a program are similar in form, you'll be led to notice the similarity and perhaps to redesign the program in a simpler way.
3. 自底向上设计提升程序可读性。这类抽象实例要求读者理解通用运算符;而函数式抽象实例则要求理解专用子程序。[1]
4. 由于这种设计促使你持续关注代码中的模式,自底向上工作有助于厘清程序设计思路。若程序中两个相距较远的组件形式相似,你会自然注意到这种相似性,并可能以更简洁的方式重构程序。
Bottom-up design is possible to a certain degree in languages other than Lisp. Whenever you see library functions, bottom-up design is happening. However, Lisp gives you much broader powers in this department, and augmenting the language plays a proportionately larger role in Lisp style-- so much so that Lisp is not just a different language, but a whole different way of programming. It's true that this style of development is better suited to programs which can be written by small groups. However, at the same time, it extends the limits of what can be done by a small group. In _The Mythical Man-Month_ , Frederick Brooks proposed that the productivity of a group of programmers does not grow linearly with its size. As the size of the group increases, the productivity of individual programmers goes down. The experience of Lisp programming suggests a more cheerful way to phrase this law: as the size of the group decreases, the productivity of individual programmers goes up. A small group wins, relatively speaking, simply because it's smaller. When a small group also takes advantage of the techniques that Lisp makes possible, it can win outright. New: Download On Lisp for Free.
在非Lisp语言中,自底向上设计也能实现到某种程度。任何库函数的存在都体现着这种设计。但Lisp在这方面赋予开发者更强大的能力,语言扩展在Lisp编程风格中占据更核心地位——这种差异如此显著,使得Lisp不仅是独特的语言,更代表着截然不同的编程范式。
诚然,这种开发风格更适合小团队编写的程序。但与此同时,它拓展了小团队的能力边界。在《人月神话》中,弗雷德里克·布鲁克斯提出程序员群体的生产力并不随规模线性增长。随着团队扩大,个体程序员的生产力反而下降。而Lisp编程经验为这一定律提供了更乐观的表述:随着团队规模缩小,个体程序员的生产力将提升。相对而言,小团队的优势恰恰在于其"小"。当小团队充分运用Lisp提供的技术时,他们能取得压倒性胜利。
[1] "But no one can read the program without understanding all your new utilities." To see why such statements are usually mistaken, see Section 4.8.
新动态:免费下载《On Lisp》。
[1] "但若不理解所有新工具函数,就无法读懂程序。"此类观点通常存在谬误,具体分析参见第4.8节。
There is a kind of mania for object-oriented programming at the moment, but some of the smartest programmers I know are some of the least excited about it. My own feeling is that object-oriented programming is a useful technique in some cases, but it isn't something that has to pervade every program you write. You should be able to define new types, but you shouldn't have to express every program as the definition of new types. I think there are five reasons people like object-oriented programming, and three and a half of them are bad:
目前有一种对面向对象编程的狂热,但我认识的一些最聪明的程序员却对此最不感兴趣。
1. Object-oriented programming is exciting if you have a statically-typed language without lexical closures or macros. To some degree, it offers a way around these limitations. (See Greenspun's Tenth Rule.)
我个人的看法是,面向对象编程在某些情况下是一种有用的技术,但它并不需要渗透到你编写的每一个程序中。你应该能够定义新类型,但不应该被迫将每个程序都表达为新类型的定义。
我认为人们喜欢面向对象编程有五个原因,其中三个半是不好的:
2. Object-oriented programming is popular in big companies, because it suits the way they write software. At big companies, software tends to be written by large (and frequently changing) teams of mediocre programmers. Object-oriented programming imposes a discipline on these programmers that prevents any one of them from doing too much damage. The price is that the resulting code is bloated with protocols and full of duplication. This is not too high a price for big companies, because their software is probably going to be bloated and full of duplication anyway.
1. 如果你的静态类型语言缺乏词法闭包或宏,面向对象编程会显得很吸引人。在某种程度上,它提供了一种绕过这些限制的方法。(参见格林斯潘第十定律。)
3. Object-oriented programming generates a lot of what looks like work. Back in the days of fanfold, there was a type of programmer who would only put five or ten lines of code on a page, preceded by twenty lines of elaborately formatted comments. Object-oriented programming is like crack for these people: it lets you incorporate all this scaffolding right into your source code. Something that a Lisp hacker might handle by pushing a symbol onto a list becomes a whole file of classes and methods. So it is a good tool if you want to convince yourself, or someone else, that you are doing a lot of work.
2. 面向对象编程在大公司中很受欢迎,因为它适合他们的软件开发方式。在大公司,软件通常由庞大(且频繁变动)的平庸程序员团队编写。面向对象编程为这些程序员强加了一种纪律,防止任何一个人造成太大的破坏。代价是生成的代码充斥着协议和大量重复。这对大公司来说不算太高的代价,因为他们的软件可能无论如何都会臃肿且充满重复。
3. 面向对象编程会生成许多看似工作量很大的内容。在折叠打印纸的时代,有一种程序员每页只放五到十行代码,前面加上二十行格式精美的注释。面向对象编程对这些人来说就像毒品:它让你把所有脚手架都塞进源代码中。Lisp黑客可能只需将一个符号推入列表就能解决的问题,在这里变成了一整个文件和类方法。因此,如果你想说服自己或别人你做了很多工作,这是一个好工具。
4. If a language is itself an object-oriented program, it can be extended by users. Well, maybe. Or maybe you can do even better by offering the sub-concepts of object-oriented programming a la carte. Overloading, for example, is not intrinsically tied to classes. We'll see.
4. 如果语言本身是一个面向对象的程序,用户就可以扩展它。嗯,也许吧。或者,你也可以通过提供面向对象编程的子概念来做得更好。例如,重载并不本质地与类绑定。我们拭目以待。
5. Object-oriented abstractions map neatly onto the domains of certain specific kinds of programs, like simulations and CAD systems.
5. 面向对象的抽象可以清晰地映射到某些特定类型程序的领域,比如模拟和CAD系统。
我个人从未需要过面向对象的抽象。Common Lisp拥有极其强大的对象系统,而我一次都未曾使用过它。我做过许多事情(例如创建装满闭包的哈希表),这些在更弱小的语言中可能需要面向对象技术来实现,但我从未不得不使用CLOS。
I personally have never needed object-oriented abstractions. Common Lisp has an enormously powerful object system and I've never used it once. I've done a lot of things (e.g. making hash tables full of closures) that would have required object-oriented techniques to do in wimpier languages, but I have never had to use CLOS. Maybe I'm just stupid, or have worked on some limited subset of applications. There is a danger in designing a language based on one's own experience of programming. But it seems more dangerous to put stuff in that you've never needed because it's thought to be a good idea.
也许我只是愚蠢,或者只接触过应用程序的某个有限子集。基于个人编程经验来设计语言是有风险的。但把那些你从未需要、只是被认为是个好主意的东西加进去,似乎更加危险。